cs usm triz slide-proposed
TRANSCRIPT
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MyTRIZ Competition 2012Proposal Team:
CS Aisyah Ismail
Azleena Mohd KassimMohd Adib Omar (Group Leader)
Tan Choo JunWan Mohd Nazmee Wan Zainon
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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
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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.
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TRIZ Process, TRIZ Tools & Potential Solutions
Problem Insufficient Awareness and Wrong Perception on ICT Career
Insufficient ICT Teachers
Computing Major is not as attractive as Medicine, Engineering,
Accounting and Pharmacy among best students
Minimal entry requirement
No cap on the student limit per intake
Many unemployed due to skill
mismatch
Stages of Educational Process
Primary and Secondary
Education
input Pre-University
Matriculation
Diploma
Form Six (STPM)
input University input Industry
Government
Further Study
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’
20. Continuity of Useful Action
19. Periodic Action
23. Feedback
Proposed Solutions 9. Cultivate Problem Solving Culture
9. National Computing Competition
9. Awareness Program: ICT camp
9. Increase ICT Teachers
10. Cultivate Algorithmic Thinking
10. Standardized and up-to-date ICT Curriculum
13. Stringent entry requirements
13. Limit intake to ensure quality
20. Industrial Training & Internships
19. Periodic Retraining the
unemployed for certification
23. Formation of ICT Professional body to monitor the best practices, curriculum and prestige
Expected Outcome inculcate the right perception to students about Careers in ICT Students who are interested in ICT are prepared for university
education
Committed students
Quality ICT Program Employable graduates by the
industry
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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.
Pipe (with water) to transport wood material
example of wood material
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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
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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
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Potential Solutions
• Cover the wood based materials with bubble wrap and then transport them through the pipe.
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Part 3:
Enhancing the FAM Learning Mechanism
using Evolutionary-based TRIZ S-Curve Model
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The Scope ofTRIZ 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
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Do you see the their differential?
FAM
Fuzzy Set ARTMAP
ART-1 ART-2
Supervised
Learning
Model
Unsupervised
Learning
Model
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The Fuzzy ARTMAP (FAM)
FAM (same as ART and ARTMAP) consists of
Training Phase Prediction Phaseand
Note:They also called as Training Model and Prediction Model
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The FAM Architecture
Nodes are created when sensation and expectation does not exceed the vigilance value
Training weights (knowledge) are kept for Prediction Phase activities
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.
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The Optimization Dilemma and FAM
• The accumulated knowledge of FAM in Optimization Dilemma
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The TRIZ-basedEvolutionary S-Curve
• The metrics of TRIZ’s Evolutionary S-Curve
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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
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The USM Extract
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The form of USM Extract Implementation with MDG
• The flow of
• Web Application Instance
The flow of
API Implementation
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The Case Study of Our Model
Prediction Phase result for Diabetes patient
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Thank you