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1. INTRODUCTION
1.1 Introduction to refactoring
Refactoring is a well-defined process that improves the quality of systems and allows
developers to repair code that is becoming hard to maintain, without throwing away the
existing source code and starting again. By careful application of refactorings the system’s
behavior will remain the same, but return to a well-structured design. The use of automated
refactoring tools makes it more likely that the developer will perform the necessary
refactorings, since the tools are much quicker and reduce chance of introducing bugs.
“Refactoring is the process of changing a software system in such a way that it does not alter
the external behavior of the code yet it improves its internal structure.”-Martin Flower in
Refactoring, Improving the Design of Existing Code.
Refactoring is a kind of reorganization. Technically, it comes from mathematics when you
factor an expression into an equivalence- the factors are cleaner ways of expressing the same
statement. Refactoring implies equivalence- the beginning and the end product must be
functionally identical. The shift from Structured Programming to Object-oriented
Programming is a fundamental example of refactoring. [1]
“Refactoring is the process of taking an object design and rearranging it in various ways to
make the design more flexible and/or usable.” – Ralph Johnson.
Four Reasons to change the code:
The four primary reasons to change the code are [2]:
1. Adding a feature
2. Fixing a bug
3. Improving the design
4. Optimizing resource usage
1.2 Preserving Behavior
Feature addition and bug fixing are very much like refactoring and optimization. In all cases
of changing code, we want to change some functionality, some behavior, but we want to
preserve much more (see Figure 1)
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Existing Behavior New Behavior
Figure 1: Preserving Behavior [2]
Figure 1 shows what is supposed to happen when we make changes, but what does it mean
for us practically? On the positive side, it seems to tell us what we have to concentrate on.
We have to make sure that small numbers of things that we change are changed correctly. On
the negative side, that isn’t the only thing we have to concentrate on. We have to figure out
how to preserve the rest of the behavior. The amount of behavior to be preserved is usually
very large.
Preserving behavior is a large challenge. When we need to make changes and preserve
behavior, it can involve considerable risk. [2] To mitigate risk, we have to ask three
questions:
1. What changes do we have to make?
2. How will we know that we’ve done them correctly?
3. How will we know that we haven’t broken anything?
1.3 Why do we need refactoring?
The longer object oriented systems are in use, the more probable it is that these systems have
to be maintained [3], i.e. they have to be optimized to a given goal (Perfective Maintenance),
they have to be corrected with respect to identified defects (Corrective Maintenance) and they
have to be adjusted to a changing environment (Adaptive Maintenance). Whereas many of
these activities can be subsumed under the reengineering area, there are additional changing
activities that are much less difficult to apply than typical reengineering activities, and which
does not change the external behavior [4]. The main goal of these “mini-reengineering
activities” is to improve the understandability and to simplify reengineering activities. Flower
calls these activities Refactorings, which he defines a “a change made to the internal
structure of a software to make it easier to understand and cheaper to modify without
changing its observable behavior” [1, p. 53].
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Fowler suggests four purposes of refactoring [1]:
1. Improve the design of software – Through accumulating code changes, code loses its
structure, thereby increasingly drifting towards a state of decay. Refactoring can be used
to cure software decay by redistributing parts of the code to the “right” places, and by
removing duplicated code. The claim that refactoring can improve the design of software
is confirmed by [3] with regard to cohesion and with respect to coupling, as indicators
for internal software quality. Another claimed benefit in the area of improved design is
improved flexibility.
2. Make software easier to understand – Refactoring can help make the code more readable
by making it better communicate its purpose. A different way in which refactoring
supports program understanding is in reflecting hypotheses about the purpose of the code
by changing the code, and afterwards testing that understanding through rerunning the
code. The suggested process to do so is to start refactoring the little details to clarify the
code, thereby exposing the design. The potential to improve understandability through
refactoring is confirmed by many authors [1, 3]. In more specific terms, [5] discusses
how refactorings can be used to improve communicating the purpose of the code.
3. Help find bugs – Through clarifying the structure of the code, the assumptions within the
code are also clarified, making it easier to find bugs.
4. Program faster – Through improving the design and overall understandability of the
code, rapid software development is supported.
1.4 When should one consider refactoring?
Ideally, refactoring would be part of a continuing quality improvement process. In other
words, refactoring would be seamlessly interwoven with other day-to-day activities of every
software developer.
Refactoring may be useful, when a bug has surfaced and the problem needs to be fixed or the
code needs to be extended. Refactoring at the same time as maintenance or adding new
features also makes management and developers more likely to allow it, since it will not
require an extra phase of testing.
If the developer in charge finds it difficult to understand the code, he will (hopefully) ask
questions, and begin to document the incomprehensible code.
Often, however, schedule pressures do not permit to implement a clean solution right away.
A feature might have to be added in a hurry, a bug patched rather than fixed. In these cases,
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the code in question should be marked with a FIXME note, in order to be reworked, when
time permits. Such circumstances call not for individual refactorings, but for a whole
refactoring project. When the time has come to address the accumulated problems, a scan for
FIXMEs, TODOs, etc. over the code base will return all the trouble spots for review. They
can be refactored according to priority.
2. SEMANTIC GAP
The concept of Semantic gap is relevant whenever a human activity, observation and task are
transferred into computational representation [6]. Like programs, programming languages are
not only mathematical objects but also software engineering artifacts. Describing the
semantics of real-world languages can help bring language theory to bear on both exciting
and important real-world problems. Achieving this is not purely a mathematical task, but
equally one of (semantic) engineering. The implementations of all major languages—
especially scripting languages defined by implementations—come with large and well-
structured test suites. These suites embody the intended semantics of the language. We
should be able to use such a test suite to retrofit semantics. For this to be useful, it is not
sufficient to merely create semantics for the core language [4].
More precisely the gap means the difference between contextual knowledge in a
powerful language (e.g. natural language) and its reproducible and computational
representation in a formal language (e.g. programming language).
The semantic gap actually opens between the selection of the rules and the representation
of the task.
With the passage of time, the business scenario keeps on changing and the software
development must match the business environment. Therefore the code of any software also
changes with respect to the business scenario. There might be architectural changes in
software due to business reengineering process. The programmer has to rethink how to do the
implementation of the code due to changes in the requirements. So, it offers opportunity to
relook, redesign, as well as refactor the code. Thus, it forces new semantics to be laid with
respect to the changing business scenario.
3. REFACTORING ACTIVITIES
The refactoring process consists of a number of different activities, each of which can be
automated to a certain extent [7]:
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1. Identify where the code should be refactored;
2. Determine which refactorings should be applied to the identified places;
3. Guarantee that the applied refactoring preserves behavior;
4. Apply the refactoring;
5. Assess the effect of refactoring on software quality characteristics;
6. Maintain consistency between refactored program code and other software artifacts (or
vice versa).
The steps taken when applying the refactoring should be small enough to oversee the
consequences they have and reproducible to allow others to understand them. Generalized
refactoring steps in away, are mere a rule that can be applied to any structure.
Refactoring not only covers the mechanics of restructuring, but also addresses the following
issues [Martin Flower]:
1. Refactoring emphasizes that, in absence of more formal guarantees, testing should be
used to ensure that each restructuring is behavior preserving. A rich test suite should be
built, which must be run before and after each test is applied.
2. Refactorings are described in a catalog, using a template reminiscent of design patterns.
3. Refactorings are applied in small steps, one by one, running the test suite after every step
to make it into commercial development tools.
4. METRICS FOR REFACTORABILITY
The various metrics are identified for calculating the values of four factors proposed here
separately. Those are defined as follows:
1. LinesOfCode (NbLines): The LOC for a method is equals to the number of sequence
point found for this method in the file. A sequence point is used to mark a spot in the
IL code that corresponds to a specific location in the original source. Notice that
sequence points which correspond to braces ‘{‘ and ‘}’ are not taken into account.
Interfaces, abstract methods and enumerations have a LOC equals to 0. Only concrete
code that is effectively executed is considered when computing LOC.
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A Likert scale is a psychometric scale commonly used in questionnaires, and is the most
widely used scale in survey research, such that the term is often used interchangeably with
rating scale even though the two are not synonymous. When responding to a Likert
questionnaire item, respondents specify their level of agreement to a statement. The scale is
named after its inventor, the US organizational-behavior psychologist Rensis Likert (1903-
81). Each item may be analyzed separately or in some cases item responses may be summed
to create a score for a group of items. Hence, Likert scales are often called summative scales.
Likert scale data can, in principle, be used as a basis for obtaining interval level estimates on
a continuum by applying the polytomous Rasch model, when data can be obtained that fit this
model. In addition, the polytomous Rasch model permits testing of the hypothesis that the
statements reflect increasing levels of an attitude or trait, as intended. For example,
application of the model often indicates that the neutral category does not represent a level of
attitude or trait between disagree and agree categories. Again, not every set of Likert scaled
items can be used for Rasch measurement. The data has to be thoroughly checked to fulfill
the strict formal axioms of the model.
Likert scales usually have five potential choices (strongly agree, agree, neutral, disagree,
strongly disagree) but sometimes go up to ten or more. The final average score represents
overall level of accomplishment or attitude toward the subject matter [8].
Since, each of the factors is intangible in nature and is hard to measure. It is also proposed
that they should be measured in terms of point system as follows:
Table 1: Scale of Reusability:
High Reusability 10-9
Medium Reusability 8-7
Low Reusability 6-5
Very low Reusability 4-3
No Reusability 2-1
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6. CORRELATION AND REGRESSION ANALYSIS
Correlation and regression are generally performed together. The application of correlation
analysis is to measure the degree of association between two sets of quantitative data. There
are virtually no limits of applying correlation analysis to any dataset of two or more variables.
It is the researcher’s responsibility to ensure correct use of correlation analysis. Correlation is
usually followed by regression analysis in many applications. The main objective of
regression analysis is to explain the variation in one variable (called the dependent variable),
based on the variation in one or more other variables (called the independent variables). If
there are only one dependent variable and only one independent variable used to explain the
variation in it, then the model is known as simple regression. If multiple independent
variables are used to explain variation in one dependent variable, it is called multiple
regressions [9]. Even though the regression equation could be either linear or non-linear, we
limited our discussion to linear models.
From the regression analysis of the various four factors (reusability, understandability,
modifiability, maintainability) separately, using their respective metrics, the analysis of
refactorability can be done by applying linear regression over refactorability using these four
factors. Thus, the regression equation for refactorability will be as follows:
Y=a+bX1+cX2+dX3+eX4
Where, Dependent Variable= Y
Independent Variables are: X1, X2, X3, and X4.
The above mentioned regression equation is applied to each factor that is considered to be
affecting the refactorability of the software. The underlying steps are carried out for each of
the factor separately, by considering their respective metrics as their independent variables.
Step 1: Collect the dataset containing the values for each metric identified. And based on that
dataset, the points based on the rating scale are assigned, considering the rules.
Step 2: The correlation is found among the independent variables and dependent variables,
for each factor affecting refactoring. The SPSS 16 tool is used to find the correlation. The
positive value of correlation specifies that the factor is directly affected by that variable. And,
the negative value shows that the factor is inversely affected by the respective variable.
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metrics that affect each factor of refactoring are determined and the values are calculated.
The correlation and regression analysis is performed to determine the associations and
variations among the various metrics used and their respective factors. The linear regression
equation for applying regression analysis used is given as
Y=a + bX1 + cX2 + dX3 + eX4
Where, Y= dependent variable, a, b, c, d, e are correlation coefficients, and X1, X2, X3, X4
are independent variables. The variation in independent variables affects the variation in
dependent variable.The measure of strength of association in the regression analysis is given
by the coefficient of determination, denoted by R-square. The coefficient varies between 0
and 1 and represents the proportion of total variation in the dependent variable that is
accounted for, by the variation in the factors.
REFERENCES
[1] Martin Flower, Kent Beck, John Brant, William F. Opdyke, Don Roberts, 1999,
Refactoring: Improving the Design of Existing Code, Addison Wesley.
[2] Robert C. Martin Series, 2004, Working Effectively with Legacy Code, Michael C.
Feathers, Prentice Hall.
[3] Frank Simon, Frank Steinbruckner, Claus Lewerentz, 2001, Metrics Based Refactorings,
In: Proceedings of 5th European Conference on Software Maintenance and Reengineering,
IEEE CS Press, Lisbon, Portugal, pp. 30-38.
[4] Arjun Guha, Shriram Krishnamurthi, 2010, Minding the (Semantic) Gap, Engineering
Programming Language Theory.
[5] W. C. Wake, 2003. Refactoring Workbook, Addison-Wesley Longman Publishing Co.,
Inc., Boston, MA, USA.
[6] C. Dorai, S. Venkatesh, 2003. Bridging the Semantic Gap with Computational Media
Aesthetics, IEEE Multimedia, Vol. 10, No. 2, pp.15-17.
[7] Tom Mens, Tom Tourwe, 2004, A Survey of Software Refactoring, IEEE Transactions on
Software Engineering, Vol. 30, No. 2, pp. 126-139.
[8] http://www.businessdictionary.com/definition/Likert-scale.html
[9] John Fox, 1997, Applied Regression Analysis, Linear Models, and Related Methods,
Thousands Oaks, CA: Sage Publications.
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INTRODUCTION:
Over the last decade there is tremendous growth of information on World Wide Web
(WWW).It has become a major source of information. Web creates the new challenges of
information retrieval as the amount of information on the web and number of users using web
growing rapidly. It is practically impossible to search through this extremely large database
for the information needed by user. Hence the need for Search Engine arises. Search Engines
uses crawlers to gather information and stores it in database maintained at search engine side.
For a given user's query the search engine searches in the local database and very quickly
displays the results.
But, the voluminous amount of web documents has resulted in problems for search engines
leading to the fact that the search results are of less relevance to the user. In addition to this,
the presence of duplicate and near-duplicate web documents has created an additional
overhead for the search engines critically affecting their performance. The demand for
integrating data from heterogeneous sources leads to the problem of near-duplicate web
pages. Near-duplicate data bear high similarity to each other, yet they are not bitwise
identical [2][4].
A. TDW Matrix Algorithm
TDW Matrix Algorithm is a three-stage algorithm which receives an input record and a threshold
value and returns an optimal set of near-duplicates. In first phase, rendering phase[3], all pre-
processing are done and a weighting scheme is applied. Then a global ordering is performed to form a
term-document weight matrix. In second phase, filtering phase, two well-known filtering mechanisms,
prefix filtering and positional filtering, are applied to reduce the size of competing record set and
hence to reduce the number of comparisons. In third phase, verification phase, singular value
decomposition is applied and a similarity checking is done based on the threshold value and finally
we get an optimal number of near-duplicate records.
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Fig.1: General Architecture [1].
B. Suffix Filtering Method:-
Suffix filtering method, is a generalization of the positional filtering to the suffixes of the
records. However, the challenge is that the suffixes of records are not indexed nor their partial
overlap has been calculated. Therefore, we face the following two technical issues:
(i) How to establish an upper bound in the absence of indices or partial overlap results?
(ii) How to find the position of a token without tokens being indexed?
The first issue is solved by converting an overlap constraint to an equivalent Hamming
distance constraint. Then lower bound the Hamming distance by partitioning the suffixes in a
coordinated way. The suffix of a record x is denoted as xs. Consider a pair of records,
(x, y), that meets the Jaccard similarity threshold t, and without loss of generality, |y| ≤ |x|.
Since their overlap in their prefixes, is at most the minimum length of the prefixes, the
following upper bound can be derived in terms of the Hamming distance of their suffixes.
H (xs, ys) ≤ Hmax =2|x| − 2 t/1 + t ・ (|x| + |y|) − ( t ・ |x| − t ・ |y| ) –(1)
In order to check whether H (xs, ys) exceeds the maximum allowable value, an estimate of the
lower bound of H (xs, ys) is provided below. First we choose an arbitrary token w from ys,
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and divide ys into two partitions: the left partition yl and the right partition yr. The criterion
for the
partitioning is that the left partition contains all the tokens in ys that precede w in the global
ordering and the right partition contains w (if any) and tokens in ys that succeed w in the
global ordering. Similarly, divide xs into xl and xr using w too (even though w might not
occur in x). Since xl (xr) shares no common token with yr (yl), H(xs, ys) = H(xl, yl) + H(xr, yr).
The lower bound of H (xl, yl) can be estimated as the difference between |xl| and |yl|, and
similarly for the right partitions. Therefore,
H (xs, ys) ≥ abs (|xl| − |yl|) + abs (|xr| − |yr|) -(2)
Finally, we can safely prune away candidates whose lower bound Hamming distance is
already larger than the allowable threshold Hmax.
RELATED WORK:
A .Prefix Filtering: Consider an Ordering O of the token universe U and a set of records,
each with tokens sorted in the order of O. Let the p-prefix of a record x be the first p tokens
of x. If O(x, y) ≥ α, then the (|x|−α+1)-prefix of x and the (|y|−α+1)-prefix of y must share at
least one token.
Prefix filtering is a necessary but not sufficient condition for the corresponding overlap
constraint, an algorithm is designed as: first build inverted indices on tokens that appear in
the prefix of each record in an indexing phase. Then generate a set of candidate pairs by
merging record identifiers returned by probing the inverted indices for tokens in the prefix of
each record in a candidate generation phase. The candidate pairs are those that have the
potential of meeting the similarity threshold and are guaranteed to be a superset of the final
answer due to the prefix filtering principle. Finally, in a verification phase, evaluate the
similarity of each candidate pair and add it to the final result if it meets the similarity
threshold.
B. Positional Filtering: Consider an ordering O of the token universe U and a set of
records, each with tokens sorted in the order of O. Let token w = x[i], w partitions the record
into the left partition xl (w) = x [1 . . . (i − 1)] And the right partition xr(w) = x[i . . |x|]. If O(x,
y) ≥ α, then for every token w x ∩ y, O (xl (w), yl(w)) + min(|xr(w)|, |yr(w)|) ≥ α.
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A natural idea to utilize the positional filtering principle is to combine it with the existing
prefix filtering method, which already keeps tracks of the current overlap of candidate pairs
and thus gives us O (xl (w), yl(w)).
PROPOSED WORK:
Here, I have proposed an idea of adding one more filtering technique suffix filtering , which
is a generalized form of positional filtering which will further reduce the candidate pairs size,
which helps in much more efficient way to detect near-duplicates.
In this new architecture, there are three phases:
1) Rendering Phase
2) Filtering Phase
3) Verification Phase
Rendering Phase consists of (i) Preprocessing which includes tokenization, stemming, and
stop word removal. Then (ii) Feature Weighting is done according to the proposed scheme
given in Ref.[1] on the preprocessed data .After that, (iii) Canonicalization[1]., is done. The
final result of this phase is the TDW Matrix [1].
Filtering Phase includes (i) Prefix Filtering, the basic idea behind this filtering principle is
that if two web pages share rare tokens, there is a chance that it might be similar. Since a
global ordering is done based on document frequencies, prefix set of a record contain rare
tokens. If no tokens are shared in prefix set, that record can be avoided from further
processing. Once prefix filtering is over, (ii) positional filtering principle[2]. is applied in
order to prune unwanted records from candidate set C. (iii) Finally, suffix filtering[2]. is done
on the candidate pairs come from positional filtering, which uses hamming distance
constraint(Hmax) instead of overlap constraints . The suffix of a record x is denoted as xs.
Consider a pair of records, (x, y), that meets the Jaccard similarity threshold t, and without
loss of generality, |y| ≤ |x|. Since their overlap in their prefixes, is at most the minimum length
of the prefixes, the upper bound can be derived in terms of the Hamming distance of their
suffixes.
H (xs, ys) ≤ Hmax =2|x| − 2 t/1 + t ・ (|x| + |y|) − ( t ・ |x| − t ・ |y| )
In order to check whether H (xs, ys) exceeds the maximum allowable value, an estimate of the
lower bound of H (xs, ys) is provided below. The lower bound of H(xl, yl) can be estimated as
the difference between |xl| and |yl|, and similarly for the right partitions. Therefore,
H (xs, ys) ≥ abs (|xl| − |yl|) + abs (|xr| − |yr|) -
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Remarks: Assume that Input_Record is represented as the first entry in TDW_Matrix
Filtering (TDW_Matrix, Record_Set, t)
r←TDW_Matrix[1];
//prefix filtering
C← φ;
Prefix_Length← |r|- t.|r| +1;
for all ri Record_Set
Prefixi←|ri|- t.|ri| +1;
for all j,k; 1≤ j ≤ Prefix_Length, 1≤ k ≤ Prefixi
if (r[j] == ri[k])
C← C ri;
//positional filtering
M1← φ;
for all ri C
O← t/t+1(|r|+|ri|);
for all p,q; 1≤ p ≤ Prefix_Length, 1≤ q ≤ Prefixi
if (r[p]==ri[q])
ubound←1+ min(|r|-p, |ri|-q);
if (ubound ≥ O)
M1 ← M 1 ri;
return M1;
// suffix filtering /* x and y are tokens*/
SuffixFilter(x, y, Hmax, d)
M← φ
if d > MAXDEPTH then return abs(|x| − |y|) ; /*d-> current recursive depth*/
mid ← |y| /2 ; w ← y[mid];
o ← (Hmax−abs(|x|−|y|))/2 /* always divisible */;
if |x| < |y| then ol ← 1, or ← 0 else ol ← 0, or ← 1;
(yl, yr, f, diff) ← Partition(y,w,mid,mid);
(xl, xr, f, diff) ← Partition(x,w,mid −o − abs(|x| − |y|) ・ ol, mid + o + abs(|x| − |y|) ・ or);
if f = 0 then
return Hmax + 1
H ← abs(|xl| − |yl|) + abs(|xr| − |yr|) + diff;
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if H > Hmax then
return H
else
Hl ←SuffixFilter(xl, yl,Hmax−abs(|xr|−|yr|)−diff, d+1) ;
H ← Hl + abs(|xr| − |yr|) + diff;
if H ≤ Hmax then
Hr ← SuffixFilter(xr, yr,Hmax − Hl − diff, d + 1) ;
return Hl + Hr + diff
else
return H, M← M ri;
//partition / *s is the set of tokens and its two subsets are sl and sr */
Partition(s,w, l, r)
sl ← φ ; sr ← φ;
if s[l] > w or s[r] < w then
return ( φ, φ, 0, 1)
p ← binary search for the position of the first token in s that is no smaller than w in the
global ordering within s[l . . r];
sl ← s[1 . . p − 1];
if s[p] = w then
sr ← s[(p + 1) . . |s|]; /* skip the token w */;
diff ← 0;
else
sr ← s[p . . |s|];
diff ← 1;
return (sl, sr, 1, diff)
CONCLUSION AND FUTURE WORK
In this paper, the proposed work is to add one more filtering method in filtering phase named
suffix filtering which is a generalization of positional filtering which will further reduce the
candidate sizes. Both, positional filtering and suffix filtering are complementary to the
existing prefix filtering technique. They successfully alleviate the problem of quadratic
growth of candidate pairs when the data grows in size. So, this will further improve the
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method to detect near-duplicates. Further research works can extend this to a more efficient
method for finding similarity joins which can be incorporated in a focused w
REFERENCES:
[1] Midhun Mathew, Shine N Das ,TR Lakshmi Narayanan, Pramod K Vijayaraghvan, A
Novel Approach for Near-Duplicate Detection of Web Pages using TDW Matrix. (IJCA, vol
19-no.7,April 2011)
[2] Chuan Xiao, Wei Wang, Xuemin Lin , Jeffrey Xu Yu, Efficient Similarity Joins for Near
Duplicate Detection, Proceeding of the 17th international conference on World Wide Web, pp
131 – 140. April 2008.
[3] Shine N Das, Midhun Mathew, Pramod K.Vijayaraghavan, An Approach for Optimal
Feature Subset Selection using a New Term Weighting Scheme and Mutual Information,
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Information Technology, Malaysia, 2011, pp 273-278, January 2011.
[4] Gurmeet Singh Manku, Arvind Jain and Anish Das Sarma, Detecting near-duplicates for
web crawling, In Proceedings of the 16th international conference on World Wide Web, pp.
141 - 150, Banff, Alberta, Canada, 2007.
.
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E Volum
me1Issue5
5 ISSN‐22
249‐ 1619
Temperat
ture 25 deg c
Dimensio (mm)
ons 1593 × 790 × 50
Area of sing panel = 1
gle 1258470 (mm
m)
Area of sing panel = 1
gle 1.259 meter²
²
Tilt angle
e(slope) of PV Module 45 degree
V
Mounting
g Fixed Type
The wirin diagram o PV array is shown in Figure 1
ng of
gure 1 wiring diagram of PV array
Fig g f
PWM inv
verters are used for supp
u pressing the harmonics p
produced aft DC to AC Conversion
ter C n.
The calcu
ulation for fi
inding the ou
utput voltage of inverter is shown be
e r elow: [26]
Phase vo
oltage= Vph= 0.4714 × Vdc= 0.4714 240= 113.
4× .136 Volts.
Line volt
tage = VL = 0.779 × Vdc = 0.779× 2 = 187 Volts.
240 V
KVA rati = KW × assumed po
ing ower factor = KW × 0.8
Interna ational Journal of Research in IT, Management and Engineering
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10 to 25 taps in secondary
Efficiency Almost 95 %
Extra features Air cooled
5. COST ANALYSIS FOR 45 KW SOLAR PV PLANT:
1.Cost of solar panels: - The BP 7180 most powerful module manufactured by BP Solar is
used; cost of solar panel is Rs.160 per watt.
So cost of 180 watt panel is = 180 × 160 = Rs. 28, 800.
Total cost of solar panels = 250 × 28800 = Rs. 72, 00000.
2. Cost of 3-φ Inverter: - 36 KVA or 45 KW of an inverter /Power Conditioning Unit is
used; multiply the size of the inverter by Rs. 25 per rated watt.
Cost of inverter = 25 × 45,000 = Rs. 11, 25,000.
3. Cost of 3-φ step up Transformer: - 36 KVA or 45 KW of a step up transformer is used;
multiply the size of the transformer by Rs. 20 per rated watt.
Cost of transformer = 20 × 45000 = Rs. 9, 00000.
4. Cost of battery bank: - Exide Invared 400 Tubular Inverter Battery 12 V, 150Ah Price –
8,400/- . 40 numbers of batteries in two strings of 20 batteries in each string are used. [34]
So, cost of battery bank = 40 × 8400 = Rs 3, 36, 000.
Subtotal: Rs. 95, 61, 000.
5. Multiply the subtotal above by 0.2 (20%) to cover balance of system costs (wire, fuses,
switches, etc.).
Cost Estimate for Balance of System: (9561000 × 0.2) Rs. 19, 12, 200.
Total Estimated PV System Cost is Rs. 1, 14, 73, 200.
6. ANNUAL ENERGY GENERATION
The annual energy generation from the SPV power plant has been worked out based on the
data on mean global solar radiant exposure over Haryana at district Kaithal. The mean global
solar radiant exposure varies from 2.53 kWh/m² /day in the month of December to 6.24 kWh/
m²/day in the month of April according to HARSAC and from 3.36 kWh/m² /day in the
month of December to 6.4 kWh/m²/day in the month of May according to NASA. The
month-wise mean global solar radiant exposure is given at table below.
Table 8 Mean Global Solar Radiant Exposure Kaithal, HARYANA (Acc. To HARSAC)
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[1]. P.Sritakaew & A.Sangswang, “On the Reliability Improvement of Distribution Systems
Using PV Grid-Connected Systems”. IEEE Asia Pacific Conference on Circuits and systems.
pp. 1354 - 1357, 2006.
[2]. Allen M. Barnett, “Solar electrical power for a better tomorrow”. Photovoltaic Specialists
IEEE Conference, Page(s): 1 – 8, 1996.
[3]. G. Ofualagba, “Photovoltaic Technology, Applications and Market”, IEEE Conference
on Power and Energy society general meeting - conversion and delivery to electrical energy,
Vol.21, Page(s): 1 – 5, 2008.
[4]. Souvik Ganguli and Sunanda Sinha, “A Study and Estimation of Grid Quality Solar
Photovoltaic Power Generation Potential in some districts of West Bengal”. National
Conference on Trends in Instrumentation & Control Engineering, Thapar University,
Patiala, Page(s): 522-528, 29-30th Oct., 2009.
[5]. Wang Jianqiang & Li Jingxin, “Design and Experience of Grid-connecting Photovoltaic
Power System”, IEEE International Conference on Sustainable Energy Technology, Page(s):
607 - 610, 2008.
[6]. B. Marion,J. Adelstein,K. Boyle and fellows, “Performance Parameters for Grid
Connected PV Systems”, Photovoltaic Specialists IEEE Conference, Page(s): 1601 - 1606,
2005.
[7]. D. Picault, B. Raison, and S. Bacha, “Guidelines for evaluating grid connected PV
system topologies”. IEEE International Conference on Industrial Technology. Page(s): pp. 1-
5, 2009.
[8]. Jinhui Xue, Zhongdong Yin, Qipeng Song, and Renzhong Shan, “Analyze and Research
of the inverter for Grid connecting photovoltaic system”, Third IEEE International
Conference on Electric Utility Deregulation and Restructuring Power Technologies, Page(s):
2530 – 2535, 2008.
[9]. Eduardo Román, Ricardo Alonso & Pedro Ibañez, “Intelligent PV Module for Grid-
Connected PV Systems”, IEEE Transactions on Industrial electronics, Vol.53.No.4, Page(s):
1066 – 1073, August 2006.
[10]. Kosuke Kurokawa, Kazuhiko Kato , Masakazu Ito , Keiichi Komoto, Tetsuo Kichim,
& Hiroyuki Sugihara “The cost analysis of very large scale PV system on the world desert”.
Photovoltaic Specialists IEEE Conference, Page(s): 1672 – 1675, 2002.
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![IJRIME Volume1Issue5 ISSN‐2249‐ 1619
[11]. Souvik Ganguli and Sunanda Sinha, “assessment of solar photovoltaic generation
potential & estimation of possible plant capacity for 100 m2 available area in Kolkata”,
International journal of engineering research and studies, vol. 1, pages 82-92.
[12].Souvik Ganguli & Sunanda Sinha , “design of a 9KW grid connected solar photovoltaic
power plant using 100 m2 available area in Patiala” , International journal of engineering
research and studies, vol. 1, pages 12-27.
[13]. Souvik Ganguli & Sunanda Sinha,” estimation of annual energy generation from a small
grid connected solar photo voltaic power plant in Patiala”, International journal of
engineering research and studies, vol. 2, pages 43-44.
[14]. E.A. Alsema, P. Frank, K. Kato,” energy payback time of photovoltaic systems for three
major PV applications”, 2nd world conference on photovoltaic solar energy
conversion,Vienna, 6-10 July, 1998.
[15]. Bangyin Liu, Chaohui Liang and Shanxu Duan,”Design Considerations and Topology
Selection for DC-Module-Based Building Integrated Photovoltaic System”. 3rd IEEE
conference on industrial electronics and applications, pp. 1066-1070, 2008.
[16]. E.W. Smiley and L. Stamenic,” Optimization of Building Integrated Systems”. IEEE
29th conference on photovoltaic specialists. pp. 1501-1503, 2002.
[17]. Tymandra Blewett, Margaret Horne and Robert Hill, “Helidon Prediction of Shading on
Building Integrated Systems”. 26th IEEE conference on photovoltaic specialist. pp. 1393-
1396, 1997.
[18]. H. MauNs, M. Schmid, B. Blersch, P. Lechner, H. Schade, “BIPV Installation
Worldwide in ASI Technology”. Proceeding of 3rd IEEE world conference on photovoltaic
energy conversion. Vol.3, pp. 2375-2378, 2003.
[19]. Chang Ying-Pin and Shen Chung-Huang “Effects of the Solar Module Installing Angles
on the Output Power” IEEE 8th international conference on electronics measurement and
instruments, pp. 1-278 - 1-282, 2007.
[20]. [http:Energy Scenario] “Solar PV Industry 2010: Contemporary scenario and emerging
trends” available at www.isaonline.org/documents/ISA_SolarPVReport_May2010.pdf
[21]. [http:Energy Scenario] “the solar PV landscape in India” available at
www.solarindiaonline.com/.../The_Solar_PV_Landscape.pdf
[22]. [http: Solar Electric Systems] “Chapter Three Introduction to Solar Electric Systems”
available at www.kysolar.org/ky_solar_energy_guide/chapters/Chapter_3_PVintro.pdf
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[23]. [http: Series and Parallel connection] “Series and Parallel Wiring” available at
www.termpro.com/articles/spkrz.html.
[24]. [http: BP_7180_V2] “specification of PV module” available at
www.bp.com/liveassets/bp_internet/solar/bp.../b/BP_7180_V2.pdf
[25] [http: Photovoltaic modules] ―Photovoltaic modules, system and application available
at www.icpress.co.uk/etextbook/p139/p139_chap15.pdf
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talents in the organization to increase the success ratio in today’s competitive global
environment. HR managers have to manage all the challenges that they would face from
recruiting employees, training them, and developing strategies for retaining them and building up
an effective career management system for them. Just taking care of employees would not be
enough; new HR initiatives should also focus on the quality needs, customer-orientation,
productivity, stress, team work and leadership building.
REFERENCES
[1] Dr. Nagaraju Battu (2007), “Human Resource Development”
[2] Dr. Pritam Singh- HR, The Taskmaster, Times of India daily Ascent, 24th November, 2010
[3] Prof. Anitha H.S. “Succession Planning”, “Benchmarking for Infusing Competitive Culture
among Indian PSUs” and “Commercial viability of PSUs”, Deccan Herald, August 25,2009
[4] Mrs. Soumya K.R. (2010) “Assessment of training need and evaluation of training
effectiveness on employees of select ITes in Bangalore”
[5] Dr. Alvin Chan (2010), “Challenges of HRM”
[6] Rituparna Banerjee (2010), “Emerging trends on HRM”
[7] Punita Jasrotia Phukan (2009), “Changing HR paradigm in the ITes sector”
[8] K.P. Kanchana (2009), “Emerging trends in HR”
[9] Sanjeev Sharma, “Retention Strategies in ITes-BPO industry”
[10] www.bpoindia.org
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INTRODUCTION & MOTIVATION
Rapid technological growth in the areas of micro electro-mechanical systems and miniaturization
has spurred the development of a new kind of network. This network is composed of small,
inexpensive sensors capable of intelligent sensing. Much research has been done with the aim of
connecting large numbers of these sensors to create robust and scalable Wireless Sensor
Networks (WSNs) on the order of hundreds of thousands of devices. Communication usually
consists of source nodes which sense the data and return it to sink nodes over multiple hops.
Sink nodes may be ordinary sensor nodes or specialized base stations with greater resources.
Sensor network proponents envision a future in which thousands to millions of tiny sensor
devices will be embedded in almost every aspect of life. The goal is to create intelligent
environments capable of collecting massive amounts of information, recognizing significant
events automatically, and responding appropriately. Sensor networks facilitate “large-scale, real-
time data processing in complex environments” [14]. If sensor networks are to attain their
potential, however, secure communication techniques must be developed in order to protect the
system and its users. The need for security in military applications is obvious, but even more
benign uses, such as home health monitoring, require confidentiality so widespread deployment
and overall success of sensor networks will be directly related to their security strength.
SENSOR SECURITY CHALLENGES
The nature of large, ad-hoc, wireless sensor networks presents significant challenges in designing
security schemes. Some of the most pronounced challenges are described below.
Wireless Medium
The pervasive applications proposed for sensor networks necessitate wireless communication
links. Furthermore, the ad-hoc deployment of sensor motes makes wired communication
completely inappropriate. The wireless medium is inherently less secure because its broadcast
nature makes eavesdropping simple. Any transmission can easily be intercepted, altered, or
replayed by an adversary. The wireless medium allows an attacker to easily intercept valid
packets and easily inject malicious ones.
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Ad-Hoc Deployment
The ad-hoc nature of sensor networks means no structure can be statically defined beforehand.
The network topology is always subject to changes due to node failure, addition, or mobility.
Nodes may be deployed by air drop, so nothing is known of the topology prior to deployment.
Since nodes may fail or be replaced the network must support self-configuration. Security
schemes must be able to operate within this dynamic environment.
Hostile Environment
Most challenging factor is the hostile environment in which sensor nodes function. Motes face
the possibility of destruction or (perhaps worse) capture by attackers. Since nodes may be in a
hostile environment, attackers can easily gain physical access to the devices. Attackers may
capture a node, physically disassemble it, and extract from it valuable information (e.g.
cryptographic keys). The highly hostile environment represents a serious challenge for security
researchers.
Resource Scarcity
The extreme resource limitations of sensor devices pose considerable challenges to resource-
hungry security mechanisms. A representative example of a sensor device is the Mica mote. It
has a 4 MHz Atmel ATMEGA103 CPU with 128 KB of instruction memory, 4 KB of RAM for
data, and 512 KB of flash memory [7]. The radio operates at up to 40 Kbps bandwidth at a range
of a few dozen meters. Such hardware constraints necessitate extremely efficient security
algorithms in terms of bandwidth, computational complexity, and memory.
Immense Scale
Finally, the proposed scale of sensor networks poses a significant challenge for security
mechanisms. Simply networking tens to hundreds of thousands of nodes has proven to be a
substantial task. Security mechanisms must be scalable to very large networks while maintaining
high computation and communication efficiency.
ATTACKS & DEFENSES
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Security goals for sensor networks include the same four primary objectives as conventional
networks: availability, confidentiality, integrity, and authentication. Although sensor network
security is characterized by the same properties as traditional network security. Karlof and
Wagner identify two major classes of attackers: mote-class and laptop-class. Mote-class attackers
are constrained to the CPU, power, bandwidth, and range limitations of the mote platform.
Laptop-class attackers, however, may possess more powerful hardware such as a faster CPU, a
larger battery, a high-power radio transmitter, or a sensitive antenna. This section examines the
security attacks and corresponding defenses at each level of the network.
Physical Layer
Attacks at the physical level include radio signal jamming and tampering with physical devices.
Jamming- well-known attack on wireless communication is simply interference with the radio
frequencies used by a device’s transceiver. It represents an attack on the availability of a
network, thus creating a denial-of-service condition [14].
The standard defense against jamming involves the use of spread-spectrum or frequency hopping
techniques. Prevention of denial of service attacks is a difficult task. Since most sensor networks
currently use single frequency communication, Wood, Stankovic, and Son have proposed a
Jammed Area Mapping (JAM) service which emphasizes detection and adaptation in response to
jamming. They assume that only a portion of the network is being jammed and attempt to map
this area so it can be avoided. Nodes in the affected area switch to low power mode. Information
about jammed areas is passed to the network layer so it can successfully route packets around the
dead areas. If spread spectrum techniques cannot be incorporated into motes, then detection
algorithms such as JAM may be important in defending against jamming attacks.
Tampering A second problematic issue at the physical layer is the relative ease and potential
harm of device tampering. This problem is exacerbated by the large-scale, ad-hoc, pervasive
nature of sensor networks. Access to thousands of nodes spread over several kilometers cannot
be completely controlled [14]. Attackers may very well have greater physical access to nodes
than the network administrator. Nodes may be captured, interrogated, and compromised without
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difficulty. While node destruction is undesirable, node compromise may be even more dangerous
because of the cryptographic material compromised.
Link Layer
The link and media access control (MAC) layer handles neighbor-to-neighbor communication
and channel arbitration. Like the physical layer, the link layer is particularly susceptible to denial
of service attacks.
Collision If an adversary can generate a collision of even part of a transmission, he can disrupt
the entire packet [Perrig, Stankovic, and Wagner 2004]. A single bit error will cause a CRC
mismatch and possibly require retransmission. In some MAC protocols, a corrupted ACK may
cause exponential back-off and unnecessarily increase latency. Although error-correcting codes
protect against some level of packet corruption, intentional corruption can occur at levels which
are beyond the encoding scheme’s ability to correct. The advantage, to the adversary, of this
MAC level jamming over physical layer jamming is that much less energy is required to achieve
the same effect: preventing devices from successfully transmitting packets.
Exhaustion Another malicious goal is the exhaustion of a network’s battery power [10]. In
addition to the previous types of attacks, exhaustion may also be induced by an interrogation
attack. In the IEEE 802.11-based protocols, for example, Request To Send (RTS) and Clear To
Send (CTS) packets are used to reserve bandwidth before data transmission. A compromised
node could repeatedly send RTS packets in order to elicit CTS packets from a targeted neighbor,
eventually consuming the battery power of both nodes [10].
Unfairness A more subtle goal of the previously described attacks may be unfairness in the
MAC layer [10]. A compromised node can be altered to intermittently attack the network in
such a way that induces unfairness in the priorities for granting medium access. This weak form
of denial of service might, for example, increase latency so that real-time protocols miss their
deadlines [10].
Network Layer
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The network layer is responsible for routing packets across multiple nodes. Due to the ad-hoc
nature of sensor networks, every node must assume routing responsibilities. WSNs are
particularly vulnerable to routing attacks because every node is essentially a router.
Classifications of routing attacks are summarized below and are followed by a general discussion
of secure routing techniques.
False Routing Information The most direct attack on routing is to spoof, alter, or replay routing
information. This false information may allow adversaries to create routing loops, attract or repel
traffic, shorten or extend route lengths, increase latency, and even partition the network
[7].Clearly, the falsification of routing information can cripple a network. The standard solution
is to require authentication for routing information,
Selective Forwarding Selective forwarding is a more subtle attack in which some packets are
correctly forwarded but others are silently and intentionally dropped. A compromised node could
be configured to drop all packets, creating a so-called black hole. Since the network is capable of
handling node failure it may conclude that the compromised node has failed and find another
route. If the compromised node selectively forwards packets, the neighboring nodes will believe
that the malicious node is still functioning correctly and continue to route packets to the node.
Sinkhole Attack In the sinkhole attack, a node spuriously advertises a very good route to a sink
node (base station) in order to lure all nearby traffic to itself. Thus all traffic within some sphere
of influence is drawn into the sinkhole centered at the compromised node. This attack enables the
selective forwarding attack along with other attacks. An adversary mounting a laptop-class attack
may actually provide the fastest route to a sink by using its greater range to reach the sink in a
single hop.
Sybil Attack The Sybil attack occurs when a single node claims to be other nodes in the network.
Geographic routing protocols are particularly vulnerable to the Sybil attack since they are
designed with the assumption that no node can be in two places at once. If a node lies about it
location, it can significantly disrupt routing performance in geographic routing protocols.
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transmitting redundant packets have also been suggested. Secure routing methods protect against
some of previous attacks. Proposed techniques are described below.
Authentication & Encryption Link layer authentication and encryption protect against most
outsider attacks on a sensor network routing protocol. Even a simple scheme which uses a
globally shared key will prevent unauthorized nodes from joining the topology of the network. In
addition to preventing selective forwarding and sinkhole attacks, authentication and encryption
also make the Sybil attack impossible because nodes will not accept even one identity from the
malicious node [7]. SPINS and TinySec are two proposed solutions for link level encryption and
authentication.
Monitoring A more active strategy for secure routing is for nodes to monitor their neighbors and
watch for suspicious behavior [14]. In this approach, nodes act as “watchdogs” to monitor the
next hop transmission of the packet.
Probing Another proactive defense against malicious routers is probing [14]. This method
periodically sends probing packets across the network to detect blackout regions. Since
geographic routing protocols have knowledge of the physical topology of the network, probing is
especially well-suited to their use.
Redundancy is another strategy for secure routing [14]. An inelegant approach, redundancy
simply transmits a packet multiple times over different routes. Hopefully, at least one route is
uncompromised and will correctly deliver the message to the destination.
PROPOSED SOLUTIONS
While the majority of the research in sensor networks has focused on making them feasible and
useful, a few researchers have proposed solutions to the security issues discussed previously.
Sensor network security mechanisms can be divided into two categories: communication
protocols and key management architectures. Communication protocols deal with the
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cryptographic algorithms used to achieve availability, confidentiality, integrity, and
authentication. Key management architectures handle the complexities of creating and
distributing keys used by communication protocols.
Communication Protocols
Currently there have been two major secure communication protocols proposed for sensor
networks: SPINS [2] and TinySec [Karlof, Sastry, and Wagner 2004]. Both protocols work at the
link level to provide message confidentiality, authentication, and integrity using symmetric
cryptography. The limited memory and CPU speeds of sensor nodes almost completely exclude
the use of asymmetric cryptography sensor networks.
SPINS SPINS (Security Protocols for Sensor Networks) is comprised of two link layer
protocols: SNEP and µTELSA. SNEP (Secure Network Encryption Protocol) provides data
confidentiality, two-party authentication, and data freshness. Perrig et al. identify three patterns
of communication in sensor networks: node to base station, base station to node, and base station
to all nodes. SNEP handles the first two types, and µTELSA handles the last. In order to
minimize computation and memory requirements, SNEP bases all symmetric cryptographic
primitives (encryption, message authentication code, hash, and random number generator) on the
same block cipher, RC5. Another design goal is to minimize communication overhead. This is
accomplished by reducing the packet overhead to 8 bytes and by storing state information instead
of transmitting it with each packet.
SNEP supports data authentication, replay protection, and semantic security [11]. Authentication
is provided by calculating and appending a message authentication code (MAC) to each
message. A MAC is essentially a cryptographically secure checksum [Karlof, Sastry, and
Wagner 2004]. The MAC is recalculated upon reception and compared to the value in the
transmission. To implement replay protection, SNEP requires a synchronized counter value at
each node. The MAC is calculated using a secret key and the counter. As a result, out-of-sync
packets will not be accepted. SPINS includes a counter exchange protocol for synchronizing
counter values between two hosts. Although maintaining a synchronized counter adds significant
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strategies exist for accomplishing this task. Some of the major approaches are summarized
below.
LEAP The efficiency and speed of symmetric algorithms are well suited to sensor nodes and
have been the default choice for sensor network designers. Most symmetric schemes require keys
be loaded onto devices before deployment. Using a different key for every link provides the best
security against compromised nodes but is incompatible with the basic nature of sensor
networks. Sensor networks rely on data aggregation and in-network processing to increase
network efficiency. Nodes along the path consolidate data to reduce the overall number of
messages in the network. This cannot take place if messages are encrypted. In an effort to
balance these two extremes, LEAP [14] utilizes four types of keys for different security levels.
LEAP supports an individual key shared only with the base station, a pairwise key shared with
another sensor node, a cluster key shared with multiple neighboring nodes, and a group key
shared by all the nodes in the network. The advantage of LEAP is that it supports in-network
processing while minimizing the security impact of a compromised node to the node’s
immediate neighbors. LEAP provides a key for every need. This property offers convenience at
the cost of storage space and complexity, neither of which are abundantly available to sensor
nodes.
LKHW Another approach to key management is to use a hierarchy to store keys. Pietro et al.
propose a scheme based on Logical Key Hierarchy (LKH) built on top of directed diffusion.
Directed diffusion is a data-centric routing protocol that uses exploratory flooding to find the
best path to send events of interest. The extension of LKH over directed diffusion comprises the
LKH Wireless (LKHW) protocol. LKHW is a secure multicast scheme that enforces backward
and forward secrecy. New nodes cannot decrypt old traffic, and evicted nodes cannot decrypt
future traffic. LKHW uses a tree structure to store keys. The root of the tree serves as the key
distribution center (KDC), and each leaf represents a user. Each leaf stores the set of keys
belonging to its direct ancestors up to the KDC. The reason for using a tree structure is to
increase the efficiency of re-keying. Re-keying occurs whenever a node joins or leaves the
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group. The energy required for re-keying is shown to be approximately logarithmic to the group
size.
Random Key Predistribution Another novel approach to key management is random key
predistribution [2]. In this strategy, a random pool of keys from the key space is preloaded into
each node. Two nodes must find a common key in their sets in order to communicate. A
challenge-response protocol is used to verify that two nodes have a key in common.
TinyPK Despite the fact that asymmetric cryptography has been almost universally considered
to be too resource-intensive for use in sensor networks, there have been some efforts to adapt
public cryptography techniques to sensor devices. TinyPK [13] is one such project that uses the
RSA cryptosystem to handle symmetric key distribution. To minimize calculations by the sensor
motes, e=3 is used as the public exponent. Encryption simply requires cubing a 1024-bit number
and taking its residue modulo a large prime number. Implementing a public-key system requires
a modest amount of infrastructure including a Certificate Authority (CA). The CA’s public key is
preloaded onto each node and is used to verify messages from the CA. Despite the adaptations,
TinyPK still performs slowly by current standards. Table 1 summarizes the operation times for
RSA encryption at various key sizes.
RSA Key Size Time (sec)
512 3.8
768 8.0
1024 14.5
Table 1: RSA encryption (exponentiation) times
Watro et al. confess that the current implementation is too slow for RSA private operations
(decryption) since execution times would be on the order of tens of minutes. They suggest using
TinyPK as a method of authenticating external parties to the sensor network and moving the
computationally expensive operations to the external device when possible. Although public key
cryptography possesses many advantages in handling key management, it is currently infeasible
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for node-to-node communication in sensor networks. Perhaps asymmetric techniques will be
viable on more powerful hardware of the future. Most researchers predict, however, that devices
will ride Moore’s Law down the price curve instead of increasing in speed. If this is the case,
then algorithmic optimizations will be required for public-key systems.
CONCLUSION
Sensor networks hold the potential to transform the way computing affects life. In order to reach
this potential, secure communication must be achieved. The wireless, ad-hoc, resource-limited
nature of sensor networks creates substantial challenges for researchers. At the physical layer,
probable attacks include frequency jamming and device tampering, two techniques with known
solutions but entailing greater financial cost. The link layer of sensor networks is also susceptible
to denial of service attacks in the form of maliciously induced collisions and exhaustion attacks.
The network layer is particularly vulnerable since every node in a sensor network is a router.
Although link layer encryption and authentication serve as a first layer of defense, maximum
security can only be achieved by designing routing algorithms with security in mind. SPINS and
TinySec satisfactorily address the issue of link layer encryption, authentication, and integrity but
require key management architectures to be practical. Current key management solutions are not
sufficiently adapted to the unique requirements of sensor networks. If sensor networks are to
reach their potential, secure communication must exist.
REFERENCES
[1] Agrawal, Dharma P.; Qing-An Zeng. 2003. Introduction to Wireless and Mobile Systems.
Brooks/Cole – Thompson, Pacific Grove, CA.
[2] Chan, H., A. Perrig, and D. Song. Random Key Predistribution Schemes for Sensor
Networks. IEEE Symposium on Security and Privacy (SP) (May 11 - 14, 2003).
[3] Hill, Jason, Robert Szewczyk, Alec Woo, Seth Hollar, David Culler, and Kristofer Pister.
System architecture directions for networked sensors. In Proceedings of the Ninth
International Conference on Architectural Support for Programming Languages and
Operating Systems (ASPLOS IX) (November 2000).
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[4] Hu, Y.C., A. Perrig, and D.B. Johnson. Rushing Attacks and Defense in Wireless Ad Hoc
Network Routing Protocols. Proceedings of the ACM Workshop on Wireless Security
(WiSe'03) (San Diego, California, September 19, 2003).
[5] Huang, Q., J. Cukier, H. Kobayashi, B. Liu, and J. Zhang. Fast Authenticated Key
Establishment Protocols for Self-Organizing Sensor Networks. Proceedings of the
Workshop on Wireless Sensor Networks and Applications, (WSNA'03) (San Diego,
California, September 19, 2003).
[6] Jolly, G., M.C. Kuscu, P. Kokate, and M. Younis. A Low-Energy Key Management
Protocol for Wireless Sensor Networks. IEEE Symposium on Computers and
Communications (ISCC'03). (Kemer – Antalya, Turkey, June 30 - July 3 2003).
[7] Karlof C. and D. Wagner. Secure Routing in Wireless Sensor Networks: Attacks and
Countermeasures. Proceedings of the First IEEE International Workshop on Sensor
Network Protocols and Applications (SNPA'03) (11 May 2003).
[8] Karlof, Chris, Naveen Sastry, and David Wagner. TinySec: A Link Layer Security
Architecture for Wireless Sensor Networks. Proceedings of the Second ACM Conference
on Embedded Networked Sensor Systems (SenSys’04) (November 3 - 5, 2004).
[9] Law, Y. W., S. Dulman, S. Etalle, and P. Havinga. Assessing Security-Critical Energy-
Efficient Sensor Networks. 18th IFIP TC11 Int. Conf. on Information Security, Security
and Privacy in the Age of Uncertainty (SEC) (Athens, Greece, May 2003).
[10] Perrig, Adrian, John Stankovic, and David Wagner. Security in Wireless Sensor
Networks. Communications of the ACM, Volume 47, Issue 6 (June 2004): 53-57.
[11] Perrig, Adrian, Robert Szewczyk, Victor Wen, David Culler, and J.D. Tygar. SPINS:
Security protocols for sensor networks. In The Seventh Annual International Conference
on Mobile Computing and Networking (MobiCom 2001), (2001).
[12] Pietro, R.D., L.V. Mancini, Y.W. Law, S. Etalle, and P. Havinga. LKHW: A Directed
Diffusion-Based Secure Multicast Scheme for Wireless Sensor Networks. International
Conference on Parallel Processing Workshops (ICPPW'03) (Kaohsiung, Taiwan. October
6 - 9, 2003).
[13] Warto, Ronald, Derrick Kong Sue-fen Cuti, Charles Gardiner, Charles Lynn, and Peter
Kruus. TinyPK: Securing Sensor Networks with Public Key Technology.
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[14] Wood, A.D. and J.A. Stankovic. Denial of Service in Sensor Networks. IEEE Computer,
Volume: 35, Issue: 10 (Oct. 2002):48-56.
[15] Wood, A.D., J.A. Stankovic, and S.H. Son. JAM: A Jammed-Area Mapping Service for
Sensor Networks. In The 24th IEEE International Real-Time Systems Symposium (RTSS)
(Cancun, Mexico, December 2003).
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1. INTRODUCTION
The fixed charge transportation problem was originally formulated by G.B Dantzig and
W.Hirisch [8] in 1954.Thirwani et.al. [9] in 1997 developed an algorithm for finding the time
cost trade off pairs in a fixed charge bi-criterion transportation problem with restricted flow.
Later, Arora et.al [1-2] also studied the indefinite quadratic transportation problem.
Another important class of transportation problem consists of capacitated transportation problem.
If the total flow in a transportation problem with bounds on rim conditions is also specified, the
resulting problem makes the transportation problem more realistic. Moreover, if the total
capacity of each route is also specified then optimal solution of such problems is of greater
importance which gives rise to a capacitated transportation problem. Many researchers like A.K
Bit et.al. [6], K.Dahiya et.al. [7] Have contributed in this field.
In 1976, Bhatia et .al. [5] provided the time cost trade off pairs in a linear transportation
problem. Then in 1994, Basu et.al. [4] Developed an algorithm for the optimum time cost trade
off pairs in a fixed charge linear transportation problem giving same priority to cost as well as
time. Arora et.al. [3] Studied time cost trade off pairs in an indefinite quadratic transportation
problem with restricted flow.
In this paper, a capacitated fixed charge indefinite quadratic transportation problem with bounds
on rim conditions giving same priority to cost and time is studied along with restriction on the
total flow. An algorithm to identify the efficient cost time trade off pairs for the problem is
developed.
2. PROBLEM FORMULATION
Linear functions are widely used in modeling a mathematical optimization problem. Also
quadratic functions and quadratic problems are the least difficult to handle out of all non linear
programming problems. A fair number of functional relationships occurring in the real world are
truly quadratic. For example-Kinetic energy carried by a rocket or an atomic particle is
proportional to the square of its velocity. There are many non linear relationships occurring in
nature that are capable of being approximated by quadratic functions.
Consider a capacitated fixed charge bi-criterion indefinite quadratic transportation problem given
by
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u i2 v 2 zij (i, j) N 1 And N2
j
2
(11)
F ij Is the change in fixed cost F i when some non basic variable xij enters the basis.
iI
z1 = value of c x
iI jJ
ij ij at the current basic feasible solution corresponding to the basis B.
z2 = value of d x
iI jJ
ij ij at the current basic feasible solution corresponding to the basis B.
ij = level at which a non basic cell (i,j) enters the basis replacing some basic cell of B.
N1 and N2 denotes the set of non basic cells (i,j) which are at their lower bounds and upper
bounds respectively.
Note: u1 , v1j , u i2 , v 2 are the corresponding dual variables which are determined by using equations
i j
(8) to (11) and taking one of the ui ,s or vj ,s. as zero.
Proof: Let z0 be the objective function value of the problem (P2).
Let z0 =z1z2 + F0 where F0 = F i
iI
Let z be the objective function value at the current basic feasible solution X= {xij}
corresponding to the basis B obtained on entering the non basic cell xij N1 in to the basis which
undergoes change by an amount ij given by
min{uij – lij ; xij - lij for all basic cells (i,j) with a (- )entry in the -loop; uij – xij for all basic
cells (i,j) with a (+ )entry in the -loop}.
Then z = z1 ij cijz1 z 2 ij dijzij F0 Fij
ij
2
z - z0 = z1z2 + z2 ij (cij-z1ij) + z1 ij (dij – z2ij) + ij (cij-z1ij) (dij – z2ij) - z1z2 + F ij
2
= ij [z2 (cij-z1ij) + z1 (dij – z2ij) + ij (cij-z1ij) (dij – z2ij)]+ F ij
This basic feasible solution will give an improved value of z if z < z0 .It implies that
ij [z2 (cij-z ij) + z1 (dij – z ij) + ij (cij-z ij) (dij – z ij)]+ F ij < 0
1 2 1 2
(12)
Therefore one can move from one basic feasible solution to another basic feasible solution on
entering the cell (i,j) N1 in to the basis for which condition (12) is satisfied.
It will be an optimal basic feasible solution if
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R1 ij z1(dijzij )z 2(cijz1 )ij(cijz1 )(dijzij ) Fij 0(i, j) N1
ij
2
ij ij
2
Similarly, when non basic variable xij N2 undergoes change by an amount ij then
z - z = ij [ ij (cij-z ij) (dij – z ij)- z2 (cij-z ij) - z1 (dij – z ij) +]+ F ij < 0
0 1 2 1 2
It will be an optimal basic feasible solution if
R ij ij ij(cijz1 )(dijzij )z1(dijzij )z 2(cijz1 ) Fij 0(i, j) N 2
2
ij
2 2
ij
Definition: Corner feasible solution: A basic feasible solution {yij} i I´, j J´ to (P2´) is
called a corner feasible solution (cfs) if ym+1,n+1 = 0
Theorem 2. A non corner feasible solution of (P2´) cannot provide a basic feasible solution to
(P2).
Proof: Let {yij}I´ xJ´ be a non corner feasible solution to (P2´).Then ym+1,n+1 = (>0)
Thus y
iI
i, n 1 yi, n 1 ym 1, n 1
iI
= yi, n 1
iI
= Ai P (13)
iI
y
iI
i, n 1 Ai (P )
iI
Now, for i I,
y
jJ
ij A i' Ai
(14)
yij Ai
iI jJ iI
(13) and (14) implies that y
iI jJ
ij P
This implies that total quantity transported from the sources in I to the destinations in J is P +
> P, a contradiction to assumption that total flow is P and hence {yij}I´ xJ´ cannot provide a
feasible solution to (P2).
Lemma 1: There is a one –to-one correspondence between the feasible solution to (P2) and the
corner feasible solution to (P2´).
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Since R1 ≥ 0 (i, j) N 1 and R ij 0(i, j) N2 , the solution in table 3 is an optimal solution
ij
2
of (P2´) and hence yields an optimal solution of (P2).Therefore minimum cost = (102 x 125) +
700 = 13450 and corresponding time is T1 = 15. Hence the first time cost trade off pair is (13450,
15)
M if t ij T1 15
1
Define cij = 1
and solving the resulting problem, the next trade off pair is
cij if t ij < T 15
(13450, 14). Similarly, the other pairs are (14266, 13), (14266, 12), (16500, 10).
6. CONCLUSION:
In order to solve a capacitated fixed charge bi – criterion indefinite quadratic transportation
problem, given problem is separated in to two problems. One of them being an indefinite
quadratic transportation problem has its optimal solution at an extreme point. After calculating
the cost, corresponding time is read. This is the first cost time trade off pair. Proceeding likes this
we get the various trade off pairs.
REFERENCES
[1] Arora, S.R., Khurana, A., “A paradox in an indefinite quadratic transportation problem”,
International Journal of Management and Systems, 18, (2002), 301-318
[2] Arora, S.R., Khurana, A., “Three dimensional fixed charge bi – criterion indefinite quadratic
transportation problem”,Yugoslav Journal of Operations Research,14(1),(2004),83-97
[3] Arora, S.R., Thirwani, D., Khurana, A.,“An algorithm for solving fixed charge bi – criterion
indefinite quadratic transportation problem with restricted flow”, International Journal of
optimization: Theory, Methods and Applications,1(4),(2009),367-380
[4] Basu, M, Pal, B.B and Kundu, A., “An algorithm for the optimum time cost trade off in a
fixed charge bi-criterion transportation problem’’, Optimization, 30, (1994), 53-68
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[5] Bhatia, H.L, Swarup, K and Puri , M.C., ‘‘Time cost trade off in a transportation problem’’,
Opsearch, 13(3-4),(1976),129-142
[6] Bit, A.K. Biswal, M.P. , Alam, S.S., “Fuzzy Programming technique for multi- objective
capacitated transportation problem” , Journal of Fuzzy Mathematics,1(2),(1993),367-376
[7] Dahiya, K. and Verma, V., ‘‘Capacitated transportation problem with bounds on rim
conditions’’, Europeon journal of Operational Research, 178, (2007), 718-737
[8] Hirisch, W.M. and Dantzig, G.B., ‘‘the fixed charge problem’’, Naval Research Logistics
Quarterly, 15(3), (1968), 413-424
[9] Khanna,S. , Thirwani,D. and Arora, S.R., ‘‘An algorithm for solving fixed charge bi –
criterion transportation problem with restricted flow”, Optimization, 40,(1997),193-206
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ii. Structure the hierarchy with the decision maker’s objective at the top with the
intermediate levels capturing criteria on which subsequent levels depend and the bottom
level containing the alternatives, and
iii. Construct the set of n× n pair wise comparison matrices for each to the lower levels with
one matrix for each element in the level immediately above. The pair wise comparisons
are made suing the relative measurement scale (as discussed above). The pair wise
comparisons capture a decision maker’s perception of which element dominates the
other.
iv. There are n(n-1)/2 judgments required to develop the set of matrices in step 3.
Reciprocals are automatically assigned in each pair wise comparison.
v. The hierarchy synthesis function is used to weight the eigenvectors by the weights of the
criteria and the sum is taken over all weighted eigenvector entries corresponding to those
in the next lower level of the hierarchy.
vi. After all the pair wise comparisons are completed, the consistency of the comparisons is
assessed by using the Eigen value, λ, to calculate a consistency index, CI:
CI = (λ-n)/ (n-1).
Where n is the matrix size. Judgment consistency can be checked by taking the
consistency ratio (CR) of CI with the appropriate value in table 2, given below. Saaty
[1980] suggests that the CR is acceptable if it does not exceed 0.10. If the CR is greater
than 0.10, the judgment matrix should be considered inconsistent. To obtain a consistent
matrix, the judgments should be reviewed and repeated.
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Analytical Hierarchy Process (AHP) as a potential decision making method for use in project
management. They used contractor prequalification problem as an example. For this a
hierarchical structure is constructed for the prequalification criteria and the contractors wishing
to prequalify for a project. They found that by applying the AHP, the prequalification criteria can
be prioritized and a descending-order list of contractors can be made in order to select the best
contractors to perform the project. Their paper presents group decision-making using the AHP.
Heung-Suk Hwang et al. (2005) used a supplier selection analysis model with the help of AHP
method.
V. THE EVALUATING MODEL CONSTRUCTION
When enterprises evaluate a thing, which have n index factors, they are marked as
c1,c2,c3………………… cn. These index factors compose a finite set C.
C = { c1,c2,c3………..cn}
According to actual needs, the revies are divided into m degree v1,v2,v3………..vm. they
compose a finite set of reviews V.
V= {v1,v2,v3……………..vm}
When enterprises need to value a thing from a several different aspects, te result is compressive.
The result is a fuzzy set B from reviews set V. Because V is a finite set, B is also a finite set.
B = b1/v1+ b2/v2 + b3/v3+bm/vm. (1)
It abbreviate as m dimension fuzzy vectors:
B= {b1, b2, b3………………bm}
Its case is V, and bj is the membership of the corresponding elements in B and bj Є [0,1] =
1,2,3…………m.
In the actual evaluating, the importance of each element is different. This is an objective fact.
The set of factors is fuzzy one. A, which is the elements set U in the case; A is also a finite set.
So the factor set is also a finite fuzzy set.
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A = a1/c1 + a2/c2 + r11 r12 ……. r1m
a3/c3……………………. an/cn
r 21 r22 …….. r2m
Similarly, A can also be said by n-
dimensional fuzzy vectors. : : : :
A = (a1, a2, a3………………… : : : : an )
Its case us C, ai is the r n1 r n2 …….. rnm membership
of the corresponding elements in A, ai Є
[0, 1], Σi=1n ai = 1.
The fuzzy comprehension evaluation is to optimize the fuzzy set A by fuzzy relation B = AR
B= A.R = (a1, a2, a3………..an).
This is fuzzy comprehension evaluation model. B is the result of the fuzzy comprehension
evaluation, and it is m- dimensional fuzzy row vectors; A is the weight set of the model, and it is
n- dimensional fuzzy row vectors; R is the fuzzy relations from C to V, and it is a n×m matrix, in
which the rij is the possibility of remark j for element i.(Ting Wang at el.2010)
VII. CASE STUDY
Here the Educational Institutions selected for the analysis are three in nos. and all are the
engineering institutions. The basic reason behind this selection is that today, the students of
these collages are facing a lot of problems regarding their studies, faculties, practicals provided
by the institution etc. In this paper we test the knowledge management level of colleges’ on
the anvil of different criteria. The selected criteria are : Teaching Practices, Practical Training
and Examination Pattern. These criteria are sub divided in sub criteria the details of which are
given as follows. Fig.3 shows the hierarchical structure.
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Saaty (2008) developed the following steps for applying AHP:
i. Define the problem and determine its goal,
ii. Structure the hierarchy with the decision maker’s objective at the top with the
intermediate levels capturing criteria on which subsequent levels depend and the bottom
level containing the alternatives, and
iii. Construct the set of n× n pair wise comparison matrices for each to the lower levels with
one matrix for each element in the level immediately above. The pair wise comparisons
are made suing the relative measurement scale (as discussed above). The pair wise
comparisons capture a decision maker’s perception of which element dominates the
other.
iv. There are n(n-1)/2 judgments required to develop the set of matrices in step 3.
Reciprocals are automatically assigned in each pair wise comparison.
v. The hierarchy synthesis function is used to weight the eigenvectors by the weights of the
criteria and the sum is taken over all weighted eigenvector entries corresponding to those
in the next lower level of the hierarchy.
vi. After all the pair wise comparisons are completed, the consistency of the comparisons is
assessed by using the Eigen value, λ, to calculate a consistency index, CI:
CI = (λ-n)/ (n-1).
Where n is the matrix size. Judgment consistency can be checked by taking the
consistency ratio (CR) of CI with the appropriate value in table 2, given below. Saaty
[1980] suggests that the CR is acceptable if it does not exceed 0.10. If the CR is greater
than 0.10, the judgment matrix should be considered inconsistent. To obtain a consistent
matrix, the judgments should be reviewed and repeated.
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[I] INTRODUCTION
In telecommunication; there are several types of micro strip antennas( also known as printed
antennas) the most common of which is the micro strip patch antenna or patch antenna. A patch
antenna is a narrowband, wide-beam antenna fabricated by etching the antenna element pattern
in metal bonded to an insulating dielectric substrate with a continuous metal layer bonded to the
opposite side of the substrate which forms a ground plane. Common micro strip antenna
radiator shapes are square, rectangular, circular and elliptical but any continuous shape is
possible. Some patch antennas eschew a dielectric substrate and suspend a metal patch in air
above a ground plane using dielectric spacers, the resulting structure is less robust but provides
better band width. Because such antennas have a very low profile; are mechanically rugged and
can be conformable, they are often mounted on the exterior of aircraft and spacecraft or are
incorporated into mobile radio communication devices; [1].
Micro strip antennas are also relatively inexpensive to manufacture and design because of the
simple two dimensional physical geometry. They are usually employed at UHF and higher
frequencies because the size of the antenna is directly tied to the wavelength at the resonance
frequency [2].
A single patch antenna provides a maximum directive gain of around -6 dBi. It is relatively easy
to print on array of patches on a single (large) substrate using lithographic techniques. Patch
arrays can provide much higher gain than a single patch at little additional cost; matching and
phase adjustment can be performed with printed micro strip feed structures, again in the some
operation that form the radiating patches. The ability to create high gain arrays in a low profile
antenna is one reason that patch arrays are common on [3] airplanes and in other military
application. An array antenna is a special arrangement of basic antenna components involving
new factors and concepts. Before you begin studying about arrays, you need to study some new
terminology [4].
An array antenna is made up of more than one ELEMENT, but the basic elements is generally
the dipole. Sometimes the basic element is made longer or shorter than a half-wave, but the
deviation usually is not great [4] [5]. Typically an antenna is tuned for a specific frequency and is
effective for a range of frequencies that are usually on that resonant frequency. Some antenna
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design have multiple resonant frequencies, and some are relatively effective over very broad
range of frequencies. [6]
Gain as a parameter measures the efficiency of a given antenna with respect to a given norm,
usually achieved by modification of its directionality. An antenna with a low gain emits
radiation with about the same power in all directions, whereas high gain antenna will radiate in
particular direction. The radiation pattern of an antenna is the geometric pattern of the relative
field strengths of field emitted by the antenna. In field of antenna the term “radiation pattern”
most commonly refers to directional (angular) dependence of radiation from the antenna or other
source. Usually, the directivity is expressed in dBi. The reason that the units are dBi, (decibel
relative to an isotropic radiations that for n isotropic radiator, the radiated lower density is a
constant and therefore equals the average radiated power density ( the denominator). The angle
across the main lobe of an antenna pattern, between the two directions, at which, the antenna’s
sensitivity is half its maximum value at the centre of the lobe. It is abbreviated as HPBW[7][8].
As an electromagnetic wave travels through the different parts of the antenna system (radio, feed
line, antenna, free space) it may encounter differences in impendence (E/H; V/I, etc.) At each
interface, depending on the impedance match, some fraction of the wave’s energy will reflected
back to the source [5], forming a standing wave in the feed line. The ratio of maximum power to
minimum power in the wave can be ratio (SWR). A SWR of 1:1 is ideal. A SWR of 1.5:1 is
considered to be marginally acceptable in low power application. Efficiency is the ratio of
power actually radiated to the power put into antenna terminals. The bandwidth of an antenna
is the range of frequencies over which it is effective, usually centered on the resonant frequency.
The band width of antenna may be increased by several techniques, including using thicker
wires, replacing wires with cages to simulate a thicker wire, tapering antenna components (like
in a feed horn); and combining multiple antenna into a single assembly and allowing the natural
impedance to select correct antenna, small antenna are usually preferred for convenience, but
there is a fundamental limit relating bandwidth, size and efficiency. The polarization of an
antenna is the orientation of the electric field (E-plane) of the radios waves with respect to the
Earth’s surface and is determined by physical structure of the antenna and by its orientation. It
has nothing in common with antenna directionality terms: horizontal, vertical and circular (9)
[10]
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In high performance aircraft, satellite and missile applications, where size, weight, cost,
performance, ease of installation and aerodynamic profile are constraints, and low profile
antenna may be required. To meet there requirement microstrip antenna can be used. These
antennas are low profile, conformable to planar and non-planar surfaces. Simple and
inexpensive to manufacture using modern printed-circuit technology. Mechanically robust when
mounted on rigid surfaces compatible with MMIC design [11].
There are many configurations that can be used to feed micro strip antenna. The four most
popular are :-
Microstrip line
Coaxial cable
Aperture coupling
Proximity coupling
The micro strip line feed is easy to fabricate; simple to match by controlling the inset position
and rather simple to model. Because the dimensions of the patch re finite along the length and
width; the fields at the edges of the patch undergo fringing. The amount of fringing is a function
of the dimensions of the patch and the height of the substrate. Due to fringing field antenna
radiate. Fringing Fields Shown in Figure 1.
Figure 1 Fringing Field Figure 2 Patch Antenna
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[II] FEED NETWORK
Feed is of different types but most popular feed are –
Transformer feed
Microstrip line feed
Coaxial cable feed
Aperture coupling feed
Proximity coupling feed.
Out of above mentioned feed for micro strip patch antenna feed applied to it is transformer feed
type. Suppose impendence at antenna is 100Ω by transformer type feed 100Ω . This 50Ω
impendence known as terminating impendence. Terminating impendence matches to probe
impedance hence power delivered to micro strip patch antenna is maximum. [11]
The exact location of the probe which can guarantee the desired performance is not given in the
literature. So, hit and trial method is used to locate the co-ordinates of probe feed which can
provide satisfactory output. Using hit and trial, the co-ordinates of the probe were found to be
(x,y) =(6,2).
[III] DESIGN OF RECTANGULAR PATCH ANTENNA WITH PROBE FEED.
The three essential parameters for the design of a rectangular patch antenna are:- The resonant
frequency of the antenna must be selected appropriately. The personal communication system
(PCS) uses the frequency range from 1850-1990 MHZ. Hence the antenna design must be able
to operate in this frequency range. The resonant frequency selected for our design is 1.9 GHZ.
The dielectric material selected for our design is FR4 which has a dielectric constant of 4.4. A
substrate with a high dielectric constant has been selected since it reduces the dimensions of the
antenna.
For the micro strip patch antenna to be used in cellular phones, it is essential that the antenna is
not bulky. Hence, the height of the dielectric substrate is selected as 1.6mm.
Calculation of width (W) :- The width of the micro strip patch antenna is given by :
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W= C____________
2f0√(Єr+1/2)
Substituting C=3e8m/s ; Єr= 4.4 and f0 = 1.9GHZ
We get W = 0.048 m = 48.0mm
Calculation of Effective dielectric constant (Єreff) :-
The effective dielectric constant is calculated as : Єreff = (Єr+1)/(Єr-1)/2[1+12h/w]-1/2
Substituting Єr =4.4; w= 48.0mm and h=1.6mm we get Єreff =4.14
Calculation of the Effective length (Leff) :- The effective length is given as Leff = C/(2
f0√Єreff).
Substituting Є reff=4.14,c=3e8m/s and f0=1.9 GHz.
Weget : Leff = 0.0388m = 38.8mm
Calculation of the length extension (∆ L):- The length extension is given as :
Substituting the values, we get; ∆ L=.412h(Єreff+ .3)( w/h+.264)/(Єreff.-.258)(w/h+.8)
Calculation of actual length of patch (L):-
The actual length is obtained by:
L= (Leff .– 2∆L )
Substituting the values, we get:
L= 37.3mm
In general, top view of probe, Feed rectangular patch micro strip antenna is shown in Fig.2.
Geometry probe feed patch antenna shown in Figure.2.
[IV] RESULTS AND ANALYSIS
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Figure 7 SMITH CHART
[V] CONCLSION
It is seen that the design adopted for the probe feed rectangular micro strip patch antenna are
accurate. This antenna can be used at 1.88 GHZ frequency for mobile communication and
computing applications where the frequency of operation is 1.88 GHZ.
For antenna to work properly the VSWR must be less than two and return loss must be less than
10dB, only then the antenna will radiate or receive the power with minimum reflection. As
designed antenna has a return loss -23.5dB and VSWR 1.15 at a frequency of 1.88 GHZ, so this
antenna is used in mobile communication and computing satisfactorily. Probe feed rectangular
micro strip antenna are ideal for mobile communication, application where weight is the main
constraint. Due to unidirectional radiational pattern antenna plays important role in next
generation mobile communication and computing. Cost of power of mobile communication
system is saved due to this antenna.
[VI] REFERENCES
[1] Y Li, C. Chen, Y.cho “ A unified optimization Framework for microelectronics Industry”
Department of communication Engineering, national chiao Tung university, Taiwan
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[2] Tang, W.chow, Y,many microstrip line Discontinuities on one General Field – Based circuit
model, city university of Hon Kong, china University of waterloo, Canada.
[3] Caver K, and Mink J,. Micro strip Antenna Technology, IEEE, Transactions on Antenna and
propagation, vol.29, No. 1, January 1981.
[4] D.N. Schaubert, “Micro strip antennas, “ Electromagnetic, vil.12, pp.381-401, 1992.
[5] G.W. Garvin, R.E.Munson, L.T. Ostwald and K.G.Schroeder,” Low pro file electrically
small missile base mounted micro strip antenna,” in Dig int-syom... Antenna Propagation soc,
urbana, IL, June 1975, pp. 224-247.
[6] J.Q.Howell “Micro strip antennas” IEEE Trans Antenna propagation, vol. AP-23, No. 1,
pp.. 90-93, Jan 1975.
[7] I.R.J.Mailloux, J.Mcilvenna and N. Kernweis, “Micro strip array technology” IEEE
Trans. Antenna and propagation, vol.AP-29 No. 1, pp 25-38, Jan.1981.
[8] H.D.Weinschel, “Progress report on development of micro strip cylindrical arrays for
sounding rockets,” physic. And Sci. Lab, NEW Mexico state univ, LAS Cruces, 1973.
[9] J.R. James and G.J. Wilson, “New design techniques for microstrip antenna array” in
proc. 5th European Micro. Conf, Hamburg, Sept. 1975, pp. 102-106.
[10] Balanis, Antenna theory.
[11] R.D.Kanphade, D.G.Wakade and N.T.Markad “Micro strip patch antenna : computer
Aided Design Methology, International Journal of Electronics Communication Engineering,
Rohini, New Delhi, Octomber 2011.
[12] FDTD IE3D Reference Manual, Fremont : Zealand software Inc, 2006.
[16]K. Dessouky & 1. Ho, Propagation Results from the Sat el 1 i t e- l a Experiment , KAT-X
Quart er l y , JPL, No. 17, October 1988, pp7-12.
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[17]J. P. McCeehan and A. Bateman, Phase-locked transparent tone-in-band TTIB: A new
spectrum configuration particularly suited to the transmission of data over SSB mobile radio
networks, IEEE Trans on Conun~, Vol.COM-32, No.1, Jan. 1984, pp 81-87.
[18]A. Kanso, Novel Signal Processing Techniques for Pilot-Based SSB Mobile Radio Systems,
Ph.D Thesis, Dept. of Elec. Eng., Univ of Bath, Bath UK, 1985.
[19]A. Bateman and D.M. Haines, Direct Conversion Transceiver for Compact Low-Cost
Portable Mobile Radio Terminals, This conference Record.
[20]A. Baternan, R.J. Wilkinson and J.D.Marvi11, The Application of Digital Signal Processing
to Transmitter Linearisation, IEEE Eurocon 88, Stockholm, Sweden, 13'h-17th July 1988.
[21]C.R. Green, A.A. Lane, R. Shulka and P.N. Tombs,GaAs M
MICs for use in Phased Array Radar T/R Modules, IEE Colloquium on 'Electronically Scanned
Antennas, 21' January 1988, London, UK.756
[22]Advances in smart antenna system. Dr. D.G. Wakade and D.G. Rameshwer kawitkar SSGM
college of Engineering shegaon 444203 . received on 19th Jan 2005 accepted on 26th June 2005.
Journal of scientific and industrial research Vol.64, September 2005, PP 660- 665
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- 1. IJRIME Volume1Issue5 ISSN-2249- 1619 Sr. TITLE & NAME OF THE AUTHOR(S) Page No. No. 1 REAL TIME NETWORK MONITORING SYSTEM IN LAN ENVIRONMENT 1 M. Shoaib Yousaf , Ahmed Mattin , Ahsan Raza Sattar 2 QUALITY OF WORKING LIFE IN INSURANCE SECTOR 12 Rita Goyal 3 REFACTORABILITY ANALYSIS USING LINEAR REGRESSION 23 Gauri Khurana, Sonika Jindal 4 OPTIMIZING FILTERING PHASE FOR NEAR‐DUPLICATE DETECTION OF WEB PAGES USING TDW‐MATRIX 38 Tanvi Gupta 5 STUDY AND DESIGN OF BUILDING INTEGRATED PHOTO VOLTAIC SYSTEM AT HCTM CAMPUS KAITHAL, HARYANA 47 Rajeev Kumar, Gagan Deep Singh 6 FUNDS MANAGEMENT OF ICICI BANK 64 Manju Sharma 7 EMERGING TRENDS IN HUMAN RESOURCE MANAGEMENT—A CHALLENGE TO THE ITES 77 Raunak Narayan 8 FUNDAMENTAL CHALLENGES IN EMERGENT FIELD OF SENSOR NETWORK SECURITY AND INITIAL APPROACHES TO SOLVE 88 THEM D. P. Mishra, M. K. Kowar 9 THE ECONOMICS & BUSINESS OF EUROPEAN LEAGUE FOOTBALL 105 Rosy Kalra 10 AN ALGORITHM FOR SOLVING A CAPACITATED FIXED CHARGE BI‐CRITERION INDEFINITE QUADRATIC TRANSPORTATION 123 PROBLEM WITH RESTRICTED FLOW S.R. Arora, Kavita Gupta 11 IMPACTS OF USE OF RFBIDW ON TAXATION 141 Sulatan Singh, Surendra Kundu, Madhu Arora 12 EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF EDUCATIONAL INSTITUTIONS USING FCE AND AHP 148 Mohit Maheshwarkar, N. Sohani, Pallavi Maheshwarkar 13 EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF EDUCATIONAL INSTITUTIONS USING ANALYTICAL HIERARCHY 165 PROCESS: A CASE STUDY IN INDIA Mohit Maheshwarkar, N. Sohani, Pallvai Maheshwarkar 14 PROBE FEED RECTANGULAR PATCH MICROSTRIP ANTENNA: CAD METHODOLOGY 180 R.D. Kanphade, D.G. Wakade, N.T. Markad 15 DETERMINANTS OF GROWTH OF TOURISM INDUSTRY IN GOA: A STUDY 191 Dr. Achut Pednekar International Journal of Research in IT, Management and Engineering www.gjmr.org
- 2. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 REAL TIME NETWORK MONITORING SYSTEM IN LAN ENVIRONMENT M. Shoaib Yousaf * Ahmed Mattin * Ahsan Raza Sattar* ABSTRACT In this research thesis, I have compared different NMS tools and their feature. I have also analyzed the available three SNMP versions and compare them in respect of security to select which one is best to use. The SNMP v1 and v2 have most of similar features but in SNMPv2 some modifications were made to overcome the deficiencies in version 1. After that SNMP version 3 (SNMPv3) added security and remotely configurations is added in the earlier versions and SNMP v3 is now most up to date version available today. I have examines the two methods to secure network traffic i.e. SNMP v3, the latest version and combination of SNMP with the non secure version like Internet Protocol Security i.e. SNMP over IPSec. These two techniques implement authorization, safety and privacy of network traffic passing through SNMP. Keywords: NMS, LAN, SNMP, TCP /IP, IPSec. *Computer Science Department, University of Agriculture, Faisalabad, Pakistan International Journal of Research in IT, Management and Engineering www.gjmr.org 1
- 3. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 INTRODUCTION Network management systems are use to make sure accessibility and complete take care of computers and network devices installed in LAN. An NMS is able of detection and report failures of devices configured in network to administrator efficiently. NMS continuously send messages across the network to all other host to confirm their status. When failures of devices and slow responses from devices shown, then these systems send extra messages called alerts to inform system administrators regarding the problems. To have control of overall network, administrator wants to know the condition of all devices on configured on the network i.e. Data flowing in / out from each host etc. there is a protocol available within the TCP / IP suite called Simple Network Management Protocol (SNMP) to meet this purpose (Amir and Maccane, 2003). Administrator used multiple tools for monitoring the internet as there is no restriction to select specific monitoring tool available. E.g. to have complete view of network devices on the internet, shared intranet, mail servers, database servers etc administrators use IP monitor software and update them upon receiving alerts via alarms, messages or e-mail etc is case of a connection fails (Bradley, 2002). The basic idea of this thesis is to compare the different NMS tools and their feature. In this research paper we will discuss the available three SNMP versions. The SNMP v1 and v2 have most of similar features but in SNMPv2 some modifications were made to overcome the deficiencies in version 1. After that SNMP version 3 (SNMPv3) added security and remotely configurations is added in the earlier versions and SNMP v3 is now most up to date version available today. Our main target is to examines the two methods to secure network traffic (i) SNMP v3, the latest version (ii) combination of SNMP with the non secure version like Internet Protocol Security i.e. SNMP over IPSec. These two techniques implement authorization, safety and privacy of network traffic passing through SNMP. MATERIALS & METHODS In this section the main focus is on the design of the network management system as well as the major parts of the system will be discus in this chapter. Also different parts and how these parts International Journal of Research in IT, Management and Engineering www.gjmr.org 2
- 4. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 correlate each other in network management system to work will be discuss here. We are going to compare the SNMP versions available and find out the better one to be used with network management system. Also administrator should be well aware of the security issues such as ability to restore, capable to delete / add user, able to monitor network accessibility, amount of traffic, rerouting, user authentication and response time of the faults. WORKING MECHANISM SNMP was proposed as a protocol that manages the nodes of network such as important servers, workstations, routers, switches etc. SNMP protocol is placed inside the UDP transport layer which is a connectionless layer in OSI model. To calculate the network performance, to locate the hosts and resolve network problem and to update the network, SNMP is used. SNMP managed networks consists of there fundamental parts: NMS devices, NMS agents and NMSs. An SNMP managed device comprises of an SNMP agent which is placed inside the network and watches all activities of network. The SNMP agent collects all the network information and stores that information to the use of this information by NMSs. All devices of network like routers, servers, switches and printers etc are control by the NMSs in the network. An agent is placed inside the SNMP device that is regularly watching all events of network. SNMP agent is provided limited access to the collected data and converted this data to a readable form necessary to use with SNMP. How NMS Works (Swee, 2006). Three versions of SNMP are most commonly used: SNMP v1, SNMP v2 and SNMP v3. The both versions 1 and 2 are similar in function except that in v2 security has been enhanced to International Journal of Research in IT, Management and Engineering www.gjmr.org 3
- 5. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 overcome the security issues. Keeping in view the importance of security a new version SNMP v3 was developed that covers all the security issues and provide more features like remote configuration. SNMP v1 is placed inside the layers of OSI and performs its functions independently without any disturbance to those OSI layers. SNMPv1 is most commonly used protocols in early days and before the invention of next version. An NMS generates a request to devices and devices respond back to these requests. There are four operations used in v1: Get, Get Next, Set, and Trap. The Get command used to request objects their values by the NMS. The Get Next operation is used to request the next value in the table. The Set operation used to fix the values inside SNMP agent. The last operation that is used for updating any change of the network to NMS is Trap. The basic limitations in version 1 are the security i.e. message authentication and protection from outside intruders. SNMP v2 was designed in 1993 to overcome above problems and was to be an improvement of its ancestor. SNMPv2 was modified then with GetBulk and Inform operation after version 1. The GetBulk function collects the huge block of information simultaneously and provides access to NMS to this information. And Inform function is used in communication of one NMS with another NMS using trap operation and then receives a response from other NMS. The major area enhanced in SNMP v2 was security that makes developers for its invention. SNMP v2 has different message formats. The difference in version 1 and 2 is purely in the field of security. However message format is same as of version 1 in the UDP for version 2. More security and remote configuration is added in newer version SNMP V3 that protects messages and provide an easy module to access these messages for SNMP. A new characteristic that was not available in previous versions is the user friendly view module for SNMPv3 addition. This feature allows the elements to control the access to the important information. SNMP engine having VACM that is consists of many message formats with different security models. This improvement in NMS and SNMP is suitable for all types of hardware. In SNMPv3 security is modified into three levels: upper level is authentication and privacy, middle level is authentication with no privacy and the bottom level is no authentication International Journal of Research in IT, Management and Engineering www.gjmr.org 4
- 6. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 no privacy. SNMP has the ability to reboot the network devices due to its security features. Below figure 3.4.3 shows security subsystem of SNMP v3 (Swee, 2006). COMPARATIVE STUDY OF EXISTING SYSTEMS It is a basic requirement that the network which I selected must have the capability to reduce the problems and other issues of traffic concerning with the delay, response time and throughput. Several materials are existing on the internet or market as concern to these networks and their relevant problems, furthermore several procedure also exist concerning to the each kind of networks. But the research is concerned with the performance analysis of NMS protocols and selecting best one protocol from them. Certain issues are there regarding to the types of traffic, throughput, latency and network availability. These issues are very common and challenging for the administration especially in those organizations having WAN link contains the routing devices. Such organizations can suffer from various kinds of issues regarding to the traffic delays if the careful selection of the proper network is not made by suspicious investigation. RESULTS I have analyzed security of SNMP in this research thesis to conclude which is best to be used in network. I have examined two techniques of security for secure SNMP traffic: firstly SNMPv3, most up-to-date invention of SNMP and non secure version of SNMP in a combination of Internet Protocol Security (IPSec). The security used in SNMP V2 consumes less network capacity as compare to SNMPv3 and also provides security to IP application which is not possible in SNMP v3. Also reduces load on administrators in configuring, managing, and maintaining monitoring systems so that their concentration is focused more on higher level policies and critical abnormal circumstances also discusses in previous chapter. Result 1 for one variable The network capacity used by SNMP is examine by running the SNMP agent with the help of an SNMP management function. The IPSec used a tunnel mode security mechanism to communicate between the gateways. Ethereal captured the IP packets generated by SNMP operations running of the host machine are shown in below table 3.3.1. International Journal of Research in IT, Management and Engineering www.gjmr.org 5
- 7. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 SNMP Version / Get Response Total Security Scheme V2c 78 102 180 V2c over IPSec 137 153 288 V3 noAuthNoPriv 141 165 306 V3 authNoPriv 153 177 330 V3 authPriv 168 192 358 V3 noAuthNoPriv over 191 217 408 IPSec V3 authNoPriv over 209 233 440 IPSec V3 authPriv over IPSec 223 249 472 Table 1 shows the SNMP-Get messages, SNMP-Response messages and the total of SNMP Get/Response sizes in byte using different security schemes for one variable. Result 2 for seven variables The second result is almost same as we get the first except it is obtain using 7 variables. SNMP Version / Security Get Response Total Scheme V2c 176 288 464 V2c over IPSec 233 345 578 V3 noAuthNoPriv 249 351 590 V3 authNoPriv 251 363 614 V3 authPriv 265 378 643 V3 noAuthNoPriv over IPSec 289 401 690 International Journal of Research in IT, Management and Engineering www.gjmr.org 6
- 8. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 V3 authNoPriv over IPSec 305 417 722 V3 authPriv over IPSec 321 433 754 Table 2 shows the SNMP-Get messages, SNMP-Response messages and the total of SNMP Get/Response sizes in byte using different security schemes for seven variables. From the above results we can conclude that the IPSec using authentication and triple-DES encryption scheme consume 57 bytes more than the normal IP packet moving this payload. Also SNMPv3 consume 89 bytes more than the normal IP packet by using HMAC-MD5- 96 authentication and DES encryption schemes. RESULT 3 NETWORK CAPACITY CONSUMED BY SNMP The SNMP agent running on gateways is used to get the processing time consumed by a secure SNMP operation. Ethereal captured the IP packets generated by the SNMP-Get operation running on observer host. We use node to node tunnel-mode security connection to distinguish the source of packet and destination of packet. As DES encryption scheme processing is computationally extremely intensive and by using triple-DES adds three times more processing than DES. But we can experiment to draw results to gain insight conclusions. The Processing time interval can be define as the time from capturing the SNMP Get message by Ethereal to the time corresponding the SNMP Response Message. Table 3.3 shows the average processing time interval and the standard deviation calculated for both approach. Mean Time SNMP Version / Security Scheme Standard Deviation V2c 310.4 12.2 V3 noAuthNoPriv 525.9 6.5 V3 AuthNoPriv 591.7 6.1 V3 AuthPriv 696.8 57.7 V2c over IPSerc 778.8 80.1 V3 noAuthNoPriv over IPSec 1057.0 19.4 International Journal of Research in IT, Management and Engineering www.gjmr.org 7
- 9. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 21.2 V3 AuthNoPriv over IPSec 1160.0 V3 AuthPriv over IPSec 1457.7 79.5 Table 3 shows the network capacity consumed by SNMP. RESULT 4 CAPACITY CONSUMED BY SNMP V3 FOR DISCOVERING EXCHANGE We calculate the capacity consumed by SNMPv3 during discovering exchange for SNMP-Get message, its corresponding SNMP-Report message and the total bytes used in discovery exchange. From the result shown below we can predict that a SNMPv3 discovery exchange is same in size and function to a typical SNMP Get/Response exchange. A more stylish SNMP management suite remembers the most recent timeliness parameters received from each SNMPv3 unit to which it communicates, thus reducing the need for discovery exchanges. SNMP Version Request Report Total SNMP V3 AuthPriv 102 139 241 SNMP V3 AuthPriv 159 193 352 over IPSec Table 4 shows capacity consumed by SNMP v3 for discovering exchange. RESULT 5 CAPACITY CONSUMED BY AN IPSEC To get the result of network capacity consumed by IPSec Free S/WAN IPSec tool is configured to keep informed about security between the gateways every minute. Many of these updates are also capture by the ethereal application running on host observer. Below table shows the IP packet sizes (in bytes) for all nine packets captured while the initial tunnel-mode security association is established. Packet # Mode Length 1 Main 204 2 Main 108 International Journal of Research in IT, Management and Engineering www.gjmr.org 8
- 10. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 3 Main 208 4 Main 208 5 Main 96 6 Main 96 7 Quick 344 8 Quick 320 9 Quick 80 Table 5 shows network capacity consumed by IPSec. SUMMARY / CONCLUSION From the obtained results in previous chapter, we conclude that the version 3 of SNMP required 24 % more capacity of network than the use of SNMP v2 with IPSec design. Also with the change in the size of application layer, the output of SNMP v2 with IPSec changes significantly. Both techniques SNMPv2 over IPSec and SNMPv3 overheads network devices equally. It will doubles the processing overhead of devices in SNMP v2 when used authentication and encryption schemes and when installing IPSec on that device. We can get better results if we used security and SNMP processing on separate devices. The security gateway is different from network devices where SNMP agent is implemented in case of SNMP v2 over IPSec. However in SNMP v3 both security processing and SNMP processing are running on single devices which creates problems to implement SNMP v3. The discovery exchange with SNMP v3 consumes 240 more bytes of network capacity. The complexity of SNMP application effect on discovery exchanges frequency. There is no As SNMP application has no feature to store the parameters of timelines, hence efficiency of network capacity badly affected in discovering process making network more overloaded. REFERENCES International Journal of Research in IT, Management and Engineering www.gjmr.org 9
- 11. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Amir, E. and S. McCanne 2003. An active service framework and its application, Communications Architectures and Protocols, pp: 178–189. Apostolopoulos, T. and V. Daskalou 1995. On the Implementation of a Prototype for Performance Management Services, IEEE symposium on computers and communications, 57- 63. A research paper on a prototype for management services. Behrouz, A. F. 2004. TCP-IP Protocol Suit, McGraw Hill publication, pp: 156-163. Bettati R. 2008. Modern Fault Trace Analysis and its Capabilities Department of Computer Science and Center for Information Assurance and Security Texas A&M University College Station, TX, 77801,USA Bierman, A. and L. Bucci 2002. Remote Network Monitoring MIB Protocol Identifiers, Proposed technical specification for RMON2 protocol identifiers, pp: 194-220. Blum A. and D. Song 2004. Monitoring and Measurements of network bounds. In Proceedings of the 7th International Symposium on Recent Advances in Intrusion Detection, RAID ’04, September 2004. Bradley, M. 2002. Remote Network Monitoring MIB Extensions for Switched Networks proposed technical specification for RMON of switched networks, pp: 51-68. Symantec Internet Security threat report highlights (Symantec.com), http://www.prdomain.com/companies/Symantec/newreleases/Symantec_internet_205032.htm Accessed on 15 May 2011. Chang, C. and L. Sung. 2008. Integration and Application of Web-Service-Based Expert System and Computer Maintenance Management Information System. In Proceedings of the 2008 IEEE Asia-Pacific Services Computing Conference, pp: 207-212. Cheswick R. 2002. Firewall and Internet Security, Addison Wesley Professional Computing Series; pp: 201-223. International Journal of Research in IT, Management and Engineering www.gjmr.org 10
- 12. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Corey V. and C. Peterman 2005. IEEE Internet Computing Volume 6, Issue 6 Pages: 60 – 66. Year of Publication: 2002 ISSN: 1089-7801 Cottrell, L. and C. Logg. 2004. Network monitoring for the LAN and WAN, http://www.slac.stanford.edu/grp/scs/net/talk/ornl-96/ornl.html,A tutorial paper on monitoring on Wide Area Network including the internet. Ergin, M., K. Ramachandran and M. Gruteser 2007. Understanding the effect of access point density on wireless LAN performance, International Conference on Mobile Computing and Networking Proceedings of the 13th annual ACM international conference on Mobile computing and networking, pp: 62-64. Gast, M. 2002. 802.11 wireless networks: the definitive guide, Wiley, pp: 85-89. Huges, J. 1996.Characterizing Network Behavior Using Remote Monitoring Devices Telecommunications, pp: 43-44. Jung H.J. and J.Y.Choen 2007. Real-time network monitoring scheme based on SNMP for dynamic information, Journal of Network and computer Applications, 30 (1), pp: 331-353. International Journal of Research in IT, Management and Engineering www.gjmr.org 11
- 13. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 QUALITY OF WORKING LIFE IN INSURANCE SECTOR Rita Goyal* ABSTRACT The study of Quality of working life has been an important and critical area in management and organizational performance from last several years especially in the LIC.. This paper aims to study the extent of QWL in the LIC, and explores the proposed link between the QWL and employees productivity. Two hundred fifty employees responded to the researcher’s questionnaire. The study makes use of statistical techniques such as mean, standard deviation, t test. ANOVA analysis to process and analysis the data collected for this study .The demographic portion of the instrument was developed by the researcher to sort out the demographic information. To explore difference between the means of two group t-test was applied. One way ANOVA was used for exploring the difference among more than two groups. The paper ends by offering useful suggestions to the management involved in the operations of the corporations. Key words: Quality of working life, Insurance Sector, Competency Development, Employees Productivity, Work-Life Balance *Lecturer Dept. of Humanities and Social Sciences, Maharishi Markendeshwar University, Mullana (Ambala) International Journal of Research in IT, Management and Engineering www.gjmr.org 12
- 14. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 INTRODUCTION Quality of Working Life is a process of work organizations which enables its members at all levels to actively participate in shaping the organization environment, methods and outcomes. Conceptual categories which together make up the quality of working life are adequate and fair compensation, safe and healthy working conditions, immediate opportunity to use and develop human capacities, opportunity for continued growth and security, social integration in the work organization, constitutionalization in the work organization, work and the total life space and the social relevance of work life. Quality of Work Life was the term actually introduced in the late 1960’s. From that period till now the term is gaining more and more importance everywhere, at every work place. Initially quality of work life was focusing on the effects of employment on the general well being and the health of the workers. But now its focus has been changed. Every organization need to give good environment to their workers including all financial and non financial incentives so that they can retain their employees for the longer period and for the achievement of the organization goals. The concept of QWL is based on the assumption that a job is more than just a job. It is the center of a person’s life. In recent years there has been increasing concern for QWL due to several factors: Increase in education level and consequently job aspirations of employees; Association of workers; Significance of human resource management; widespread industrial unrest; Growing of knowledge in human behaviors, etc. LITERATURE REVIEWS Bear field, (2003) used 16 questions to examine quality of working life, and distinguished between causes of dissatisfaction in professionals, intermediate clerical, sales and service workers, indicating that different concerns might have to be addressed for different groups. The distinction made between job satisfaction and dissatisfaction in quality of working life reflects the influence of job satisfaction theories. Lawler, (2004) Quality of Working Life is not a unitary concept, but has been seen as incorporating a hierarchy of perspectives that not only include work-based factors such as job satisfaction, satisfaction with pay and relationships with work colleagues, but also factors that broadly reflect life satisfaction and general feelings of well-being suggested that quality of working life was associated with satisfaction with wages, hours and working conditions, describing the “basic elements of a good quality of work life” as: International Journal of Research in IT, Management and Engineering www.gjmr.org 13
- 15. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 safe work environment, equitable wages, Equal employment opportunities and opportunities for advancement. Waddell Jane and Carr Paul (2005) In addition to competition of globalization and products, organization face competition related to employee retention at the same time employees face competition for their time. As increasing number of employees face competing demands between work and family, the importance of maintaining a healthy work life balance is of paramount consideration. In spite of family- friendly policies, many employees perceive negative consequences associated with availing themselves of these policies. At the same time, over 50% of American employees fail to take their allotted vacation time. Failure to achieve a healthy work life balance can lead to overload, which may result in loss of employees. Encouraging a healthy work life balance benefits both the organization and the employees. Lawler and Porter (2006). An individual’s experience of satisfaction or dissatisfaction can be substantially rooted in their perception, rather than simply reflecting their “real world”. Further, an individual’s perception can be affected by relative comparison – am I paid as much as that person - and comparisons of internalized ideals, aspirations, and expectations, for example, with the individual’s current state In summary, where it has been considered, authors differ in their views on the core constituents of Quality of Working Life (e.g. Sirgy, Efraty, Siegel & Lee, 2001 and Warr, Cook & Wall, 1979). It has generally been agreed however that Quality of Working Life is conceptually similar to well-being of employees but differs from job satisfaction which solely represents the workplace domain. Banerjee Indranil (2006) Jobs are getting increasingly demanding, as the organization face competition and become leaner in structure, leading to conflict between people’s professionals deliverable and personal requirements. It is acknowledged that continuous disregard of personal issues ultimately lead to employees’ underperformance and so people often discuss work life balance but seldom act on it. So, the focus now is “Who is going to bell the cat?” For tackling the problem, multi-pronged effort, comprising the organization, the employee, the Government, the Industry, the society, etc., is required. Tekuru Siva ram (2007) Work- life balance is all about need for individuals having complete control over their work, i.e. deciding when, why, where and how to work. Finding these pressures encroaching into their private life and time, they are unable to do anything about it and are finally squeezed out. Organization should consider Work –life balance as an extension of the fringe benefits offered to the International Journal of Research in IT, Management and Engineering www.gjmr.org 14
- 16. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 employees. This will help both the employees and the organization. Aggarwala Tanuja (2007) Conflicting demands and pressures from works and life (family) can interfere with each other since the two domains are complementary, not conflicting priorities. Acceptance of this reality by the organization and new business and societal trends, have seen the growth of family- friendly practices at work place. Adopting a win- win approach, growing number of organization believe that helping employees balance and integrate their work lives with the rest of their lives leads to positive outcomes for both the employee and the employer. Work- family practices should be viewed as a part of overall HR and business strategy that is related to a firm’s competitive advantage. Swamy (2007) In today’s business context the pressures of work have been intensifying and there is a growing feeling among employees that the demand of work being to dominate life and a sense of work-life imbalance is felt. The challenge of integrating work and family life is a part of everyday reality for the majority of employees. Organizations have to continually innovate and come up with programs that provide scope for employees to balance their responsibility at their work place and interest they have outside work. Suman Ghalawat (2010) states that QWL is a Process of work organizations which enables its members at all levels to actively participate in shaping the organizations’ environment, methods and outcomes. This value based process is aimed towards meeting the twin goals of enhanced effectiveness of organization and improved quality of the life at work for employees. Work is an integral part of our everyday life, as it is our livelihood or career or business. On an average we spend around twelve hours daily in the work place, that is one third of our entire life; it does influence the overall quality of our life. It should yield job satisfaction, give peace of mind, a fulfillment of having done a task, as it is expected, without any flaw and having spent the time fruitfully, constructively and purposefully. Even if it is a small step towards our lifetime goal, at the end of the day it gives satisfaction and eagerness to look forward to the next day. The factors that influence and decide the Quality of Work Life are: Attitude, environment, opportunities, nature of job, people, stress level, career prospects, growth and development, risk involved and reward. OBJECTIVES OF STUDY In light of the domain for research, the study was undertaken:- International Journal of Research in IT, Management and Engineering www.gjmr.org 15
- 17. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 1. To examine the nature of quality of working life prevailing in some selected Branches of LIC. 2. To study the differences in the perception of employees on the basis of gender. 3. To study the differences in the perception of employees on the basis of designation. 4. To study the differences in the perception of employees on the basis of Qualification. HYPOTHESIS In view of the objectives set for the study, following null hypothesis was formulated: Ho1.1 There is no significant difference between the perception of male and female employees regarding quality of working life. Ho1.2There is no significant difference between the perceptions of employees at different levels regarding quality of working life Ho1.3 There is no significant difference between the perception of graduate and post graduate employees regarding quality of working life. RESEARCH METHODOLOGY Data A total of 400 employees were chosen randomly from the 4branches, keeping in view their total strength and range of activities. Out of 400 questionnaires distributed only 250questionnaires were received completed in all respects. Therefore with 62.5% response rate the researcher has conducted this study. SAMPLE OF THE STUDY Following table represents the sample of study: Gender-wise distribution of employees N Percent Male 185 74 Female 65 26 Total 250 100 International Journal of Research in IT, Management and Engineering www.gjmr.org 16
- 18. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Designation-wise distribution of employees Employees N Percent Class-1 100 40 Class-11 69 27.6 Class-111 81 32. 4 Total 250 100 Qualification wise distribution of Employees Employees No. Percent Graduate 140 56 Post Graduate 110 44 Total 250 100 QUESTIONNAIRE The questions were designed to facilitate the respondents to identify major strengths and weakness of the Corporations and provide insights. The endeavors were to identify the key quality of working life issues, on which employee’s perception can be obtained. The respondents were requested specifically to ignore their personal prejudices and use their best judgment on a 5 point Likert scale. The purpose of this exercise was to make the response a true reflection of organization reality rather than an individual opinion. The 5 point of the scale indicated in the questionnaire are- 1. Strongly disagree, 2 disagree, 3-Undecided, 4-Agree and 5- Strongly Agree. Reliability (Cronbach’s coefficient alpha) of the questionnaire has found to be 0.89.This shows data has satisfactory internal consistency. Descriptive Analysis: Result & Discussion The results in the following table reveal that in the scale for quality of working Life, the highest mean score (44.29) is for male and the lowest (33.56) is for level III employees. The same has been shown graphically in figure1.1 International Journal of Research in IT, Management and Engineering www.gjmr.org 17
- 19. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Summary of “t”test presented in the table 1.2 indicates that t-value (1.60) is significant as p- value (.110) is more than 0.05.Hence the hypothesis stating the difference is not significant between the perception of male and female employees regarding. Quality of working life is accepted at 0.05 level of significance. So there is not a significant difference between the perception of male and female employees regarding quality of working life. Mean value for males (74.29) is less than females (78.89) therefore it is concluded that female employees have better perception of QWC than male employees. Summary of the univariate analysis of variance presented in the table 1.3 indicates that p-value (0.232) is greater than 0.05as F value (1.469) is not significant at 0.05 level of significance. Hence the hypothesis is accepted at 0.05 level of significance, so there is no significant difference among the perception of employees at different levels regarding quality of working life. Summary of “t”test presented in the table 1.4 indicates that t-value (.348) is significant as p- value (0.728) is more than 0.05.Hence the hypothesis stating, The difference is not significant between the perception of graduate and post graduates employees regarding QWC. “Is accepted at 0.05 level of significance. So there is not a significant difference between the perception of graduate and post graduate employees regarding QWC in selected branches of LIC. Mean value for graduate (34.69) is less than Postgraduate Employees (35.58) therefore it is concluded that post graduate employees have better perception of QWC than graduate employees. Thus findings are: The difference is not significant between the perception of male and female employees regarding quality of working life. It shows that gender does not affect the perception of QWL System of employees as all are equally aware of the significance of it. There is no significant difference among the perception of employees at different levels regarding quality of working life. As all are equally aware of the significance of it. It shows that the need of the employee’s development is felt in all cases. The difference is not significant between the perception of Graduates and Post Graduates employees regarding the quality of work life in selected branches of LIC. As both areas are equally related to improvement and progress. International Journal of Research in IT, Management and Engineering www.gjmr.org 18
- 20. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 CONCLUSION In LIC, Quality of Working Life principles are the principle of security, the principle of equity, the principle of individuation and the principle of democracy. On the basis of my study I can say that employees of LIC in Northern region are happy with the working conditions of the LIC. They feel that they are safe and secure in LIC. They feel that corporation should start their own transport facilities for the staff. However, the dissatisfaction among them is the less growth opportunities. They are not provided with extra care like health camps etc Poor work life balance leads to many disastrous things like tardy, bad performance, lack of motivation, more errors, absence from work and so on. The worst thing is that poor work-life balance reduces work quality and productivity without any doubt. When an employee won't be able to give time to his family at home, he will feel stressed out at work Sound work life balance will definitely have a positive impact on employee’s productivity. The quality of work improves significantly as employees feel fresh and not stressed out at all. Suggestion 1.Corporation must be committed to an open and transparent style of operation that include sharing appropriate information with employees and sincerely inviting their input regarding problems opportunities and implementation of improvement plans. 2. Employees must be given opportunities for advancement in the corporation. 3. Traditional status barriers between different classes must be broken to permit establishment of an atmosphere of trust and open communication. 4. Employees should receive feed back on results achieved and recognition for superior performance. Other forms of positive reinforcement such as financial incentives should also be made available where feasible. 5. Improved communication and co-ordination among the workers and organization helps to integrate different jobs resulting in better task performance. 6. Better working condition enhances workers motivation to work in a healthy atmosphere resulting in motivation and increase in production. 7. As QWL includes participation in group discussion and solving the problem, improving the skill, enhancing their capabilities and thus building confidence and increased output. International Journal of Research in IT, Management and Engineering www.gjmr.org 19
- 21. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 REFERENCES: Anonymous (2005). Quality of Work Life Task Force looks to integrate home and work. Vanderbilt University Medical Center, House Organ. Available from http:// www.Quality20%of/20%work/20% life. htm. Anbarasan, V & Mehta, N. (2009), "An Exploratory Study on Perceived Quality of Working Life among Sales Professionals Employed in Pharmaceuticals, Banking, Finance and Insurance Companies in Mumbai", Abhigyan, 27(1): 70-81. Ebrahim (2010) “The relation between QWL and job satisfaction”, Middle –East Journal of scientific Research 6(4), 317-323-2010. Feuer, D., Quality of work life: a cure for all ills? Training: The Magazine of Human Resources Development, 26: 65-66, 1989. Mishra, S. & Gupta, B. (2009), "Work Place Motivators and Employee's Satisfaction: A Study on Retail Sector in India", The Journal of Industrial Relations, 44(3): 509-17. Raduan,C. R., Loosee .B., Jegak,U & Khairuddin, I. (2006), "Quality of Work Life: Implications of Career Dimensions", Journal of Social Sciences. 2 (2): 61-67. Sandrick k (2003). Putting the emphasis on employees as an award. Winning employer, Baptist health care has distant memories of the workforce shortage, Trustee. pp. 6- Straw, R.J. and C.C. Heckscher, 1984. QWL: New working relationships in the communication industry. Labor Studies J., Vol. 9: 261-274. Walton, R. (1973), ― Quality of Work life Indicators- Prospects and Problems- A Portigal Measuring the Quality of working life, pp-57-70, Ottawa International Journal of Research in IT, Management and Engineering www.gjmr.org 20
- 22. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 1.1: Scale for Quality of working Life Factor No. Mean S.D Gender-Male 185 44.29 19.85 Female 65 38.89 20.13 Designation-Level 1 100 39.27 18.69 Level 11 69 34.72 20.88 Level 111 81 33.56 22.86 Qualification- 140 34.69 19.34 Graduate Post Graduate 110 35.58 20.95 Tab 1.2 Perceptual differences between male and female employees regarding quality of working life. Group Sample Mean S.D. t- value df p-value size Male 185 44.29 19.85 1.60 248 .110 Employee Female 65 48.89 20.13 Employees P>0.05 International Journal of Research in IT, Management and Engineering www.gjmr.org 21
- 23. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Tab.1.3 Perceptual differences between employees at different level regarding quality of working life. Particulars Sample size Mean d.f F value P value Class-1 100 39.27 2 1.469 0.232 Class-11 69 34.72 Class-111 81 33.56 P>0.05 Tab1.4: Perceptual differences between Employees with graduate and postgraduate qualification regarding quality of working life. Particulars Sample Size Mean SD t-test df p-Value Graduate 140 34.69 19.34 .348 248 .728 Employee Postgraduate 110 35.58 20.95 Employees P>0.05 International Journal of Research in IT, Management and Engineering www.gjmr.org 22
- 24. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 REFACTORABILITY ANALYSIS USING LINEAR REGRESSION Gauri Khurana* Sonika Jindal ** ABSTRACT Software refactoring - improving the internal structure of the software without changing its external behavior - is an important action towards avoiding software quality decay. Key to this activity is the identification of portions of the source code that offers opportunities for refactoring -- the so called bad smells. The underlying objective is to improve the quality of the software system, with regard to future maintenance and development activities. The goal of this review paper is the discussion of an approach to help on the detection of code bad smells through source code metrics and the results obtained from its use. In this discussion, we propose measure of refactorability based on the four factors- reusability, understandability, modifiability and maintainability. Since, each of the factors is intangible in nature and is hard to measure. It is also proposed that they should be measured in terms of point system. It is also important to bring new elements that might be affected through a refactoring sequence as, for example, structural testing requirements that can be used in the future as a new metric to detect refactoring opportunities. Keywords: Refactoring, reusability, understandability, modifiability, maintainability, bad smell, metrics *CSE, SBSCET, Ferozpur. PTU, Jalandhar ** Assistant Professor, Department of Computer Science, SBSCET, Ferozpur. PTU, Jalandhar. International Journal of Research in IT, Management and Engineering www.gjmr.org 23
- 25. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 1. INTRODUCTION 1.1 Introduction to refactoring Refactoring is a well-defined process that improves the quality of systems and allows developers to repair code that is becoming hard to maintain, without throwing away the existing source code and starting again. By careful application of refactorings the system’s behavior will remain the same, but return to a well-structured design. The use of automated refactoring tools makes it more likely that the developer will perform the necessary refactorings, since the tools are much quicker and reduce chance of introducing bugs. “Refactoring is the process of changing a software system in such a way that it does not alter the external behavior of the code yet it improves its internal structure.”-Martin Flower in Refactoring, Improving the Design of Existing Code. Refactoring is a kind of reorganization. Technically, it comes from mathematics when you factor an expression into an equivalence- the factors are cleaner ways of expressing the same statement. Refactoring implies equivalence- the beginning and the end product must be functionally identical. The shift from Structured Programming to Object-oriented Programming is a fundamental example of refactoring. [1] “Refactoring is the process of taking an object design and rearranging it in various ways to make the design more flexible and/or usable.” – Ralph Johnson. Four Reasons to change the code: The four primary reasons to change the code are [2]: 1. Adding a feature 2. Fixing a bug 3. Improving the design 4. Optimizing resource usage 1.2 Preserving Behavior Feature addition and bug fixing are very much like refactoring and optimization. In all cases of changing code, we want to change some functionality, some behavior, but we want to preserve much more (see Figure 1) International Journal of Research in IT, Management and Engineering www.gjmr.org 24
- 26. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Existing Behavior New Behavior Figure 1: Preserving Behavior [2] Figure 1 shows what is supposed to happen when we make changes, but what does it mean for us practically? On the positive side, it seems to tell us what we have to concentrate on. We have to make sure that small numbers of things that we change are changed correctly. On the negative side, that isn’t the only thing we have to concentrate on. We have to figure out how to preserve the rest of the behavior. The amount of behavior to be preserved is usually very large. Preserving behavior is a large challenge. When we need to make changes and preserve behavior, it can involve considerable risk. [2] To mitigate risk, we have to ask three questions: 1. What changes do we have to make? 2. How will we know that we’ve done them correctly? 3. How will we know that we haven’t broken anything? 1.3 Why do we need refactoring? The longer object oriented systems are in use, the more probable it is that these systems have to be maintained [3], i.e. they have to be optimized to a given goal (Perfective Maintenance), they have to be corrected with respect to identified defects (Corrective Maintenance) and they have to be adjusted to a changing environment (Adaptive Maintenance). Whereas many of these activities can be subsumed under the reengineering area, there are additional changing activities that are much less difficult to apply than typical reengineering activities, and which does not change the external behavior [4]. The main goal of these “mini-reengineering activities” is to improve the understandability and to simplify reengineering activities. Flower calls these activities Refactorings, which he defines a “a change made to the internal structure of a software to make it easier to understand and cheaper to modify without changing its observable behavior” [1, p. 53]. International Journal of Research in IT, Management and Engineering www.gjmr.org 25
- 27. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Fowler suggests four purposes of refactoring [1]: 1. Improve the design of software – Through accumulating code changes, code loses its structure, thereby increasingly drifting towards a state of decay. Refactoring can be used to cure software decay by redistributing parts of the code to the “right” places, and by removing duplicated code. The claim that refactoring can improve the design of software is confirmed by [3] with regard to cohesion and with respect to coupling, as indicators for internal software quality. Another claimed benefit in the area of improved design is improved flexibility. 2. Make software easier to understand – Refactoring can help make the code more readable by making it better communicate its purpose. A different way in which refactoring supports program understanding is in reflecting hypotheses about the purpose of the code by changing the code, and afterwards testing that understanding through rerunning the code. The suggested process to do so is to start refactoring the little details to clarify the code, thereby exposing the design. The potential to improve understandability through refactoring is confirmed by many authors [1, 3]. In more specific terms, [5] discusses how refactorings can be used to improve communicating the purpose of the code. 3. Help find bugs – Through clarifying the structure of the code, the assumptions within the code are also clarified, making it easier to find bugs. 4. Program faster – Through improving the design and overall understandability of the code, rapid software development is supported. 1.4 When should one consider refactoring? Ideally, refactoring would be part of a continuing quality improvement process. In other words, refactoring would be seamlessly interwoven with other day-to-day activities of every software developer. Refactoring may be useful, when a bug has surfaced and the problem needs to be fixed or the code needs to be extended. Refactoring at the same time as maintenance or adding new features also makes management and developers more likely to allow it, since it will not require an extra phase of testing. If the developer in charge finds it difficult to understand the code, he will (hopefully) ask questions, and begin to document the incomprehensible code. Often, however, schedule pressures do not permit to implement a clean solution right away. A feature might have to be added in a hurry, a bug patched rather than fixed. In these cases, International Journal of Research in IT, Management and Engineering www.gjmr.org 26
- 28. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 the code in question should be marked with a FIXME note, in order to be reworked, when time permits. Such circumstances call not for individual refactorings, but for a whole refactoring project. When the time has come to address the accumulated problems, a scan for FIXMEs, TODOs, etc. over the code base will return all the trouble spots for review. They can be refactored according to priority. 2. SEMANTIC GAP The concept of Semantic gap is relevant whenever a human activity, observation and task are transferred into computational representation [6]. Like programs, programming languages are not only mathematical objects but also software engineering artifacts. Describing the semantics of real-world languages can help bring language theory to bear on both exciting and important real-world problems. Achieving this is not purely a mathematical task, but equally one of (semantic) engineering. The implementations of all major languages— especially scripting languages defined by implementations—come with large and well- structured test suites. These suites embody the intended semantics of the language. We should be able to use such a test suite to retrofit semantics. For this to be useful, it is not sufficient to merely create semantics for the core language [4]. More precisely the gap means the difference between contextual knowledge in a powerful language (e.g. natural language) and its reproducible and computational representation in a formal language (e.g. programming language). The semantic gap actually opens between the selection of the rules and the representation of the task. With the passage of time, the business scenario keeps on changing and the software development must match the business environment. Therefore the code of any software also changes with respect to the business scenario. There might be architectural changes in software due to business reengineering process. The programmer has to rethink how to do the implementation of the code due to changes in the requirements. So, it offers opportunity to relook, redesign, as well as refactor the code. Thus, it forces new semantics to be laid with respect to the changing business scenario. 3. REFACTORING ACTIVITIES The refactoring process consists of a number of different activities, each of which can be automated to a certain extent [7]: International Journal of Research in IT, Management and Engineering www.gjmr.org 27
- 29. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 1. Identify where the code should be refactored; 2. Determine which refactorings should be applied to the identified places; 3. Guarantee that the applied refactoring preserves behavior; 4. Apply the refactoring; 5. Assess the effect of refactoring on software quality characteristics; 6. Maintain consistency between refactored program code and other software artifacts (or vice versa). The steps taken when applying the refactoring should be small enough to oversee the consequences they have and reproducible to allow others to understand them. Generalized refactoring steps in away, are mere a rule that can be applied to any structure. Refactoring not only covers the mechanics of restructuring, but also addresses the following issues [Martin Flower]: 1. Refactoring emphasizes that, in absence of more formal guarantees, testing should be used to ensure that each restructuring is behavior preserving. A rich test suite should be built, which must be run before and after each test is applied. 2. Refactorings are described in a catalog, using a template reminiscent of design patterns. 3. Refactorings are applied in small steps, one by one, running the test suite after every step to make it into commercial development tools. 4. METRICS FOR REFACTORABILITY The various metrics are identified for calculating the values of four factors proposed here separately. Those are defined as follows: 1. LinesOfCode (NbLines): The LOC for a method is equals to the number of sequence point found for this method in the file. A sequence point is used to mark a spot in the IL code that corresponds to a specific location in the original source. Notice that sequence points which correspond to braces ‘{‘ and ‘}’ are not taken into account. Interfaces, abstract methods and enumerations have a LOC equals to 0. Only concrete code that is effectively executed is considered when computing LOC. International Journal of Research in IT, Management and Engineering www.gjmr.org 28
- 30. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Namespaces, types, fields and methods declarations are not considered as line of code because they don’t have corresponding sequence points. LOC computed from an anonymous method doesn’t interfere with the LOC of its outer declaring methods. Recommendations: Methods where LinesOfCode is higher than 20 are hard to understand and maintain. Methods where ILInstructions is higher than 40 are extremely complex and should be split in smaller methods (except if they are automatically generated by a tool). 2. LinesOfComment(NbComments): This metric can be computed only if PDB files are present and if corresponding source files can be found. The number of lines of comment is computed as follow: For a method, it is the number of lines of comment that can be found in its body. If a method contains an anonymous method, lines of comment defined in the anonymous method are not counted for the outer method but are counted for the anonymous method. For a type, it is the sum of the number of lines of comment that can be found in each of its partial definition. For a namespace, it is the sum of the number of lines of comment that can be found in each of its partial definition. For an assembly, it is the sum of the number of lines of comment that can be found in each of its source file. Notice that this metric is not an additive metric (i.e. for example, the number of lines of comment of a namespace can be greater than the number of lines of comment over all its types). Recommendations: This metric is not helpful to asses the quality of source code. We prefer to use the metric PercentageComment. 3. NbMethods: The number of methods. A method can be an abstract, virtual or non- virtual method, a method declared in an interface, a constructor, a class constructor, a finalizer, a property/indexer getter or setter, an event adder or remover. Recommendations: Types where NbMethods > 20 might be hard to understand and International Journal of Research in IT, Management and Engineering www.gjmr.org 29
- 31. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 maintain but there might be cases where it is relevant to have a high value for NbMethods. 4. NbFields: The number of fields. A field can be a regular field, an enumeration's value or a read only or a const field. Recommendations: Types that are not enumeration and where NbFields is higher 20 might be hard to understand and maintain but there might be cases where it is relevant to have a high value for NbFields. 5. Afferent coupling (Ca): The number of types outside this assembly that depend on types within this assembly. High afferent coupling indicates that the concerned assemblies have many responsibilities. 6. Efferent coupling (Ce): The number of types outside this assembly used by child types of this assembly. High efferent coupling indicates that the concerned assembly is dependant. There is a whole range of interesting code metrics relative to coupling. The simplest ones are named Afferent Coupling (Ca) and Efferent Coupling (Ce). Basically, the Ca for a code element is the number of code elements that use it and the Ce is the number of code elements that it uses. Figure 2: Afferent and Efferent Coupling You can define Ca and Ce for the graph of assemblies dependencies, the graph of namespaces dependencies, the graph of types dependencies and the graph of methods dependencies of a code base. You can also define the Ca metric on the fields of a program as the number of methods that access the field. International Journal of Research in IT, Management and Engineering www.gjmr.org 30
- 32. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 7. Cyclomatic Complexity (CC): Cyclomatic complexity is a popular procedural software metric equal to the number of decisions that can be taken in a procedure. Concretely, in C# the CC of a method is 1 + {the number of following expressions found in the body of the method }: if | while | for | foreach | case | default | continue | goto | && | || | catch | ternary operator? : | ?? Following expressions are notcounted for CC computation: else | do | switch | try | using | throw | finally | return | object creation | method call | field access The Cyclomatic Complexity metric is defined on methods. Adapted to the OO world, this metric is also defined for classes and structures as the sum of its methods CC. Notice that the CC of an anonymous method is not counted when computing the CC of its outer method. Recommendations: Methods where CC is higher than 15 are hard to understand and maintain. Methods where CC is higher than 30, are extremely complex and should be split in smaller methods (except if they are automatically generated by a tool). 8. Efferent coupling at method level (MethodCe): The Efferent Coupling for a particular method is the number of methods it directly depends on. 9. Afferent coupling at field level (FieldCa): The Afferent Coupling for a particular field is the number of methods that directly use it. 10. NbOverloads: The number of overloads of a method. . If a method is not overloaded, its NbOverloads value is equals to 1. This metric is also applicable to constructors. Recommendations: Methods where NbOverloads is higher than 6 might be a problem to maintain and provoke higher coupling than necessary. This feature helps reducing the number of constructors of a class. 11. Association Between Classes (ABC): The Association between Classes metric for a particular class or structure is the number of members of others types it directly uses in the body of its methods. 12. Depth of Inheritance Tree (DIT): The Depth of Inheritance Tree for a class or a structure is its number of base classes (including the System.Object class thus DIT >= International Journal of Research in IT, Management and Engineering www.gjmr.org 31
- 33. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 1). Recommendations: Types where DepthOfInheritance is higher or equal than 6 might be hard to maintain. However it is not a rule since sometime your classes might inherit from third-party classes which have a high value for depth of inheritance. 13. NbAssemblies: Only application assemblies are taken into account. 14. NbNamespaces: The number of namespaces. The anonymous namespace counts as one. If a namespace is defined over N assemblies, it will count as N. 15. PercentageCoverage: The percentage of code coverage by tests. Code coverage data are imported from coverage files. If you are using the uncoverable attribute feature on a method for example, if all sibling methods are 100% covered, then the parent type will be considered as 100% covered. Coverage metrics are not available if the metric LinesOfCode is not available. Recommendations: The closer to 100%, the better. 16. Relational Cohesion (H): Average number of internal relationships per type. Let R be the number of type relationships that are internal to this project (i.e. that do not connect to types outside the project). Let N be the number of types within the project. H = (R + 1)/ N. The extra 1 in the formula prevents H=0 when N=1. The relational cohesion represents the relationship that this project has to all its types. Recommendations: As classes inside an project should be strongly related, the cohesion should be high. On the other hand, too high values may indicate over- coupling. A good range for RelationalCohesion is 1.5 to 4.0. Projects where, RelationalCohesion < 1.5 or RelationalCohesion > 4.0 might be problematic. 5. RATING SCALE A rating scale is a set of categorize designed to elicit information about a quantitative or a qualitative attribute. In the social sciences, common examples are the Likert scale and 1-10 rating scales in which a person selects the number which is considered to reflect the perceived quality of a product. More than one rating scale is required to measure an attitude or perception due to the requirement for statistical comparisons between the categories in the polytomous Rasch model for ordered categories (Andrich, 1978). 5.1 Likert scale International Journal of Research in IT, Management and Engineering www.gjmr.org 32
- 34. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 A Likert scale is a psychometric scale commonly used in questionnaires, and is the most widely used scale in survey research, such that the term is often used interchangeably with rating scale even though the two are not synonymous. When responding to a Likert questionnaire item, respondents specify their level of agreement to a statement. The scale is named after its inventor, the US organizational-behavior psychologist Rensis Likert (1903- 81). Each item may be analyzed separately or in some cases item responses may be summed to create a score for a group of items. Hence, Likert scales are often called summative scales. Likert scale data can, in principle, be used as a basis for obtaining interval level estimates on a continuum by applying the polytomous Rasch model, when data can be obtained that fit this model. In addition, the polytomous Rasch model permits testing of the hypothesis that the statements reflect increasing levels of an attitude or trait, as intended. For example, application of the model often indicates that the neutral category does not represent a level of attitude or trait between disagree and agree categories. Again, not every set of Likert scaled items can be used for Rasch measurement. The data has to be thoroughly checked to fulfill the strict formal axioms of the model. Likert scales usually have five potential choices (strongly agree, agree, neutral, disagree, strongly disagree) but sometimes go up to ten or more. The final average score represents overall level of accomplishment or attitude toward the subject matter [8]. Since, each of the factors is intangible in nature and is hard to measure. It is also proposed that they should be measured in terms of point system as follows: Table 1: Scale of Reusability: High Reusability 10-9 Medium Reusability 8-7 Low Reusability 6-5 Very low Reusability 4-3 No Reusability 2-1 International Journal of Research in IT, Management and Engineering www.gjmr.org 33
- 35. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 2: Scale of Maintainability: High Maintainability 10-9 Medium Maintainability 8-7 Low Maintainability 6-5 Very low Maintainability 4-3 No Maintainability 2-1 Table 3: Scale of Understandability: High Understandability 10-9 Medium Understandability 8-7 Low Understandability 6-5 Very low Understandability 4-3 No Understandability 2-1 Table 4: Scale of Modifiability: High Modifiability 10-9 Medium Modifiability 8-7 Low Modifiability 6-5 Very low Modifiability 4-3 No Modifiability 2-1 International Journal of Research in IT, Management and Engineering www.gjmr.org 34
- 36. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 6. CORRELATION AND REGRESSION ANALYSIS Correlation and regression are generally performed together. The application of correlation analysis is to measure the degree of association between two sets of quantitative data. There are virtually no limits of applying correlation analysis to any dataset of two or more variables. It is the researcher’s responsibility to ensure correct use of correlation analysis. Correlation is usually followed by regression analysis in many applications. The main objective of regression analysis is to explain the variation in one variable (called the dependent variable), based on the variation in one or more other variables (called the independent variables). If there are only one dependent variable and only one independent variable used to explain the variation in it, then the model is known as simple regression. If multiple independent variables are used to explain variation in one dependent variable, it is called multiple regressions [9]. Even though the regression equation could be either linear or non-linear, we limited our discussion to linear models. From the regression analysis of the various four factors (reusability, understandability, modifiability, maintainability) separately, using their respective metrics, the analysis of refactorability can be done by applying linear regression over refactorability using these four factors. Thus, the regression equation for refactorability will be as follows: Y=a+bX1+cX2+dX3+eX4 Where, Dependent Variable= Y Independent Variables are: X1, X2, X3, and X4. The above mentioned regression equation is applied to each factor that is considered to be affecting the refactorability of the software. The underlying steps are carried out for each of the factor separately, by considering their respective metrics as their independent variables. Step 1: Collect the dataset containing the values for each metric identified. And based on that dataset, the points based on the rating scale are assigned, considering the rules. Step 2: The correlation is found among the independent variables and dependent variables, for each factor affecting refactoring. The SPSS 16 tool is used to find the correlation. The positive value of correlation specifies that the factor is directly affected by that variable. And, the negative value shows that the factor is inversely affected by the respective variable. International Journal of Research in IT, Management and Engineering www.gjmr.org 35
- 37. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Step 3: The regression analysis is done to explain the variation in one variable (dependent variable), based on the other variable (independent variable). The linear equation is used for a regression analysis and the values of the coefficients of the linear equation are determined. Step 4: The output of the regression is determined with the help of value of R-square. The measure of strength of association in the regression analysis is given by the determination of R-square. The coefficient varies between 0 and 1 and represents the proportion of total variation in the dependent variable that is accounted by the variation in the factors. After applying all the steps to each factor, the refactorability is estimated using the linear regression equation, considering refactorability as the dependent variable and other four factors affecting refactoring as independent variables. The partial regression plots are obtained for each factor, the slope of which determines that the model designed to determine the refactorability is good or bad. The linear slope of the graph determines that the model developed for refactorability based on that factor is good enough to determine the refactorability. The results of the regression analysis of all the factors, considered, that affect refactoring are studied. Based on the results of each factor the points on the Rating scale are obtained for refactorability. 7. CONCLUSION Software Refactoring is an important area of research that promises substantial benefits to software maintenance. Refactoring is a process that improves the quality and allows developers to repair code that is becoming hard to maintain, without throwing away the existing source code and starting again. We can return with a well structured and well designed code after proper application of refactoring techniques. By careful application of refactorings the system’s behavior will remain the same, but return to a well-structured design. The use of automated refactoring tools makes it more likely that the developer will perform the necessary refactorings, since the tools are much quicker and reduce chance of introducing bugs. From the literature survey of various research papers, the following factors are determined for measuring refactoring of code and level of optimization of code namely- reusability, maintainability, understandability, modifiability. Here, we have proposed a 10-point system, to measure refactorability. The 10-point system is based on the Likert’s Rating Scale. The International Journal of Research in IT, Management and Engineering www.gjmr.org 36
- 38. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 metrics that affect each factor of refactoring are determined and the values are calculated. The correlation and regression analysis is performed to determine the associations and variations among the various metrics used and their respective factors. The linear regression equation for applying regression analysis used is given as Y=a + bX1 + cX2 + dX3 + eX4 Where, Y= dependent variable, a, b, c, d, e are correlation coefficients, and X1, X2, X3, X4 are independent variables. The variation in independent variables affects the variation in dependent variable.The measure of strength of association in the regression analysis is given by the coefficient of determination, denoted by R-square. The coefficient varies between 0 and 1 and represents the proportion of total variation in the dependent variable that is accounted for, by the variation in the factors. REFERENCES [1] Martin Flower, Kent Beck, John Brant, William F. Opdyke, Don Roberts, 1999, Refactoring: Improving the Design of Existing Code, Addison Wesley. [2] Robert C. Martin Series, 2004, Working Effectively with Legacy Code, Michael C. Feathers, Prentice Hall. [3] Frank Simon, Frank Steinbruckner, Claus Lewerentz, 2001, Metrics Based Refactorings, In: Proceedings of 5th European Conference on Software Maintenance and Reengineering, IEEE CS Press, Lisbon, Portugal, pp. 30-38. [4] Arjun Guha, Shriram Krishnamurthi, 2010, Minding the (Semantic) Gap, Engineering Programming Language Theory. [5] W. C. Wake, 2003. Refactoring Workbook, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA. [6] C. Dorai, S. Venkatesh, 2003. Bridging the Semantic Gap with Computational Media Aesthetics, IEEE Multimedia, Vol. 10, No. 2, pp.15-17. [7] Tom Mens, Tom Tourwe, 2004, A Survey of Software Refactoring, IEEE Transactions on Software Engineering, Vol. 30, No. 2, pp. 126-139. [8] http://www.businessdictionary.com/definition/Likert-scale.html [9] John Fox, 1997, Applied Regression Analysis, Linear Models, and Related Methods, Thousands Oaks, CA: Sage Publications. International Journal of Research in IT, Management and Engineering www.gjmr.org 37
- 39. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 OPTIMIZING FILTERING PHASE FOR NEAR-DUPLICATE DETECTION OF WEB PAGES USING TDW-MATRIX Tanvi Gupta* ABSTRACT The voluminous amount of web documents has weakened the performance and reliability of web search engines. Web content mining face huge problems due to the existence of duplicate and near-duplicate web pages. These pages either increase the index storage space or increase the serving costs thereby irritating the users. In this paper, the proposed work is to optimize the filtering phase consists of prefix and positional filtering by adding suffix filtering which is a generalization of positional filtering to the suffixes of the records. The goal is to add one more filtering method that prunes candidates that survive the prefix and positional filtering. Keywords: near-duplicates, TDW-matrix, Prefix-filtering, Positional-filtering, suffix-filtering *Lingaya’s University, Faridabad, India International Journal of Research in IT, Management and Engineering www.gjmr.org 38
- 40. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 INTRODUCTION: Over the last decade there is tremendous growth of information on World Wide Web (WWW).It has become a major source of information. Web creates the new challenges of information retrieval as the amount of information on the web and number of users using web growing rapidly. It is practically impossible to search through this extremely large database for the information needed by user. Hence the need for Search Engine arises. Search Engines uses crawlers to gather information and stores it in database maintained at search engine side. For a given user's query the search engine searches in the local database and very quickly displays the results. But, the voluminous amount of web documents has resulted in problems for search engines leading to the fact that the search results are of less relevance to the user. In addition to this, the presence of duplicate and near-duplicate web documents has created an additional overhead for the search engines critically affecting their performance. The demand for integrating data from heterogeneous sources leads to the problem of near-duplicate web pages. Near-duplicate data bear high similarity to each other, yet they are not bitwise identical [2][4]. A. TDW Matrix Algorithm TDW Matrix Algorithm is a three-stage algorithm which receives an input record and a threshold value and returns an optimal set of near-duplicates. In first phase, rendering phase[3], all pre- processing are done and a weighting scheme is applied. Then a global ordering is performed to form a term-document weight matrix. In second phase, filtering phase, two well-known filtering mechanisms, prefix filtering and positional filtering, are applied to reduce the size of competing record set and hence to reduce the number of comparisons. In third phase, verification phase, singular value decomposition is applied and a similarity checking is done based on the threshold value and finally we get an optimal number of near-duplicate records. International Journal of Research in IT, Management and Engineering www.gjmr.org 39
- 41. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Fig.1: General Architecture [1]. B. Suffix Filtering Method:- Suffix filtering method, is a generalization of the positional filtering to the suffixes of the records. However, the challenge is that the suffixes of records are not indexed nor their partial overlap has been calculated. Therefore, we face the following two technical issues: (i) How to establish an upper bound in the absence of indices or partial overlap results? (ii) How to find the position of a token without tokens being indexed? The first issue is solved by converting an overlap constraint to an equivalent Hamming distance constraint. Then lower bound the Hamming distance by partitioning the suffixes in a coordinated way. The suffix of a record x is denoted as xs. Consider a pair of records, (x, y), that meets the Jaccard similarity threshold t, and without loss of generality, |y| ≤ |x|. Since their overlap in their prefixes, is at most the minimum length of the prefixes, the following upper bound can be derived in terms of the Hamming distance of their suffixes. H (xs, ys) ≤ Hmax =2|x| − 2 t/1 + t ・ (|x| + |y|) − ( t ・ |x| − t ・ |y| ) –(1) In order to check whether H (xs, ys) exceeds the maximum allowable value, an estimate of the lower bound of H (xs, ys) is provided below. First we choose an arbitrary token w from ys, International Journal of Research in IT, Management and Engineering www.gjmr.org 40
- 42. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 and divide ys into two partitions: the left partition yl and the right partition yr. The criterion for the partitioning is that the left partition contains all the tokens in ys that precede w in the global ordering and the right partition contains w (if any) and tokens in ys that succeed w in the global ordering. Similarly, divide xs into xl and xr using w too (even though w might not occur in x). Since xl (xr) shares no common token with yr (yl), H(xs, ys) = H(xl, yl) + H(xr, yr). The lower bound of H (xl, yl) can be estimated as the difference between |xl| and |yl|, and similarly for the right partitions. Therefore, H (xs, ys) ≥ abs (|xl| − |yl|) + abs (|xr| − |yr|) -(2) Finally, we can safely prune away candidates whose lower bound Hamming distance is already larger than the allowable threshold Hmax. RELATED WORK: A .Prefix Filtering: Consider an Ordering O of the token universe U and a set of records, each with tokens sorted in the order of O. Let the p-prefix of a record x be the first p tokens of x. If O(x, y) ≥ α, then the (|x|−α+1)-prefix of x and the (|y|−α+1)-prefix of y must share at least one token. Prefix filtering is a necessary but not sufficient condition for the corresponding overlap constraint, an algorithm is designed as: first build inverted indices on tokens that appear in the prefix of each record in an indexing phase. Then generate a set of candidate pairs by merging record identifiers returned by probing the inverted indices for tokens in the prefix of each record in a candidate generation phase. The candidate pairs are those that have the potential of meeting the similarity threshold and are guaranteed to be a superset of the final answer due to the prefix filtering principle. Finally, in a verification phase, evaluate the similarity of each candidate pair and add it to the final result if it meets the similarity threshold. B. Positional Filtering: Consider an ordering O of the token universe U and a set of records, each with tokens sorted in the order of O. Let token w = x[i], w partitions the record into the left partition xl (w) = x [1 . . . (i − 1)] And the right partition xr(w) = x[i . . |x|]. If O(x, y) ≥ α, then for every token w x ∩ y, O (xl (w), yl(w)) + min(|xr(w)|, |yr(w)|) ≥ α. International Journal of Research in IT, Management and Engineering www.gjmr.org 41
- 43. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 A natural idea to utilize the positional filtering principle is to combine it with the existing prefix filtering method, which already keeps tracks of the current overlap of candidate pairs and thus gives us O (xl (w), yl(w)). PROPOSED WORK: Here, I have proposed an idea of adding one more filtering technique suffix filtering , which is a generalized form of positional filtering which will further reduce the candidate pairs size, which helps in much more efficient way to detect near-duplicates. In this new architecture, there are three phases: 1) Rendering Phase 2) Filtering Phase 3) Verification Phase Rendering Phase consists of (i) Preprocessing which includes tokenization, stemming, and stop word removal. Then (ii) Feature Weighting is done according to the proposed scheme given in Ref.[1] on the preprocessed data .After that, (iii) Canonicalization[1]., is done. The final result of this phase is the TDW Matrix [1]. Filtering Phase includes (i) Prefix Filtering, the basic idea behind this filtering principle is that if two web pages share rare tokens, there is a chance that it might be similar. Since a global ordering is done based on document frequencies, prefix set of a record contain rare tokens. If no tokens are shared in prefix set, that record can be avoided from further processing. Once prefix filtering is over, (ii) positional filtering principle[2]. is applied in order to prune unwanted records from candidate set C. (iii) Finally, suffix filtering[2]. is done on the candidate pairs come from positional filtering, which uses hamming distance constraint(Hmax) instead of overlap constraints . The suffix of a record x is denoted as xs. Consider a pair of records, (x, y), that meets the Jaccard similarity threshold t, and without loss of generality, |y| ≤ |x|. Since their overlap in their prefixes, is at most the minimum length of the prefixes, the upper bound can be derived in terms of the Hamming distance of their suffixes. H (xs, ys) ≤ Hmax =2|x| − 2 t/1 + t ・ (|x| + |y|) − ( t ・ |x| − t ・ |y| ) In order to check whether H (xs, ys) exceeds the maximum allowable value, an estimate of the lower bound of H (xs, ys) is provided below. The lower bound of H(xl, yl) can be estimated as the difference between |xl| and |yl|, and similarly for the right partitions. Therefore, H (xs, ys) ≥ abs (|xl| − |yl|) + abs (|xr| − |yr|) - International Journal of Research in IT, Management and Engineering www.gjmr.org 42
- 44. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Finally, we can safely prune away candidates whose lower bound Hamming distance is already larger than the allowable threshold Hmax. Based on the records from mezzanine set M, a weight matrix A is created such that columns represent documents and rows represent terms. An element aij represents the weight of the global feature xi in record rj-1 since the first column represents input record r. In verification phase, (i) singular value decomposition is applied on weight matrix A and each record can be represented as a vector in 2D space. Then Jaccard threshold 0 ≤ t ≤1, can be mapped into an angle 180 ≥ θ ≥ 0 accordingly, using the formula θ =180*(1 – t) - (3) We can say that two records are purely dissimilar when the angle between them is 180 and they are exactly similar if it is 0. Ultimately we get an optimum set of records by analyzing the angle of a document with respect to input record r. If it satisfies the threshold θ, it can be marked as a near- duplicate of r and ranked on the basis of angle. t- Jaccard Threshold -Angle O- Overlap Threshold C- Candidate Set Hmax- Hamming Constraint M- Mezzanine Set O*- Optimal set Fig. 2 : Optimizing filtering phase in general architecture Proposed Algorithm for filtering Phase Input: TDW_Matrix,Record_Set,t Output: M International Journal of Research in IT, Management and Engineering www.gjmr.org 43
- 45. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Remarks: Assume that Input_Record is represented as the first entry in TDW_Matrix Filtering (TDW_Matrix, Record_Set, t) r←TDW_Matrix[1]; //prefix filtering C← φ; Prefix_Length← |r|- t.|r| +1; for all ri Record_Set Prefixi←|ri|- t.|ri| +1; for all j,k; 1≤ j ≤ Prefix_Length, 1≤ k ≤ Prefixi if (r[j] == ri[k]) C← C ri; //positional filtering M1← φ; for all ri C O← t/t+1(|r|+|ri|); for all p,q; 1≤ p ≤ Prefix_Length, 1≤ q ≤ Prefixi if (r[p]==ri[q]) ubound←1+ min(|r|-p, |ri|-q); if (ubound ≥ O) M1 ← M 1 ri; return M1; // suffix filtering /* x and y are tokens*/ SuffixFilter(x, y, Hmax, d) M← φ if d > MAXDEPTH then return abs(|x| − |y|) ; /*d-> current recursive depth*/ mid ← |y| /2 ; w ← y[mid]; o ← (Hmax−abs(|x|−|y|))/2 /* always divisible */; if |x| < |y| then ol ← 1, or ← 0 else ol ← 0, or ← 1; (yl, yr, f, diff) ← Partition(y,w,mid,mid); (xl, xr, f, diff) ← Partition(x,w,mid −o − abs(|x| − |y|) ・ ol, mid + o + abs(|x| − |y|) ・ or); if f = 0 then return Hmax + 1 H ← abs(|xl| − |yl|) + abs(|xr| − |yr|) + diff; International Journal of Research in IT, Management and Engineering www.gjmr.org 44
- 46. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 if H > Hmax then return H else Hl ←SuffixFilter(xl, yl,Hmax−abs(|xr|−|yr|)−diff, d+1) ; H ← Hl + abs(|xr| − |yr|) + diff; if H ≤ Hmax then Hr ← SuffixFilter(xr, yr,Hmax − Hl − diff, d + 1) ; return Hl + Hr + diff else return H, M← M ri; //partition / *s is the set of tokens and its two subsets are sl and sr */ Partition(s,w, l, r) sl ← φ ; sr ← φ; if s[l] > w or s[r] < w then return ( φ, φ, 0, 1) p ← binary search for the position of the first token in s that is no smaller than w in the global ordering within s[l . . r]; sl ← s[1 . . p − 1]; if s[p] = w then sr ← s[(p + 1) . . |s|]; /* skip the token w */; diff ← 0; else sr ← s[p . . |s|]; diff ← 1; return (sl, sr, 1, diff) CONCLUSION AND FUTURE WORK In this paper, the proposed work is to add one more filtering method in filtering phase named suffix filtering which is a generalization of positional filtering which will further reduce the candidate sizes. Both, positional filtering and suffix filtering are complementary to the existing prefix filtering technique. They successfully alleviate the problem of quadratic growth of candidate pairs when the data grows in size. So, this will further improve the International Journal of Research in IT, Management and Engineering www.gjmr.org 45
- 47. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 method to detect near-duplicates. Further research works can extend this to a more efficient method for finding similarity joins which can be incorporated in a focused w REFERENCES: [1] Midhun Mathew, Shine N Das ,TR Lakshmi Narayanan, Pramod K Vijayaraghvan, A Novel Approach for Near-Duplicate Detection of Web Pages using TDW Matrix. (IJCA, vol 19-no.7,April 2011) [2] Chuan Xiao, Wei Wang, Xuemin Lin , Jeffrey Xu Yu, Efficient Similarity Joins for Near Duplicate Detection, Proceeding of the 17th international conference on World Wide Web, pp 131 – 140. April 2008. [3] Shine N Das, Midhun Mathew, Pramod K.Vijayaraghavan, An Approach for Optimal Feature Subset Selection using a New Term Weighting Scheme and Mutual Information, Proceeding of the International Conference on Advanced Science, Engineering and Information Technology, Malaysia, 2011, pp 273-278, January 2011. [4] Gurmeet Singh Manku, Arvind Jain and Anish Das Sarma, Detecting near-duplicates for web crawling, In Proceedings of the 16th international conference on World Wide Web, pp. 141 - 150, Banff, Alberta, Canada, 2007. . International Journal of Research in IT, Management and Engineering www.gjmr.org 46
- 48. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 STUDY AND DESIGN OF BUILDING INTEGRATED PHOTO VOLTAIC SYSTEM AT HCTM CAMPUS KAITHAL, HARYANA Rajeev Kumar* Gagan Deep Singh** ABSTRACT The depletion of fossil fuel resources on a worldwide basis has necessitated an urgent search for alternative energy sources to meet up the present day demands. Solar energy is clean, inexhaustible and environment-friendly potential resource among renewable energy options. But neither a standalone solar photovoltaic system nor a wind energy system can provide a continuous supply of energy due to seasonal and periodic variations. Therefore, in order to satisfy the load demand, grid connected energy systems are now being implemented that combine solar and conventional conversion units. The objective of this work is to estimate the potential of grid quality solar photovoltaic power in HCTM Campus, Kaithal district of Haryana and finally develop a system based on the potential estimations made for a chosen area. Equipment specifications are provided based on the availability of the components in India. Annual energy generation by proposed Grid connected SPV power plant is also calculated. In the last, cost estimation and payback analysis of grid connected SPV power plant is done to show whether it is economically viable or not. Keywords: diurnal variations, daily energy output, monthly energy output, grid connected photovoltaic (PV) system, PWM inverters, solar radiation, yearly energy output. *Department of Electrical and Electronics Engineering, Haryana College of Engineering and Technology, Kaithal, Haryana **Department of Electrical Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab International Journal of Research in IT, Management and Engineering www.gjmr.org 47
- 49. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 1. INTRODUCTION Electricity is obtained from the PV array most efficiently during daytime. But at night or during cloudy periods, independent power systems use storage batteries to supply the electricity needs. With grid interactive systems, the grid acts as the battery, supplying electricity when the PV array cannot. The energy storage devices viz. battery has been avoided in this work. This approach reduces the capital as well as the running cost. We have tried to develop a grid connected photovoltaic system. Grid connected photovoltaic system is well known in various parts of world, and several technologies are used. There have been efforts to develop the power electronics circuitry involved. Several types of inverters have been designed. But our focus is to obtain the potential of grid connected photovoltaic system in Kaithal district of Haryana and finally develop a system based on the potential estimations made for a chosen area. Equipment specifications are provided based on the availability of the components in India. Annual energy generation by proposed Grid connected SPV power plant is also calculated. In the last, cost estimation and payback analysis of grid connected SPV power plant is done to show whether it is economically viable or not. 2. METHODOLOGY To find out the solar potential available at Kaithal district of Haryana, reading of solar radiation for site is required. So these readings are taken from HAREDA, Sec-26 Chandigarh. The data for solar radiation for Kaithal district of Haryana is shown in table 1 Table 1 Comparison of average solar insolation data {kwhr/m2/day} of district Kaithal Months HARSAC NASA % Deviation Jan. 2.76 3.58 22.9 Feb. 4.15 4.38 5.25 March 4.86 5.59 13 April 6.24 6.1 2.2 May 5.86 6.4 8 June 5.04 6.2 18 July 4.6 5.5 16 Aug. 4.47 5.14 13 Sep. 4.5 5.23 13 International Journal of Research in IT, Management and Engineering www.gjmr.org 48
- 50. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Oct. 4.85 4.71 2.9 Nov. 3.42 4.01 14 Dec. 2.53 3.36 24 Annual 4.44 5.02 11 HARSAC: Average values from January 2003 to December 2007 NASA: Average values from July 1983 to June 2005 Graph for monthly peak variation in Kaithal 8 solar insolation in 6 Kwh/m2 4 2 0 Graph 1 So, in order to design building integrated PV system in HCTM campus, district Kaithal, the average of annual solar insolation in district Kaithal measured by two agencies i.e. HARSAC and NASA is taken. According to HARSAC, annual solar insolation in Kaithal = 4.44 kwhr/m2/day. According to NASA, annual solar insolation in Kaithal = 5.02 kwhr/m2/day. So, average annual solar insolation in Kaithal = (4.44 + 5.02)/2 = 4.73 kwhr/m2/day. = 4.73/6 = 788.333w/m2/day. Efficiency of solar panel = 14.3% So, average peak output = 788.3×0.143 = 112.73 W/m2 International Journal of Research in IT, Management and Engineering www.gjmr.org 49
- 51. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 2 Load calculation of block A Fan load Tube Lights 6A/3pinsocket load Coolers Computers load Total (KW) load (KW) (KW) load (KW) load (KW) (KW) 262 × 80 = 286 × 40 = 77 × 40 = 3.08 6 × 300 = 26 × 300 = 7.8 45.08 20.96 11.44 1.8 Total load of A-Block = 45.08 KW Roof Area of Block A Length = 358 ft = 109.14 m; Breadth = 58 ft = 17.68 m Roof area = 109.14 × 17.68 = 1929.59 m2 3. ENERGY CALCULATION Table 3 Energy generated from Block A Name Available Area Average Possible Energy Energy of Area (m2) used Peak Plant Generated Generated Block (m2) Output Capacity per day per month (W/m2) (KW) (KW-hr) (KW-hr) A 1929.59 400 112.73 45 270 8100 4. SYSTEM SIZING Table 4 Solar Panel Specification Watt 180 Watt Voltage 24 Volts Current 7.5 A Type Polycrystalline Efficiency 14.3% International Journal of Research in IT, Management and Engineering www.gjmr.org 50
- 52. IJRIME E Volum me1Issue5 5 ISSN‐22 249‐ 1619 Temperat ture 25 deg c Dimensio (mm) ons 1593 × 790 × 50 Area of sing panel = 1 gle 1258470 (mm m) Area of sing panel = 1 gle 1.259 meter² ² Tilt angle e(slope) of PV Module 45 degree V Mounting g Fixed Type The wirin diagram o PV array is shown in Figure 1 ng of gure 1 wiring diagram of PV array Fig g f PWM inv verters are used for supp u pressing the harmonics p produced aft DC to AC Conversion ter C n. The calcu ulation for fi inding the ou utput voltage of inverter is shown be e r elow: [26] Phase vo oltage= Vph= 0.4714 × Vdc= 0.4714 240= 113. 4× .136 Volts. Line volt tage = VL = 0.779 × Vdc = 0.779× 2 = 187 Volts. 240 V KVA rati = KW × assumed po ing ower factor = KW × 0.8 Interna ational Journal of Research in IT, Management and Engineering www.gjmr.org
- 53. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 5 Solar Photovoltaic Power Plant Specification Plant Capacity 45 KW Voltage Output 240 Volts dc Current Output 187.5 A No. of Modules 250 Area 400 m2 Table 6 Inverter Specification KVA rating 36 KVA Input DC voltage 240Volts DC Input dc current 187.5A Output AC voltage 113.136 V ac (phase voltage) 187 V ac (line voltage) No. of Phases 3-φ Type PWM (for suppressing 3rd harmonics) Efficiency Almost 90-95% Total harmonic distortion < 5% Table 7 Transformer Specification KVA rating 36 KVA No of phases 3-φ Frequency rating 50 Hz Primary voltage rating 187 V Secondary voltage rating 400 V Primary current rating 192.51 A Secondary current rating 90A Connections Primary – delta (for suppressing3rd harmonics) Secondary – star International Journal of Research in IT, Management and Engineering www.gjmr.org 52
- 54. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 10 to 25 taps in secondary Efficiency Almost 95 % Extra features Air cooled 5. COST ANALYSIS FOR 45 KW SOLAR PV PLANT: 1.Cost of solar panels: - The BP 7180 most powerful module manufactured by BP Solar is used; cost of solar panel is Rs.160 per watt. So cost of 180 watt panel is = 180 × 160 = Rs. 28, 800. Total cost of solar panels = 250 × 28800 = Rs. 72, 00000. 2. Cost of 3-φ Inverter: - 36 KVA or 45 KW of an inverter /Power Conditioning Unit is used; multiply the size of the inverter by Rs. 25 per rated watt. Cost of inverter = 25 × 45,000 = Rs. 11, 25,000. 3. Cost of 3-φ step up Transformer: - 36 KVA or 45 KW of a step up transformer is used; multiply the size of the transformer by Rs. 20 per rated watt. Cost of transformer = 20 × 45000 = Rs. 9, 00000. 4. Cost of battery bank: - Exide Invared 400 Tubular Inverter Battery 12 V, 150Ah Price – 8,400/- . 40 numbers of batteries in two strings of 20 batteries in each string are used. [34] So, cost of battery bank = 40 × 8400 = Rs 3, 36, 000. Subtotal: Rs. 95, 61, 000. 5. Multiply the subtotal above by 0.2 (20%) to cover balance of system costs (wire, fuses, switches, etc.). Cost Estimate for Balance of System: (9561000 × 0.2) Rs. 19, 12, 200. Total Estimated PV System Cost is Rs. 1, 14, 73, 200. 6. ANNUAL ENERGY GENERATION The annual energy generation from the SPV power plant has been worked out based on the data on mean global solar radiant exposure over Haryana at district Kaithal. The mean global solar radiant exposure varies from 2.53 kWh/m² /day in the month of December to 6.24 kWh/ m²/day in the month of April according to HARSAC and from 3.36 kWh/m² /day in the month of December to 6.4 kWh/m²/day in the month of May according to NASA. The month-wise mean global solar radiant exposure is given at table below. Table 8 Mean Global Solar Radiant Exposure Kaithal, HARYANA (Acc. To HARSAC) International Journal of Research in IT, Management and Engineering www.gjmr.org 53
- 55. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Month Daily solar insolation in (kWh/m²/day) Energy Generated(kWh) Jan 2.76 4894 Feb 4.15 6646 March 4.86 8617 April 6.24 10707 May 5.86 10390 June 5.04 8648 July 4.6 8156 Aug 4.47 7926 Sept 4.5 7722 Oct 4.85 8600 Nov 3.42 5868 Dec. 2.53 4486 Monthly Average 4.44 7619 Table 9 Mean Global Solar Radiant Exposure Kaithal, HARYANA (Acc. To NASA) Month Daily solar insolation in (kWh/m²/day) Energy Generated(kWh) Jan 3.58 6348 Feb 4.38 7015 March 5.59 9912 April 6.1 10467 May 6.4 11348 June 6.2 10639 July 5.5 9752 Aug 5.14 9114 Sept 5.23 8974 Oct 4.71 8351 Nov 4.01 6881 Dec. 3.36 5957 Monthly Average 5.02 8614 Month Wise load calculation of HCTM, Campus based upon assumptions: Table 10 Month wise load assumption International Journal of Research in IT, Management and Engineering www.gjmr.org 54
- 56. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Month Type of load Load (KW) % of Total load (45 KW) Jan Lighting+ computer 18 40 Feb Lighting+ computer 18 40 March Lighting+ computer + fan load 27 60 April Lighting+ computer + fan load 38 85 May Lighting+ computer + fan load 38 85 June Lighting+ computer + fan load 12 25 July Lighting+ computer + fan load 12 25 Aug Lighting+ computer + fan load 40 90 Sept Lighting+ computer + fan load 40 90 Oct Lighting+ computer + fan load 40 90 Nov Lighting+ computer 16 35 Dec. Lighting+ computer 16 35 Table 11 Month wise load and energy generation (according to HARSAC) Month Energy consumption(KWh) Energy generated(KWh) Energy surplus (KWh) Jan 3348 4894 1546 Feb 3024 6646 3622 March 5022 8617 3595 April 6840 10707 3867 May 7068 10390 3322 June 2160 8648 6488 July 2232 8156 5924 Aug 7440 7926 486 Sept 7200 7722 522 Oct 7440 8600 1160 Nov 2880 5868 2988 Dec. 2976 4486 1510 International Journal of Research in IT, Management and Engineering www.gjmr.org 55
- 57. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 12 Month wise load and energy generation (according to NASA) Month Energy consumption(KWh) Energy generated(KWh) Energy surplus (KWh) Jan 3348 6348 3000 Feb 3024 7015 3991 March 5022 9912 4890 April 6840 10467 3627 May 7068 11348 4280 June 2160 10639 8479 July 2232 9752 7520 Aug 7440 9114 1674 Sept 7200 8974 1774 Oct 7440 8351 911 Nov 2880 6881 4001 Dec. 2976 5957 2981 7. SIMPLE PAYBACK ANALYSIS: A simplified form of cost/benefit analysis is the simple payback technique. In this method, the total first cost of the system is divided by the first-year energy cost savings produced by the system. This method yields the number of years required for the system to pay for itself. For new construction, it can be used to evaluate conventional construction to energy-efficient design alternatives. In simple payback analysis, we are assuming that the service life of the energy efficiency measure will equal or exceed the simple payback time. Simple payback analysis provides a relatively easy way to examine the overall costs and savings potentials for International Journal of Research in IT, Management and Engineering www.gjmr.org 56
- 58. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 a variety of project alternatives. While the payback period analysis does not take into consideration the time dependent value of money, nor the total accumulated cost or savings over the life of the system, for systems with equal expected lives, simple payback period can be applied to determine relative performance among alternatives. Simple Payback time (years) = Total cost of the system/ Annual Savings Energy Consumption data The energy consumption data from year 2010 -11 of HCTM, campus provided by accounts office, HCTM was used for this study and is shown in Table 13 Table 13 Energy Consumption data of HCTM, campus S.No. Month Total Units Utility Rate inclusive all charges Total Consumed (Rs./KWh) Electricity Bill (Rs.) 1 Jan 50385 4.6 2,31,771 2 Feb 52290 4.6 2,40,534 3 March 59500 4.67 2,78,234 4 April 94500 4.76 4,49,820 5 May 139250 4.68 6,52,554 6 June 155250 5.64 8,76,620 7 July 124250 6.06 7,53,220 8 Aug 136250 6.06 8,25,675 9 Sep 105045 4.93 5,18,670 10 Oct 93885 4.56 4,28,163 11 Nov 62465 4.6 2,87,339 12 Dec 53150 4.6 2,44,490 Graph for Monthly Variations in electricity bill of HCTM, Kaithal International Journal of Research in IT, Management and Engineering www.gjmr.org 57
- 59. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 monthly variation in electricity bill of HCTM, Kaithal 1,000,000 Bill in Rs. 0 Aug Sept Dec. Feb March Oct May April Nov June Jan July Graph 2 Simple Pay Back Time the total savings are given below. Table 14 – Savings for different months (According to HARSAC) S.No. Month Total Units produced with Utility Rate inclusive all charges Savings PV (Rs./KWh) (Rs.) 1 Jan 4894 4.6 22,512 2 Feb 6646 4.6 30,571 3 March 8617 4.67 40,241 4 April 10707 4.76 50,965 5 May 10390 4.68 48,625 6 June 8648 5.64 48,774 7 July 8156 6.06 49,425 8 Aug 7926 6.06 48,031 9 Sep 7722 4.93 38,069 10 Oct 8600 4.56 39,216 11 Nov 5868 4.6 26,992 12 Dec 4486 4.6 20,635 Annual Savings = Rs. 4, 64,056. Simple payback time = Total cost of system / Annual savings = 1, 14, 73, 200/ 4, 64, 056 = 24.7 years (According to HARSAC) International Journal of Research in IT, Management and Engineering www.gjmr.org 58
- 60. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 15 – Savings for different months (According to NASA) S.No. Month Total Units produced with Utility Rate inclusive all charges Savings PV (Rs./KWh) (Rs.) 1 Jan 6348 4.6 29,200 2 Feb 7015 4.6 32,269 3 March 9912 4.67 46,289 4 April 10467 4.76 49,822 5 May 11348 4.68 53,108 6 June 10639 5.64 60,003 7 July 9752 6.06 59,097 8 Aug 9114 6.06 55,230 9 Sep 8974 4.93 44,241 10 Oct 8351 4.56 38,080 11 Nov 6881 4.6 31,652 12 Dec 5957 4.6 27,402 Annual Savings = Rs. 5, 26, 393. Simple payback time = Total cost of system / Annual savings = 1, 14, 73,200/ 5, 26, 393 = 21.7 years (According to NASA) 8. CONCLUSION The methodology adopted seems satisfactory for determining the possible plant capacity for an arbitrarily chosen area. The design described is based on the potential measured. System sizing and specifications are provided based on the design made. Finally, cost analysis is carried out for the proposed design. Total Estimated 45 KW PV System Cost is Rs. 1, 14, 73,200. Annual energy generation is also calculated. From calculations done in chapter 6, it is clear that the estimated energy generated per month from block A is more than the energy requirement. This surplus energy generated can be stored and supplied to the hostels or .residential blocks in the campus during night time or may be used when sun is not available or can be sold to grid. . In the end of chapter 6, the simple payback period is calculated according to the solar radiation data given by two agencies namely HARSAC and NASA and found to be 24.7 years and 21.7 years respectively. From the results, it can be concluded that at current utility rate and demand charges, the system is not economically feasible. However, International Journal of Research in IT, Management and Engineering www.gjmr.org 59
- 61. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 in future, at higher utility rates like Rs 10-12/Kwhr and rebates from the government or utility, the system may be cost effective. With rebates, the demand for the PV panels will rise gradually leading to more production of panels and a likely drop in price thereby making the system more cost- effective. FUTURE SCOPE In future we will calculate the number of PV arrays and cost of the system which can meet the load demand of all campus. In starting we have not taken into account the air-conditioners load. In future we will include the load of air-conditioners. A detailed Cost analysis can be conducted considering carbon credit to show whether it is economically viable or not. Since the performance of PV system is strongly dependent on loss factors such as shading, PCS losses, mismatch, PV array temperature rise, etc. There is a necessity for reviewing these loss factors to evaluate and analyze accurately the performance of PV system. This system can be designed with also some another electrical appliances like DC- DC booster for boosting up the voltage wherever is necessary, filter for suppressing the ripples etc. Another transformer less design also can be done. DC –DC choppers with variable duty cycle can be used along with filters. For direct application of DC that kind of system can be designed. Intelligent devices like microprocessors, PLC (programmable logic controller) may be added to the system to keep the operating point (maximum power point) for maximum efficiency. To taken care of the uncertainty in the insolation level, use of fuzzy control can be done. Use of feedback path for automatic control-position control servo for changing the transformation ratio of variac can be used. A detailed performance analysis of the present system can be carried out to show its reliability as a future work. Solar PV is a technology that offers a solution for a number of problems associated with fossil fuels. It is clean decentralized, indigenous and does not need continuous import of a resource. On top of that, India has among the highest solar irradiance in the world which makes Solar PV all the more attractive for India. The state of Orissa and Andhra Pradesh also houses some of the best quality reserves of silica. India has a large number of cells and modules manufacturers. In spite of all above advantages Indian Photo Voltaic programme is still in the infancy stage. One of the reasons could be absence of simple, action oriented and aggressive PV policy of the country both in the state and central level. More quickly we do it with the professionals more we protect our future energy security. REFERENCES International Journal of Research in IT, Management and Engineering www.gjmr.org 60
- 62. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 [1]. P.Sritakaew & A.Sangswang, “On the Reliability Improvement of Distribution Systems Using PV Grid-Connected Systems”. IEEE Asia Pacific Conference on Circuits and systems. pp. 1354 - 1357, 2006. [2]. Allen M. Barnett, “Solar electrical power for a better tomorrow”. Photovoltaic Specialists IEEE Conference, Page(s): 1 – 8, 1996. [3]. G. Ofualagba, “Photovoltaic Technology, Applications and Market”, IEEE Conference on Power and Energy society general meeting - conversion and delivery to electrical energy, Vol.21, Page(s): 1 – 5, 2008. [4]. Souvik Ganguli and Sunanda Sinha, “A Study and Estimation of Grid Quality Solar Photovoltaic Power Generation Potential in some districts of West Bengal”. National Conference on Trends in Instrumentation & Control Engineering, Thapar University, Patiala, Page(s): 522-528, 29-30th Oct., 2009. [5]. Wang Jianqiang & Li Jingxin, “Design and Experience of Grid-connecting Photovoltaic Power System”, IEEE International Conference on Sustainable Energy Technology, Page(s): 607 - 610, 2008. [6]. B. Marion,J. Adelstein,K. Boyle and fellows, “Performance Parameters for Grid Connected PV Systems”, Photovoltaic Specialists IEEE Conference, Page(s): 1601 - 1606, 2005. [7]. D. Picault, B. Raison, and S. Bacha, “Guidelines for evaluating grid connected PV system topologies”. IEEE International Conference on Industrial Technology. Page(s): pp. 1- 5, 2009. [8]. Jinhui Xue, Zhongdong Yin, Qipeng Song, and Renzhong Shan, “Analyze and Research of the inverter for Grid connecting photovoltaic system”, Third IEEE International Conference on Electric Utility Deregulation and Restructuring Power Technologies, Page(s): 2530 – 2535, 2008. [9]. Eduardo Román, Ricardo Alonso & Pedro Ibañez, “Intelligent PV Module for Grid- Connected PV Systems”, IEEE Transactions on Industrial electronics, Vol.53.No.4, Page(s): 1066 – 1073, August 2006. [10]. Kosuke Kurokawa, Kazuhiko Kato , Masakazu Ito , Keiichi Komoto, Tetsuo Kichim, & Hiroyuki Sugihara “The cost analysis of very large scale PV system on the world desert”. Photovoltaic Specialists IEEE Conference, Page(s): 1672 – 1675, 2002. International Journal of Research in IT, Management and Engineering www.gjmr.org 61
- 63. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 [11]. Souvik Ganguli and Sunanda Sinha, “assessment of solar photovoltaic generation potential & estimation of possible plant capacity for 100 m2 available area in Kolkata”, International journal of engineering research and studies, vol. 1, pages 82-92. [12].Souvik Ganguli & Sunanda Sinha , “design of a 9KW grid connected solar photovoltaic power plant using 100 m2 available area in Patiala” , International journal of engineering research and studies, vol. 1, pages 12-27. [13]. Souvik Ganguli & Sunanda Sinha,” estimation of annual energy generation from a small grid connected solar photo voltaic power plant in Patiala”, International journal of engineering research and studies, vol. 2, pages 43-44. [14]. E.A. Alsema, P. Frank, K. Kato,” energy payback time of photovoltaic systems for three major PV applications”, 2nd world conference on photovoltaic solar energy conversion,Vienna, 6-10 July, 1998. [15]. Bangyin Liu, Chaohui Liang and Shanxu Duan,”Design Considerations and Topology Selection for DC-Module-Based Building Integrated Photovoltaic System”. 3rd IEEE conference on industrial electronics and applications, pp. 1066-1070, 2008. [16]. E.W. Smiley and L. Stamenic,” Optimization of Building Integrated Systems”. IEEE 29th conference on photovoltaic specialists. pp. 1501-1503, 2002. [17]. Tymandra Blewett, Margaret Horne and Robert Hill, “Helidon Prediction of Shading on Building Integrated Systems”. 26th IEEE conference on photovoltaic specialist. pp. 1393- 1396, 1997. [18]. H. MauNs, M. Schmid, B. Blersch, P. Lechner, H. Schade, “BIPV Installation Worldwide in ASI Technology”. Proceeding of 3rd IEEE world conference on photovoltaic energy conversion. Vol.3, pp. 2375-2378, 2003. [19]. Chang Ying-Pin and Shen Chung-Huang “Effects of the Solar Module Installing Angles on the Output Power” IEEE 8th international conference on electronics measurement and instruments, pp. 1-278 - 1-282, 2007. [20]. [http:Energy Scenario] “Solar PV Industry 2010: Contemporary scenario and emerging trends” available at www.isaonline.org/documents/ISA_SolarPVReport_May2010.pdf [21]. [http:Energy Scenario] “the solar PV landscape in India” available at www.solarindiaonline.com/.../The_Solar_PV_Landscape.pdf [22]. [http: Solar Electric Systems] “Chapter Three Introduction to Solar Electric Systems” available at www.kysolar.org/ky_solar_energy_guide/chapters/Chapter_3_PVintro.pdf International Journal of Research in IT, Management and Engineering www.gjmr.org 62
- 64. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 [23]. [http: Series and Parallel connection] “Series and Parallel Wiring” available at www.termpro.com/articles/spkrz.html. [24]. [http: BP_7180_V2] “specification of PV module” available at www.bp.com/liveassets/bp_internet/solar/bp.../b/BP_7180_V2.pdf [25] [http: Photovoltaic modules] ―Photovoltaic modules, system and application available at www.icpress.co.uk/etextbook/p139/p139_chap15.pdf International Journal of Research in IT, Management and Engineering www.gjmr.org 63
- 65. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 FUNDS MANAGEMENT OF ICICI BANK Manju Sharma* ABSTRACT “The ICICI total business Rs. 52000 crores, it is a gigantic Financial Institution. At present the total business is 1.91 lakh crore. The total deposits are Rs. 202017 crores total a advances Rs. 181206, net profit for the year Rs. 1006 crores, Net Interest income Rs. 2035 crores on 31 March 2010.” Total Assets are worth Rs. 363400 crores, operating profits are worth Rs. 9732 crore, interest income Rs. 25707 crores. In this paper, I am trying to analyze the the funds management of ICICI bank. Keywords: Credit, Demat, Funds, Management, Trade. * Research Scholar, Singhania University International Journal of Research in IT, Management and Engineering www.gjmr.org 64
- 66. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 ANALYSIS OF ICICI FUNDS MANAGEMENT: The huge funds available with ICICI Bank following functional activities are taken care are as: MAIN SERVICES The following are the main services: Credit Services Home Loan Services Trade Services Agricultural Services International Banking Services Vestro Accounts Services Proxy Banking Services OTHER SERVICES The following are the others services: Security Market Services Corporate and Structural Services Investment Services Cash Management Services Foreign Exchange Services Demat Securities Credit Services Abn Amro Bank, Allahabad Bank, American Express Bank, Andhra Bank, Bank of India, Canara Bank, Central Bank of India, Citibank, Corporation Bank, HDFC Bank, HSBC Bank, ICICI Bank, Indian Overseas Bank, Oriental Bank of Commerce, Punjab National International Journal of Research in IT, Management and Engineering www.gjmr.org 65
- 67. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Bank, State Bank of India (SBI), Standard Chartered Bank, IDBI, United Bank of India, UTI Bank. The advancement of technology and the birth of competition, banks are in the race of becoming the best in the country. With an eye upon customer satisfaction policy they are providing best of the best services with the minimum hazards. Banks like ABN AMRO introduced banking with a coffee. It made a tie-up with one of the best coffee bar in the country, Barista and remained open till late evening for customers with a setup of a coffee bar in the premises. Few banks have introduced world ATM card to make travelers across the globe more safe and secure. What else. Internet and Phone Banking is the call of the day for banks. In this race towards the best, selected top 20 banks in the country from all segment it is not the ranking of banks but only for general information about the top banks in India. (I) CREDIT SERVICES ICICI Banks offer a varied range of cards to suit your requirements. These cards having a wide acceptance, nationally and internationally, coupled with benefits of channels like Internet and Mobile, with enhance your experiences. ICICI Bank Credit Cards give you the facility of cash, convenience and a range of benefits, anywhere in the world. These benefits range from life time free cards, Insurance Benefits, global emergency assistance service, discounts, utility payments, travel discounts and much more. The ICICI Bank Debit Card is a revolutionary form of cash that allows customers to access their bank account round the clock, around the world. The ICICI Bank Debit Card can be used for shopping at more than 100,000 merchants in India and 13 million merchants worldwide. Presenting ICICI Bank Travel Card. The Hassle Free way to Travel the world. Traveling with US Dollar, Euro, Pound Sterling or Swiss Francs; Looking for security and convenience; take ICICI Bank Travel Card. Issued in duplicate. Offers the Pin based security. Has the convenience of usage of Credit or Debit card. International Journal of Research in IT, Management and Engineering www.gjmr.org 66
- 68. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 II) HOME LOANS – SERVICES The ICICI Bank Home Loans are available in the following cities: * Aurangabad * Delhi * Ahmedabad * Mumbai * Bangalore * Nasik * Baroda * Nagpur * Chennai * Pune * Calcutta Loan Amount: The loan amount is up to a maximum of 85% of the value of the property to be financed. Minimum Amount : Rs. 1 lakh Maximum Amount : Rs. 10 million Tenor The tenor of a ICICI Bank home loan ranges from a period of 1 year to 30 years depending on the type of loan availed. Eligibility The eligibility criteria are: The applicant should be at least 25 years of age and a maximum of 65 years at the time of loan maturity. The applicant should have a regular source of income. Documentation: The documents required are: Passport size photograph of all the applicants. Residence and age verification, which may be established from the Pan Card, Election ID, Passport, Driving License or Ration Card Bank statements for the last six months Latest salary slip/ statement showing all deductions in case of employed applicants International Journal of Research in IT, Management and Engineering www.gjmr.org 67
- 69. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Certified copies of Balance Sheets and Profit and Loss accounts, IT acknowledgments, advance tax challans (for company/ firm and personal account) for the last three years in case of self-employed applicants. Memorandum /Articles of Associations for Companies, partnership deeds for firms and a brief profile of your company/ firm in case of self-employed applicants. Property Documents (as and where applicable): Application form duly filled and signed. Draft sale agreement Previous sale agreements NOC to mortgage from society/ builder as per our format? Society Share Certificates Occupancy certificate (Ready property or U/C property) Original stamped receipts for the payments already made to the builder/ seller, till date 371 Clearance from the appropriate Income Tax authorities, if applicable. List of additional amenities from builder where applicable. Interest Rate Structure Tenure (years) Interest Rate 1-5 11.25% 6-20 12.75% 21-30 12.85% EMI Chart per Rs. 1,00,000 Tenor Interest: Interest: Interest: 11.25% 12.75% 12.85% 5 years Rs. 2269 N.A. N.A. 20 Years N.A. Rs.1168 N.A. 30 Years N.A. N.A. Rs. 1100 Note: of cause these rates are subject to change with the ordinance of RBI. International Journal of Research in IT, Management and Engineering www.gjmr.org 68
- 70. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Other Costs Fees: 1.8% of the sanctioned Loan amount. Processing fee: Rs. 500 (at the time of application) III) TRADE SERVICES ICICI Bank offers a wide range of Trade Services designed to assist you in building on your strengths, so that your company can seize business opportunities across the world. ICICI Bank has in place a Centralized Trade Services Unit, which adheres to six sigma standards. As a result, ICICI Bank customers experience fewer delays in receiving payment, require less effort in locating collecting information, gain increased control over foreign receivables and experience improved cash flows. Online Trade Services: ICICI Bank customers can effect remittances as well as get their applications for issuance of Letters of Credit and Bank Guarantees processed online. This not only extends tremendous convenience to the entire process, but also allows the customer to enjoy the benefits of simplified documentation, online verification of status and savings in cost and time. Online Trade Services can be availed by enrolling for Corporate Internet Banking (CIB) offered by ICICI Bank. Online LC Online EPC Online Bank Guarantee Online Remittances Online EEFC Track the status of your export and import bills, view details of your LCs, guarantees and forward contracts, get your export LC electronically advised – do all this and more through our web services. Advisory Services: International Journal of Research in IT, Management and Engineering www.gjmr.org 69
- 71. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Banks believe in delivering value. ICICI Bank clients can avail our advisory services on forex markets, currency movements, regulatory issues, risk management and other issues in trade finance. Exchange Rates Track the latest movements in currency to plan your business. Customized Solutions and New Product Development ICICI Bank constantly customizes solutions and introduces innovative products for its Trade Services clients. Export Document Tracking: Bank realizes the criticality of time in your trade transaction process. You can now track the status of shipment of your export documents online. Arrange for Export Credit Insurance: Export credit insurance is an important aspect of international trade. Know more about the services of India’s leading export credit agencies ICICI Lombard and ECGC. Trade Regulation & Policy Update: The global trade scenario is governed by country specific as well as international regulation. Refer to the existing regulations and update yourself with the latest. Trade Facilitation In a developing country like India, a number of organizations occupy the role of trade facilitators. They are a source of valuable information, resources, services and guidance to Indian exporters. Country Scan The economic and political climate of a country influences business decisions of exporter sand importers across the globe. Coface country reports and country ratings aid you in taking informed decisions. Concepts in International Trade: Global trade transactions are complex. The exporter and importer entering a contract is only the beginning of a chain of events that need to be precisely coordinated. At one level it involves document preparation, at another level it requires coordinating with third party. International Journal of Research in IT, Management and Engineering www.gjmr.org 70
- 72. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 IV) AGRICULTURE SERVICES Adopting innovative approach to Agriculture Business financing and by offering complete supply chain solutions. ICICI Bank has changed the face/ dynamics of Agriculture Business Finance in the country. ICICI Bank, India’s first universal bank, has the financial strength and the expertise to offer probably the widest array of financial services for your business. Whatever your requirements, if you are into agriculture business, out dedicated tam of agriculture sector specialists and finance professionals with deep understanding of the sectoral business environment will device custom solutions and offer complete supply chain solutions for your business. Whether you are in the business of Diary, Sugar, Plantations, Seed sector, Fertilizer Sector, Infrastructure, Markfeds or Food Processing, ICICI Bank is the one stop shop for all your financial needs. V) INTERNATIONAL BANKING SERVICES… ICICI Bank’s International Banking Division Offers a complete range of correspondent banking services to banks and financial institutions. The products offered are as under: Automated INR Payment Services VOSTRO Accounts Cross Border Trade Services Trust and Retention Account Services INR Agency Clearing Services Automated INR Payment Services: International Journal of Research in IT, Management and Engineering www.gjmr.org 71
- 73. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 This product offers efficient distribution of inward remittance from exchange Houses and Banks abroad. Key features of this service are:- Web/SWIFT messaging facility Routing of payment through our internal electric network if the account is with any of our branches. If accounts are with other banks, distribution is achieved through bank drafts/ cheques by courier. Cover funding through INR account/or through foreign currency accounts On-line access to INR account if maintained MT 950/940 facility Dedicated helpdesk for backup and tracking Convenience in funding/ providing cover Evolving a structure that best address the concerns of all institutions involved in financing of the project/ other financial requirements. Key features of the product are: Waterfall management of cash flows Acting as paying and receiving agent Foreign Exchange agent Safekeeping and Custody for the underlying Account administration Cash escrows and security escrows Pre constructions and post construction management of cash flows Investment services Regulatory liaison Advisory Services Electronic reporting via the Internet or specialist on-line system; Customized MIS reporting. INR Agency Clearing Services: ICICI Bank offers Clearing Services across all major centers for facilitating clearing of their customer cheques. Key features of the product are: Clearing of customer cheques through our code as a sub member International Journal of Research in IT, Management and Engineering www.gjmr.org 72
- 74. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Facility to issue demand drafts payable across all our branches by your branch/ branches Collection of cheques/ instruments through our network Funds transfer services from other centers to your branch/ branches through our networks Customized MIS and a dedicated helpdesk. VI) VOSTRO ACCOUNTS SERVICE VOSTRO accounts provide INR account services to correspondent banks. All the accounts are held in a special center located in our Nariman Point branch at Mumbai. Key features of the product are: Access to our network spread across all major centers Internet access to account Web based messaging facility/ SWIFT based Customized MIS Funding convenience Competitive tariff Cross Border Trade Services: ICICI Bank offers full range of cross border trade services to its correspondent banks. This services is available across all major destinations in India with significant foreign trade potential. We have fully integrated communication channels amongst branches, which directly helps in saving valuable time facilitating cross border transactions. Advising and confirming of documentary letters of credit Confirmation/ reissuance of standby LCs and guarantees. Documentary collections/ open account transactions Payment processing and distribution Advising and confirming of documentary credits Negotiation of documents Computerized processing ensuring speedy services Trust and Retention Account Services: International Journal of Research in IT, Management and Engineering www.gjmr.org 73
- 75. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 ICICI Bank is one of the leading Trust and Retention (Escrow) Account services providers in India, have a considerable experience in managing various types of Trust and Retention accounts including. VII) PROXY BANKING SERVICES Indian villages were miles away from mutual funds, insurance and even equity trading. Thanks to Internet Kiosk and the ATM duo which had made it possible for rural India. This kiosk has been set up by ICICI Bank in partnership with network n-Logue Communications in remote villages of Southern part of the country. This is known as Proxy Banking. With the help of fibre optic cables, this works on wireless in local loop technology. Reasons for Setting up of Proxy Banking 58% of rural households still do not have bank accounts. Only 21% of rural households have access to credit from a formal source. 70% of marginal farmers do not have deposit account. 87% households have no formal credit. Only 1% rural households rely on a loan from a financial intermediary. The loans take between 24 to 33 weeks to get sanctioned. Consumer bribe officials to get loans approved which varies between 10 and 20 percent of the loan amount. Branch including in rural is a loss-making. Others Services; To name a few as: Security Market Services Corporate and Structural Services Investment Services Cash Management Services Foreign Exchange Services Demat Securities Credit Services International Journal of Research in IT, Management and Engineering www.gjmr.org 74
- 76. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 BIBLIOGRAPHY 1. Ahmed, K. & Nicholls, D., “The impact of non-financial company characteristics on mandatory disclosure compliance in developing countries: the case of Bangladesh”, The International Journal of Accounting Education and Research, 1994, pp: 62-77. 2. Baker, Kent H. & Haslem, J.A., “Information Needs of Individual Investors”, The Journal of Accountancy, November 1973, pp: 64-69. 3. Barrett, M. E., “The extent of disclosure in annual reports of large companies in seven countries”, The International Journal of Accounting Education and Research, 1977, pp: 1-25. 4. Barrett, M. Edgar, “Financial Reporting Practices: Disclosure and Comprehensiveness in International Setting”, Journal of Accounting Research, Vol. 14 No.1, Spring 1976, pp: 10-26. 5. Buzby, S.L., “Company Size, Listed Versus Unlisted Stocks and the Extent of Financial Disclosure”, Journal of Accounting Research’, Vol. 13, 1975, pp: 16-37. 6. Buzby, Stephen L., “Selected Items of Information and Their Disclosure in Annual Reports”, The Accounting Review, Vol. XLIX No. 3, July 1974, pp: 423- 435. 7. Cayanan, Arthur S., “An Assessment Of The Financial Reporting Practices Of Some Listed Philippine Banks In 2008”, Philippine Management Review, 2009, Vol.16, pp :13 -23. 8. Chander, Subhash, “Regulation of Corporate Disclosure Practices in India”, Indian Journal of Accountancy, Vol. XXXV (2), June 2005, pp: 20-28. 9. Chandra, Gyan, “A Study of the Consensus on Disclosure among Public Accountants and Security Analysts”, The Accounting Review, October 1974, pp: 733-742. 10. Chandra, Gyan, “Corporate Business Reporting Consensus between Preparers and Auditors”, Journal of Accounting and Finance, Vol. 16 No.1, October 2001 – March 2002, pp: 3-22. International Journal of Research in IT, Management and Engineering www.gjmr.org 75
- 77. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 11. Chandra, Gyan, “Information Needs of Security Analysts”, The Journal of Accountancy, December 1975, pp: 65-70. 12. Chipalkatti, Niranjan, “Market Microstructure Effects of the Transparency of Indian Banks”, National Stock Exchange, India Working Paper No.51, 2002, pp: 1-36. 13. Choi, Frederick D.S., “Financial Disclosure and Entry to the European Capital Market”, Journal of Accounting Research, autumn 1973, pp: 159-174. 14. Chow, Chee W. & Wong-Boren, Adrian, “Voluntary Financial Disclosures by Mexican Firms,” The Accounting Review, July 1987, pp: 533-41. 15. Cooke, T.E., “An Assessment of Voluntary Disclosure in the Annual Reports of Japanese Corporations”, International Journal of Accounting, 1991, pp: 174-189. 16. Cooke, T.E., “The Impact of Size, Stock Market Listing and Industry, Type on Disclosure in the Annual Reports of Japanese Listed Corporations”, Accounting and Business Research, 1992, pp: 229-237. 17. Coombs, H.M. & Tayib, M., “Developing a Disclosure Index of Local Authority Published Accounts – A comparative study of local authority published financial reports between the U.K. and Malaysia”, www.glam.ac.uk/kus/1244/ publications.1998. International Journal of Research in IT, Management and Engineering www.gjmr.org 76
- 78. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 EMERGING TRENDS IN HUMAN RESOURCE MANAGEMENT— A CHALLENGE TO THE ITES Raunak Narayan* ABSTRACT Today’s euphoric corporate environment has posed daunting challenges for human resource management. While demand for manpower is rising, supply is not able to keep pace. While wage bills are bloating, quality of manpower is deteriorating. And while, there is a surfeit of graduates, their employability is low, due to poor skills. This is just the ideal setting for the management to shed its decades of inhibition take centre stage and dictate strategy alongside other key functions such as finance, marketing and sales. Human resource management (HRM) is a process of bringing people and organizations together so that the goals of each other are met. Over the years, highly skilled and knowledge based jobs are increasing while low skilled jobs are decreasing. This calls for future skill mapping through proper HRM initiatives. Globalization of the world economy and several other trends are again triggering changes in how companies manage and utilize their human resources. The Indian Information Technology Enabled Services (ITes) industry has been one of the great success stories of modern India. An industry that did not exist two decades ago is now the bread and butter of the nation and the envy to the world. It has created international benchmark for quality, proving to the world and to ourselves that Indian companies can compete globally and win on quality. It has demonstrated what can be achieved by unleashing the power of middle class, first generation entrepreneurship in India. Hence, The ITes organizations which is working on the principle of attracting, managing, nurturing and retaining their employees is moving ahead with the competition and is having competitive advantage over other organizations. And to adopt this principle, now it has become very essential to face the challenges posed by the new trends of HR. It is this theme upon which this paper has been worked out. International Journal of Research in IT, Management and Engineering www.gjmr.org 77
- 79. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Keywords—Human Resource Management, Information Technology Enabled Services (ITes), Competitive Advantage, Attrition, BPO INTRODUCTION In the life of any nation, company or individual, movement is life and stagnation is death. Therefore, as long as companies are growing, they are fully alive. Organizations must move continuously from one process to another, from one strategy to another, and from one structure to another. So long as we are renewing these kinds of things and re-looking at them, that’s where growth and achievement comes in. Human Resource Management (HRM) has evolved considerably over the past century, and experiences a major transformation in form and function primarily within the past two decades. Driven by a number of significant internal and external environmental forces, HRM has progressed from a largely maintenance function, to what many scholars and practitioners today regard as the source of sustained competitive advantage for organizations operating in a global economy. Human Resource (HR) is the only function where building capabilities takes place—building capabilities of organization and individuals. And that is why HR will have to build organizations whether it is ITes or any other. Building, grooming/preparing people, building different kind of mindsets, defining roles and making them understand what kind of society and landscape is going to emerge, become extremely important. ITes is defined as outsourcing of processes that can be enabled with information technology and covers diverse areas like finance, HR, administration, health care, telecommunication, manufacturing, etc. Armed with technology and manpower, these services are provided from e- enabled locations. ITes is a catchall term used for the myriad processes that ant bureaucratic entity undertakes in servicing its employees, vendors, customers. The Indian Ites industry has rapidly opened up, expanded, matured and with a wave of consolidation has scripted new initiatives. *University of Calcutta International Journal of Research in IT, Management and Engineering www.gjmr.org 78
- 80. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 With substantial evolution being witnessed, India has become the ideal and most preferred offshore destination. Numerous factors such as supply of skilled manpower, global standard telecom infrastructure, proactive and positive policy environment and friendly corporate tax policies have given India an edge in the global marketplace. In spite of offering distinct advantages such as cost competitiveness, highly skilled labor and a high level of service maturity, the industry witnessed certain unique challenges especially in the area of HR. Of myriad HR-related challenges faced by the industry, the critical ones are the attrition and scarcity of professionals equipped with necessary domain knowledge and communication skills. Despite being global phenomena, these challenges have become a matter of concern in Indian ITes industry. EMERGING TRENDS IN HR Over the years, highly skilled and knowledge based jobs are increasing while low skilled jobs are decreasing. This calls for future skill mapping through proper HRM initiatives. Indian organizations are also witnessing a change in systems, management cultures and philosophy due to the global alignment of Indian organizations. Hence, it is necessary for the management to invest considerable time and amount, to learn the changing scenario of the HR in the 21st century. In order to survive the competition and be in the race, HR department should consciously update itself with the transformation in HR and be aware of the HR issues cropping up. With high attrition rates, poaching strategies of competitors, there is a huge shortage of skilled employees and hence, a company’s HR activities play a vital role in combating this crisis. Suitable HR policies that would lead to the achievement of the organization as well as the individual’s goals should be formulated. Some recent trends that are being observed are as follows: Traditional HR Practice Emerging HR practice Administrative Role Strategic Role Reactive Proactive International Journal of Research in IT, Management and Engineering www.gjmr.org 79
- 81. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Separate from Company Mission Key part of Organizational Mission Production Focus Service Focus Functional Organization Process based Organization People as expenses People as key Investments/ Assets To leapfrog ahead of competition in this world of uncertainty, organizations have introduced six- sigma practices. Six-sigma uses rigorous analytical tools with leadership from the top and develops a method for sustainable improvement. These practices improve organizational values and helps in creating defect free products or services at minimum costs. Human resource outsourcing is a new accession that makes a traditional HR department redundant in an organization With the increase of global job mobility, recruiting competent people is also increasingly becoming difficult, especially in India. Therefore, organizations are required to work out a retention strategy for the existing skilled manpower. To have a competitive advantage over rivals, organizations are working on the principle of Attracting, Managing, Nurturing and Retaining their employees. Companies no more believe in the tall hierarchical structures, and cubical with closed doors of the boss, but have given way for flat organizational structures with more spans of control and less chain of command. In place of being the autocratic leader or manager, they play the role of team builders, mentors, coach, or counselors. Following the principles of retaining the brains in the organization, the policies have become more and more flexible providing alternative and flexible work schedule. Flexi time, compressed week, job sharing, etc Organizations today are not only making the structure and policies employee friendly rather they are trying to improve the quality of work life where International Journal of Research in IT, Management and Engineering www.gjmr.org 80
- 82. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 employees can enjoy their working and will be able to manage the balance between work life and personal life. They provide them the in-house facility of health club, yoga, meditation, alternative work schedule, picnics, and family get together where they can reduce their stress and strains. They also provide educational and medical facility. Training and Development are the other areas where organizations are trying to take the lead over other organizations so that employees can be made multi- skilled to handle multiple tasks. The new horizon has opened up where the organizations competing are clubbing together to form the network of talents. Other areas where remarkable changes are being made are in communication pattern. Gone are those days when employees feared talking to their bosses. Things are replaced by cross communication, gang plank mechanism, open door policy, internet, intranet, mentoring, counseling, coaching, etc. Communication is no more restricted to form top to bottom rather bottom to up is encouraged more in the organization to make functioning more smooth and to have grievance free, satisfied employees. With the continuous rise in competition, business cannot flourish if individualism is prevailing in the organization. Therefore, to meet the need of the time the growing organizations are following collectivism culture, where working in groups and teams are emphasized. Performance appraisal has also taken a new shape. It is not confined to the boss and subordinates, rather more emphasis is being given on overall appraisal of the employees (360 degree appraisal). Employees are also given opportunities for succession growth. The ITes industry, which is rapidly growing industry in India, is not an exclusive of the above stated emerging trends; moreover it is mainly the cause and effected industry for the changes in HRM. Hence, it is very essential to know the challenges posed by those merging HR trends to ITes industry. International Journal of Research in IT, Management and Engineering www.gjmr.org 81
- 83. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 CHALLENGES OF EMERGING HR TRENDS TO ITES Attracting and Retaining Talent— The ITes industry has, during the last decade, been probably the most attractive sector to work in. It has therefore been able to get nest talent. The challenge now is to safeguard and build on this prime position. Attractive compensation, challenging assignments, good working conditions and growth opportunities are amongst the main determinants of where talent gravitates, along with the indefinable “glamour value” of a company. Taking care of these parameters is a necessary task for the ITes industry. High level of Attrition While India does have a large talent pool, not all are ‘industry –ready’ or equipped with the necessary skill sets to become useful to the companies. This means there is plenty of supply at the entry level but huge gaps in the middle and senior management levels. This has resulted in increased levels of poaching and attrition cases. Presently, the average attrition rate faced by this industry is somewhere around 30-35 percent. Not a serious career option Another very critical issue of concern for HR managers is that most students and professionals working in call centers do not see this industry as a long-term career option due to the inherent nature of the job (monotonous and lacking challenges), most of the time there is low interest in the work. Mismatch of Expectations Expectations mismatch leads to higher attrition. This is partly due to the perceptions created in the general public with respect to the career growth, type of work, compensation offered, competition, etc. Many a times, people are not able to create a work-life balance and often opt out. The right positioning will help attract the right profile of associates , which will International Journal of Research in IT, Management and Engineering www.gjmr.org 82
- 84. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 automatically manage their expectations from the industry and this will, in turn lead to lower attrition rates. Communication Issue Lack of effective communication is another contentious issue. The absence of regular, two-way communication between agents, their team managers and the senior management is a common complaint in the industry. High training costs On an average, the ITes companies incur three types of training costs—voice/ accent, soft skills and process training. For a start-up, in the initial stage the training costs will be high. It generally accounts for four months salary of employee hired, though the actual training would be probably being for just a month. Generating motivation and increasing efficiency Generating motivation and increasing efficiency is far more difficult in situations where the job is repetitive and routine, as in many ITes operations. This is a real challenge to managers. This is important because a key part of India’s value proposition as the outsourcing destination is based on productivity and quality- factors that depend critically on motivation. Compensation Compensation is probably the single most important parameter in most cases. The challenge here is to provide an attractive package in context of rising expectations, and yet minimize overall cost escalation. In this situation, “poaching” people from other companies by offering higher pay packages is self-defeating for the industry as a whole. An important correction lies in ensuring an ever-growing and sufficiently large supply pipeline for fresh entrants. The challenges of workplace diversity The future success of any organization relies on the ability to manage a diverse body of talent that can bring innovative ideas, perspectives and views to their work. The challenge faced of workplace diversity can be turned into a strategic organizational asset if an organization is able International Journal of Research in IT, Management and Engineering www.gjmr.org 83
- 85. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 to capitalize on this melting pot of diverse talents. With the mixture of talents of diverse cultural backgrounds, genders, ages, and lifestyles, an organization can respond to business opportunities more rapidly and creatively, especially in the global arena, which must be one of the important organizational goals to be attained. More importantly, if the organizational environment does not support diversity broadly, one risks losing talent to competitors. Dearth of innovative and efficient HR professional AIMA 2003 report projected that tourism and IT/ ITes would generate between 20- 72 million jobs by 2020. Most of this employment-generation is happening in people-intensive sectors. Thus, the need for a strong HR backbone arises. Even at a very conservative estimate we are looking at least 5 million new jobs in the next five years. And a quick calculation would show that even if we need one HR professional for 1000 employees, one needs at least 5000 new HR professionals Few Solutions Moving towards ‘B class’ cities Due to the high demand and supply gap and scaling attrition numbers, many companies are moving towards ‘B class’ cities like Chandigarh, Bhopal, Lucknow and Dehradun, to attract talent and set up their operations. In Karnataka, the ITes companies are looking towards Mangalore, Hubli, and Mysore rather than concentrating only in Bangalore. Looking for career oriented employees—there is also a change in employee profile, with organizations looking for older and experienced people who will bring in stability. The requirement is for those people for whom salary is not just a pocket money, but a career opportunity. The ideal employees for BPOs would be people from the middle and lower-middle income households, who are willing to work hard and have a strong sense of responsibility and dedication towards their employers. Initially, though it might lead to scaling training costs, as the section might lack in basic communication and soft skills. Proper rewarding A research report says that in today’s scenario. International Journal of Research in IT, Management and Engineering www.gjmr.org 84
- 86. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 70% of your employees are less motivated than they used to be 80% of your employees could perform significantly better if they wanted to 50% of your employees only put enough effort into their work to keep their job One might be aware of Employee reward covers how people are rewarded on accordance with their value to an organization. The ways in which people are valued can make a considerable impact on the effectiveness of the organization, and is at the heart of the employment relationship. Educating about career opportunities The common misconception is that there are only three position in ITes or BPOs-that of an agent, a team leader and the project leader. There is however more to it. According to Deepak Dhawan, VP (HR) of EXL Services, there is an immense opportunity for professionals with a CA or MBA background: “An individual can choose from managing quality, get into training, Sex sigma process, problem solving equations, relationship management, HR and workflow activities or business development”. Government initiatives Nasscom has recently started a project with different private players training institutes and academia in Andhra Pradesh, Karnataka and Kerala, for preparing “employable” ITes workforce. According to A. Sundararajan, IT secretary of Kerala, “It will help chart out indicative domain- wise manpower requirement projections from the industry. Skill set standardization, Government recognized certification in ITes, and inclusion of ITes as a discipline in graduate studies by universities will help in making ITes as a career choice by students”. Creating effectiveness and efficiency through motivation Empowering, engaging and energizing employees are established ways of creating effectiveness and efficiency through motivation. Organizational structures, systems and procedures are facilitators of these, and companies need to focus greater attention on these aspects. Providing an excellent physical work environment International Journal of Research in IT, Management and Engineering www.gjmr.org 85
- 87. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 The ITes industry has to provide an excellent physical work environment. It needs to continue to be a leader in providing these facilities, including food, fitness and sports facilities. While these “add-ons” are not inconsequential, work satisfaction through challenging, cutting-edge assignments, and substantial growth prospects are definitely major determinants for retention. Consider the employees as a resource The statement “people are our greatest asset”, though a cliché that is often heard in corporate boardrooms is, nevertheless, true in most industries. However, nowhere are human resources as critically important as in the ITes sector. Human resources are not only the drivers and principal value-creators of the output of this industry; they are also the intellectual capital or the “infrastructure investment”. HR managers should evolve with new roles With the increase in competition, locally or globally, organizations must become more adaptable, resilient, agile and customer-focused to succeed. And within this change in environment, the HR professional has to evolve to become a strategic partner, an employee sponsor or advocate, change mentor within the organization. The HR manager will also promote and fight for values, ethics, beliefs, and spirituality within the organizations. Improving employability Despite the large number of students graduating, it is common to hear companies complain about not finding suitable candidates. The updating of syllabi and ensuring relevant content would be useful. In addition, it would be worthwhile to include some basic IT courses for the Science, Mathematics, and Commerce and Economics students. This would enable graduates in these streams to be considered for employment in a number of ITes jobs. CONCLUSION To conclude, change is necessary to survive. Those who change with the change survive and those don’t vanish. What is today may be obsolete tomorrow. It is necessary to upgrade and restructure every time to withstand and face the situations. HR policies of the ITes organization should also be changed with the time and new strategies, policies should come up to retain the International Journal of Research in IT, Management and Engineering www.gjmr.org 86
- 88. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 talents in the organization to increase the success ratio in today’s competitive global environment. HR managers have to manage all the challenges that they would face from recruiting employees, training them, and developing strategies for retaining them and building up an effective career management system for them. Just taking care of employees would not be enough; new HR initiatives should also focus on the quality needs, customer-orientation, productivity, stress, team work and leadership building. REFERENCES [1] Dr. Nagaraju Battu (2007), “Human Resource Development” [2] Dr. Pritam Singh- HR, The Taskmaster, Times of India daily Ascent, 24th November, 2010 [3] Prof. Anitha H.S. “Succession Planning”, “Benchmarking for Infusing Competitive Culture among Indian PSUs” and “Commercial viability of PSUs”, Deccan Herald, August 25,2009 [4] Mrs. Soumya K.R. (2010) “Assessment of training need and evaluation of training effectiveness on employees of select ITes in Bangalore” [5] Dr. Alvin Chan (2010), “Challenges of HRM” [6] Rituparna Banerjee (2010), “Emerging trends on HRM” [7] Punita Jasrotia Phukan (2009), “Changing HR paradigm in the ITes sector” [8] K.P. Kanchana (2009), “Emerging trends in HR” [9] Sanjeev Sharma, “Retention Strategies in ITes-BPO industry” [10] www.bpoindia.org International Journal of Research in IT, Management and Engineering www.gjmr.org 87
- 89. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 FUNDAMENTAL CHALLENGES IN EMERGENT FIELD OF SENSOR NETWORK SECURITY AND INITIAL APPROACHES TO SOLVE THEM D. P. Mishra* M. K. Kowar ** ABSTRACT Rapid technological growth in the area of micro electro-mechanical systems (MEMS) has spurred the development of small inexpensive sensors capable of intelligent sensing. A significant amount of research has been done in the area of connecting large numbers of these sensors to create robust and scalable Wireless Sensor Networks (WSNs). Proposed applications for WSNs include habitat monitoring, battlefield surveillance, and security systems. Although individual sensor nodes have limited capabilities, WSNs aim to be energy efficient, self- organizing, scalable, and robust. Almost all of the research is centered on meeting these challenges, but relatively little work has been done on security issues related to sensor networks. The resource scarcity, ad-hoc deployment, and immense scale of WSNs make secure communication a challenging problem. Since the primary consideration for sensor networks is energy efficiency, security schemes must balance their security features against the communication and computational overhead. Paper will describe the fundamental challenges in the emergent field of sensor network security and the initial approaches to solve them. Keywords: Security, Sensor Networks *Department of Computer Science & Engineering, BIT, Durg ** Department of Electronics & Telecommunication Engineering, BIT, Durg International Journal of Research in IT, Management and Engineering www.gjmr.org 88
- 90. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 INTRODUCTION & MOTIVATION Rapid technological growth in the areas of micro electro-mechanical systems and miniaturization has spurred the development of a new kind of network. This network is composed of small, inexpensive sensors capable of intelligent sensing. Much research has been done with the aim of connecting large numbers of these sensors to create robust and scalable Wireless Sensor Networks (WSNs) on the order of hundreds of thousands of devices. Communication usually consists of source nodes which sense the data and return it to sink nodes over multiple hops. Sink nodes may be ordinary sensor nodes or specialized base stations with greater resources. Sensor network proponents envision a future in which thousands to millions of tiny sensor devices will be embedded in almost every aspect of life. The goal is to create intelligent environments capable of collecting massive amounts of information, recognizing significant events automatically, and responding appropriately. Sensor networks facilitate “large-scale, real- time data processing in complex environments” [14]. If sensor networks are to attain their potential, however, secure communication techniques must be developed in order to protect the system and its users. The need for security in military applications is obvious, but even more benign uses, such as home health monitoring, require confidentiality so widespread deployment and overall success of sensor networks will be directly related to their security strength. SENSOR SECURITY CHALLENGES The nature of large, ad-hoc, wireless sensor networks presents significant challenges in designing security schemes. Some of the most pronounced challenges are described below. Wireless Medium The pervasive applications proposed for sensor networks necessitate wireless communication links. Furthermore, the ad-hoc deployment of sensor motes makes wired communication completely inappropriate. The wireless medium is inherently less secure because its broadcast nature makes eavesdropping simple. Any transmission can easily be intercepted, altered, or replayed by an adversary. The wireless medium allows an attacker to easily intercept valid packets and easily inject malicious ones. International Journal of Research in IT, Management and Engineering www.gjmr.org 89
- 91. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Ad-Hoc Deployment The ad-hoc nature of sensor networks means no structure can be statically defined beforehand. The network topology is always subject to changes due to node failure, addition, or mobility. Nodes may be deployed by air drop, so nothing is known of the topology prior to deployment. Since nodes may fail or be replaced the network must support self-configuration. Security schemes must be able to operate within this dynamic environment. Hostile Environment Most challenging factor is the hostile environment in which sensor nodes function. Motes face the possibility of destruction or (perhaps worse) capture by attackers. Since nodes may be in a hostile environment, attackers can easily gain physical access to the devices. Attackers may capture a node, physically disassemble it, and extract from it valuable information (e.g. cryptographic keys). The highly hostile environment represents a serious challenge for security researchers. Resource Scarcity The extreme resource limitations of sensor devices pose considerable challenges to resource- hungry security mechanisms. A representative example of a sensor device is the Mica mote. It has a 4 MHz Atmel ATMEGA103 CPU with 128 KB of instruction memory, 4 KB of RAM for data, and 512 KB of flash memory [7]. The radio operates at up to 40 Kbps bandwidth at a range of a few dozen meters. Such hardware constraints necessitate extremely efficient security algorithms in terms of bandwidth, computational complexity, and memory. Immense Scale Finally, the proposed scale of sensor networks poses a significant challenge for security mechanisms. Simply networking tens to hundreds of thousands of nodes has proven to be a substantial task. Security mechanisms must be scalable to very large networks while maintaining high computation and communication efficiency. ATTACKS & DEFENSES International Journal of Research in IT, Management and Engineering www.gjmr.org 90
- 92. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Security goals for sensor networks include the same four primary objectives as conventional networks: availability, confidentiality, integrity, and authentication. Although sensor network security is characterized by the same properties as traditional network security. Karlof and Wagner identify two major classes of attackers: mote-class and laptop-class. Mote-class attackers are constrained to the CPU, power, bandwidth, and range limitations of the mote platform. Laptop-class attackers, however, may possess more powerful hardware such as a faster CPU, a larger battery, a high-power radio transmitter, or a sensitive antenna. This section examines the security attacks and corresponding defenses at each level of the network. Physical Layer Attacks at the physical level include radio signal jamming and tampering with physical devices. Jamming- well-known attack on wireless communication is simply interference with the radio frequencies used by a device’s transceiver. It represents an attack on the availability of a network, thus creating a denial-of-service condition [14]. The standard defense against jamming involves the use of spread-spectrum or frequency hopping techniques. Prevention of denial of service attacks is a difficult task. Since most sensor networks currently use single frequency communication, Wood, Stankovic, and Son have proposed a Jammed Area Mapping (JAM) service which emphasizes detection and adaptation in response to jamming. They assume that only a portion of the network is being jammed and attempt to map this area so it can be avoided. Nodes in the affected area switch to low power mode. Information about jammed areas is passed to the network layer so it can successfully route packets around the dead areas. If spread spectrum techniques cannot be incorporated into motes, then detection algorithms such as JAM may be important in defending against jamming attacks. Tampering A second problematic issue at the physical layer is the relative ease and potential harm of device tampering. This problem is exacerbated by the large-scale, ad-hoc, pervasive nature of sensor networks. Access to thousands of nodes spread over several kilometers cannot be completely controlled [14]. Attackers may very well have greater physical access to nodes than the network administrator. Nodes may be captured, interrogated, and compromised without International Journal of Research in IT, Management and Engineering www.gjmr.org 91
- 93. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 difficulty. While node destruction is undesirable, node compromise may be even more dangerous because of the cryptographic material compromised. Link Layer The link and media access control (MAC) layer handles neighbor-to-neighbor communication and channel arbitration. Like the physical layer, the link layer is particularly susceptible to denial of service attacks. Collision If an adversary can generate a collision of even part of a transmission, he can disrupt the entire packet [Perrig, Stankovic, and Wagner 2004]. A single bit error will cause a CRC mismatch and possibly require retransmission. In some MAC protocols, a corrupted ACK may cause exponential back-off and unnecessarily increase latency. Although error-correcting codes protect against some level of packet corruption, intentional corruption can occur at levels which are beyond the encoding scheme’s ability to correct. The advantage, to the adversary, of this MAC level jamming over physical layer jamming is that much less energy is required to achieve the same effect: preventing devices from successfully transmitting packets. Exhaustion Another malicious goal is the exhaustion of a network’s battery power [10]. In addition to the previous types of attacks, exhaustion may also be induced by an interrogation attack. In the IEEE 802.11-based protocols, for example, Request To Send (RTS) and Clear To Send (CTS) packets are used to reserve bandwidth before data transmission. A compromised node could repeatedly send RTS packets in order to elicit CTS packets from a targeted neighbor, eventually consuming the battery power of both nodes [10]. Unfairness A more subtle goal of the previously described attacks may be unfairness in the MAC layer [10]. A compromised node can be altered to intermittently attack the network in such a way that induces unfairness in the priorities for granting medium access. This weak form of denial of service might, for example, increase latency so that real-time protocols miss their deadlines [10]. Network Layer International Journal of Research in IT, Management and Engineering www.gjmr.org 92
- 94. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 The network layer is responsible for routing packets across multiple nodes. Due to the ad-hoc nature of sensor networks, every node must assume routing responsibilities. WSNs are particularly vulnerable to routing attacks because every node is essentially a router. Classifications of routing attacks are summarized below and are followed by a general discussion of secure routing techniques. False Routing Information The most direct attack on routing is to spoof, alter, or replay routing information. This false information may allow adversaries to create routing loops, attract or repel traffic, shorten or extend route lengths, increase latency, and even partition the network [7].Clearly, the falsification of routing information can cripple a network. The standard solution is to require authentication for routing information, Selective Forwarding Selective forwarding is a more subtle attack in which some packets are correctly forwarded but others are silently and intentionally dropped. A compromised node could be configured to drop all packets, creating a so-called black hole. Since the network is capable of handling node failure it may conclude that the compromised node has failed and find another route. If the compromised node selectively forwards packets, the neighboring nodes will believe that the malicious node is still functioning correctly and continue to route packets to the node. Sinkhole Attack In the sinkhole attack, a node spuriously advertises a very good route to a sink node (base station) in order to lure all nearby traffic to itself. Thus all traffic within some sphere of influence is drawn into the sinkhole centered at the compromised node. This attack enables the selective forwarding attack along with other attacks. An adversary mounting a laptop-class attack may actually provide the fastest route to a sink by using its greater range to reach the sink in a single hop. Sybil Attack The Sybil attack occurs when a single node claims to be other nodes in the network. Geographic routing protocols are particularly vulnerable to the Sybil attack since they are designed with the assumption that no node can be in two places at once. If a node lies about it location, it can significantly disrupt routing performance in geographic routing protocols. International Journal of Research in IT, Management and Engineering www.gjmr.org 93
- 95. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Wormhole Attack The wormhole attack is used to convince two possibly distant nodes that they are neighbors so that the attacker can place himself on the route between them. Basically, the adversary tunnels messages from one part of the network to another through an out-of-bound channel available only to the attacker. Wormholes typically involve two colluding nodes. HELLO Flood Attack The Hello flood attack, a novel attack proposed by Karlof and Wagner, exploits routing protocols that require periodic HELLO packets be transmitted to announce the presence of a node. Nodes which receive a HELLO packet assume they are within radio range of the sender, i.e., the sender is a neighboring node. This assumption may be false in the case of a laptop-class attacker. An adversary with a powerful transmitter may be able to transmit a single HELLO packet to every node in the network and convince every node that it is a one-hop neighbor. As a result, the network is left in a state of confusion. If, for example, the attacker advertises a very quick route to a base station in the HELLO packet, many non-neighbor nodes will attempt to route packets through the malicious node. In actuality, however, they will be sending packets into oblivion. Karlof and Wagner point out that this attack is actually a “one- way, broadcast wormhole.” The simplest solution for this attack is to verify the bidirectionality of a link before acting on its information. Essentially, routing messages from one-way links are ignored. Karlof and Wagner propose an identity verification protocol to defend against the HELLO flood attack. Acknowledgement Spoofing The last routing attack Karlof and Wagner identify is the acknowledgement spoofing attack. Several routing protocols rely on link layer acknowledgements for determining next-hop reliability. If an adversary can respond for weak or dead nodes, he can deceive the sender about the strength of the link and effectively mount a selective forwarding attack. The artificial reinforcement allows the attacker to manipulate the routing through the weak or dead node. There have been several approaches to defend against network layer attacks. Authentication and encryption are a first step, but more proactive techniques such as monitoring, probing, and International Journal of Research in IT, Management and Engineering www.gjmr.org 94
- 96. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 transmitting redundant packets have also been suggested. Secure routing methods protect against some of previous attacks. Proposed techniques are described below. Authentication & Encryption Link layer authentication and encryption protect against most outsider attacks on a sensor network routing protocol. Even a simple scheme which uses a globally shared key will prevent unauthorized nodes from joining the topology of the network. In addition to preventing selective forwarding and sinkhole attacks, authentication and encryption also make the Sybil attack impossible because nodes will not accept even one identity from the malicious node [7]. SPINS and TinySec are two proposed solutions for link level encryption and authentication. Monitoring A more active strategy for secure routing is for nodes to monitor their neighbors and watch for suspicious behavior [14]. In this approach, nodes act as “watchdogs” to monitor the next hop transmission of the packet. Probing Another proactive defense against malicious routers is probing [14]. This method periodically sends probing packets across the network to detect blackout regions. Since geographic routing protocols have knowledge of the physical topology of the network, probing is especially well-suited to their use. Redundancy is another strategy for secure routing [14]. An inelegant approach, redundancy simply transmits a packet multiple times over different routes. Hopefully, at least one route is uncompromised and will correctly deliver the message to the destination. PROPOSED SOLUTIONS While the majority of the research in sensor networks has focused on making them feasible and useful, a few researchers have proposed solutions to the security issues discussed previously. Sensor network security mechanisms can be divided into two categories: communication protocols and key management architectures. Communication protocols deal with the International Journal of Research in IT, Management and Engineering www.gjmr.org 95
- 97. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 cryptographic algorithms used to achieve availability, confidentiality, integrity, and authentication. Key management architectures handle the complexities of creating and distributing keys used by communication protocols. Communication Protocols Currently there have been two major secure communication protocols proposed for sensor networks: SPINS [2] and TinySec [Karlof, Sastry, and Wagner 2004]. Both protocols work at the link level to provide message confidentiality, authentication, and integrity using symmetric cryptography. The limited memory and CPU speeds of sensor nodes almost completely exclude the use of asymmetric cryptography sensor networks. SPINS SPINS (Security Protocols for Sensor Networks) is comprised of two link layer protocols: SNEP and µTELSA. SNEP (Secure Network Encryption Protocol) provides data confidentiality, two-party authentication, and data freshness. Perrig et al. identify three patterns of communication in sensor networks: node to base station, base station to node, and base station to all nodes. SNEP handles the first two types, and µTELSA handles the last. In order to minimize computation and memory requirements, SNEP bases all symmetric cryptographic primitives (encryption, message authentication code, hash, and random number generator) on the same block cipher, RC5. Another design goal is to minimize communication overhead. This is accomplished by reducing the packet overhead to 8 bytes and by storing state information instead of transmitting it with each packet. SNEP supports data authentication, replay protection, and semantic security [11]. Authentication is provided by calculating and appending a message authentication code (MAC) to each message. A MAC is essentially a cryptographically secure checksum [Karlof, Sastry, and Wagner 2004]. The MAC is recalculated upon reception and compared to the value in the transmission. To implement replay protection, SNEP requires a synchronized counter value at each node. The MAC is calculated using a secret key and the counter. As a result, out-of-sync packets will not be accepted. SPINS includes a counter exchange protocol for synchronizing counter values between two hosts. Although maintaining a synchronized counter adds significant International Journal of Research in IT, Management and Engineering www.gjmr.org 96
- 98. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 overhead, it allows semantic security, a strong security property which assures that identical messages are encrypted differently each time they are encrypted. For example, if a sensor is simply reporting YES or NO regarding the occurrence of some event, an attacker may be able to discover the encrypted value of NO and subsequently be able to understand all encrypted transmissions. By encrypting the data based on the counter as well as the key, each NO will encrypt differently. μTELSA, the second part of SPINS, provides authenticated broadcast for sensor networks. The goal of μTELSA is to allow base stations to transmit authenticated broadcasts to all of the nodes while preventing a compromised node from forging messages from the sender. μTELSA uses symmetric mechanisms to create an asymmetric system using a loosely synchronized clock. Receivers buffer broadcast packets until they receive the decryption key which is disclosed once in a specified time interval (epoch). The keys are calculated using a one-way hash function (F) and are disclosed in the reverse order that they are generated. Once a node receives a key, it can apply the same hash function to calculate the keys for previous epochs and decrypt buffered packets. Figure 1 illustrates this process. Figure 1: μTELSA key disclosure and computation. Each hash mark denotes an epoch. P1, P2,…P7 represent packets. SPINS performs reasonably well according to its authors. Although key setup is expensive (4 ms), encrypting a 16 byte message and calculating its MAC only takes 2.5 ms. The limited bandwidth of the test platform, 10 kbps, allows time to perform key setup, encryption, and MAC calculation for every packet. The performance of μTELSA is bounded by the amount of buffer space available. Consequently, key disclosures must happen relatively frequently and must be reliably received. The stated limitations of SPINS are that it does not completely deal with compromised nodes and it does not deal with denial-of-service attacks. SPINS merely ensures that a comprised node does not reveal the key to every node in the network. Additionally, SNEP needs tight synchronization of counters since they are not transmitted. Another design weakness is the International Journal of Research in IT, Management and Engineering www.gjmr.org 97
- 99. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 dependence of μTELSA on buffering packets. The extremely limited storage space characteristic of sensors devices makes buffering particularly unattractive. TinySec TinySec is a more recent solution to the sensor link layer security problem. The TinySec protocol provides access control, message integrity, and message confidentiality. TinySec explicitly omits replay protection, recommending it be performed at the application layer. The designers of the protocol emphasized usability and transparency in hopes of increasing TinySec’s adoption. To this end, TinySec has been incorporated into the official release of TinyOS, the small, event-driven operating system designed for sensor motes. Unlike SPINS, TinySec has been fully implemented and exhibits promising performance. Encryption and authentication can be performed in software with only 10% energy overhead and 8% increased latency. TinySec operates in two modes: authenticated encryption (TinySec-AE) and authentication only (TinySec-Auth). Like SPINS, TinySec implements authentication and integrity by the use of message authentication codes (MACs). TinySec uses a cipher block chaining construction (CBC- MAC) for computing and verifying MACS because of its efficiency and speed. TinySec’s designers make authentication mandatory but encryption optional because not all messages need to be kept secret. Message authentication and integrity, both provided by the MAC, are critical for security since they block invalid senders and protect the data from corruption. The MAC protects the entire contents of the packet, including header information. Since the 2 byte CRC of a normal TinyOS packet is redundant, it is replaced by a 4 byte MAC. IV Dest AM Len Src Ctr Data MAC (2) (1) (1) (2) (2) (0 - 29) (4) (a) Tiny-Sec AE Packet Format Dest AM Len Data MAC (2) (1) (1) (0 - 29) (4) (b) Tiny-Sec Authentication Packet Format Dest AM Len Grp Data MAC (2) (1) (1) (1) (0 - 29) (4) (c) Tiny-OS Packet Format Figure:2 International Journal of Research in IT, Management and Engineering www.gjmr.org 98
- 100. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Figure 2: TinyOS and TinySec packet formats. The byte size of each field is indicated. Hatched fields are protected by the MAC. In TinySec-AE, the dark grey data portion is encrypted. This effectively adds only 2 bytes of overhead for authentication. Refer to Figure 2(b) for an illustration of the TinySec-Auth packet format. If confidentiality of message contents is required by the application, TinySec-AE is used. For encryption, TinySec uses the Skipjack block cipher by default but also supports RC5. In order to provide semantic security, TinySec uses an initialization vector (IV) to encrypt each packet and sends this value in each packet. To minimize packet size overhead, the entire header contents (destination, AM, length, and source) and a 2 byte counter are used as the IV. This effectively gives an 8 byte IV for the cost of only 2 bytes. Figure 2(c) illustrates this structure. Sufficiently long IVs are critical because repeated IVs leak information about a cryptosystem. In the case of the CBC cipher used by TinySec, only the length of the longest shared prefix of two messages is revealed if the entire 8 byte IV repeats. A repetition only occurs when one node sends two packets to the same destination with the same AM type, length, and counter value. Given the low data rate for sensor nodes, the probability for such a repetition is low. The performance of TinySec has proven that sensor network security can be efficiently done in software. TinySec requires 728 bytes of RAM and 7146 bytes of program space. The energy overhead imposed by TinySec is 3% for TinySec-Auth and 10% for TinySec-AE. The extra computation increases the time to transmit a packet 1.6% for TinySec-Auth and 7.9% for TinySec-AE. The energy, bandwidth, and latency of TinySec are all less than 10% and due almost entirely to the increased packet length. Not surprisingly, TinySec is being used by several other research projects throughout the country. With its impressive performance and ease of use, TinySec is the best sensor network security communication protocol to date. Key Management Architectures Despite TinySec’s merits as a communication protocol, it does not even attempt to solve the issue of key management. Key management handles the generation and secure distribution of cryptographic keys as well as techniques to protect the network from lost keys. A variety of International Journal of Research in IT, Management and Engineering www.gjmr.org 99
- 101. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 strategies exist for accomplishing this task. Some of the major approaches are summarized below. LEAP The efficiency and speed of symmetric algorithms are well suited to sensor nodes and have been the default choice for sensor network designers. Most symmetric schemes require keys be loaded onto devices before deployment. Using a different key for every link provides the best security against compromised nodes but is incompatible with the basic nature of sensor networks. Sensor networks rely on data aggregation and in-network processing to increase network efficiency. Nodes along the path consolidate data to reduce the overall number of messages in the network. This cannot take place if messages are encrypted. In an effort to balance these two extremes, LEAP [14] utilizes four types of keys for different security levels. LEAP supports an individual key shared only with the base station, a pairwise key shared with another sensor node, a cluster key shared with multiple neighboring nodes, and a group key shared by all the nodes in the network. The advantage of LEAP is that it supports in-network processing while minimizing the security impact of a compromised node to the node’s immediate neighbors. LEAP provides a key for every need. This property offers convenience at the cost of storage space and complexity, neither of which are abundantly available to sensor nodes. LKHW Another approach to key management is to use a hierarchy to store keys. Pietro et al. propose a scheme based on Logical Key Hierarchy (LKH) built on top of directed diffusion. Directed diffusion is a data-centric routing protocol that uses exploratory flooding to find the best path to send events of interest. The extension of LKH over directed diffusion comprises the LKH Wireless (LKHW) protocol. LKHW is a secure multicast scheme that enforces backward and forward secrecy. New nodes cannot decrypt old traffic, and evicted nodes cannot decrypt future traffic. LKHW uses a tree structure to store keys. The root of the tree serves as the key distribution center (KDC), and each leaf represents a user. Each leaf stores the set of keys belonging to its direct ancestors up to the KDC. The reason for using a tree structure is to increase the efficiency of re-keying. Re-keying occurs whenever a node joins or leaves the International Journal of Research in IT, Management and Engineering www.gjmr.org 100
- 102. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 group. The energy required for re-keying is shown to be approximately logarithmic to the group size. Random Key Predistribution Another novel approach to key management is random key predistribution [2]. In this strategy, a random pool of keys from the key space is preloaded into each node. Two nodes must find a common key in their sets in order to communicate. A challenge-response protocol is used to verify that two nodes have a key in common. TinyPK Despite the fact that asymmetric cryptography has been almost universally considered to be too resource-intensive for use in sensor networks, there have been some efforts to adapt public cryptography techniques to sensor devices. TinyPK [13] is one such project that uses the RSA cryptosystem to handle symmetric key distribution. To minimize calculations by the sensor motes, e=3 is used as the public exponent. Encryption simply requires cubing a 1024-bit number and taking its residue modulo a large prime number. Implementing a public-key system requires a modest amount of infrastructure including a Certificate Authority (CA). The CA’s public key is preloaded onto each node and is used to verify messages from the CA. Despite the adaptations, TinyPK still performs slowly by current standards. Table 1 summarizes the operation times for RSA encryption at various key sizes. RSA Key Size Time (sec) 512 3.8 768 8.0 1024 14.5 Table 1: RSA encryption (exponentiation) times Watro et al. confess that the current implementation is too slow for RSA private operations (decryption) since execution times would be on the order of tens of minutes. They suggest using TinyPK as a method of authenticating external parties to the sensor network and moving the computationally expensive operations to the external device when possible. Although public key cryptography possesses many advantages in handling key management, it is currently infeasible International Journal of Research in IT, Management and Engineering www.gjmr.org 101
- 103. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 for node-to-node communication in sensor networks. Perhaps asymmetric techniques will be viable on more powerful hardware of the future. Most researchers predict, however, that devices will ride Moore’s Law down the price curve instead of increasing in speed. If this is the case, then algorithmic optimizations will be required for public-key systems. CONCLUSION Sensor networks hold the potential to transform the way computing affects life. In order to reach this potential, secure communication must be achieved. The wireless, ad-hoc, resource-limited nature of sensor networks creates substantial challenges for researchers. At the physical layer, probable attacks include frequency jamming and device tampering, two techniques with known solutions but entailing greater financial cost. The link layer of sensor networks is also susceptible to denial of service attacks in the form of maliciously induced collisions and exhaustion attacks. The network layer is particularly vulnerable since every node in a sensor network is a router. Although link layer encryption and authentication serve as a first layer of defense, maximum security can only be achieved by designing routing algorithms with security in mind. SPINS and TinySec satisfactorily address the issue of link layer encryption, authentication, and integrity but require key management architectures to be practical. Current key management solutions are not sufficiently adapted to the unique requirements of sensor networks. If sensor networks are to reach their potential, secure communication must exist. REFERENCES [1] Agrawal, Dharma P.; Qing-An Zeng. 2003. Introduction to Wireless and Mobile Systems. Brooks/Cole – Thompson, Pacific Grove, CA. [2] Chan, H., A. Perrig, and D. Song. Random Key Predistribution Schemes for Sensor Networks. IEEE Symposium on Security and Privacy (SP) (May 11 - 14, 2003). [3] Hill, Jason, Robert Szewczyk, Alec Woo, Seth Hollar, David Culler, and Kristofer Pister. System architecture directions for networked sensors. In Proceedings of the Ninth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS IX) (November 2000). International Journal of Research in IT, Management and Engineering www.gjmr.org 102
- 104. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 [4] Hu, Y.C., A. Perrig, and D.B. Johnson. Rushing Attacks and Defense in Wireless Ad Hoc Network Routing Protocols. Proceedings of the ACM Workshop on Wireless Security (WiSe'03) (San Diego, California, September 19, 2003). [5] Huang, Q., J. Cukier, H. Kobayashi, B. Liu, and J. Zhang. Fast Authenticated Key Establishment Protocols for Self-Organizing Sensor Networks. Proceedings of the Workshop on Wireless Sensor Networks and Applications, (WSNA'03) (San Diego, California, September 19, 2003). [6] Jolly, G., M.C. Kuscu, P. Kokate, and M. Younis. A Low-Energy Key Management Protocol for Wireless Sensor Networks. IEEE Symposium on Computers and Communications (ISCC'03). (Kemer – Antalya, Turkey, June 30 - July 3 2003). [7] Karlof C. and D. Wagner. Secure Routing in Wireless Sensor Networks: Attacks and Countermeasures. Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications (SNPA'03) (11 May 2003). [8] Karlof, Chris, Naveen Sastry, and David Wagner. TinySec: A Link Layer Security Architecture for Wireless Sensor Networks. Proceedings of the Second ACM Conference on Embedded Networked Sensor Systems (SenSys’04) (November 3 - 5, 2004). [9] Law, Y. W., S. Dulman, S. Etalle, and P. Havinga. Assessing Security-Critical Energy- Efficient Sensor Networks. 18th IFIP TC11 Int. Conf. on Information Security, Security and Privacy in the Age of Uncertainty (SEC) (Athens, Greece, May 2003). [10] Perrig, Adrian, John Stankovic, and David Wagner. Security in Wireless Sensor Networks. Communications of the ACM, Volume 47, Issue 6 (June 2004): 53-57. [11] Perrig, Adrian, Robert Szewczyk, Victor Wen, David Culler, and J.D. Tygar. SPINS: Security protocols for sensor networks. In The Seventh Annual International Conference on Mobile Computing and Networking (MobiCom 2001), (2001). [12] Pietro, R.D., L.V. Mancini, Y.W. Law, S. Etalle, and P. Havinga. LKHW: A Directed Diffusion-Based Secure Multicast Scheme for Wireless Sensor Networks. International Conference on Parallel Processing Workshops (ICPPW'03) (Kaohsiung, Taiwan. October 6 - 9, 2003). [13] Warto, Ronald, Derrick Kong Sue-fen Cuti, Charles Gardiner, Charles Lynn, and Peter Kruus. TinyPK: Securing Sensor Networks with Public Key Technology. International Journal of Research in IT, Management and Engineering www.gjmr.org 103
- 105. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 [14] Wood, A.D. and J.A. Stankovic. Denial of Service in Sensor Networks. IEEE Computer, Volume: 35, Issue: 10 (Oct. 2002):48-56. [15] Wood, A.D., J.A. Stankovic, and S.H. Son. JAM: A Jammed-Area Mapping Service for Sensor Networks. In The 24th IEEE International Real-Time Systems Symposium (RTSS) (Cancun, Mexico, December 2003). International Journal of Research in IT, Management and Engineering www.gjmr.org 104
- 106. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 THE ECONOMICS & BUSINESS OF EUROPEAN LEAGUE FOOTBALL Dr. Rosy Kalra* ABSTRACT Football is the most popular sport in the world & certainly one of the most lucrative businesses. It remains unparalleled in generating emotion & passion across the planet irrespective of the divide & differences separating people. Furthermore, Football is a surprisingly resilient industry & not only weathered the storm of the global financial crisis that crippled major European economies, but emerged unscathed & stronger from it all. Just a look into the latest revenue figures amongst the richest European League clubs confirms this belief as their combined revenue has for the first time exceeded the €4 billion mark with almost all the clubs managing to improve upon their last years performance. Key Terminology: Amortization -The annual cost of writing down the cost of buying new players *Assistant Professor, Amity Business School, Amity University, Noida (UP). International Journal of Research in IT, Management and Engineering www.gjmr.org 105
- 107. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 INTRODUCTION Amongst a seemingly positive ambit, there lies great churning not only in the operation of the Football clubs but also the governing regulations. The major concern stem from the almost precipitous levels of debt prevailing amongst the richest, most successful & popular European League clubs. 56% of the 733 clubs that had an audit done by UEFA (Union of European Football Associations) suffered a loss. In the English Premier League alone 14 of the 20 clubs made a loss in their most recent accounts. But what is more worrying is that debt levels continue to increase at an alarming rate & shows no sign of abating. As Football clubs continue to grow more & more indebted serious question are being leveled at the sustainability of the various business models prevalent amongst European Football Clubs. The above developments subsequently are of major significance to one of the most popular & lucrative football leagues in Europe – The English Premier League. The success & consistent presence of English clubs in the latter stages of the elite European competitions display the importance of top tier English Football clubs & therefore how the top English Football clubs adapt to the changing landscape has deep ramifications in the evolution of the European Footballing landscape in the long run. LITERATURE REVIEW The review of literature was carried to explore the ways & techniques that could be used to better understand & interpret the Football industry & its true economic reality. The review of literature facilitated comparison of the results of previous analysis & the results of this study. Hence, review of literature has been instrumental in giving a better meaning to this study & has been a source of guidance for carrying out this study. Some of them include- Babatunde Buraimo and Rob Simmons (2006) model the impacts of market size and team competition for fan base on matchday attendance in the English Premier League over the period 1997-2004 using a large panel data set. It constructs a comprehensive set of control variables and use tobit estimation to overcome the problems caused by sell-out crowds. It also accounts for unobserved influences on attendance by means of random effects attached to home teams. Also International Journal of Research in IT, Management and Engineering www.gjmr.org 106
- 108. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 treatment of market size, with its use of Geographical Information System techniques, is more sophisticated than in previous attendance demand studies. The European Club Footballing Landscape report by UEFA (2008) is an 80-page report published in four languages – English, French, German and Russian – and the analyses contained within have formed an important basis for recent discussions on financial fair play, as well as contributing to increased transparency in club football – one of UEFA's key club licensing objectives. The report also deals with non-financial areas such as competition structures and attendance trends and, for the first time, features a pan-European analysis of stadium ownership and licensing results. The Bundesliga’s report on “The Economic State of Professional Football” The DFL released report detailing the economic state of professional football in Germany & includes the financial results that had previously been part of the DFL’s Bundesliga Report. The release presents the particulars of increased revenue & increased equity in the German league but also points to the subsequent increase in the prevailing debt levels inspite of strong performances in the elite European competitions translating to higher prize money payouts. Deloitte’s Annual Review of Football Finance describes a comparative survey of revenue among European clubs through its annual editions of Deloitte’s Football Money League. It details its finding through a football “Rich List”, ranking the top 20 European clubs on the basis of their financial clout & turnover. The Football Money league profiles the highest earning clubs in the world’s most popular sport & is considered the most contemporary and reliable analysis of clubs’ relative financial performance. There are a number of methods that can be used to determine clubs’ relative size – including measures of fan base, attendance, broadcast audience, or on-pitch success. However, the Money League focuses on the clubs themselves, comparing revenue from day to day football operations which we believe is the best publicly available financial comparison. International Journal of Research in IT, Management and Engineering www.gjmr.org 107
- 109. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 RESEARCH METHODOLOGY Type of Research: Analytical research uses facts and information already available, and analyzes these to make a critical evaluation of the material. This study is an analytical research carried out to critically examine the functioning of Elite European League Football with a focus towards top English Football clubs & to study the viability of the various prevalent economic models existing within the Football industry. For the analysis historical data of past six years (2004-2009) has been taken spanning the top clubs in England. Objective(s) Determine functional sustainability amongst current operating practices of financial indiscipline in Major football clubs To evaluate the colossal debt levels prevalent at the top echelons of club football, To determine the adequacy of legislations governing major clubs. Data Analysis Method Description 1) Critical analysis of the financials of Football clubs qualifying for UEFA’s elite European competition spanning England’s Top Tier Football Clubs 2) To analyse the revenue streams & expenditure patterns of major football enterprises including review of Balance Sheets released by individual clubs wherever applicable. 3) To examine the correlation between transfers spend & player wages contributing towards financial brinkmanship between clubs. 4) Excerpts of interview & opinions of top football experts including analysis of newspaper reports & articles by eminent football authors. International Journal of Research in IT, Management and Engineering www.gjmr.org 108
- 110. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 DATA ANALYSIS & INTERPRETATION For any credible analysis of the health of football finances, it is imperative to objectively examine the biggest & the most lucrative money spinning Football leagues & their domestic clubs. Therefore the English Premier League which is the world's most watched association football league & consequently the world's most lucrative football league in terms of revenue, with combined club revenues of over £2 billion in 2008–09 exceeding that of Spain's La Liga and Germany's Bundesliga , form the crux of the focus in examining the status of Football’s financial Landscape. ARSENAL Football Club Arsenals financial results for the year ended 31 May 2010, have been nothing short of record breaking with revenue of £380 million (Year 2009 £313 million) and profit before tax of £56 million (Year 2009 £46 million).Another notable figure was that of Profit Before Tax which was up 23%, from previous year’s profit of £35 million. But the most impressive element was that this enabled the club to repay £130 million of bank loans, thereby reducing the net debt to £136 million from just under £300 million. So any further International Journal of Research in IT, Management and Engineering www.gjmr.org 109
- 111. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 sales on the property front will generate surplus cash as the property business is now essentially debt-free. This is especially credit worthy given the downturn in the property market arising out of recession. Table 1: Arsenal- Profit Growth Arsenal has earned significant property revenue - £157 million from £88 million previously as displayed in Table 1. But this was also marked by a subsequent growth in expenses as well, so the profit from property only increased marginally from £6 million to £11 million. But clearly, the £45 million football profit still drives the business. There is also some hefty gains that can be now anticipated generating surplus cash from property sales. International Journal of Research in IT, Management and Engineering www.gjmr.org 110
- 112. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Given the healthy numbers, operating profit for the football business actually fell by a third (£10 million) to £20 million from £30 million. Also there was a small decrease in revenues by £2 million attributed to the economic downturn & fewer home games. But at the same time, higher wages also increased expenses by £8 million. Fortunately, the football operating profit of £45 million pre-tax profit (including player sales) more than made up for the rise in expenses. .In the last three years alone, Arsenal have produced combined pre-tax profits of £138 million – an astonishing figure in the world of football.Arsenal’s profit growth has been largely driven by impressive revenue growth which has ballooned to £223 million from £115 million, almost double in the last 5 years consequently placing Arsenal 5th in the last year’s Deloittes Money League. Arsenal’s revenue growth is a consequence of moving into their new stadium & not television unlike the vast majority of other clubs in the English league. Gate receipts doubled to £90 million from £44 million, reflected in the steep change in revenue figures from the year 2007 after moving into Ashburton Grove. The £20 million “mortgage” is now easily serviced from additional £50 million revenue per season generated as a result of the increased capacity stadium. Television Broadcast rights has been the biggest revenue driver for all clubs including arsenal. In 2010 alone, Arsenal’s television revenue jumped to £85 million from £73 million, a 15% increase. Still as a percentage of revenue, the clubs dependence on T.V Broadcast revenue is relatively small at 38% than compared to other clubs as shown in Table 2 International Journal of Research in IT, Management and Engineering www.gjmr.org 111
- 113. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 2: Revenue of Premier League 2008/09 One aspect where Arsenal lags behind their competitors, especially the continental European teams, is in Commercial Revenue. In spite of weak figures in this section which is much lower than that of other big English clubs, there was actually a decline of £4 million generating a total of only £44 million. Arsenal have already moved to address this glaring void with the new CEO Ivan Gazidis strengthening the clubs commercial team with high profile recruits with an aim to significantly bolster Commercial revenue while aggressively exploring overseas markets including in the Middle East, Far East and the USA while expanding retail presence through international brand building. International Journal of Research in IT, Management and Engineering www.gjmr.org 112
- 114. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 On the cost side, reflecting the resigning of many players on long term contracts have resulted in a rise in wages to £111 million, a jump of 6% .They also include the strengthening of the executive team, which must come at a price, though theoretically should also increase revenue. Also as a result of wage increases, the wages to turnover ratio has increased reversing the trend of the last 3 years although this still remains the runner-up in terms of the best wages to turnover ratio prevalent in the English League. Figure 1: Wages vs. Turnover The entry of the Russian oil tycoon Roman Abramovich through his purchase of Chelsea Football Club in 2003 heralded a new era in football & its operations where balancing books was International Journal of Research in IT, Management and Engineering www.gjmr.org 113
- 115. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 considered no longer an important requirement. As attempts to keep up & compete with Roman Abramovich’s Chelsea, many clubs followed its method of purchasing success & glory through wielding the cheque book, often without considering neither the cost nor its consequences. Remarkably, arsenal in this turbulent period has remained one of the only few clubs to earn a surplus of £2 million in player transfers... This figure pales in comparison to the huge sums splashed in the transfer market by other clubs, the likes of Manchester City, Chelsea, Liverpool and Manchester United. This approach of being averse to spending huge amounts of money by risking financial collapse & bankruptcy is especially laudable in the context of the free spending competitors. Another impressive performance has been in the clubs property venture which subsequently earned the club a significant £157 million from the sale of apartments as part of the Queensland redevelopment project undertaken by the club. This deserves special praise as such results were achieved in the face of one of the worst recessions the world has witness coupled with the subsequent downturn in the property market which had, at time forced the club into requesting extension of the deadline for the repayment of the bank loan. This has significantly curtailed & subsequently eliminated the property debt, enabling the club bring down its gross level of debt to £263 million. The net debt is significantly lowered to only £136 million if one takes into account the cash balances of £128 million as shown in Figure 2. Figure 2: Annual Debt International Journal of Research in IT, Management and Engineering www.gjmr.org 114
- 116. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Chelsea Football Club Limited The entry of the Russian oil tycoon Roman Abramovich through his purchase of Chelsea Football Club in 2003 heralded a new era in football & its operations where balancing books was considered no longer an important requirement. As attempts to keep up & compete with Roman Abramovich’s Chelsea, many clubs followed its method of purchasing success & glory through wielding the cheque book, often without considering neither the cost nor its consequences. International Journal of Research in IT, Management and Engineering www.gjmr.org 115
- 117. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 A look at Chelsea’s financial accounts reveals few distinct points, the foremost being that the club held the rather unenviable record for the highest wage bill ever accounted for by a Club in the English premier League at the time of submission of the Club’s accounts in the year 2009. This mammoth wage bill & high transfer spending is in stark contrast to the often announced goal of breaking even as stated by the then CEO of the Club Peter Kenyon. As displayed in Table 3, Chelsea have incurred continual losses since 2004 with the £44.4m loss incurred in the 2009..Although the clubs have managed to consistently reduce losses (until 2010 where excess of £70 million in losses were disclosed) it does not detract from the fact that the deficit was massive in the form of £140 million back in the year 2005. As the clubs management insist that the losses are on a downward trajectory, Chelsea’s recent foray into the transfer marker splashing in excess of £70 million on just two players (Fernando Torres & David Luis) especially after recently announcing massive losses does not augur well for the financial health of the club. Table 3: Chelsea Football Club Profit and Loss Account International Journal of Research in IT, Management and Engineering www.gjmr.org 116
- 118. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 From the £140 million back in the year 2005, losses have now reduced to £44.4 million, a net reduction of about £95.6 million. But significantly nearly 80% of this reduction can be attributed to have come from the transfer market, i.e. £74m with £40.4 million higher profit on account of player sales notwithstanding lower amortization which is £33.6 million lower & fewer termination payments. This translates into only £8.7 million of the reduction actually coming from football operations. In the context of the T.V broadcast bonanza era the results are a dampener to say the least. International Journal of Research in IT, Management and Engineering www.gjmr.org 117
- 119. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 In spite of the Clubs keenness to pat them on the back regarding improvement in cash flows the net cash outflow from operating activities of £13.1m 2009 is exactly the same as it was in 2004 & still is in the negative. Another moot point being the revised valuations of the players in the balance sheet, intangible assets (basically net book value of the players) have decreased from £143.6m to £77.8m by £65.8m in just twelve months. This is further compounded by the fact that the squad now needs major replacements & for the club itself the vicious cycle of debts & losses shows no sight of an end. Therefore, it is clear that Chelsea need to find ways of reaching the elusive break-even target and the right way is to increment revenue.. In the long-term it is vital to leverage Brand Chelsea to increase commercial revenue in a significant way if the club is to progress financially. This involves exploring sponsorship revenue & stadium naming rights in which Chelsea lags behind in comparison with the other big four of the league. Revenue from T.V Broadcasting rights is at a healthy £79.1 million, behind only Manchester United in the league. In addition to this, like other English football clubs Chelsea too will receive an additional windfall of funds as a result of the new agreement on overseas rights, translating into an extra £7.5m per annum for the next three years for the club. There seems to be little revenue potential left for the club to pursue to achieve its target of breaking even, as a result Deloittes in their annual football review report quoted, “the club faces a significant challenge to regain a top five position in our Money League.” Therefore, it is clear that the club is significantly farther from attaining its stated financial objectives while struggling to break free from its dependence on its Russian owner. The club at the very least has to start thinking about the changing footballing landscape & evolve into a viable business. A good start would be to stop hemorrhaging further losses & significantly improve bottom lines. FINDINGS & RECOMMENDATIONS According to UEFA report 54% of Europe's top-division teams reported operating losses (before transfers) in the 2008 financial year. International Journal of Research in IT, Management and Engineering www.gjmr.org 118
- 120. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 The above analysis of top English clubs provides clear warnings of financial mismanagement & unsustainability. In addition, it is clear from the above analysis of the top clubs in Europe that very few manage to generate profits & fewer still can lay claim to have a viable & sustainable business model. This is a stark indictment of not only the larger governance of the sport where lackadaisical financial excesses have not only been tolerated but encouraged as also the questionable conduct of individual football clubs in England & across Europe adopting irrational financial measures leading themselves to precipitous levels of unsustainable wage inflation & debt. Amidst this backdrop of financial excesses & subsequent losses the German Bundesliga is the flag bearer & role model for the much touted UEFA fair play regulations. The German football association’s success can be gauged from the fact that no Bundesliga club has ever gone bankrupt during a running competition or was unable to complete the season. The Bundesliga’s success in this matter spans 40 years with member clubs operating for years with positive results & definitely offers approaches that can be adopted elsewhere to restore financial perspective among the other European footballing heavyweights. It owes its success to a robust licensing system, exercising rigorous financial control over member clubs where expenditure is strictly required to be in line with existing revenues thus limiting the possibilities for using incoming capital to replace revenues. Spiraling wage inflation is a serious concern affecting football clubs. A salary cap vis-à-vis Major league baseball would be difficult to implement in the sport of football. Another effective approach therefore, would be to strictly enforce wage discipline among football clubs by establishing the maximum limit that the club can spend on player salaries based upon a percentage of their turnover. This would ensure that if even a club over extends itself financially while purchasing a player, his wages would have to necessarily come from the revenues generated by the club. Thus such clubs would have to exercise prudence to see if they can afford the player’s wages before making a purchase decision in the transfer market. When one considers the complexity of football when compared to a more traditional business, it is strange that it is subject to the current “one size fits all” model of legislation. Few other International Journal of Research in IT, Management and Engineering www.gjmr.org 119
- 121. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 businesses pay vast fees to secure employees, nor do they pay their employees in a complex manner that includes basic pay, image rights and performance-related bonuses, and yet no special demands are made of football clubs to disclose this clearly in their annual financial statements. Naturally, this has big implications for financial transparency within the industry. With outside observers relying on measures such as wages as a percentage of a club’s turnover to gauge a club’s sustainability, the lack of breakdown of the “wage” mean that one struggles to draw any reliable conclusions. CONCLUSION Even in the game of Football, questions of financial prudence & perspective ultimately seek their resolution through optimum balance, and the same is true for the economics of sport. The challenge for the sport is to find a dynamic balance between desire for success and money necessary to analytically grasp the passionate and pragmatic complexities of the beautiful game. A strong revolutionary wind is blowing through Europe’s footballing landscape providing a compelling paradigm shift in how the business of football functions & evolves. UEFA has produced a club licensing benchmarking report on European club football – the broadest of its kind ever undertaken – covering financial results from more than 600 top-division clubs from UEFA's 53 member national associations forming an important basis for recent discussions on financial fair play, as well as contributing to increased transparency in club football – one of UEFA's key club licensing objectives. All in all, it is clear that while many clubs are continuing to operate successfully, there are many operating less-sustainable strategies. Reports indicate that 54% of Europe's top-division teams reported operating losses (before transfers) in the 2008 financial year. While some clubs in every UEFA member association were able to break even, the analyses identify other signs of financial overstretching and clubs living beyond their current means. Amid the record Broadcast deals & revenues there are some increasingly clear warning signs. The many clubs across Europe that continue to operate on a sustainable basis are finding it increasingly difficult to coexist & compete with clubs that incur losses & transfer fees beyond International Journal of Research in IT, Management and Engineering www.gjmr.org 120
- 122. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 their means & reporting losses year after year, without themselves following the same approach at the same time succumbing to a vicious cycle of debt. Unless there is a comprehensive overhaul in the way football clubs operate & conduct business, there is a distinct possibility of grave consequences. REFERENCES Rodney Fort and Joel Maxcy, " Competitive Balance in Sports Leagues: An Introduction” Journal of Sports Economics, (2003) Babatunde Buraimo and Rob Simmons, “Market size and attendance in English Premier League Football” The Department of Economics, Lancaster University Management School, Lancaster LA1 4YX,UK, (2006) Leit˜ao, Jo˜ao, “The Taylor Effect on the Performances of the Red Devil’s Football Brand”, University of Beira Interior, (2007) The Bundesliga’s report on “The Economic State of Professional Football” The UEFA Club Licensing and Financial Fair Play Regulations Report http://soccernet.espn.go.com/news/story/_/id/874859/gordon-taylor:-football-facing- government-intervention?cc=4716 http://www.thesun.co.uk/sol/homepage/sport/football/3392577/Chelseas-wage-bill-is-an- amazing-172million.html http://www.telegraph.co.uk/sport/football/competitions/premier-league/8314698/English- clubs-defy-the-economic-recession-to-retain-elite-status-in-European-money-league.html http://www.espnstar.com/football/premierleague/news/detail/item581775/Clarke:-Level-of- football-debt-precipitous/ http://en.wikipedia.org/wiki/Uefa International Journal of Research in IT, Management and Engineering www.gjmr.org 121
- 123. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 http://en.wikipedia.org/wiki/UEFA_Champions_League http://en.wikipedia.org/wiki/FIFA http://en.wikipedia.org/wiki/Premier_League International Journal of Research in IT, Management and Engineering www.gjmr.org 122
- 124. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 AN ALGORITHM FOR SOLVING A CAPACITATED FIXED CHARGE BI-CRITERION INDEFINITE QUADRATIC TRANSPORTATION PROBLEM WITH RESTRICTED FLOW S.R. Arora* Kavita Gupta** ABSTRACT In this paper a capacitated fixed charge bi-criterion indefinite quadratic transportation problem with restriction on the total flow is studied. An algorithm to find the efficient cost time trade off pairs in a capacitated fixed charge bi-criterion indefinite quadratic transportation problem with bounds on rim conditions is developed. The algorithm is developed by forming a related fixed charge indefinite quadratic transportation problem and it is shown that to each basic feasible solution called corner feasible solution to related transportation problem, there is a corresponding feasible solution to this restricted flow problem. It is also shown that the efficient cost time trades off pairs to the given problem are derivable from this related problem the algorithm is illustrated with the help of a numerical example. Keywords: optimum time cost trade off, capacitated transportation problem, fixed charge, bi- criterion indefinite quadratic transportation problem, restricted flow. * Ex-Principal, Hans Raj College, University of Delhi, Delhi-110007, India ** Department of Mathematics, Jagan Institute of Management Studies, 3 Institutional Areas, Sector-5, Rohini, Delhi, India International Journal of Research in IT, Management and Engineering www.gjmr.org 123
- 125. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 1. INTRODUCTION The fixed charge transportation problem was originally formulated by G.B Dantzig and W.Hirisch [8] in 1954.Thirwani et.al. [9] in 1997 developed an algorithm for finding the time cost trade off pairs in a fixed charge bi-criterion transportation problem with restricted flow. Later, Arora et.al [1-2] also studied the indefinite quadratic transportation problem. Another important class of transportation problem consists of capacitated transportation problem. If the total flow in a transportation problem with bounds on rim conditions is also specified, the resulting problem makes the transportation problem more realistic. Moreover, if the total capacity of each route is also specified then optimal solution of such problems is of greater importance which gives rise to a capacitated transportation problem. Many researchers like A.K Bit et.al. [6], K.Dahiya et.al. [7] Have contributed in this field. In 1976, Bhatia et .al. [5] provided the time cost trade off pairs in a linear transportation problem. Then in 1994, Basu et.al. [4] Developed an algorithm for the optimum time cost trade off pairs in a fixed charge linear transportation problem giving same priority to cost as well as time. Arora et.al. [3] Studied time cost trade off pairs in an indefinite quadratic transportation problem with restricted flow. In this paper, a capacitated fixed charge indefinite quadratic transportation problem with bounds on rim conditions giving same priority to cost and time is studied along with restriction on the total flow. An algorithm to identify the efficient cost time trade off pairs for the problem is developed. 2. PROBLEM FORMULATION Linear functions are widely used in modeling a mathematical optimization problem. Also quadratic functions and quadratic problems are the least difficult to handle out of all non linear programming problems. A fair number of functional relationships occurring in the real world are truly quadratic. For example-Kinetic energy carried by a rocket or an atomic particle is proportional to the square of its velocity. There are many non linear relationships occurring in nature that are capable of being approximated by quadratic functions. Consider a capacitated fixed charge bi-criterion indefinite quadratic transportation problem given by International Journal of Research in IT, Management and Engineering www.gjmr.org 124
- 126. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 (P1): min cijxij dijxij Fi, max tij / xij 0 i, j I J iI jJ iI jJ iI Subject to ai xij Ai i I (1) jJ bj xij Bj j J (2) iI l ij x ij u ij i, j I J (3) x ij P min Ai, Bj (4) iI jJ iI jJ I = {1, 2 … m} is the index set of m origins. J = {1, 2… n} is the index set of n destinations. xij = number of units transported from origin i to the destination j. cij = variable cost of transporting one unit of commodity from ith origin to the jth destination. dij = the per unit damage cost or depreciation cost of commodity transported from the ith origin to the jth destination. lij and uij are the bounds on number of units to be transported from the ith origin to the jth destination. ai and Ai are the bounds on the availability at the ith origin, i I bj and Bj are the bounds on the demand at the jth destination, j J tij is the time of transporting goods from ith origin to the jth destination. Fi is the fixed cost associated with ith origin. For the formulation of Fi (i=1,2 … m), we assume that Fi (i = 1, 2 .. m) has p number of steps so that p Fi Fil il , i = 1, 2 … m l 1 International Journal of Research in IT, Management and Engineering www.gjmr.org 125
- 127. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 n Where, il = 1 if Fi = x j1 ij ail ,l=1,2,3……..p, i=1,2,……m =0 otherwise Here, 0 = ai1 < ai2 … < aip ai1, ai2 …,< aip (i = 1,2, … m) are constants and Fil are the fixed costs. i= 1, 2 …m, l = 1,2 ..p In the problem (P1), we need to minimize the total transportation cost and the depreciation cost simultaneously. Also we need to minimize the fixed cost associated with ith origin and the time of transportation from ith origin to jth destination. Sometimes, situations arise when one wishes to keep reserve stocks at the origins for emergencies, there by restricting the total transportation flow to a known specified level, say P min Ai, Bj .This flow constraint changes the jJ iI structure of the transportation problem. In order to solve the problem (P1), we separate it in to two problems (P2) and (P3) where (P2): minimize the cost function cijxij dijxij Fi subject to (1),(2),(3) and (4). iI jJ iI jJ iI (P3): minimize the time function max t ij / x ij 0 subject to (1), (2), (3) and (4). iI, jJ The flow constraint in the problem (P1) implies that a total Ai P of the source reserves iI have to be kept at the various sources and a total Bj P of destination slacks is to be jJ retained at the various destinations. Therefore an extra destination to receive the source reserves and an extra source to fill up the destination slacks are introduced. In order to solve the problem (P2) we convert it in to a related problem (P2´) given below. (P2´): min Z cijyij dijyij Fi subject to iI jJ iI jJ iI y jJ ij Ai' i I (5) International Journal of Research in IT, Management and Engineering www.gjmr.org 126
- 128. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 y iI ij B'j j J (6) l ij y ij u ij i, j I J (7) 0 ym 1, j Bj bj j J 0 yi, n 1 A i ai i I ym 1, n 1 0 Ai = Ai iI, A m+1 = B jJ j -P , Bj = Bj jJ , Bn+1 = A -P iI i cij = cij , iI, jJ, cm+1,j = ci,n+1 = 0 iI, jJ, cm+1,n+1 = M d´ij = dij iI, jJ, dm+1,j = di,n+1 = 0 iI, jJ; d´m+1,n+1 = M Fi = Fi i=1,2 …m, Fm+1 = 0 Where I = {1, 2 … m, m+1}, J = {1, 2, … n, n+1} In order to solve the problem (P3), we convert it to a related problem (P3´) given below. (P3´): min T max t ij / yij 0 i I and j J subject to y jJ ij Ai' i I y iI ij B'j j J l ij y ij u ij i, j I J 0 ym 1, j B j b j j J 0 yi, n 1 A i ai i I ym 1, n 1 0 Ai = Ai iI, A m+1 = B jJ j -P, Bj = Bj jJ , Bn+1 = A -P iI i cij = cij , iI, jJ, cm+1,j = ci,n+1 = 0 iI, jJ, cm+1,n+1 = M d´ij = dij iI, jJ, d´m+1,n+1 = M t´ij= tij i, j I J ,t´m+1,j = t´i,n+1= 0 iI, jJ International Journal of Research in IT, Management and Engineering www.gjmr.org 127
- 129. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 t´m+1,n+1 > max tij / xij 0 i I, j J To obtain the set of efficient time cost trade off pairs, we first solve (P2´) and read the time with respect to the minimum cost Z where time T is given by problem (P3´) At the first iteration, let Z1* be the minimum total cost of the problem (P2) and T1* be the optimal time of the problem (P3) with respect to Z1* , then any schedule which is completed earlier than T1* would cost more than Z1* . So (Z1* , T1*) is the first time cost trade off pair at the first iteration. After modifying the costs with respect to the time obtained, a new optimal cost is obtained and time is read with respect to the new optimal cost .This procedure is called re-optimization procedure. Let after q th iteration, the problem becomes infeasible. Thus, we get the following complete set of time-cost trade off pairs. (Z1*, T1*) ( Z2*, T2*),( Z3*,T3*),…………….( Zq*, Tq*) where Z1* ≤ Z2* ≤ Z3*≤………..≤ Zq* and T 1* ≥ T2* ≥ T3*………..≥ Tq* with strict inequality holding in atleast one of the two conditions .The pairs so obtained are pareto optimal solutions of the given problem. Then we identify the minimum cost Z1* and minimum time T q* among the above trade off pairs. The pair (Z1*, T q*) with minimum cost and minimum time is termed as the ideal pair which can not be achieved in practical situations. 3. THEORETICAL DEVELOPMENT: Theorem 1: Let X = {Xij} be a basic feasible solution of problem (P2´) with basis matrix B. Then it will be an optimal basic feasible solution if R 1ij ij z1(d ij z 2ij) z 2 (cij z1ij) ij(cij z1ij)(d ij z 2 ij) Fij 0 (i, j) N 1 And R 2 ij ij ij(cij z1ij)(d ij z 2ij) z1(d ij z 2ij) z 2 (cij z1ij) Fij 0 (i, j) N 2 Such that u 1 v1j cij i (i, j) B (8) u i2 v 2 dij j (i, j) B (9) u1 v1j z1 i ij (i, j) N 1 And N2 (10) International Journal of Research in IT, Management and Engineering www.gjmr.org 128
- 130. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 u i2 v 2 zij (i, j) N 1 And N2 j 2 (11) F ij Is the change in fixed cost F i when some non basic variable xij enters the basis. iI z1 = value of c x iI jJ ij ij at the current basic feasible solution corresponding to the basis B. z2 = value of d x iI jJ ij ij at the current basic feasible solution corresponding to the basis B. ij = level at which a non basic cell (i,j) enters the basis replacing some basic cell of B. N1 and N2 denotes the set of non basic cells (i,j) which are at their lower bounds and upper bounds respectively. Note: u1 , v1j , u i2 , v 2 are the corresponding dual variables which are determined by using equations i j (8) to (11) and taking one of the ui ,s or vj ,s. as zero. Proof: Let z0 be the objective function value of the problem (P2). Let z0 =z1z2 + F0 where F0 = F i iI Let z be the objective function value at the current basic feasible solution X= {xij} corresponding to the basis B obtained on entering the non basic cell xij N1 in to the basis which undergoes change by an amount ij given by min{uij – lij ; xij - lij for all basic cells (i,j) with a (- )entry in the -loop; uij – xij for all basic cells (i,j) with a (+ )entry in the -loop}. Then z = z1 ij cijz1 z 2 ij dijzij F0 Fij ij 2 z - z0 = z1z2 + z2 ij (cij-z1ij) + z1 ij (dij – z2ij) + ij (cij-z1ij) (dij – z2ij) - z1z2 + F ij 2 = ij [z2 (cij-z1ij) + z1 (dij – z2ij) + ij (cij-z1ij) (dij – z2ij)]+ F ij This basic feasible solution will give an improved value of z if z < z0 .It implies that ij [z2 (cij-z ij) + z1 (dij – z ij) + ij (cij-z ij) (dij – z ij)]+ F ij < 0 1 2 1 2 (12) Therefore one can move from one basic feasible solution to another basic feasible solution on entering the cell (i,j) N1 in to the basis for which condition (12) is satisfied. It will be an optimal basic feasible solution if International Journal of Research in IT, Management and Engineering www.gjmr.org 129
- 131. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 R1 ij z1(dijzij )z 2(cijz1 )ij(cijz1 )(dijzij ) Fij 0(i, j) N1 ij 2 ij ij 2 Similarly, when non basic variable xij N2 undergoes change by an amount ij then z - z = ij [ ij (cij-z ij) (dij – z ij)- z2 (cij-z ij) - z1 (dij – z ij) +]+ F ij < 0 0 1 2 1 2 It will be an optimal basic feasible solution if R ij ij ij(cijz1 )(dijzij )z1(dijzij )z 2(cijz1 ) Fij 0(i, j) N 2 2 ij 2 2 ij Definition: Corner feasible solution: A basic feasible solution {yij} i I´, j J´ to (P2´) is called a corner feasible solution (cfs) if ym+1,n+1 = 0 Theorem 2. A non corner feasible solution of (P2´) cannot provide a basic feasible solution to (P2). Proof: Let {yij}I´ xJ´ be a non corner feasible solution to (P2´).Then ym+1,n+1 = (>0) Thus y iI i, n 1 yi, n 1 ym 1, n 1 iI = yi, n 1 iI = Ai P (13) iI y iI i, n 1 Ai (P ) iI Now, for i I, y jJ ij A i' Ai (14) yij Ai iI jJ iI (13) and (14) implies that y iI jJ ij P This implies that total quantity transported from the sources in I to the destinations in J is P + > P, a contradiction to assumption that total flow is P and hence {yij}I´ xJ´ cannot provide a feasible solution to (P2). Lemma 1: There is a one –to-one correspondence between the feasible solution to (P2) and the corner feasible solution to (P2´). International Journal of Research in IT, Management and Engineering www.gjmr.org 130
- 132. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Proof: Let {xij}I xJ be a feasible solution of (P2).So {xij}I xJ will satisfy (1) to (4). Define {yij}I´ xJ´ by the following transformation yij = xij ,i I, j J yi,n+1 = Ai - x jJ ij , i I ym+1,j = Bj - x iI ij , j J ym+1,n+1 = 0 It can be shown that {yij} so defined is cfs to (P2´). Relation (1) to (3) implies that l ij y ij u ij for all i I, j J 0 yi, n 1 A i ai , i I 0 ym 1, j Bj bj , j J ym+1,n+1 ≥ 0 Also for i I y y jJ ij jJ ij yi, n 1 x ij Ai x ij Ai A i' jJ jJ For i = m+1 y jJ m 1, j yij ym 1, n 1 (B j x ij) jJ jJ iI = B x jJ j iI jJ ij = B P jJ j = A´m+1 yij A i' ; i I jJ Similarly, it can be shown that y iI ij B'j ; j J Therefore {yij}I´ xJ´ is a cfs to (P2´). Conversely, let {yij}I´ xJ´ be a cfs to (P2´).Define xij , i I, j J by the following transformation. xij= yij , i I, j J International Journal of Research in IT, Management and Engineering www.gjmr.org 131
- 133. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 It implies that l i j x i j u i j , i I, j J Now for i I, the source constraints in (P2´) implies y jJ ij A i' A i y jJ ij yi, n 1 Ai ai yij Ai (Since 0 ≤ yi,n+1 ≤ Ai –ai , i I) jJ Hence, ai x jJ ij Ai , i I Similarly, for j J, bj xij Bj iI For i= m+1 y jJ m 1, j A 'm 1 Bj P jJ ym 1, j Bj P Because ym+1,n+1 = 0 jJ jJ Now, for j J the destination constraints in (P2´) give y iI ij ym 1, j Bj Therefore, yij ym 1, j Bj iI jJ jJ jJ y B y iI jJ ij jJ j jJ m 1, j P xij P iI jJ Therefore {xij}I xJ is a feasible solution to (P2) Remark 1: If (P2´) has a cfs, then since c´m+1,n+1=M and d´m+1,n+1= M, it follows that non corner feasible solution cannot be an optimal solution of (P2´) . Lemma 2: The value of the objective function of problem (P2) at a feasible solution {xij}I x J is equal to the value of the objective function of (P2´) at its corresponding cfs {yij}I´xJ´ and conversely. Proof: The value of the objective function of problem (P2) at a feasible solution {xij}I x J is International Journal of Research in IT, Management and Engineering www.gjmr.org 132
- 134. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 cijxij dijxij Fi iI jJ iI jJ iI cij = cij, i I, j J ' xij = yij, i I, j J c ' = c ' i,n +1 m+1, j = 0; i I, j J ' cijyij dijyij Fi' Because d i,n+1 = d 'm+1, j = 0; i I, j J iI jJ iI jJ iI y m 1,n 1 0 F' = 0, F' = Fi, i I m+1 i = the value of the objective function of (P2´) at the corresponding cfs {yij}I´xJ´ The converse can be proved in a similar way. Lemma 3: There is a one –to-one correspondence between the optimal solution to (P2) and optimal solution to the corner feasible solution to (P2´). Proof: Let {xij}I J be an optimal solution to (P2) yielding objective function value z0 and {yij}I J be the corresponding cfs to (P2´). Then by Lemma 2, the value yielded by {yij}I J is z0 ..If possible,let {yij}I J be not an optimal solution to (P2´). Therefore, there exists a cfs {y ij} to ' (P2´) with the value z1 < z0. Let {x ij} be the corresponding feasible solution to (P2).Then by ' lemma 2, ' ' cijx ij dijx ij Fi = z , a contradiction to the assumption that {xij}I J is an 1 iI jJ iI jJ iI optimal solution of (P2).Similarly, an optimal corner feasible solution to (P2´) will give an optimal solution to (P2). Theorem 3: Optimizing (P2´) is equivalent to optimizing (P2) provided (P2) has a feasible solution. Proof: As (P2) has a feasible solution, by lemma 1, there exists a cfs to (P2´).Thus by remark 1; an optimal solution to (P2´) will be a cfs. Hence, by lemma 3,an optimal solution to (P2) can be obtained. 4. ALGORITHM: International Journal of Research in IT, Management and Engineering www.gjmr.org 133
- 135. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Step1: Given a capacitated fixed charge bi-criterion indefinite quadratic transportation problem with restricted flow (P1), separate the problem (P1) in to two problems (P2) and (P3).Form the related transportation problems (P2´) and (P3´).Find a basic feasible solution of problem (P2´) with respect to variable cost only. Let B be its corresponding basis. Step 2: Calculate the fixed cost of the current basic feasible solution and denote it by F(current) m Where F (current) = F i 1 i Step 3(a): Find F ij F ( N B ) F (cu rren t ) where F (NB) is the total fixed cost obtained when some non basic cell (i,j) enters the basis. (b) Calculate ij ,(cij-z1ij) , (dij – z2ij), z1, z2 for all non basic cells such that u 1 v1j cij i (i, j) B u i2 v 2 dij j (i, j) B u1 v1j z1 i ij (i, j) N 1 And N2 u i2 v 2 zij (i, j) N 1 And N2 j 2 z1 = value of c x iI jJ ij ij at the current basic feasible solution corresponding to the basis B z2 = value of d x iI jJ ij ij at the current basic feasible solution corresponding to the basis B. ij = level at which a non basic cell (i,j) enters the basis replacing some basic cell of B. N1 and N2 denotes the set of non basic cells (i,j) which are at their lower bounds and upper bounds respectively. Note: u1 , v1j , u i2 , v 2 are the dual variables which are determined by using the above equations and i j taking one of the ui, s or vj, s. as zero. (c) Find R1 (i, j) N1 and R ij(i, j) N2 where ij 2 R1 ij z1(dijzij )z 2(cijz1 )ij(cijz1 )(dijzij ) Fij 0(i, j) N1 and ij 2 ij ij 2 R ij ij ij(cijz1 )(dijzij )z1(dijzij )z 2(cijz1 ) Fij 0(i, j) N 2 2 ij 2 2 ij N1 and N2 denotes the set of non basic cells (i,j) which are at their lower bounds and upper bounds respectively. International Journal of Research in IT, Management and Engineering www.gjmr.org 134
- 136. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Step 4: If R1 0(i, j) N1 and R ij 0(i, j) N 2 then the current solution is optimal to (P2´).Go ij 2 to step 5.Otherwise, some (i,j) N1 for which R 1 0 or some (i,j) N2 for which R ij 0 will ij 2 enter the basis. Go to step 2. Step 5: Let Z1 be the optimal cost of (P2´) yielded by the basic feasible solution {y´ij}. Step 6: Find T1 where T1 = max{tij /y´ij > 0 } from the problem (P3´).Then the corresponding pair (Z1 , T1 ) will be the first time cost trade off pair for the problem (P1).To find the next best time-cost trade off pair, go to step 7. Step7: Define cij1 = M if tij ≥T1 cij if tij < T1 where M is a sufficiently large positive number. Form the corresponding capacitated fixed 1 charge quadratic transportation problem with variable cost cij .Repeat the above process till the problem gets infeasible. The complete set of time cost trade off pairs of (P1) at the end of qth iteration are given by (Z1,T1),(Z2,T2)……….(Zq,Tq) where Z1 ≤ Z2 ≤ …..≤ Zq and T1 ≥T2 ≥……≥Tq. with strict inequality holding in atleast one of the two conditions. Remark 2: The pair (Z1, Tq) with minimum cost and minimum time is the ideal pair which cannot be achieved in practice except in some trivial case. Convergence of the algorithm: The algorithm will converge after a finite number of steps because the choice of cij, s in step 7 will ensure an infeasible solution after a finite number of iterations. 5. NUMERICAL ILLUSTRATION: Consider a 3 x 3 capacitated fixed charge bi-criterion indefinite quadratic transportation problem with restricted flow .Table 1 gives the values of cij, dij, Ai ,Bj for i=1,2,3 and j=1,2,3 International Journal of Research in IT, Management and Engineering www.gjmr.org 135
- 137. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 1: cost matrix of problem (P2) D1 D2 D3 Ai O1 5 9 9 30 O2 4 6 2 40 3 7 4 O3 2 1 1 50 2 9 4 Bj 30 20 30 ,s ,s Note: values in the upper left corners are cij and values in lower left corners are dij for i=1,2,3.and j=1,2,3. 3 3 3 x1j ≤ 30, x2j ≤40, 10 ≤ x3j ≤ 50, 5≤ 3 Also, 3 ≤ j1 10≤ j1 j1 x i 1 i1 ≤30 , 3 3 5≤ xi2 ≤ 20, 5 ≤ i 1 x i 1 i3 ≤ 30 1≤ x11 ≤ 10 , 2 ≤ x12 ≤ 10 , 0 ≤ x13 ≤ 5 ,0≤ x21 ≤ 15 , 3 ≤ x22 ≤ 15 , 1 ≤ x23 ≤ 20 , 0≤ x31≤ 20 , 0≤ x32≤ 13, 0≤ x33≤ 25 F11= 100, F12 = 50, F13 = 50, F21 = 150, F22 = 100, F23 = 50, F31= 200, F32= 150, F33 = 100 3 Fi = F l 1 il il where for i= 1, 2, 3 3 il = 1 if x j1 ij 0 0 otherwise International Journal of Research in IT, Management and Engineering www.gjmr.org 136
- 138. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 3 i 2 = 1 if x j1 ij 10 0 otherwise 3 i3 = 1 if x j1 ij 20 0 otherwise Table 2 gives the values of t ij, s for i=1, 2, 3 and j=1, 2, 3 Table 2: Time matrix of problem (P3) D1 D2 D3 O1 15 8 13 O2 10 13 14 O3 12 10 9 3 3 Let the restricted flow be P = 40 where P = 40 < min Ai 120, Bj 80 i 1 j1 Introduce a dummy origin and a dummy destination in Table 1 with ci4 = 0 = d i4 for all i = 1,2 ,3 and c4j = 0 = d4jfor all j = 1,2,3 . c44=d44=M where M is a large positive number. Also we have 0≤ x14 ≤ 27 , 0≤ x24 ≤ 30 , 0 ≤ x34 ≤ 40 , 0 ≤ x41 ≤ 25 , 0 ≤ x42 ≤ 15 , 0 ≤ x43 ≤ 25 and F4j = 0 for j=1,2,3,4 In this way , we form the problem (P2´).Similarly on introducing a dummy origin and a dummy destination in Table 2 with ti4 = 0 for i=1,2 ,3and t4j= 0 for j=1,2,3, 3 t44 > max tij / xij 0 i I, j J ,we form problem (P3´) . Also, B4 = A P =120-40 = 80 i 1 i 3 and A4= B P = 80-40 = 40 j1 j Now we find an initial basic feasible solution of problem (P2´) which is given in table 3 below. International Journal of Research in IT, Management and Engineering www.gjmr.org 137
- 139. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 3: A basic feasible solution of problem (P2´) D1 D2 D3 D4 u1 i ui2 F(current) O1 5 1 9 2 9 0 27 1 4 100 4 2 1 0 O2 4 6 3 2 7 0 30 2 4 150 3 7 4 0 O3 2 20 1 1 7 0 23 1 4 450 2 9 4 0 O4 0 9 0 15 0 16 M 0 0 0 0 0 0 M vj1 0 0 0 -1 vj2 0 0 0 -4 Note: entries of the form a and b represent non basic cells which are at their lower and upper bounds respectively. Entries in bold are basic cells. F (current) = 700, z1 = 102, z2 = 125 Table 4: Computation of R1 , R ij ij 2 NB O1D1 O1D2 O1D3 O2D1 O2D2 O2D4 O3D1 O3D2 ij 7 7 5 6 6 7 16 7 cij z1 ij 4 8 8 2 4 -1 1 0 dij zij 2 0 -2 -3 -1 3 0 -2 5 F(NB) 600 600 700 700 700 700 700 700 F ij -100 -100 0 0 0 0 0 0 R1 ij 3400 4688 2870 816 5268 3570 2 R ij 875 752 International Journal of Research in IT, Management and Engineering www.gjmr.org 138
- 140. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Since R1 ≥ 0 (i, j) N 1 and R ij 0(i, j) N2 , the solution in table 3 is an optimal solution ij 2 of (P2´) and hence yields an optimal solution of (P2).Therefore minimum cost = (102 x 125) + 700 = 13450 and corresponding time is T1 = 15. Hence the first time cost trade off pair is (13450, 15) M if t ij T1 15 1 Define cij = 1 and solving the resulting problem, the next trade off pair is cij if t ij < T 15 (13450, 14). Similarly, the other pairs are (14266, 13), (14266, 12), (16500, 10). 6. CONCLUSION: In order to solve a capacitated fixed charge bi – criterion indefinite quadratic transportation problem, given problem is separated in to two problems. One of them being an indefinite quadratic transportation problem has its optimal solution at an extreme point. After calculating the cost, corresponding time is read. This is the first cost time trade off pair. Proceeding likes this we get the various trade off pairs. REFERENCES [1] Arora, S.R., Khurana, A., “A paradox in an indefinite quadratic transportation problem”, International Journal of Management and Systems, 18, (2002), 301-318 [2] Arora, S.R., Khurana, A., “Three dimensional fixed charge bi – criterion indefinite quadratic transportation problem”,Yugoslav Journal of Operations Research,14(1),(2004),83-97 [3] Arora, S.R., Thirwani, D., Khurana, A.,“An algorithm for solving fixed charge bi – criterion indefinite quadratic transportation problem with restricted flow”, International Journal of optimization: Theory, Methods and Applications,1(4),(2009),367-380 [4] Basu, M, Pal, B.B and Kundu, A., “An algorithm for the optimum time cost trade off in a fixed charge bi-criterion transportation problem’’, Optimization, 30, (1994), 53-68 International Journal of Research in IT, Management and Engineering www.gjmr.org 139
- 141. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 [5] Bhatia, H.L, Swarup, K and Puri , M.C., ‘‘Time cost trade off in a transportation problem’’, Opsearch, 13(3-4),(1976),129-142 [6] Bit, A.K. Biswal, M.P. , Alam, S.S., “Fuzzy Programming technique for multi- objective capacitated transportation problem” , Journal of Fuzzy Mathematics,1(2),(1993),367-376 [7] Dahiya, K. and Verma, V., ‘‘Capacitated transportation problem with bounds on rim conditions’’, Europeon journal of Operational Research, 178, (2007), 718-737 [8] Hirisch, W.M. and Dantzig, G.B., ‘‘the fixed charge problem’’, Naval Research Logistics Quarterly, 15(3), (1968), 413-424 [9] Khanna,S. , Thirwani,D. and Arora, S.R., ‘‘An algorithm for solving fixed charge bi – criterion transportation problem with restricted flow”, Optimization, 40,(1997),193-206 International Journal of Research in IT, Management and Engineering www.gjmr.org 140
- 142. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 IMPACTS OF USE OF RFBIDW ON TAXATION Prof Sulatan Singh* Prof Surendra Kundu** Ms. Madhu Arora** ABSTRACT The CBDT is statutory authority for policy and planning of direct taxes in India.Business intelligence (BI) mainly refers to computer-based techniques used in identifying, extracting, and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes.Computerized processing of returns all over the country introduced in 2002. To enhance revenue realization and catch tax evaders quickly, the Central Board of Direct Taxes is working on a comprehensive data warehousing system which will transform the functioning of the Income Tax Department called Revenue Forecasting & Business Intelligence Data Warehouse(RFBIDW).From data pertaining to mobile users to electoral records and database of high net worth individuals, a universe of diverse information will be assembled in the I-T warehouse for analysis and generating credible information and reports for investigation purposes and revenue forecasting. Present study conceptual in nature is based on analyzing impact of RFBIDW on taxation and found that it will be a remarkable step if used honestly and intelligently. *Chairman, CDLU, Sirsa **Professor, CDLU, Sirsa ***Research Scholar, CDLU, Sirsa International Journal of Research in IT, Management and Engineering www.gjmr.org 141
- 143. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 INTRODUCTION Kautilya’s Arthasastra was the first authoritative text on public finance, administration and the fiscal laws in this country. His concept of tax revenue and the on-tax revenue was a unique contribution in the field of tax administration. It was he, who gave the tax revenues its due importance in the running of the State and its far-reaching contribution to the prosperity and stability of the Empire. It is truly a unique treatise. It lays down in precise terms the art of state craft including economic and financial administration. The introduction of electronic filing of I-T returns, e-payment of taxes, establishment of the national network (TAXNET), and consolidation of the Regional Computer Centers into the National Data Center have laid the foundation for the next generation administrative reforms in the Department with the Computerised processing of returns all over the country introduced in 2002.Net direct tax collection in the current financial year is higher by 6.7% at R1,27,858croreas against R1,19,849 crore collected from 1st April to 15thSeptember last year. The net collection has been impacted by R61, 000crore of refunds. Gross direct tax mop-up duringthe period has been R1,88,868crore, a growth of 29.5% over the previous year’s collection during the period of R1,45,825crore.(Source: http://www.indianexpress.com) this can be increased to standards if government shift attention from individual assessed to groups such as families, business groups, trades, dealers in particular items and intermediaries for curbing tax evasion. RESEARCH METHODOLOGY The design of the research helps to get the ways for doing the work. Summary of the proposed research work is given as under:. As the purpose of research is to discover answers to questions through the application of scientific procedures, research objectives can be one of the following categories: 1. Exploratory research to gain familiarity with a phenomenon or to achieve new insights into it. 2. Descriptive research is to portray accurately the characteristics of a particular individual, situation or a group. International Journal of Research in IT, Management and Engineering www.gjmr.org 142
- 144. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 3. Diagnostic research is to determine the frequency with which something occurs or with it is associated with something else. 4. Hypothesis testing research to test a hypothesis of a causal relationship between variables Present study is conceptual in nature research of an exploratory r OBJECTIVES OF THE STUDY: i. To study about the present system for business intelligence for tax used. ii. To analyze the concept of RFBIDW iii. To understand impacts of using RFBIDW on present system iv. To suggest changes if any for improvement of proposed data warehouse. Data Collection: Secondary data available on official website of CBDT, journals, newspapers and books has been considered for studyhas been duly acknowledged in references. Time period: This study has been done in October-November 2011.data after study may vary due to vastness and changing nature of subject. Limitation of the study: Due to vastness, time bound and complexity of subject only RFBIDW is main focus of the study. Innovations in future may provide scope for future researchers in this context. Analysis Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, benchmarking, and text mining and predictive analytics. Information available with the ministry of corporate affairs, select data from excise and Customs and the Goods and Services Tax, customised data from think-tanks such as CMIE and data received from other enforcement agencies in India and abroad, will also be available at the facility, to be known as the Revenue Forecasting & Business Intelligence Data Warehouse (RFBIDW). International Journal of Research in IT, Management and Engineering www.gjmr.org 143
- 145. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 1: External data Internal data Base RFBIDW Information on PAN e-filing data tax deduction at source share transaction tax payment annual information return on high value transaction specific information gathered by central information branch With this, RFBIDW is also expected to have certain locally relevant information, especially for investigation, and also specialized database on venture intelligence, trade analyst reports, equity analysis and fiscal reports. According to an internal estimate of the department, the size to be handled by the I-T warehouse could be around four billion data pieces. The Integrated Taxpayer Database Management System alone has over 600 million pieces of information, mobile numbers would throw up around 1.2 billion data pieces and PAN database had 120 million entries. Besides, there would be local data and also information gathered from different sources. The idea behind RFBIDW was to shift attention from individual assesse to groups such as families, business groups, trades, dealers in particular items and intermediaries for curbing tax evasion. By using the warehouse, the risk assessment wing of the department would prepare and update the database created on suspect intermediaries and known offenders and also organized schemes of tax avoidance and evasion. International Journal of Research in IT, Management and Engineering www.gjmr.org 144
- 146. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table 2: Examples of tax evasion failing to report all income claiming deductions for expenses not incurred or legally deductible claiming input credits for goods or services that GST has not been paid on not reporting cash wages not forwarding tax withheld from employee's wages to the ATO not withholding tax from a worker's wages (for example, paying in cash) not paying employee super entitlements not lodging tax returns in an attempt to avoid payment Not lodging a tax return to avoid child care or other obligation. Tax evasion is an activity commonly associated with businesses that use cash transactions, which gives them the opportunity not to declare it and pay tax on it.Investigation unit of the department would be able to quickly develop a 360-degree profile of suspected tax evaders from RFBIDW information and intelligence. The forecasting section would prepare reports on the basis of RFBIDW data on the revenue potential in specific areas and provide inputs for policy decisions. Table 3: Data from following sources will be cleaned and profiled: SOURCES DATA INTERNAL DATABASES PAN / E-Filing / TDS, OLTAS, CIB, Annual Information Return, Share Transaction Tax EXTERNAL DATABASES Mobile phone, MCA database, GST / Excise / Customs, CMIE, Capital Line, Other Enforcement International Journal of Research in IT, Management and Engineering www.gjmr.org 145
- 147. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 agencies, Current / alternate addresses LOCAL DATABASES Locally relevant databases with specific relevance for investigation purposes SPECIALIZED DATABASE Venture Intelligence, Trade Analyst Reports, Equity Analysis Reports, Fiscal Reports etc MIS Reports Analytic Reports Data Findings and Suggestions Kautilya has also described in great detail the system of tax administration in the Mauryan Empire People who were suffering from diseases or were minor and students were exempted from tax or given suitable remissions. The revenue collectors maintained up-to-date records of collection and exemptions. The total revenue of the State was collected from a large number of sources as enumerated above. There were also other sources like profits from Stand land (Sita) religious taxes (Bali) and taxes paid in cash (Kara). Vanikpath was the income from roads and traffic paid as tolls. If RFBIDW is used honestly and intelligently its 360 degree profile will be useful to detect black money and tax evasions. It will cover a large section of society and will not consider small groups, individual assess. Plans are afoot to assemble critical data from various sources under one umbrella to nab tax evaders and better policy-making. REFERNCES: NEWSPAPERS BUSINESS STANDARD SEPTEMBER 14, 2011 International Journal of Research in IT, Management and Engineering www.gjmr.org 146
- 148. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 1. http://www.business-standard.com/india/news/cbdts-business-intelligence-data-warehousing-to- boost-tax-mop-up/449094/ 2. http://en.wikipedia.org/wiki/Business_intelligence 3. http://www.information-management.com/white_papers/1210202- htmlhttp://www.cainindia.org/news/9_2011/cbdts_business_intelligence_data_warehousing_to_b oost_tax_mopup.html 4. http://incometaxindia.gov.in/ccit/CBDT.asp: 5. http://www.indianexpress.com 6. http://www.incometaxindia.gov.in/archive/BreakingNews_FMSpeech_05312010.pdfhttp: //www.business-standard.com/india/) 7. http://www.ato.gov.au/corporate/content.aspx?doc=/content/30331.htmhttp://www.incom etaxindia.gov.in/HISTORY/PRE-1922.ASP International Journal of Research in IT, Management and Engineering www.gjmr.org 147
- 149. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF EDUCATIONAL INSTITUTIONS USING FCE AND AHP Mohit Maheshwarkar* Dr. N. Sohani** Pallavi Maheshwarkar*** ABSTRACT Knowledge Management (KM) comprises a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizational processes or practice. Today many enterprises’ main profit gradually relies on the innovation, which should be established on the knowledge management system. However, the cost of executing the project of knowledge management is always high, and to build up a set of effective criterion to realize the achievement of the project is significant. This research bases on the key success factors of the KM project and applies to the Fuzzy Comprehensive Evaluation (FCE) and Analytical Hierarchy Process (AHP) to calculate the level of Knowledge Management for Educational Institutions. Keywords: Knowledge Management, FCE, AHP. *Assist. Professor, R.I.T, Indore (M.P) **Reader, I.E.T, D.A.V.V. , Indore (M.P) ***Assist. Professor, P.I.T.S, Ujjain (M.P) International Journal of Research in IT, Management and Engineering www.gjmr.org 148
- 150. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 I. INTRODUCTION Knowledge Management (KM) comprises a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizational processes or practice. Knowledge management is a management whose core is knowledge, and a series of process management that is collections, organization, innovation, diffusion, use and development of knowledge on which production and operation of enterprises relies. It is a management philosophy and methods, through the systematic use of information content, processes and expert skills; it can improve the innovative capability of enterprises and rapid response capability. Knowledge management is a process. The content of knowledge management includes the contents of a system, not only referring only to a particular aspect. The main content of knowledge management should include four parts: knowledge acquisition, knowledge management systems, knowledge sharing, and knowledge utilization. These four sections are closely connected, interdependent and mutually reinforcing. Educational Institutions face huge competition.Due to the introduction of competition in the market, these Educational Institutions face unprecedented challenges. Therefore, KM is of extreme importance to these institutions. II. EVALUATION OF EDUCATIONAL INSTITUTIONS’ KNOWLEDGE MANAGEMENT LEVEL Knowledge management underlines the learning and inheritance of human knowledge, and emphasize on creation, accumulation, use and updates of internal knowledge. Through the implementation of knowledge management, colleges can update and manage their knowledge innovation to create favorable conditions and environment, and can achieve the best combination and effective use of the knowledge of their faculty members .Therefore, the introduction of knowledge management theory to these institutions is the only way to survival and development. To gain a leading edge in the competition, colleges faced with the primary task is to enhance the ability of individual faculty members. Through the strengthening and aggregation of individual capacities, we can improve the overall organization's ability to win competitive advantage in the management, knowledge and talent areas. The Educational Institutions perform a difficult task of International Journal of Research in IT, Management and Engineering www.gjmr.org 149
- 151. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 handling the future of the country.They provide services which lead and represent the nation at the global level. The evaluation of level of knowledge management is the important work which should be considered as a primary task from educatioal point of view for the country.In the evaluation the level of a college’s knowledge management, the objective has great significance for the development of facilities provided to the students. For this purpose we follow the principles of scientific, systematic, hierarchical nature, practicality and operability. III. ANALYTICAL HIERARCHY PROCESS The Analytic Hierarchy Process (AHP) is a structured technique for helping people deal with complex decisions. Rather than prescribing a "correct" decision, the AHP helps people to determine one. An AHP hierarchy is a structured means of describing the problem at hand. It consists of an overall goal, a group of options or alternatives for reaching the goal, and a group of factors or criteria that relate the alternatives to the goal. In most cases the criteria are further broken down into sub criteria, sub-sub criteria, and so on, in as many levels as the problem requires (Fig. 1).The hierarchy can be visualized as a diagram like the one below, with the goal at the top, the alternatives at the bottom, and the criteria filling up the middle. In such diagrams, each box is called a node. The boxes descending from any node are called its children. The node from which a child node descends is called its parent. Applying these definitions to the diagram below, the five Criteria are children of the Goal, and the Goal is the parent of each of the five Criteria. Each Alternative is the child of each of the Criteria, and each Criterion is the parent of three Alternatives. Fig. 1 – Hierarchical Structure for AHP (Thomas L. Saaty, 2008) International Journal of Research in IT, Management and Engineering www.gjmr.org 150
- 152. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Once the hierarchy is built, the decision makers systematically evaluate its various elements, comparing them to one another in pairs. In making the comparisons, the decision makers can use concrete data about the elements, or they can use their judgments about the elements' relative meaning and importance. It is the essence of the AHP that human judgments, and not just the underlying information, can be used in performing the evaluations. For this purpose a pair wise comparison scale is used, which is shown in the Table 1 given below. After that AHP converts the evaluations to numerical values that can be processed and compared over the entire range of the problem. A numerical weight or priority is derived for each element of the hierarchy, allowing diverse and often incommensurable elements to be compared to one another in a rational and consistent way. This capability distinguishes the AHP from other decision making techniques. In the final step of the process, numerical priorities are derived for each of the decision alternatives. Since these numbers represent the alternatives' relative ability to achieve the decision goal, they allow a straightforward consideration of the various courses of action. Table.1– Pair Wise Comparison Scale (Thomas L. Saaty, 2008) Saaty (2008) developed the following steps for applying AHP: i. Define the problem and determine its goal, International Journal of Research in IT, Management and Engineering www.gjmr.org 151
- 153. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 ii. Structure the hierarchy with the decision maker’s objective at the top with the intermediate levels capturing criteria on which subsequent levels depend and the bottom level containing the alternatives, and iii. Construct the set of n× n pair wise comparison matrices for each to the lower levels with one matrix for each element in the level immediately above. The pair wise comparisons are made suing the relative measurement scale (as discussed above). The pair wise comparisons capture a decision maker’s perception of which element dominates the other. iv. There are n(n-1)/2 judgments required to develop the set of matrices in step 3. Reciprocals are automatically assigned in each pair wise comparison. v. The hierarchy synthesis function is used to weight the eigenvectors by the weights of the criteria and the sum is taken over all weighted eigenvector entries corresponding to those in the next lower level of the hierarchy. vi. After all the pair wise comparisons are completed, the consistency of the comparisons is assessed by using the Eigen value, λ, to calculate a consistency index, CI: CI = (λ-n)/ (n-1). Where n is the matrix size. Judgment consistency can be checked by taking the consistency ratio (CR) of CI with the appropriate value in table 2, given below. Saaty [1980] suggests that the CR is acceptable if it does not exceed 0.10. If the CR is greater than 0.10, the judgment matrix should be considered inconsistent. To obtain a consistent matrix, the judgments should be reviewed and repeated. International Journal of Research in IT, Management and Engineering www.gjmr.org 152
- 154. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table.2- Average Random Consistency Index Size of 1 2 3 4 5 6 7 8 9 10 Matrix Random 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 Consistency IV. LITRETURE REVIEW Robert G. and Eure P.E (2009) tell that Knowledge needs to be managed by the enterprise as an enterprise asset. They also focus on knowledge management. According to them Knowledge management provides tools to achieve optimum effectiveness. They also insisted to include the KM as a topic in the Systems Engineering Handbook. Rizwana Irfan and Maqbool uddin-Shaikh (2010) find that data and knowledge coming from heterogeneous sources and formats are required to be efficiently extracted, transformed and stored for decision making. Their proposal provides qualitative approach for enhancing the existing conceptual model for knowledge processing to do transformation. NIU Dongxiao and LI Jianqing (2010) investigate that Knowledge management is a process to improve the competitiveness of enterprises and identify the knowledge, acquire it and play its full role in the process. Knowledge Management is a new tool in management studies and a powerful tool for the development, use and sublimation of enterprise knowledge resources. They conclude that if the power generation companies want to sustain competitive advantage in the knowledge economy era, they should be started a developed corporate culture based on knowledge management-oriented as soon as possible, so that the organization's innovative capacity and creativity of staff's personal mutually promote and make common progress. Qian- Wang Deng and Yong-Zheng Tian (2008) used an approach of integrating knowledge management process models into product development process models. In the approach, a method named knowledge-based engineering process model is adopted as the method of International Journal of Research in IT, Management and Engineering www.gjmr.org 153
- 155. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 modeling a product development process. To realize the integration between knowledge management process model sand the product development process models, a basic rule, considering the knowledge management process as a special kind of sub-process in product development processes, is followed. Maryam Alavi and Dorothy E. Leidner (1999) focus on achieving the correct amount and type of accurate knowledge and garnering support for contributing to the Knowledge Management System (KMS). Yang Tong (2009) classifies and concludes the risks existed in knowledge management from a view of identification. The research has been divided into following aspects of knowledge assets at risk: the risk of knowledge spillovers, knowledge conversion risk, the risk of wastage, leakage risks, contractual risks, moral hazard from Knowledge and knowledge of risk vector. Thomas L. Saaty (2008) tells that the Analytic Hierarchy Process (AHP) is a theory of measurement through pair wise comparisons and relies on the judgments of experts to derive priority scales. It is these scales that measure intangibles in relative terms. The comparisons are made using a scale of absolute judgments that represents how much more; one element dominates another with respect to a given attribute. The judgments may be inconsistent, and how to measure inconsistency and improve the judgments, when possible to obtain better consistency is a concern of the AHP. The derived priority scales are synthesized by multiplying them by the priority of their parent nodes and adding for all such nodes. He also tells that Analytic Hierarchy Process (AHP) is a theory of relative measurement with absolute scales of both tangible and intangible criteria based on the judgment of knowledgeable and expert people. How to measure intangibles is the main concern of the mathematics of the AHP. The AHP reduces a multidimensional problem into a one dimensional one. Decisions are determined by a single number for the best outcome or by a vector of priorities that gives an ordering of the different possible outcomes. We can also combine our judgments or our final choices obtained from a group when we wish to cooperate to agree on a single outcome. Jay Liebowitz (2005) discusses about the novel approach in applying the analytic hierarchy process (AHP) to generate the ratio scores for the valued graphs to be used in Social Network Analysis (SNA) in order to develop a knowledge map of the organization. According to him it quantifies subjective judgments used in decision-making, and has been applied in numerous applications throughout the world. Kamal M. Al-Subhi and Al-Harbi (2001) tell that the International Journal of Research in IT, Management and Engineering www.gjmr.org 154
- 156. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Analytical Hierarchy Process (AHP) as a potential decision making method for use in project management. They used contractor prequalification problem as an example. For this a hierarchical structure is constructed for the prequalification criteria and the contractors wishing to prequalify for a project. They found that by applying the AHP, the prequalification criteria can be prioritized and a descending-order list of contractors can be made in order to select the best contractors to perform the project. Their paper presents group decision-making using the AHP. Heung-Suk Hwang et al. (2005) used a supplier selection analysis model with the help of AHP method. V. THE EVALUATING MODEL CONSTRUCTION When enterprises evaluate a thing, which have n index factors, they are marked as c1,c2,c3………………… cn. These index factors compose a finite set C. C = { c1,c2,c3………..cn} According to actual needs, the revies are divided into m degree v1,v2,v3………..vm. they compose a finite set of reviews V. V= {v1,v2,v3……………..vm} When enterprises need to value a thing from a several different aspects, te result is compressive. The result is a fuzzy set B from reviews set V. Because V is a finite set, B is also a finite set. B = b1/v1+ b2/v2 + b3/v3+bm/vm. (1) It abbreviate as m dimension fuzzy vectors: B= {b1, b2, b3………………bm} Its case is V, and bj is the membership of the corresponding elements in B and bj Є [0,1] = 1,2,3…………m. In the actual evaluating, the importance of each element is different. This is an objective fact. The set of factors is fuzzy one. A, which is the elements set U in the case; A is also a finite set. So the factor set is also a finite fuzzy set. International Journal of Research in IT, Management and Engineering www.gjmr.org 155
- 157. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 A = a1/c1 + a2/c2 + r11 r12 ……. r1m a3/c3……………………. an/cn r 21 r22 …….. r2m Similarly, A can also be said by n- dimensional fuzzy vectors. : : : : A = (a1, a2, a3………………… : : : : an ) Its case us C, ai is the r n1 r n2 …….. rnm membership of the corresponding elements in A, ai Є [0, 1], Σi=1n ai = 1. The fuzzy comprehension evaluation is to optimize the fuzzy set A by fuzzy relation B = AR B= A.R = (a1, a2, a3………..an). This is fuzzy comprehension evaluation model. B is the result of the fuzzy comprehension evaluation, and it is m- dimensional fuzzy row vectors; A is the weight set of the model, and it is n- dimensional fuzzy row vectors; R is the fuzzy relations from C to V, and it is a n×m matrix, in which the rij is the possibility of remark j for element i.(Ting Wang at el.2010) VII. CASE STUDY Here the Educational Institutions selected for the analysis are three in nos. and all are the engineering institutions. The basic reason behind this selection is that today, the students of these collages are facing a lot of problems regarding their studies, faculties, practicals provided by the institution etc. In this paper we test the knowledge management level of colleges’ on the anvil of different criteria. The selected criteria are : Teaching Practices, Practical Training and Examination Pattern. These criteria are sub divided in sub criteria the details of which are given as follows. Fig.3 shows the hierarchical structure. International Journal of Research in IT, Management and Engineering www.gjmr.org 156
- 158. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Fig.2 – Hierarchical Structrue for Knowledge Management Level Evaluation Conceptual teaching by the faculty: It defines how serious is the faculty about the concept making of the student. Expert Lectures: Expert lectures provide easy to grasp approach and make the students aware of the current practices running on in the company. Level of study material provided: The study material provided/ suggested should be such that it should not be treated as bunch of useless papers by the students. Levels of practicals conducted: Practicals conducted should not fulfill only the basic requirements of the syllabus. Practicals should be designed in order to make the concepts of the students clearer about the subject. No. of practicals conducted: Numbering of the practicals conducted should be such that it should clear almost each topic of the syllabus. Educational Visits: These are directly hand to mouth approach and should not be neglected or underestimated in any case. International Journal of Research in IT, Management and Engineering www.gjmr.org 157
- 159. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Projects delivered and guided: Projects delivered for submission must be carefully analyzed and reviewed by the departmental faculty members before assigning the students. Level of question paper: Initial test paper designed for the students should be easy in order to see where the student is lacking. After problem Remidification, the later stages of the question paper may be modified on the basis of complexity. Frequency of tests: The tests carried out by the institution should not daily but frequently. Problem Remidification: After declaring the test’s results, each of the paper must be shown before the students in the class and there should be a large problem solving session in order to magnify the problems of the students. The detailed evaluation plan is given as follows: A. Determine the reviews set, V= {Strongest, Stronger, Strong, Weak and Weaker} to determine the KM level. The factors are constructed on the basis of examination of the education system analyzed by various experts, faculty members, students and parents. B. Comparison matrix is constructed according to hierarchical structure model for one institution. Here, in this paper we have chosen total no. of institutions as three out of which evaluation details of one institution are provided. The analysis of others will be similar to the first one. Table.2- Comparison matrix for C- Ck C C1 C2 C3 W C1 1 1/5 1/3 0.1042 C2 5 1 3 0.6372 C3 3 1/3 1 0.2583 International Journal of Research in IT, Management and Engineering www.gjmr.org 158
- 160. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Σ 9 1.5333 4.333 1.000 λ max = 3.0341, CI = 0.0179, RI= 0.58, CR = 0.0332 < 0.10 Calculations for λ max, CI, RI and CR: λ max = 9(0.1042) + 1.5333(0.6372)+ 4.333(0.2583) = 3.0341 CI = (3.0358- 3)/2 = 0.0179 RI = 0.58 (From Table.1) & CR = CI/RI = 0.0179/0.58 = 0.030 < 0.10 Table.3 - Comparison Matrix for Ck- Cij C C11 C12 C13 W C11 1 1/3 1/5 0.1061 C12 3 1 1/3 0.2604 C13 5 3 1 0. 6334 λ max = 3.0385, CI = 0.0192, RI= 0.58, CR = 0.0332 < 0.10 Table.4 - Comparison Matrix for C2- Cij C C21 C22 C23 C24 W C21 1 3 1/3 1 0. 20087 C22 1/3 1 1/5 1/3 0.07885 C23 3 5 1 3 0.51941 C24 1 3 1/3 1 0.20087 λ max = 4.0428, CI = 0.01426, RI= 0.90, CR = 0.0158 < 0.10 International Journal of Research in IT, Management and Engineering www.gjmr.org 159
- 161. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table.5 - Comparison Matrix for C3- Cij C C1 C2 C3 W C1 1 1/5 1/3 0.1042 C2 5 1 3 0.6372 C3 3 1/3 1 0.2583 λ max = 3.0341, CI = 0.0179, RI= 0.58, CR = 0.0332 < 0.10 C. Students, parents and faculty members gave their opinions on the basis of questionnaire given to them for the purpose of evaluation of level of knowledge management. On the basis of these opinions, experts give the weights to different colleges. Table.6-Weights for Teaching Practices Ck TEACHING PRACTICES (1.042) Cij 0.1061 0.2604 0. 6334 Strongest 0.3 0.4 0.3 Stronger 0.4 0.3 0.2 Strong 0.2 0.1 0.2 Weak 0.1 0.1 0.2 Weaker 0 0.1 0.1 International Journal of Research in IT, Management and Engineering www.gjmr.org 160
- 162. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table.7-Weights for Practical Training Ck PRACTICAL TRAINING (0.6372) Cij 0. 20087 0.07885 0.51941 0.20087 Strongest 0.3 0.4 0.3 0.3 Stronger 0.3 0.2 0.2 0.4 Strong 0.2 0.1 0.2 0.2 Weak 0.1 0.1 0.2 0.1 Weaker 0.1 0.1 0.1 0 Table.8-Weights for Exam Pattern Ck EXAM PATTERN (0.2583) Cij 0.1042 0.6372 0.2583 Strongest 0.4 0.2 0.4 Stronger 0.2 0.4 0.2 Strong 0.1 0.3 0.1 Weak 0.2 0.1 0.1 Weaker 0.1 0 0.2 International Journal of Research in IT, Management and Engineering www.gjmr.org 161
- 163. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 The above digitals can be used to investigate, B1= (0.1061 0.2064 0.6334) 0.3 0.4 0.2 0.1 0 0.4 0.3 0.1 0.1 0.1 0.3 0.2 0.2 0.2 0.1 B1 = (0.3044 0.2310 0.1685 0.1579 0.0840) Similarly, we can get B2 = (0.3079 0.2603 0.1921 0.1519 0.0799), and B3 = (0.2724 0.3274 0.2274 0.1104 0.0621) So, B = Uk . B1 B2 B3 OR = (0.1042 0.6372 0.2583). 0.3044 0.2310 0.1685 0.1579 0.0840 0.3079 0.2603 0.1921 0.1519 0.0799 0.2724 0.3274 0.2274 0.1104 0.0621 B = (0.2983 0.2745 0.1987 0.1418 0.0757) If V= (2,1,0,-1,-2), then the result will be KML1 = (0.2983 0.2745 0.1987 0.1418 0.0757). (2,1,0,-1,-2) KML1 = 0.5779, where KM1.= Knowledge Management level of Ist college. International Journal of Research in IT, Management and Engineering www.gjmr.org 162
- 164. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Proceeding in the similar manner we can get KML2 = 0.1310 and KML3 = 0.6995. The above result shows that KM level of third educational institution is best among all the three institutions. VII. CONCLUSIONS Today, colleges play an important role in shaping the future of the country, so the evaluation of their knowledge management level is of great significance. In this paper, we have used the Analytical Hierarchy process combined with Fuzzy Comprehensive Evaluation Technique to evaluate the level of knowledge management for Educational Institutions which seems to be worthwhile in taking such a type of decisions, as it gives the results in the form of numerical quantities which is very helpful in understanding the underlying problem. From this research work we can conclude that the average knowledge management level of the Educational Institutions is still very low and there is a strong need of taking corrective actions in this direction. REFERENCES 1 Heung-Suk Hwang, Chiung Moon, Chun-Ling Chuang and Meng-Jong Goan3 (2005). Supplier Selection and Planning Model Using AHP. International Journal of the Information Systems for Logistics and Management (IJISLM), Vol. 1, No. 1, pp. 47-53 (2005) 2 Jay Liebowitz (2005) Linking Social Network Analysis with the Analytic Hierarchy Process for Knowledge Mapping in Organizations Journal Of Knowledge Management Vol. 9 NO. 1 2005, pp. 76-86, Q Emerald Group Publishing Limited, ISSN 1367-3270 3 Kamal M. Al-Subhi Al-Harbi (2001). Application of the AHP in Project Management. International Journal of Project Management 19 (2001) 4 Maryam Alavi and Dorothy E. Leidner (1999). Knowledge Management Systems: Issues, Challenges, and Benefits. Association for Information Systems. International Journal of Research in IT, Management and Engineering www.gjmr.org 163
- 165. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 5 NIU Dongxiao, LI Jianqing (2010), Evaluation on the Level of generation Enterprise Knowledge Management Based on AHP and Gray Relational Analysis. IEEE International Conference. 6 Qian-Wang Deng, Yong-Zheng Tian (2008). Modeling Knowledge Management Processes from Perspectives of Knowledge Agents. IEEE International Conference. 7 Rizwana Irfan, Maqbool uddin-Shaikh (2010). Enhanced Knowledge Management Process for Group Decision Making. Second IEEE International Conference on Future Information Technology and Management Engineering. 8 Robert G. and Eure, P.E (2009). Knowledge Management As an Integral Component of Systems Engineering .Incose International Council of System Engineering. 9 Thomas L. Saaty (2008). Decision Making with the Analytic Hierarchy Process. Int. J. Services Sciences, Vol. 1, No. 1, 2008. 10 Yang Tong (2009) Summary Research of Risk Identification in the Process of Knowledge Management. Second IEEE International Conference on Future Information Technology and Management Engineering. 11 Ting Wang and Lifeng Li (2010). A New Hybrid Method to Evaluate the HPR Performance Based on FCE and AHP. Third IEEE, Computer society’s International Conference on Knowledge Discovery and Data Mining. International Journal of Research in IT, Management and Engineering www.gjmr.org 164
- 166. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 EVALUATION OF KNOWLEDGE MANAGEMENT LEVEL OF EDUCATIONAL INSTITUTIONS USING ANALYTICAL HIERARCHY PROCESS: A CASE STUDY IN INDIA Mohit Maheshwarkar* N. Sohani, ** Pallvai Maheshwarkar*** ABSTRACT Knowledge Management (KM) comprises a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizational processes or practice. Today many enterprises’ main profit gradually relies on the innovation, which should be established on the knowledge management system. However, the cost of executing the project of knowledge management is always high, and to build up a set of effective criterion to realize the achievement of the project is significant. This research bases on the key success factors of the KM project and applies to the Analytical Hierarchy Process (AHP) to calculate the level of Knowledge Management for Educational Institutions in an Indian city, Indore. Keywords: Knowledge Management, Analytical Hierarchy Process. *Assist. Professor, R.I.T, Indore (M.P) ** Reader ,I.E.T, D.A.V.V. , Indore (M.P) ***Assist. Professor, P.I.T.S, Ujjain (M.P) International Journal of Research in IT, Management and Engineering www.gjmr.org 165
- 167. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 I. INTRODUCTION Knowledge Management (KM) comprises a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizational processes or practice. Knowledge management is a management whose core is knowledge, and a series of process management that is collections, organization, innovation, diffusion, use and development of knowledge on which production and operation of enterprises relies. It is a management philosophy and methods, through the systematic use of information content, processes and expert skills; it can improve the innovative capability of enterprises and rapid response capability. Knowledge management is a process. The content of knowledge management includes the contents of a system, not only referring only to a particular aspect. The main content of knowledge management should include four parts: knowledge acquisition, knowledge management systems, knowledge sharing, and knowledge utilization. These four sections are closely connected, interdependent and mutually reinforcing. Educational Institutions face huge competition. Due to the introduction of competition in the market in Indian , these Educational Institutions face unprecedented challenges. Therefore, KM is of extreme importance to these institutions. II. EVALUATION OF EDUCATIONAL INSTITUTIONS’ KNOWLEDGE MANAGEMENT LEVEL Knowledge management underlines the learning and inheritance of human knowledge, and emphasize on creation, accumulation, use and updates of internal knowledge. Through the implementation of knowledge management, colleges can update and manage their knowledge innovation to create favorable conditions and environment, and can achieve the best combination and effective use of the knowledge of their faculty members .Therefore, the introduction of knowledge management theory to these institutions is the only way to survival and development. To gain a leading edge in the competition, colleges faced with the primary task is to enhance the ability of individual faculty members. Through the strengthening and aggregation of individual capacities, we can improve the overall organization's ability to win competitive advantage in the management, knowledge and talent areas. The Educational Institutions perform a difficult task of handling the future of the country.They provide services which lead and represent the nation at International Journal of Research in IT, Management and Engineering www.gjmr.org 166
- 168. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 the global level. The evaluation of level of knowledge management is the important work which should be considered as a primary task from educatioal point of view for the country.In the evaluation the level of a college’s knowledge management, the objective has great significance for the development of facilities provided to the students. For this purpose we follow the principles of scientific, systematic, hierarchical nature, practicality and operability. III. ANALYTICAL HIERARCHY PROCESS The Analytic Hierarchy Process (AHP) is a structured technique for helping people deal with complex decisions. Rather than prescribing a "correct" decision, the AHP helps people to determine one. An AHP hierarchy is a structured means of describing the problem at hand. It consists of an overall goal, a group of options or alternatives for reaching the goal, and a group of factors or criteria that relate the alternatives to the goal. In most cases the criteria are further broken down into sub criteria, sub-sub criteria, and so on, in as many levels as the problem requires (Fig. 1).The hierarchy can be visualized as a diagram like the one below, with the goal at the top, the alternatives at the bottom, and the criteria filling up the middle. In such diagrams, each box is called a node. The boxes descending from any node are called its children. The node from which a child node descends is called its parent. Applying these definitions to the diagram below, the five Criteria are children of the Goal, and the Goal is the parent of each of the five Criteria. Each Alternative is the child of each of the Criteria, and each Criterion is the parent of three Alternatives. International Journal of Research in IT, Management and Engineering www.gjmr.org 167
- 169. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Fig. 1 – Hierarchical Structure for AHP (Thomas L. Saaty, 2008) Once the hierarchy is built, the decision makers systematically evaluate its various elements, comparing them to one another in pairs. In making the comparisons, the decision makers can use concrete data about the elements, or they can use their judgments about the elements' relative meaning and importance. It is the essence of the AHP that human judgments, and not just the underlying information, can be used in performing the evaluations. For this purpose a pair wise comparison scale is used, which is shown in the Table.2 given below. After that AHP converts the evaluations to numerical values that can be processed and compared over the entire range of the problem. A numerical weight or priority is derived for each element of the hierarchy, allowing diverse and often incommensurable elements to be compared to one another in a rational and consistent way. Priorities are numbers associated with the nodes of the hierarchy. The priority of the Goal is taken as 1.000. The priorities of the children of any Criterion can also vary but will always add up to 1.000, as will those of their own children, and so on down the hierarchy. If the priorities within every group of child nodes are equal then the priorities are called Default Priorities. The priority of an attribute with respect to the ultimate goal is called Global Priority. The priorities indicate the relative weights given to the items in a given group of nodes. Depending on the problem at hand, "weight" can refer to importance, or preference, or likelihood, or whatever factor is being considered by the participants. This capability distinguishes the AHP from other decision making techniques. In the final step of the process, numerical priorities are derived for each of the decision alternatives. Since these numbers represent the alternatives' relative ability to achieve the decision goal, they allow a straightforward consideration of the various courses of action. Table 1 – Pair Wise Comparison Scale (Thomas L. Saaty, 2008) International Journal of Research in IT, Management and Engineering www.gjmr.org 168
- 170. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Saaty (2008) developed the following steps for applying AHP: i. Define the problem and determine its goal, ii. Structure the hierarchy with the decision maker’s objective at the top with the intermediate levels capturing criteria on which subsequent levels depend and the bottom level containing the alternatives, and iii. Construct the set of n× n pair wise comparison matrices for each to the lower levels with one matrix for each element in the level immediately above. The pair wise comparisons are made suing the relative measurement scale (as discussed above). The pair wise comparisons capture a decision maker’s perception of which element dominates the other. iv. There are n(n-1)/2 judgments required to develop the set of matrices in step 3. Reciprocals are automatically assigned in each pair wise comparison. v. The hierarchy synthesis function is used to weight the eigenvectors by the weights of the criteria and the sum is taken over all weighted eigenvector entries corresponding to those in the next lower level of the hierarchy. vi. After all the pair wise comparisons are completed, the consistency of the comparisons is assessed by using the Eigen value, λ, to calculate a consistency index, CI: CI = (λ-n)/ (n-1). Where n is the matrix size. Judgment consistency can be checked by taking the consistency ratio (CR) of CI with the appropriate value in table 2, given below. Saaty [1980] suggests that the CR is acceptable if it does not exceed 0.10. If the CR is greater than 0.10, the judgment matrix should be considered inconsistent. To obtain a consistent matrix, the judgments should be reviewed and repeated. International Journal of Research in IT, Management and Engineering www.gjmr.org 169
- 171. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table.2- Average Random Consistency Index Size of 1 2 3 4 5 6 7 8 9 10 Matrix Random 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 Consistency IV. LITRETURE REVIEW Robert G. and Eure P.E (2009) tell that Knowledge needs to be managed by the enterprise as an enterprise asset. They also focus on knowledge management. According to them Knowledge management provides tools to achieve optimum effectiveness. They also insisted to include the KM as a topic in the Systems Engineering Handbook. Rizwana Irfan and Maqbool uddin-Shaikh (2010) find that data and knowledge coming from heterogeneous sources and formats are required to be efficiently extracted, transformed and stored for decision making. Their proposal provides qualitative approach for enhancing the existing conceptual model for knowledge processing to do transformation. NIU Dongxiao and LI Jianqing (2010) investigate that Knowledge management is a process to improve the competitiveness of enterprises and identify the knowledge, acquire it and play its full role in the process. Knowledge Management is a new tool in management studies and a powerful tool for the development, use and sublimation of enterprise knowledge resources. They conclude that if the power generation companies want to sustain competitive advantage in the knowledge economy era, they should be started a developed corporate culture based on knowledge management-oriented as soon as possible, so that the organization's innovative capacity and creativity of staff's personal mutually promote and make common progress. Qian- Wang Deng and Yong-Zheng Tian (2008) used an approach of integrating knowledge management process models into product development process models. In the approach, a method named knowledge-based engineering process model is adopted as the method of modeling a product development process. To realize the integration between knowledge management process model sand the product development process models, a basic rule, considering the knowledge management process as a special kind of sub-process in product International Journal of Research in IT, Management and Engineering www.gjmr.org 170
- 172. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 development processes, is followed. Maryam Alavi and Dorothy E. Leidner (1999) focus on achieving the correct amount and type of accurate knowledge and garnering support for contributing to the Knowledge Management System (KMS). Yang Tong (2009) classifies and concludes the risks existed in knowledge management from a view of identification. The research has been divided into following aspects of knowledge assets at risk: the risk of knowledge spillovers, knowledge conversion risk, the risk of wastage, leakage risks, contractual risks, moral hazard from Knowledge and knowledge of risk vector. Thomas L. Saaty (2008) tells that the Analytic Hierarchy Process (AHP) is a theory of measurement through pair wise comparisons and relies on the judgments of experts to derive priority scales. It is these scales that measure intangibles in relative terms. The comparisons are made using a scale of absolute judgments that represents how much more; one element dominates another with respect to a given attribute. The judgments may be inconsistent, and how to measure inconsistency and improve the judgments, when possible to obtain better consistency is a concern of the AHP. The derived priority scales are synthesized by multiplying them by the priority of their parent nodes and adding for all such nodes. He also tells that Analytic Hierarchy Process (AHP) is a theory of relative measurement with absolute scales of both tangible and intangible criteria based on the judgment of knowledgeable and expert people. How to measure intangibles is the main concern of the mathematics of the AHP. The AHP reduces a multidimensional problem into a one dimensional one. Decisions are determined by a single number for the best outcome or by a vector of priorities that gives an ordering of the different possible outcomes. We can also combine our judgments or our final choices obtained from a group when we wish to cooperate to agree on a single outcome. Jay Liebowitz (2005) discusses about the novel approach in applying the analytic hierarchy process (AHP) to generate the ratio scores for the valued graphs to be used in Social Network Analysis (SNA) in order to develop a knowledge map of the organization. According to him it quantifies subjective judgments used in decision-making, and has been applied in numerous applications throughout the world. Kamal M. Al-Subhi and Al-Harbi (2001) tell that the Analytical Hierarchy Process (AHP) as a potential decision making method for use in project management. They used contractor prequalification problem as an example. For this a hierarchical structure is constructed for the prequalification criteria and the contractors wishing to prequalify for a project. They found that by applying the AHP, the prequalification criteria can International Journal of Research in IT, Management and Engineering www.gjmr.org 171
- 173. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 be prioritized and a descending-order list of contractors can be made in order to select the best contractors to perform the project. Their paper presents group decision-making using the AHP. Heung-Suk Hwang et al. (2005) used a supplier selection analysis model with the help of AHP method. V. CASE STUDY In this paper we test the knowledge management level of colleges’ on the anvil of different criteria. The selected evaluationa criteria are : Conceptual Teaching, Practical Assessment, Expert Lecture Criteria, Educational Visits and Problem Sorting. This evaluation criterion has been developed on the basis of literature review and a series of informal discussions with a large number of academicians. On these selected criteria different Educational Institutions will be tested. Here the Educational Institutions selected for the analysis are three in nos. Fig.2 shows the hierarchical structure. Fig.2 – Hierarchical Structrue for Knowledge Management Level Evaluation A. Comparison of Criterion On making pairwise comparisons of all the five criterias we will get the following combinations. Conceptual Teaching Vs. Practical Assessment Conceptual Teaching Vs. Expert Lecture Criteria Conceptual Teaching Vs. Educational Visits Conceptual Teaching Vs. Problem Sorting Practical Assessment Vs. Expert Lecture Criteria Practical Assessment Vs. Educational Visits International Journal of Research in IT, Management and Engineering www.gjmr.org 172
- 174. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Practical Assessment Vs. Problem Sorting Expert Lecture Criteria Vs. Educational Visits Expert Lecture Criteria Vs. Problem Sorting Educational Visits Vs. Problem Sorting As a result of these pair wise comparisons we will get the following pairwise comparison matrix: Table.3- Pairwise Comparison Matrix for different criteria Expert Conceptual Practical Educational Problem From/To Lecture Teaching Assessment Visits Sorting Criteria Conceptual Teaching 1 1 5 3 4 Practical Assessment 1 1 1 4 4 Expert Lecture Criteria 1/5 1 1 4 5 Educational Visits 1/3 1/4 1/4 1 5 Problem Sorting 1/4 1/4 1/5 1/5 1 On solving the above matrix analytically or simply putting the values in AHP software we will get the following results: International Journal of Research in IT, Management and Engineering www.gjmr.org 173
- 175. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table.4- Priority values for different criteria S.No Criteria Priority 1. Conceptual Teaching 0.3545 2. Practical Assessment 0.263 3. Expert Lecture Criteria 0.21656 4. Educational Visits 0.1139 5. Problem Sorting 0.05142 C.I. = 0.070911, R.I. = 1.12, C.R. = 0.0625<0.10 B. Comparion of Institutions Now the priorities for the Educational Institutions were calculated. For the purpose of comparison of evaluation of level of conceptual teaching, syatametically disigned quesitonnire was given to the students and the results were plotted on a pairwise comparison matrix, given as follows: Table.5- Pairwise comparison matrix for Conceptual Teaching Criteria From/To A B C A 1 1/3 1/5 B 3 1 1/3 C 5 3 1 On solving the above matrix we will get the following priority values: International Journal of Research in IT, Management and Engineering www.gjmr.org 174
- 176. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table.6- priority values for Conceptual Teaching Criteria COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL) A 0.106 0.037577 B 0.2604 0.09231 C 0.633345 0.22452 C.I.= 0.0192555, R.I.=0.58, C.R.=0.033<0.10 Proceeding in the similar manner we will get the different priority matrices and different values of priorities for different criteria. The details of matrices along with the results are given as follows: Table.7- Pairwise comparison matrix for Practical Assessment Criteria From/To A B C A 1 5 6 B 1/5 1 3 C 1/6 1/3 1 Table.8- priority values for Practical Assessment Criteria COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL) A 0.70708 0.1859 B 0.20141 0.05297 C 0.0915 0.0240 C.I. =0.0470076, R.I.=0.58, C.R.=0.0810<0.10 International Journal of Research in IT, Management and Engineering www.gjmr.org 175
- 177. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table.9- Pairwise Comparison for Expert Lecture Criteria From/To A B C A 1 1/4 2 B 4 1 5 C 1/2 1/5 1 Table.10- Priority values for Expert Lecture Criteria COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL) A 0.2014 0.043615 B 0.6806 0.147390 C 0.1179 0.025532 C.I. =0.0122975, R.I. =0.58, C.R. = 0.0210<0.10 Table.11- Pairwise Comparison for Educational Visits Criteria From/To A B C A 1 4 8 B 1/4 1 5 C 1/8 1/5 1 Table.12- Priority values for Educational Visits Criteria COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL) A 0.6893 0.07851 B 0.2437 0.02775 C 0.0666 0.00758 C.I. =0.0470076, R.I. =0.58, C.R. = 0.0810<0.10 International Journal of Research in IT, Management and Engineering www.gjmr.org 176
- 178. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table.13- Pairwise comparison matrix for Problem Sorting Criteria From/To A B C A 1 3 9 B 1/3 1 7 C 1/9 1/7 1 Table.14 – Priority values for Problem Sorting Criteria COLLEGES PRIORITIES (LOCAL) PRIORITIES (GLOBAL) A 0.6486 0.03335 B 0.2946 0.015148 C 0.0567 0.00291 C.I. =0.0401499, R.I. =0.58, C.R. =0.0692<0.10 Finally, on adding up the priority values for different criteria we will get the value of knowledge management level for an institution. Table.15- Comprehensive Evaluation of Educational Institutions Evaluation of Knowledge Management Level – An AHP Approach Conceptual Practical Expert Lecture Educational Problem COLLEGES /CRITERIA TOTAL Teaching Assessment Criteria Visits Sorting A 0.037577 0.1859 0.043615 0.07851 0.03335 0.378952 B 0.09231 0.05297 0.147390 0.02775 0.015148 0.335568 C 0.22452 0.0240 0.025532 0.00758 0.00291 0.284542 0.3545 0.263 0.21656 0.1139 0.05142 1.00000 TOTAL 1.000000 International Journal of Research in IT, Management and Engineering www.gjmr.org 177
- 179. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 According to the evaluation system, the grades of "very high”, "Medium" and "low", are set respectively. On this basis the colleges' are evaluated. Table.16- Evaluation of Knowledge management level S.No College Knowledge Management Level 1. A Very High 2. B Medium 3. C Low VI. CONCLUSIONS Today, colleges play an important role in shaping the future of the country, So the evaluation of their knowledge management level is of great significance. In this paper, we have used the Analytical Hierarchy process to evaluate the level of knowledge management for Educational Institutions which seems to be worthwhile in taking such a type of decisions, as it gives the results in the form of numerical quantities which is very helpful in understanding the underlying problem. From this research work we can conclude that the average knowledge management level of the Educational Institutions is still very low and there is a strong need of taking corrective actions in this direction. REFERENCES 1 Heung-Suk Hwang, Chiung Moon, Chun-Ling Chuang and Meng-Jong Goan3 (2005). Supplier Selection and Planning Model Using AHP. International Journal of the Information Systems for Logistics and Management (IJISLM), Vol. 1, No. 1, pp. 47-53 (2005) International Journal of Research in IT, Management and Engineering www.gjmr.org 178
- 180. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 2 Jay Liebowitz (2005) Linking Social Network Analysis with the Analytic Hierarchy Process for Knowledge Mapping in Organizations Journal Of Knowledge Management Vol. 9 NO. 1 2005, pp. 76-86, Q Emerald Group Publishing Limited, ISSN 1367-3270 3 Kamal M. Al-Subhi Al-Harbi (2001). Application of the AHP in Project Management. International Journal of Project Management 19 (2001) 4 Maryam Alavi and Dorothy E. Leidner (1999). Knowledge Management Systems: Issues, Challenges, and Benefits. Association for Information Systems. 5 NIU Dongxiao, LI Jianqing (2010), Evaluation on the Level of generation Enterprise Knowledge Management Based on AHP and Gray Relational Analysis. IEEE International Conference. 6 Qian-Wang Deng, Yong-Zheng Tian (2008). Modeling Knowledge Management Processes from Perspectives of Knowledge Agents. IEEE International Conference. 7 Rizwana Irfan, Maqbool uddin-Shaikh (2010). Enhanced Knowledge Management Process for Group Decision Making. Second IEEE International Conference on Future Information Technology and Management Engineering. 8 Robert G. and Eure, P.E (2009). Knowledge Management As an Integral Component of Systems Engineering .Incose International Council of System Engineering. 9 Thomas L. Saaty(2008). Decision Making with the Analytic Hierarchy Process. Int. J. Services Sciences, Vol. 1, No. 1, 2008. 10 Yang Tong (2009) Summary Research of Risk Identification in the Process of Knowledge Management. Second IEEE International Conference on Future Information Technology and Management Engineering. International Journal of Research in IT, Management and Engineering www.gjmr.org 179
- 181. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 PROBE FEED RECTANGULAR PATCH MICROSTRIP ANTENNA: CAD METHODOLOGY Dr. R.D. Kanphade* Dr. D.G. Wakade** Prof. N.T. Markad*** ABSTRACT Antenna is a means for radiating or receiving radio waves. In addition to receiving or transmitting energy, an antenna is used in an advanced wireless system is usually required to optimize the radiation energy in same direction and suppress it in others. A micro strip patch antenna also referred to as patch antenna is a narrowband, wide beam antenna fabricated by etching the antenna element patch in metal trace bonded to an insulating dielectric substrate with a continuous metal layer bonded to opposite side of substrate which forms a ground plane. Probe feed rectangular patch Micro strip antenna simulated in FDTD software IE3D. Proposed novel probe feed rectangular patch microstrip antenna is presented. It has a return loss of - 23.5dBat a frequency of 1.88GHZ. Antenna offers VSWR 1.15at a frequency of 1.88GHZ. Antenna offers a band width of 14 MHZ. By observing a smith chart it is seen that antenna offers resistive, capacitive and inductive impedance. Antenna offers unidirectional radiation pattern. Unidirectional radiation pattern plays important role in next generation mobile communication and computing Due to unidirectional radiation pattern cost of power of a mobile communication system is reduced. Probe feed rectangular patch micro strip antenna offer an antenna efficiency of 87%. Also antenna offers radiation efficiency of 86%. The exact location of the probe which can guarantee the desired performance is not given in the literature. So, hit and trial method is used to locate the co-ordinates of the probe feed which can provide satisfactory output. Using hit and trial, the co-ordinates of the probe were found to be (x, y) =(6,2). KEYWORDS: Probe feed, Micro strip patch antenna, Efficiency, Radiation efficiency, VSWR, Smith chart. *Principal,Dhole Patil College of Engineering,Wagholi,Pune **Director,P.R.Patil College of Engineering,Amravati ***Associate Professor,BVCOE,Deptt. Of ECE International Journal of Research in IT, Management and Engineering www.gjmr.org 180
- 182. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 [I] INTRODUCTION In telecommunication; there are several types of micro strip antennas( also known as printed antennas) the most common of which is the micro strip patch antenna or patch antenna. A patch antenna is a narrowband, wide-beam antenna fabricated by etching the antenna element pattern in metal bonded to an insulating dielectric substrate with a continuous metal layer bonded to the opposite side of the substrate which forms a ground plane. Common micro strip antenna radiator shapes are square, rectangular, circular and elliptical but any continuous shape is possible. Some patch antennas eschew a dielectric substrate and suspend a metal patch in air above a ground plane using dielectric spacers, the resulting structure is less robust but provides better band width. Because such antennas have a very low profile; are mechanically rugged and can be conformable, they are often mounted on the exterior of aircraft and spacecraft or are incorporated into mobile radio communication devices; [1]. Micro strip antennas are also relatively inexpensive to manufacture and design because of the simple two dimensional physical geometry. They are usually employed at UHF and higher frequencies because the size of the antenna is directly tied to the wavelength at the resonance frequency [2]. A single patch antenna provides a maximum directive gain of around -6 dBi. It is relatively easy to print on array of patches on a single (large) substrate using lithographic techniques. Patch arrays can provide much higher gain than a single patch at little additional cost; matching and phase adjustment can be performed with printed micro strip feed structures, again in the some operation that form the radiating patches. The ability to create high gain arrays in a low profile antenna is one reason that patch arrays are common on [3] airplanes and in other military application. An array antenna is a special arrangement of basic antenna components involving new factors and concepts. Before you begin studying about arrays, you need to study some new terminology [4]. An array antenna is made up of more than one ELEMENT, but the basic elements is generally the dipole. Sometimes the basic element is made longer or shorter than a half-wave, but the deviation usually is not great [4] [5]. Typically an antenna is tuned for a specific frequency and is effective for a range of frequencies that are usually on that resonant frequency. Some antenna International Journal of Research in IT, Management and Engineering www.gjmr.org 181
- 183. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 design have multiple resonant frequencies, and some are relatively effective over very broad range of frequencies. [6] Gain as a parameter measures the efficiency of a given antenna with respect to a given norm, usually achieved by modification of its directionality. An antenna with a low gain emits radiation with about the same power in all directions, whereas high gain antenna will radiate in particular direction. The radiation pattern of an antenna is the geometric pattern of the relative field strengths of field emitted by the antenna. In field of antenna the term “radiation pattern” most commonly refers to directional (angular) dependence of radiation from the antenna or other source. Usually, the directivity is expressed in dBi. The reason that the units are dBi, (decibel relative to an isotropic radiations that for n isotropic radiator, the radiated lower density is a constant and therefore equals the average radiated power density ( the denominator). The angle across the main lobe of an antenna pattern, between the two directions, at which, the antenna’s sensitivity is half its maximum value at the centre of the lobe. It is abbreviated as HPBW[7][8]. As an electromagnetic wave travels through the different parts of the antenna system (radio, feed line, antenna, free space) it may encounter differences in impendence (E/H; V/I, etc.) At each interface, depending on the impedance match, some fraction of the wave’s energy will reflected back to the source [5], forming a standing wave in the feed line. The ratio of maximum power to minimum power in the wave can be ratio (SWR). A SWR of 1:1 is ideal. A SWR of 1.5:1 is considered to be marginally acceptable in low power application. Efficiency is the ratio of power actually radiated to the power put into antenna terminals. The bandwidth of an antenna is the range of frequencies over which it is effective, usually centered on the resonant frequency. The band width of antenna may be increased by several techniques, including using thicker wires, replacing wires with cages to simulate a thicker wire, tapering antenna components (like in a feed horn); and combining multiple antenna into a single assembly and allowing the natural impedance to select correct antenna, small antenna are usually preferred for convenience, but there is a fundamental limit relating bandwidth, size and efficiency. The polarization of an antenna is the orientation of the electric field (E-plane) of the radios waves with respect to the Earth’s surface and is determined by physical structure of the antenna and by its orientation. It has nothing in common with antenna directionality terms: horizontal, vertical and circular (9) [10] International Journal of Research in IT, Management and Engineering www.gjmr.org 182
- 184. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 In high performance aircraft, satellite and missile applications, where size, weight, cost, performance, ease of installation and aerodynamic profile are constraints, and low profile antenna may be required. To meet there requirement microstrip antenna can be used. These antennas are low profile, conformable to planar and non-planar surfaces. Simple and inexpensive to manufacture using modern printed-circuit technology. Mechanically robust when mounted on rigid surfaces compatible with MMIC design [11]. There are many configurations that can be used to feed micro strip antenna. The four most popular are :- Microstrip line Coaxial cable Aperture coupling Proximity coupling The micro strip line feed is easy to fabricate; simple to match by controlling the inset position and rather simple to model. Because the dimensions of the patch re finite along the length and width; the fields at the edges of the patch undergo fringing. The amount of fringing is a function of the dimensions of the patch and the height of the substrate. Due to fringing field antenna radiate. Fringing Fields Shown in Figure 1. Figure 1 Fringing Field Figure 2 Patch Antenna International Journal of Research in IT, Management and Engineering www.gjmr.org 183
- 185. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 [II] FEED NETWORK Feed is of different types but most popular feed are – Transformer feed Microstrip line feed Coaxial cable feed Aperture coupling feed Proximity coupling feed. Out of above mentioned feed for micro strip patch antenna feed applied to it is transformer feed type. Suppose impendence at antenna is 100Ω by transformer type feed 100Ω . This 50Ω impendence known as terminating impendence. Terminating impendence matches to probe impedance hence power delivered to micro strip patch antenna is maximum. [11] The exact location of the probe which can guarantee the desired performance is not given in the literature. So, hit and trial method is used to locate the co-ordinates of probe feed which can provide satisfactory output. Using hit and trial, the co-ordinates of the probe were found to be (x,y) =(6,2). [III] DESIGN OF RECTANGULAR PATCH ANTENNA WITH PROBE FEED. The three essential parameters for the design of a rectangular patch antenna are:- The resonant frequency of the antenna must be selected appropriately. The personal communication system (PCS) uses the frequency range from 1850-1990 MHZ. Hence the antenna design must be able to operate in this frequency range. The resonant frequency selected for our design is 1.9 GHZ. The dielectric material selected for our design is FR4 which has a dielectric constant of 4.4. A substrate with a high dielectric constant has been selected since it reduces the dimensions of the antenna. For the micro strip patch antenna to be used in cellular phones, it is essential that the antenna is not bulky. Hence, the height of the dielectric substrate is selected as 1.6mm. Calculation of width (W) :- The width of the micro strip patch antenna is given by : International Journal of Research in IT, Management and Engineering www.gjmr.org 184
- 186. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 W= C____________ 2f0√(Єr+1/2) Substituting C=3e8m/s ; Єr= 4.4 and f0 = 1.9GHZ We get W = 0.048 m = 48.0mm Calculation of Effective dielectric constant (Єreff) :- The effective dielectric constant is calculated as : Єreff = (Єr+1)/(Єr-1)/2[1+12h/w]-1/2 Substituting Єr =4.4; w= 48.0mm and h=1.6mm we get Єreff =4.14 Calculation of the Effective length (Leff) :- The effective length is given as Leff = C/(2 f0√Єreff). Substituting Є reff=4.14,c=3e8m/s and f0=1.9 GHz. Weget : Leff = 0.0388m = 38.8mm Calculation of the length extension (∆ L):- The length extension is given as : Substituting the values, we get; ∆ L=.412h(Єreff+ .3)( w/h+.264)/(Єreff.-.258)(w/h+.8) Calculation of actual length of patch (L):- The actual length is obtained by: L= (Leff .– 2∆L ) Substituting the values, we get: L= 37.3mm In general, top view of probe, Feed rectangular patch micro strip antenna is shown in Fig.2. Geometry probe feed patch antenna shown in Figure.2. [IV] RESULTS AND ANALYSIS International Journal of Research in IT, Management and Engineering www.gjmr.org 185
- 187. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 The design analysis gave the following results. Radiation pattern of probe feed rectangular patch micro strip antenna is shown in Figure.3. The radiation pattern of probe feed rectangular patch micro strip antenna is unidirectional. This unidirectional radiation pattern plays important role in next generation mobile communication and computing. Due to unidirectional radiation pattern cost of power of mobile communication is reduced. Gain v/s frequency plot of probe feed rectangular patch micro strip antenna is shown in Figure.4. From this plot, it is seen that antenna offers return loss of -23.5 dB at a frequency of 1.88 GHZ. VSWR V/S frequency plot shown in Figure 5, From Figure 5 it is seen that antenna has a VSWR of 1.15 at a frequency of 1.88 GHZ. Smith chart shown in Figure 6. From smith chart it is seen that antenna offered resistive, capacitive as well as inductive impendence. Figure. 7 shows efficiency v/s frequency plot. From this plot it is seen that probe feed rectangular patch micro strip antenna offered antenna efficiency of 87% and radiation efficiency of 86%. International Journal of Research in IT, Management and Engineering www.gjmr.org 186
- 188. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Figure 3 RADIATION PARTTREN Figure 4 RETURN LOSS Figure 5 VSWR Figure 6 EFFICIENCY International Journal of Research in IT, Management and Engineering www.gjmr.org 187
- 189. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Figure 7 SMITH CHART [V] CONCLSION It is seen that the design adopted for the probe feed rectangular micro strip patch antenna are accurate. This antenna can be used at 1.88 GHZ frequency for mobile communication and computing applications where the frequency of operation is 1.88 GHZ. For antenna to work properly the VSWR must be less than two and return loss must be less than 10dB, only then the antenna will radiate or receive the power with minimum reflection. As designed antenna has a return loss -23.5dB and VSWR 1.15 at a frequency of 1.88 GHZ, so this antenna is used in mobile communication and computing satisfactorily. Probe feed rectangular micro strip antenna are ideal for mobile communication, application where weight is the main constraint. Due to unidirectional radiational pattern antenna plays important role in next generation mobile communication and computing. Cost of power of mobile communication system is saved due to this antenna. [VI] REFERENCES [1] Y Li, C. Chen, Y.cho “ A unified optimization Framework for microelectronics Industry” Department of communication Engineering, national chiao Tung university, Taiwan International Journal of Research in IT, Management and Engineering www.gjmr.org 188
- 190. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 [2] Tang, W.chow, Y,many microstrip line Discontinuities on one General Field – Based circuit model, city university of Hon Kong, china University of waterloo, Canada. [3] Caver K, and Mink J,. Micro strip Antenna Technology, IEEE, Transactions on Antenna and propagation, vol.29, No. 1, January 1981. [4] D.N. Schaubert, “Micro strip antennas, “ Electromagnetic, vil.12, pp.381-401, 1992. [5] G.W. Garvin, R.E.Munson, L.T. Ostwald and K.G.Schroeder,” Low pro file electrically small missile base mounted micro strip antenna,” in Dig int-syom... Antenna Propagation soc, urbana, IL, June 1975, pp. 224-247. [6] J.Q.Howell “Micro strip antennas” IEEE Trans Antenna propagation, vol. AP-23, No. 1, pp.. 90-93, Jan 1975. [7] I.R.J.Mailloux, J.Mcilvenna and N. Kernweis, “Micro strip array technology” IEEE Trans. Antenna and propagation, vol.AP-29 No. 1, pp 25-38, Jan.1981. [8] H.D.Weinschel, “Progress report on development of micro strip cylindrical arrays for sounding rockets,” physic. And Sci. Lab, NEW Mexico state univ, LAS Cruces, 1973. [9] J.R. James and G.J. Wilson, “New design techniques for microstrip antenna array” in proc. 5th European Micro. Conf, Hamburg, Sept. 1975, pp. 102-106. [10] Balanis, Antenna theory. [11] R.D.Kanphade, D.G.Wakade and N.T.Markad “Micro strip patch antenna : computer Aided Design Methology, International Journal of Electronics Communication Engineering, Rohini, New Delhi, Octomber 2011. [12] FDTD IE3D Reference Manual, Fremont : Zealand software Inc, 2006. [16]K. Dessouky & 1. Ho, Propagation Results from the Sat el 1 i t e- l a Experiment , KAT-X Quart er l y , JPL, No. 17, October 1988, pp7-12. International Journal of Research in IT, Management and Engineering www.gjmr.org 189
- 191. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 [17]J. P. McCeehan and A. Bateman, Phase-locked transparent tone-in-band TTIB: A new spectrum configuration particularly suited to the transmission of data over SSB mobile radio networks, IEEE Trans on Conun~, Vol.COM-32, No.1, Jan. 1984, pp 81-87. [18]A. Kanso, Novel Signal Processing Techniques for Pilot-Based SSB Mobile Radio Systems, Ph.D Thesis, Dept. of Elec. Eng., Univ of Bath, Bath UK, 1985. [19]A. Bateman and D.M. Haines, Direct Conversion Transceiver for Compact Low-Cost Portable Mobile Radio Terminals, This conference Record. [20]A. Baternan, R.J. Wilkinson and J.D.Marvi11, The Application of Digital Signal Processing to Transmitter Linearisation, IEEE Eurocon 88, Stockholm, Sweden, 13'h-17th July 1988. [21]C.R. Green, A.A. Lane, R. Shulka and P.N. Tombs,GaAs M MICs for use in Phased Array Radar T/R Modules, IEE Colloquium on 'Electronically Scanned Antennas, 21' January 1988, London, UK.756 [22]Advances in smart antenna system. Dr. D.G. Wakade and D.G. Rameshwer kawitkar SSGM college of Engineering shegaon 444203 . received on 19th Jan 2005 accepted on 26th June 2005. Journal of scientific and industrial research Vol.64, September 2005, PP 660- 665 International Journal of Research in IT, Management and Engineering www.gjmr.org 190
- 192. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 DETERMINANTS OF GROWTH OF TOURISM INDUSTRY IN GOA: A STUDY Dr. Achut Pednekar* ABSTRACT Goa is known as the beach country of India. As per the projection made by the consultants, around 1.6 million tourists are expected by the turnoff and with an expected average annual growth rate of 6.36 per cent, the total traffic in the horizon year i.e. 2021 would increase to 3.2 million. The resultant growth in tourist traffic is infuse a heavy and steady to upgrade and augment the present infrastructures, hence the study. A multiple regression coefficient has been utilized to analyze the relationship between the arrival of tourists and the expenditure plan. Apart from this, the trends of tourist’s arrivals as well as foreign charter flights have been considered and analyzed with the help of percentage change method. Implications of the research are that expenditure plan is not only the factors which are influencing the tourists in Goa. Government of Goa should introduce and enhance new tourism and existing activities i.e. adventure tourism, cultural heritage tourism, pilgrim tourism, business tourism, sports tourism, and education and medical tourism. The existing facilities are not sufficient and should channelize way to identify infrastructure and other developmental needs for tourism. Keywords: Goa, Receipt, Capital, Expenditure Plan *D.M’s College, Goa International Journal of Research in IT, Management and Engineering www.gjmr.org 191
- 193. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 INTRODUCTION The World Tourism Organization (WTO) in its Tourism 2020 vision has estimated that there would be about 1.0 billion total international tourists in all countries in the world in the year 2010 and 1.6 billion in 2020 compared to 0.57 billion in 1995. According to WTO estimates Europe will continue to remain the most popular tourist destination with about 0.7 billion tourists estimated for the year 2020. East Asia and Pacific region will surpass America by 2010 to become the second most visited destination. International tourists in South Asia is expected at 0.2 billion in 2020 which is almost five times that of 1995 but still quite low compared to other destinations. India is expected to fuel 4.5 times growth in international tourist’s arrival, between 1995 and 2020. Goa has attracted 1.2 million of tourist traffic in the year 1997. As per the projection made by the consultants, around 1.6 million tourists are expected by the turnoff and with an expected average annual growth rate of 6.36 per cent, the total traffic in the horizon year i.e. 2021 would increase to 3.2 million. It is projected that in 2021 domestic tourists would be 2 times the present level and foreign tourist would be 4 times the present level and overall about 2.5 times.(Tourism Master Plan : Goa 2011 Final Report February 2001) The resultant growth in tourist traffic is infuse a heavy and steady to upgrade and augment the present infrastructures. Therefore urgent efforts are required from the state to upgrade and augment the present infrastructure stock to meet future requirement. The Government of Goa has declared Tourism as an Industry with effect from 01/04/2000. The Master Plan for tourism development upto 2011 A.D. has been prepared. The Tourism Policy of the State has also been framed. Since a large multitude of the people in Goa are economically dependent on tourism and related activities a decisive promotional thrust and reworking of the appropriate tourism model have been identified as key elements in placing the potential of our touristic state on a higher growth orbit. Tourism sector has been accorded the status of industry entitling the hospitality sector to avail of benefits of concession available on water and power tariffs, relief in service tax, luxury tax on hotel rooms and sales tax on cooked foods as well as non alcoholic beverages in restaurants. The tourism departmental has proposed some new projects like development of the tourism jetty and parking lot at Panaji, Paryatan Bhavan at Patto Panaji, beach safety management system in the form of up gradation of access of tourist International Journal of Research in IT, Management and Engineering www.gjmr.org 192
- 194. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 destination in the state, development of eco-tourism project for state of goa, capacity building organization of workshops/seminars/training programmes etc for improvement of tourism manpower. The above infrastructure development projects have been processed for central financial assistance to the tune of Rs. 7182.66 lakh with state component of Rs. 961.34 lakh. Since it is decided to utilize proposed land for golf course at betul for food and park auxiliary, town and country planning department has been requested to suggest suitable site for setting up of golf course in the state. Development of infrastructure facilities, beautification of important tourist destinations, improvement of roads in tourism circuit, appointment of more life guards and improvement of different safety measures have been continuing in order to improve services to the tourists visiting the state. Department of tourism has already entrusted the work to a competent organization “M/s Drishthi special Response Service, Pvt Ltd, Mumbai”. Special Tourist Security force named as Tourist Security Organisation is proposed to be formulated in order to provide additional protection and guidance to the tourists visiting the state. Goa Heritage Tourism Scheme has been formulated which is approved by the Government and is being implemented. The objective of this scheme is to restore and maintain ancestral houses of goa by giving financial assistance with subsidy to the interested parties. In order to promote eco- tourism, the Forest Department has been idenfied as nodal agency. TOURISM MARKETING AND PROMOTION Tourism has become a highly competitive industry. The department of tourism has strengthened its marketing strategy by envisaging various publicity measures viz organizing road shows, advertising through print and electronic media, participating in various travels marts. The department of tourism participated in travel related overseas events like, road show at Durban and cape town in south Africa, Leisure-08 at Moscow, WTM-2008 at London and domestic events in India, like TTF at Jamshedpur, TTF at Hyderabad, TT F at Ahmadabad, ITM at Jaipur, Rajasthan, TTE at Chennai, Discovery India. The Department also organized Explore the Incredible State in Mumbai in coordination with Goa Tourism Corporation, Goa. Some festivals are organized at state level to attract the domestic as well as foreign tourists such as carnival, International Journal of Research in IT, Management and Engineering www.gjmr.org 193
- 195. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Shigmotsav, Saraswat food festival, wine festival etc. Fund for organizing these festivals are provided by Tourism Department in order to promote tourism. REVIEW OF LITERATURE The Consulting Engineering Services (I) Ltd. New Delhi in his Tourism Master Plan: Goa – 2011 Final Report February 2001 has carefully studied views expressed by the Goa Chamber of Commerce & Industry. GCCI have stressed on creation of facilities in order to sustain growth of tourism in Goa. Abhinav K. Raina Director, Centre for Tourists and Heritage Research Dayanand College, Ajmer in his presentation in the 3rd Bi-annual referred international journal held on 23/01/2011 topic entitle “Development of Health Tourism services – A Study” stated that there is a need for a training in the field of medical facilities in order to further boost tourism industry. Tourism in Goa: A perspective (Collection of Domestic Tourism Statistics for the State of Goa) in their survey report highlighted that almost 42.05% of the domestic tourist and 43.2% of foreign tourist rated local transport services as good, with 12.1% and 10.8% respectively, rating it as poor. 14.32% of domestic and 12.9% foreign tourists, reported the accommodation units as excellent while 10.57% of domestic and 6.7% foreign tourists rated it as poor. 36.79% foreign tourists and 35.1% domestic tourists rated quality of entertainment facilities as excellent. Almost 40.71% of domestic tourists and 42.1% foreign tourists rated the tourist attractions in Goa as “Very Good”. Almost 61.3% of domestic tourists and 59.8% of foreign tourists rated shopping facilities as adequate. RESEARCH OBJECTIVES 1. To study and analysis of trends of tourist arrivals in goa. 2. To study and analysis of trends of arrivals of foreign charter flights. 3. To ascertain the relationship between arrival of tourist with expenditure plan. Hypothesis There is a significant relationship between arrivals of tourist with revenue and capital outlay on tourism. (Expenditure plan) RESEARCH METHODOLOGY International Journal of Research in IT, Management and Engineering www.gjmr.org 194
- 196. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 The study is based on secondary data conducted in the state of goa. Data is collected from Govt of Goa Department of tourism. Secondary data also has been collected by referring to various journals, published and unpublished texts, books, reports, newspapers and net. Data analysis was carried out by using the statistical program packages SPSS. The other statistical techniques used for data analysis is percentage change method. In order to know the aforementioned hypothesis, expenditure plan and arrivals of tourists from the period 2000-01 to 2010-11 has been considered. I TREND ANALYSIS OF TOURIST ARRIVALS IN GOA Growth of tourism in Goa has been phenomenal. Growth of tourism has led to economic growth, improved infrastructure and quality of life. Construction boom has led to increased urbanization. Changes in pattern of livelihood and socio cultural changes have also occurred. People from different parts of the country has come and settled in Goa in search of livelihood. There is also a large expatriate community who come to enjoy the beauty of the land of sun and sea. Rapid changes in economy, society and culture have led to greater inclination among the people to earn quick money along with increased Westernization and growth in consumerism. Eco Tourism has been promoted to develop the Hinterland, so that people living in these areas can reap the benefits of tourism. Express ways are envisaged in an effort to shorten distances between either extremities of the State, and these expressways will be connected to the golden quadrilateral. Beach-life safety programme implemented successfully is probably the first of its kind project in the country. Table – I Trends showing number of tourist arrivals in goa Year Domestic Foreign Total % Change 1985 682545 92667 775212 - 1986 736548 97533 834081 7.6 1987 766846 94602 861448 3.3 1988 761859 93076 854935 -0.7 1989 771013 91430 862443 0.9 1990 776993 104330 881323 2.2 1991 756786 78281 835067 -5.6 International Journal of Research in IT, Management and Engineering www.gjmr.org 195
- 197. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 1992 774568 121442 896010 7.3 1993 798576 170658 969234 8.2 1994 849404 210191 1059595 9.3 1995 878487 229218 1107705 4.5 1996 888914 237216 1126130 1.7 1997 928925 261673 1190598 5.7 1998 953212 275047 1228259 3.2 1999 960114 284298 1244412 1.3 2000 976804 291709 1268513 1.9 2001 1120242 260071 1380313 8.8 2002 1325296 271645 1596941 15.7 2003 1725140 314357 2039497 27 .7 2004 2085729 363230 2448959 20.1 2005 1965343 336803 2302146 -6.0 2006 2098654 380414 2479068 7.7 2007 2208986 388457 2597443 4.8 2008 2020416 351123 2371539 -8.7 2009 2127063 376640 2503703 5.5 Economic survey 2008-09 International Journal of Research in IT, Management and Engineering www.gjmr.org 196
- 198. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Figure – I Chart showing number of tourist arrivals in Goa 3000000 2500000 2000000 1500000 DOMESTIC FOREIGN 1000000 TOTAL % CHANGE 500000 0 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 ‐500000 The share of domestic overnight visitors was 84.50% & foreign overnight visitors were 15.50% in the total overnight visitors in the state. Total domestic tourist estimated was 18.99 lakh, International Journal of Research in IT, Management and Engineering www.gjmr.org 197
- 199. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 foreign tourists 3.48 lakh, and total tourists 22.47 lakh. Estimated day tourists are 2.42 lakh and total tourists & day tourists combined is estimated to 24.89 lakh. During the years from 1990 to 1998, the share of foreign tourists as share of total tourists visiting goa has considerably increased from 11.83 per cent in 1990 to 22.39 per cent in 1998. This is significantly higher than the normal trend of about 3.37 per cent (1997) of foreign tourists observed in India. In between the year 1991 has seen a drastic fall in the arrival of foreign tourists which may be attributed to unstable socio-political situation in the country. As per the Tourism Department, in the year 2008, 2020416 domestic tourists’ and 351123 foreign tourists, whereas, in 2009, 2127063 domestic tourists and 376640 foreign visited Goa. As per Economic Survey released by the Government, contribution of tourism is 33 percent of the total GDP. The growth of tourist in Goa is due various reasons. Place of tourist interest are so numerous and of varied nature that it is not easy to describe these places comprehensively. In general the tourist spots of Goa are counted more like, Shrines, Forts, places of historical importance, springs, lakes and birds, sanctuaries, religious centers, science spots, sea beaches, summer resorts, waterfalls and wild lives etc. Goa has been one of the major tourist destinations in India for foreign visitors. Its share is around 11 per cent of the total foreigners visiting the country. II TREND ANALYSIS OF ARRIVALS OF FOREIGN CHARTER FLIGHTS Table –II Trends showing arrivals by foreign charter flights Year Number of flights Passengers 2000-01 419 116992 2001-02 279 76410 2002-03 384 94350 2003-04 523 126255 2004-05 690 158993 2005-06 719 180310 2006-07 720 169836 2007-08 710 175951 2008-09 615 145428 International Journal of Research in IT, Management and Engineering www.gjmr.org 198
- 200. IJRIME E Volum me1Issue5 ISSN‐ ‐2249‐ 16 619 Econom survey 2008-09 mic Figure II Chart sho I owing arriva by foreig charter f als gn flights 200000 180000 160000 140000 120000 100000 80000 NUMBER OF FLIGHTS 60000 PASSENG GERS 40000 20000 0 On accou of aggre unt essive media campaign undertaken by the Depa a artment, the actual tour in e rist flow to t state has reached to more than 2.60 million marks for the calenda year 2007 To the s o n r ar 7. cater to i increased tou urist traffic i flow, the h in hotel bed ca apacity has g gone up to 42 2145 for the year e 2008. During t tourist seaso 2007-200 710 char flights h on 08, rter have brough in 175951 tourists an 48 ht 1 nd condor F Flights has brought in 10043 tourist During t current s b ts. the season 2008-09, 615 Ch harter Flights in ncluding Con ndor Flights has brought in 145428 foreign touri t ists’ to the S State. In spite o the adver effect of terrorist att of rse f tack in Mum mbai and int ternational m market reces ssion, there wa good resp as ponse from tourists vis siting Goa. Arrivals of foreign tou f urists as we as ell domestic tourists rea c ached to 388 8457 and 220 08986 respectively, for t year 200 and durin the the 07 ng year 200 351123 foreign and 2020416 do 08, f omestic tou urist visited the state. The state rec ceives Inter rnational Jour rnal of Resear rch in IT, Man nagement and d Engineering g www.gjmr.org 199
- 201. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 tourists from more than 25 different countries including UK, Germany, Sweden, Switzerland, Finland, Russia, etc. About 39% of the tourists came from UK followed by Russia, Germany, Finland and France. III THE RELATIONSHIP BETWEEN ARRIVAL OF TOURIST WITH EXPENDITURE PLAN Data was tabulated in Microsoft Excel Sheet and the data edited, coded and verified for validity. The data was analyzed using statistical package for social sciences software. Table III showing the arrival of tourists and expenditure plan for the year 2000-01 to 2010- 11 year Tourist(y) Revenue(x1) Capital(x2) 2000-2001 1268513 2.2 4 2001-2002 1380313 5.3 7 2002-2003 1596941 13 6 2003-2004 2039497 7 0.0033 2004-2005 2448959 4.3 1 2005-2006 23021146 24 2 2006-2007 2479068 7.23 1 2007-2008 2597443 5 2 2008-2009 2020416 0.26 0 2009-2010 2127063 10 24 2010-2011 21123000 7.2 8 Source: Department of tourism, Govt. of Goa. Note: Compilation of secondary data International Journal of Research in IT, Management and Engineering www.gjmr.org 200
- 202. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table IV: Pearson Correlations between tourist and capital tourist capital Variables tourist Pearson 1 -0.158 Correlation Sig. (2-tailed) 0.644 N 11 11 capital Pearson -0.158 1 Correlation Sig. (2-tailed) 0.644 N 11 11 The result of Table I shows that there is (- 0.158) negative insignificant correlation between the tourist and capital. International Journal of Research in IT, Management and Engineering www.gjmr.org 201
- 203. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Table V: Pearson Correlations between capital and revenue capital revenue Variables capital Pearson 1 0.144 Correlation Sig. (2-tailed) 0.673 N 11 11 revenue Pearson 0.144 1 Correlation Sig. (2-tailed) 0.673 N 11 11 The result of Table II shows that there is (+0.144) positive insignificant correlation between the capital and revenue. Table VI: Pearson Correlations between revenue and tourist revenue Tourist variables International Journal of Research in IT, Management and Engineering www.gjmr.org 202
- 204. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 revenue Pearson 1 0.174 Correlation Sig. (2-tailed) 0.609 N 11 11 tourist Pearson 0.174 1 Correlation Sig. (2-tailed) 0.609 N 11 11 The result of Table III shows that there is (+0.174) positive insignificant correlation between the tourist and revenue. Table VII: Model Summary of the Regression of arrival of tourist and capital and revenue Adjusted R Std. Error of the R R Square Square Estimate Model 1 0.254(a) 0.064 -0.170 481324.74843 1. Predictors: (Constant), revenue, capital Table IX Multiple Regression Analysis of Expenditure plan Coefficient (a) Unstandardized Standardized Coefficients Coefficients Std. Variables B Error Beta t Sig. (Constant) 1986566.0 249673. 7.957 0.000 International Journal of Research in IT, Management and Engineering www.gjmr.org 203
- 205. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 16 080 capital - 22294.2 -0.186 -0.540 0.604 12028.573 41 revenue 24015.3 13951.539 0.201 0.581 0.577 97 Dependent Variable: tourist As seen from the table, revenue and capital have determined only 06 percent of the variance of tourist. In the regression model both are insignicant, capital and revenue are not the only factors which are influencing the tourists in Goa. There are other factors responsible for which the study has to be done. CONCLUSION Implications of the research are that capital and revenue are not the only factors which are influencing the tourists in Goa. The various factors that have contributed to this rise in domestic tourism in the country are: increased disposable income of the middle class; increased urbanization and stress of living in cities and towns; increased ownership of cars, which is making domestic tourism more attractive; especially among the upper-middle and middle classes; improved employment benefits, such as the leave travel concession; development of inexpensive mass transport and improved connections to various places of tourist interest; increased number of cheap accommodations and resorts, greater advertising targeted at domestic tourists both by the central and the state governments, as well as the tourist industry, and increasing of time-sharing in holiday spent, among the middle class. Government of Goa should introduce and enhance new tourism and existing activities i.e. adventure tourism, cultural heritage tourism, pilgrim tourism, business tourism, sports tourism, and education and health tourism. The existing facilities are not sufficient and should channelize way to identify infrastructure and other development needs for tourism. REFERENCES Books International Journal of Research in IT, Management and Engineering www.gjmr.org 204
- 206. IJRIME Volume1Issue5 ISSN‐2249‐ 1619 Batra G.S.and A.S Chawla (1995) Tourism Management: A Global Perspective, Deep and Deep Publications, New Delhi. Chawla R. (2005) Ecotourism Planning and Management, Sonali Publications, New Delhi. Chawla R. (2006) Responsible Tourism, Sonali Publications, New Delhi. Chawla R. (2006) Agri- Tourism, Sonali Publications, New Delhi. Magazines De Costa I. (2005) Need for a New Approach, Goa Today. De Souza R. (2006) Boosting State Tourism, Goa Today. De Costa I. (2005) Need for a New Approach, Goa Today. Report Tourist Statistics 2006-07, Department Of Tourism, Goa Tourism Master Plan: Goa – 2011 Final Report February 2001 Websites log on 18-07-2011 http://www.hindu.com http://www.goa-tourism.com www.gdrc.org www.ecoindia.com/sustainable-tourism www.du.ac.in/coursematerial/ba/tourism/Lesson21-23 banglanatak dot com research report –Goa.pdf (application/pdfobject) Websites log on 25-07-2011 http://tourism.visitcalifornia.com/Research/ www.mcos.com/Tourism_Industry.htm www.mcos.com/Healthcare_Industry.htm http://goacom.blogspot.com/2009/01/goa-beach-strip-of-paradise.html International Journal of Research in IT, Management and Engineering www.gjmr.org 205