November 2024: Top 10 Read Article in Computer Science, Engineering and Applications

November 2024: Top 10 Read Article in
Computer Science, Engineering and
Applications
International Journal of Computer Science, Engineering
and Applications (IJCSEA)
World Journal Clout Index (WJCI) Impact Factor : 0.071 (2019)
ISSN : 2230 - 9616 [Online] ; 2231 - 0088 [Print]
https://airccse.org/journal/ijcsea/index.html

DESIGN AND DEVELOPMENT OF AUTOMATIC WATER FLOW METER
Ria Sood1
, Manjit Kaur2
, Hemant Lenka3
1,2
Academic and Consultancy Services-Division Centre for Development of Advanced
Computing(C-DAC), Mohali, India
3
Digital Electronics and Communication Division (DECD) Centre for Development of
Advanced Computing(C-DAC), Mohali, India
ABSTRACT
Effective irrigation water management begins with timing and regulating irrigation water
application in a way that will satisfy the need of the crop without wasting water, soil and crop
nutrients. This involves supplying water according to the crop requirement, quantity that can
be held by the soil and is available to the crop at rates tolerated according to the soil
characteristics. So measuring water in fields is very essential step in irrigation management
systems. There are many water flow measurement techniques as well as different types of
water flow meters used in irrigation to measure the volume of water flow in pipelines but
these all are too costly. This paper describes design and development of low cost automatic
water flow meter which supplies only required amount of water to the crops saving water as
well as energy. G1/2 Hall Effect water flow sensor is used as a sensing unit with a turbine
rotor inside it whose speed of rotation changes with the different rate of flow of water. The
Hall Effect sensor outputs the corresponding pulse train for frequency input to the
microcontroller. The whole system comprises of AT89S52 microcontroller, G1/2 Hall Effect
water flow sensor, relay, optocoupler, a water pump, 5V supply, LCD, keypad and some
passive components. The AT89S52 microcontroller is programmed in Keil development
Tool.
KEYWORDS
Low cost sensor, Hall Effect sensor, rotation of rotor, flow rate of water, AT89S52
microcontroller, Keil software, Ultrasonic flow meter.
Full Text: https://airccse.org/journal/ijcsea/papers/3313ijcsea06.pdf
Volume URL: https://airccse.org/journal/ijcsea/current2013.html

DEALING CRISIS MANAGEMENT USING AI
Yew Kee Wong
School of Information Engineering, HuangHuai University, Henan, China
ABSTRACT
Artificial intelligence has been a buzz word that is impacting every industry in the world.
With the rise of such advanced technology, there will be always a question regarding its
impact on our social life, environment and economy thus impacting all efforts exerted
towards sustainable development. In the information era, enormous amounts of data have
become available on hand to decision makers. Big data refers to datasets that are not only big,
but also high in variety and velocity, which makes them difficult to handle using traditional
tools and techniques. Due to the rapid growth of such data, solutions need to be studied and
provided in order to handle and extract value and knowledge from these datasets for different
industries and business operations. Numerous use cases have shown that AI can ensure an
effective supply of information to citizens, users and customers in times of crisis. This paper
aims to analyse some of the different methods and scenario which can be applied to AI and
big data, as well as the opportunities provided by the application in various business
operations and crisis management domains.
KEYWORDS
Artificial Intelligence, Big Data, Business Operations, Crisis Management

LINEAR SEARCH VERSUS BINARY SEARCH: A STATISTICAL COMPARISON
FOR BINOMIAL INPUTS
Anchala Kumari1
, Rama Tripathi2
, Mita Pal3
and Soubhik Chakraborty4
*
1
University Department of Statistics, Patna University, Patna-800005, India
2
Department of Information Technology, BIT Mesra, Ranchi-835215, India
3, 4
Department of Applied Mathematics, BIT Mesra, Ranchi-835215, India
*corresponding author’s email: soubhikc@yahoo.co.in (S. Chakraborty)
ABSTRACT
For certain algorithms such as sorting and searching, the parameters of the input probability
distribution, in addition to the size of the input, have been found to influence the complexity
of the underlying algorithm. The present paper makes a statistical comparative study on
parameterized complexity between linear and binary search algorithms for binomial inputs.
KEY WORDS
Linear search; binary search; parameterized complexity; statistics; factorial experiments

PROPOSAL OF A TWO WAY SORTING ALGORITHM AND PERFORMANCE
COMPARISON WITH EXISTING ALGORITHMS
Eshan Kapur1
, Parveen Kumar2
and Sahil Gupta3
Department of Computer Science, Lovely Professional University, Phagwara, Punjab
ABSTRACT
An algorithm is any well-defined procedure or set of instructions, that takes some input in the
form of some values, processes them and gives some values as output. Sorting involves
rearranging information into either ascending or descending order. Sorting is considered as a
fundamental operation in computer science as it is used as an intermediate step in many
operations. A new sorting algorithm namely ‘An Endto-End Bi-directional Sorting (EEBS)
Algorithm’ is proposed to address the shortcomings of the current popular sorting algorithms.
The goal of this research is to perform an extensive empirical analysis of the newly
developed algorithm and present its functionality. The results of the analysis proved that
EEBS is much more efficient than the other algorithms having O(n2 ) complexity, like
bubble, selection and insertion sort.
KEYWORDS
End-to-End Bi-directional sort (EEBS), algorithms, selection sort, bubble sort, insertion sort.
Full Text: http://airccse.org/journal/ijcsea/papers/2312ijcsea06.pdf

CLASSIFICATION OF ECG ARRHYTHMIAS USING DISCRETE WAVELET
TRANSFORM AND NEURAL NETWORKS
Maedeh Kiani Sarkaleh and Asadollah Shahbahrami
Department of Computer Engineering, Faculty of Engineering P.O.Box: 3756-41635
University of Guilan, Rasht, Iran
ABSTRACT
Automatic recognition of cardiac arrhythmias is important for diagnosis of cardiac
abnormalies. Several algorithms have been proposed to classify ECG arrhythmias; however,
they cannot perform very well. Therefore, in this paper, an expert system for
ElectroCardioGram (ECG) arrhythmia classification is proposed. Discrete wavelet transform
is used for processing ECG recordings, and extracting some features, and the Multi-Layer
Perceptron (MLP) neural network performs the classification task. Two types of arrhythmias
can be detected by the proposed system. Some recordings of the MIT-BIH arrhythmias
database have been used for training and testing our neural network based classifier. The
simulation results show that the classification accuracy of our algorithm is 96.5% using 10
files including normal and two arrhythmias.
KEYWORDS
ECG, Arrhythmia, Daubechies Wavelets, Discrete Wavelet Transform (DWT), Neural
Network (NN).

DESIGN AND DEVELOPMENT OF CALIBRATION UNIT FOR PRECISION
PLANTER
Tejminder Kaur 1 , Dilip Kumar2
1,2Academic and Consultancy Services-Division Centre for Development of Advanced
Computing(C-DAC), Mohali, India
ABSTRACT
The critical parameters for plant population with desired planting geometry include uniform
distribution and precision placement of seeds. R&D efforts in metering of single seeds at
predetermined intervals are carried in this paper. Proximity sensor technique based seed
spacing evaluation system that measure time intervals between seeds and transmission ratio
between two velocities is use to determine planter seed spacing uniformity. The calibration
unit includes frame light barrier sensor that consists of square crosssection window including
transmitter and receiver with innovative microcontroller technology in its casing along with
the inductive type gear tooth sensor that calculates rpm of roller. For acquiring the data
serially to personal computer the system includes circuitry to interface the sensors with the
AT89S52 microcontroller. Mechanical mechanism of motor/roller/ SMU is controlled using
V/F drive through PC itself. Calibration of whole system is based on ISO defined standard
parameters that are Quality of feed index, multiple index and Miss index. This calibration
unit can be used instead of grease belt stand to rapidly obtain quantitative evaluations of
planter seed spacing uniformity in the laboratory.
KEYWORDS
Frame light barrier sensor, gear tooth sensor, SMU, 1 hp AC motor, Yaskawa J1000 AC
drive, RS232 and USB communication.

ANALYSIS OF EMOTION DISORDERS BASED ON EEG SIGNALS OF HUMAN
BRAIN
Ashish Panat1
and Anita Patil2
1
Priyadarshini Indira College of Engineering
2
Department of Electronics & Telecommunication, Cummins College of Engineering for
Women, Pune.
ABSTRACT
In this research, the emotions and the patterns of EEG signals of human brain are studied.
The aim of this research is to study the analysis of the changes in the brain signals in the
domain of different emotions. The observations can be analysed for its utility in the diagnosis
of psychosomatic disorders like anxiety and depression in economical way with higher
precision.
KEYWORDS
EEG, EDF format, Feature extraction, Image classifiers, Emotions, Psychosomatic disorders,
Normal and excited brain, Anxiety and Depression.

CLASSICAL DISCRETE-TIME FOURIER TRANSFORMBASED CHANNEL
ESTIMATION FOR MIMO-OFDM SYSTEMS IN VEHICULAR
COMMUNICATIONS TECHNOLOGY
Mohammad Reza KaghazGaran1
, Afsaneh KaghazGaran2
ABSTRACT
In this document, we look at various time domain channel estimation methods with this
constraint of null carriers at spectrumborders.We showin detail howto gauge the importance
of the “border effect” depending on the number of null carriers, which may vary from one
system to another. Thereby we assess the limit of the technique discussed when the number
of null carriers is large. Finally the DFT with the truncated singular value decomposition
(SVD) technique is proposed to completely eliminate the impact of the null subcarriers
whatever their number. A technique for the determination of the truncation threshold for any
MIMO-OFDM system is also proposed.
KEYWORD
Singular Value Decomposition,Discrete-Time Fourier Transform
Volume URL: https://airccse.org/journal/ijcsea/current.html

WORD AND SENTENCE LEVEL EMOTION ANALYZATION IN TELUGU BLOG
AND NEWS
Sadanandam. Manchala1 , D. Chandra Mohan2 and A. Nagesh3
1 Assistant professor of CSE KUCE&T, Kakatiya University Campus (KU) Warangal,
Andhra Pradesh, India.
2Assistant professor of CSE Matrix Institute of Technology&Engg., Hyderbadad,
3Assoc. Professor of CSE Mahatma Gandhi Institute of Technology Hyderabad ,
ABSTRACT:
Emotion analysis, a recent sub discipline at the crossroads of information retrieval and
computational linguistics is becoming increasingly important from application viewpoints of
affective computing.Emotion is crucial to identify as it is not open to any objective
observation or verification. In this paper, emotion analysis on blog texts has been carried out
for a less privileged language, Telugu and the same system has been applied on the English
SemEval 2007 affect sensing corpus containing only news headlines. A set of six emotion
tags, namely, happy ( ), sad ( ), anger ( ), fear ( ), surprise ( )and disgust ( ), have been
selected towards this emotion detection task for reliable and semi-automatic annotation of
blog and news data. Conditional Random Field (CRF) based classifier has been applied for
recognizing six basic emotion tags for different words of a sentence. The classifier accuracy
has been improved by arranging an equal distribution of emotional tags and non-emotional
tag. A score based technique has been adopted to calculate and assign tag weights to each of
the six emotion tags. A sense based scoring strategy has been applied to identify sentence
level emotion scores for the six emotion tags based on the acquired word level emotion tags.
Sentence level emotion tagging has been carried out based on the maximum obtained
sentence level emotion scores. Evaluation has been conducted for each emotion class
separately on 200 test sentences from each of the Telugu blog and English news data. The
system has resulted accuracies of 69.82% and 71.06% for happy, 70.24% and 66.42% for sad,
65.73% and 64.27% for anger, 76.01% and 69.90% for disgust, 72.19% and 73.59% for fear
and 70.54% and 66.64% for surprise emotion classes on blog and news test data respectively.
KEYWORDS:
SentiWordNet, Blog, News, Emotion, CRF, Emotion tag, happy, sad, anger, fear, disgust,
surprise

BASIC ANALYSIS ON PROSODIC FEATURES IN EMOTIONAL SPEECH
X.Arputha Rathina[1], K.M.Mehata[1], M.Ponnavaikko[2]
[1] Department of Computer Science and Engineering, B.S.Abdur Rahman University,
Vandalur, Chennai, India.
[2] SRM University, Kattankulathur, Chennai, India.
ABSTRACT
Speech is a rich source of information which gives not only about what a speaker says, but
also about what the speaker’s attitude is toward the listener and toward the topic under
discussion—as well as the speaker’s own current state of mind. Recently increasing attention
has been directed to the study of the emotional content of speech signals, and hence, many
systems have been proposed to identify the emotional content of a spoken utterance.
The focus of this research work is to enhance man machine interface by focusing on user’s
speech emotion. This paper gives the results of the basic analysis on prosodic features and
also compares the prosodic features of, various types and degrees of emotional expressions in
Tamil speech based on the auditory impressions between the two genders of speakers as well
as listeners. The speech samples consist of “neutral” speech as well as speech with three
types of emotions (“anger”, “joy”, and “sadness”) of three degrees (“light”, “medium”, and
“strong”). A listening test is also being conducted using 300 speech samples uttered by
students at the ages of 19 -22 the ages of 19-22 years old. The features of prosodic parameters
based on the emotional speech classified according to the auditory impressions of the subjects
are analyzed. Analysis results suggest that prosodic features that identify their emotions and
degrees are not only speakers’ gender dependent, but also listeners’ gender dependent.

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