CS USM TRIZ Slide-proposed
- 1. MyTRIZ Competition 2012 Proposal Team: CS Aisyah Ismail Azleena Mohd Kassim Mohd Adib Omar (Group Leader) Tan Choo Jun Wan Mohd Nazmee Wan Zainon
- 2. Contents • Part 1 • Question (a) • Impact: The country will have sustainable skilled and qualified ICT workers needed for the future. • Part 2 • Impact: The wood materials are transported without damaging the pipe. • Part 3 • Impact: Enhancing the FAM Learning Mechanism using Evolutionary-based TRIZ S-Curve Model
- 3. Part 1: Problem Analysis • Shortage of skilled ICT graduates • Why? Because current Institute of Higher Learning (IPT/IPTA) is unable to produce sufficient "skilled" graduates • Why? Because good students tend to choose other fields, e.g. Medicine, Dentistry & Pharmacy etc. • Why? Students believe that career in ICT does not provide good pay and job satisfaction • Why? Misperceptions that ICT field does not provide better pay, low jobs satisfaction and lacks of jobs opportunities.
- 4. TRIZ Process, TRIZ Tools & Potential Solutions Insufficient Awareness and Wrong Perception on ICT Career Computing Major is not as attractive as Medicine, Minimal entry requirement Many unemployed due to skill Problem Engineering, Accounting and Pharmacy among best students mismatch Insufficient ICT Teachers No cap on the student limit per intake Pre-University Industry Primary and Secondary input input University input Stages of Educational Matriculation Government Education Process Diploma Further Study Form Six (STPM) Entrepreneurship TRIZ Process and Tools Physical Contradiction by Separation in Time Physical Contradiction by Separation in Time Physical Contradiction by Separation in Space and Physical Contradiction by Separation in Time Physical Contradiction by Separation in System Level - Supersystem Inventive Principles 9. Preliminary anti-action 10. Preliminary action 13. ’The other way round’ 19. Periodic Action 20. Continuity of Useful Action 23. Feedback Proposed Solutions 9. Cultivate Problem Solving Culture 10. Cultivate Algorithmic Thinking 13. Stringent entry requirements 19. Periodic Retraining the unemployed for certification 9. National Computing Competition 10. Standardized and up-to-date ICT Curriculum 13. Limit intake to ensure quality 9. Awareness Program: ICT camp 20. Industrial Training & Internships 9. Increase ICT Teachers 23. Formation of ICT Professional body to monitor the best practices, curriculum and prestige Committed students Expected Outcome inculcate the right perception to students about Careers in Students who are interested in ICT are prepared for Employable graduates by the Quality ICT Program ICT university education industry
- 5. Part 2: Problem Statement • The 1-meter pipe leaks due to the rubbing and knocking of wood materials transported inside the pipe using water as a medium of transport. example of wood material Pipe (with water) to transport wood material
- 6. TRIZ process used Function Analysis: Pipe contains water and wood based materials Water holds the wood based materials inside the pipe Water flows with wood based materials through the pipe Identify the type of contradictions: Administrative contradictions: We want to allow the wood based materials to traverse through the pipe without damaging the pipe. Engineering contradictions: wood based material surface contact damages the pipe Physical Contradiction Solution Strategies: Separation in Space Inventive Principle: 30. Flexible Shells / Thin Films
- 7. TRIZ tools used • Contradiction Matrix cannot be used since we are dealing single parameter, in this case, the contact surface of wood based materials. • Instead, Physical Contradiction Solution Strategies: Separation in Space is used. It leads to the Inventive Principle: 30. Flexible Shells / Thin Films
- 8. Potential Solutions • Cover the wood based materials with bubble wrap and then transport them through the pipe.
- 9. Part 3: Enhancing the FAM Learning Mechanism using Evolutionary-based TRIZ S- Curve Model
- 10. The Scope of TRIZ Hybridization Model 1. A combination with a Pareto-based algorithm (MmGA) to undertaking the efficiency of learning process in FAM 2. An optimization of the number of nodes in FAM network without prior configuration towards Pareto Front solutions 3. An implementation of proposed model using USM Extract with Mobile Desktop Grid (MDG) in the form of web application and API level
- 11. Do you see the their differential? Unsupervised ART-1 ART-2 Learning Model Fuzzy Set ARTMAP Supervised Learning FAM Model
- 12. The Fuzzy ARTMAP (FAM) FAM (same as ART and ARTMAP) consists of Training Phase and Prediction Phase Note: They also called as Training Model and Prediction Model
- 13. The FAM Architecture Adapted from: G. A. Carpenter, S. Grossberg, N. Markuzon, J. H. Reynolds, and D. B. Rosen, “Fuzzy artmap: A neural network architecture for incremental su-pervised learning of analog multidimensional maps,” IEEE Transactions on Neural Networks, vol. 3, pp. 698–713, Sept. 1992. Nodes are created when sensation and expectation does not exceed the vigilance value Training weights (knowledge) are kept for Prediction Phase activities
- 14. The Optimization Dilemma and FAM • The accumulated knowledge of FAM in Optimization Dilemma
- 15. The TRIZ-based Evolutionary S-Curve • The metrics of TRIZ’s Evolutionary S- Curve
- 16. The FAM and TRIZ-based Evolutionary S- Curve • Metrics of determining the FAM's knowledge laying alone the TRIZ-based Evolutionary S-Curve 1. Performance 2. Number of Inventions 3. Level of Inventions 4. Profitability 5. Cost Reduction Related Inventions
- 17. The USM Extract
- 18. The form of USM Extract Implementation with MDG • The flow of The flow of • Web Application API Implementation Instance
- 19. The Case Study of Our Model Prediction Phase result for Diabetes patient
- 20. Thank you