Contents
Contributors
Preface

1. Parallel Optimization for Intelligent Systems: Principles and New Results

1.1. Introduction
1.2. Related Work
1.3. Basic Idea of the Self-Optimization Algorithm
1.3.1. No Optimization
1.3.2. Load Optimization
1.3.3. Trust Optimization
1.3.4. Trust and Load Optimization
1.4. Metrics and Notions
1.5. The Algorithm in Detail
1.5.1. No Optimization
1.5.2. Load Optimization
1.5.3. Trust Optimization
1.5.4. Trust and Load Optimization
1.6. Multiple Simultaneous Requests
1.6.1. Selective Request Handling
1.6.2. Parallel Request Handling
1.7. Evaluation
1.7.1. Results Regarding the Rating Function Fworkload
1.7.2. Results Regarding the Rating Function Ftrust
1.7.3. Basic Algorithm vs. Extensions
1.7.4. Different Network Settings
1.8. Conclusions and Future Work
References

2. Task Mapping in Heterogeneous NoC by Means of Population-Based Incremental Learning

2.1. Introduction
2.2. The Population-Based Incremental Learning (PBIL) Algorithm
2.3. Experimental Results
2.4. Concluding Remarks
Acknowledgements
References

3. From Static to Dynamic: A New Methodology for Development of Simulation Applications

3.1. Introduction
3.2. Methodology of Dynamic Simulation
3.3. Underground Mine Ventilation Systems as Objects of Dynamic Simulation
3.3.1. General Overview
3.3.2. Exemplary Models
3.4. Implementation with PHANTOM Framework
3.5. Conclusions
Acknowledgements
References

4. Improvement of the Calibration Uncertainty for Class E1 Weights Using an Adaptive Subdivision Method on an Automatic Mass Comparator

4.1. Introduction
4.2. Equipment and Standards used in Calibration
4.2.1. Some Aspects Regarding the Kilogram “Ni81”
4.2.2. The Weights Involved in Calibration
4.2.3. Precision (or Imprecision) of the Balance
4.3. Mass Determination of Reference Disc Weights Used as Check Standards in the Calibration of E1 Weights
4.3.1. Measurement Matrix Design
4.3.2. Estimated Mass Values for Disc Weights
4.4. Statistical Tools for Evaluation of the Measurement Process and Mass Determination of Class E1 Weights
4.4.1. Method Used to Evaluate the Efficiency of the Weighing Design
4.4.2. Mass Results Obtained in the Calibration of Weights
4.5. Analysis of Uncertainties
4.5.1. Uncertainty of the Weighing Process, uA
4.5.2. Type B Uncertainty
4.5.3. Combined Standard Uncertainty, uc
4.5.4. Expanded Uncertainty
4.6. Quality Assessment of the Calibration
4.7. Conclusions
References

5. RH Control Developments for Applied Uncertainty Management in Industrial Processes

5.1. Introduction
5.2. Safety and Security
5.2.1. Safety and Security Technologies
5.2.2. Emergency Shut Down Systems
5.2.3. Fire and Gas (F&G) Detection and Alarm Systems
5.2.4. Burner Management Systems
5.3. RH Control the New Level of Decision
5.3.1. Generalities
5.3.2. RH Control – the New Challenge
5.3.3. Control and Strategy
5.3.4. Reusability
5.3.5. Software Architecture
5.4. Emerging Technologies
5.4.1. Simulation Technologies
5.4.2. Developed Computer Networks
5.4.3. Intelligent I/O Interfaces
5.4.4. High Speed Simulators
5.4.5. The Systems Modeling and Simulating with Discrete or Hybrid Events
5.4.6. On Line Testing and Diagnosis
5.4.7. Asset Management
5.5. System Development Methodologies and Techniques
5.5.1. System Engineering
5.5.2. Extended V Model for Uncertainty Control Development
5.5.3. Architecting Systems
5.6. Concurrent Engineering
5.7. Applying Uncertainty Management Principles for System Architecture Design
5.7.1. A Framework for Control System Architecture Design
5.7.2. A Holonic Architecture for Plant Wide Control
5.7.3. Integrated Architecture for Real-time Control and Uncertainty Management
5.8. Results and Discussion
5.8.1. Evaluation of the Response Time for Uncertainty Control
5.8.2. Methods for Response Elaboration
5.8.3. Developed Platforms and Case Studies
5.9. Conclusions
References

6. A Slow-growing Hierarchy of Time-bounded Programs

6.1. Introduction
6.2. Basic Instructions and Definition Schemes
6.2.1. Recursion-free Programs and Class T0
6.2.2. Safe Recursion and Class T1
6.3. Computation by Register Machines
6.4. The Time Hierarchy
6.5. Extending the Polynomial-Time Hierarchy to Transfinite
6.5.1. Structured Ordinals and Hierarchies
6.5.2. Diagonalization and Transfinite Hierarchy
6.6. The Time-Space Hierarchy
6.6.1. Recursion-free Programs and Class S0
6.6.2. Safe Recursion and Class S1
6.7. Conclusions and Further Work
References

7. Games as Actors: Interaction, Play, Design and Actor Network Theory

7.1. Introduction
7.2. Actor Network Theory
7.2.1. The Traffic Example
7.2.2. Translation
7.2.3. Design as Inscription
7.3. Research Methodology
7.4. Case: The Game “Quackle”
7.4.1. Quackle! Explained
7.4.2. Game Inscription
7.4.3. Translation
7.4.4. What the Game Does
7.5. Playing a Computer Game
7.6. Theory of Play and Games
7.7. Exergames
7.8. Design Implications
7.9. A Word on Scripts
7.10. Conclusion and Future Work
References

8. Multiscale Modelling and Simulation of Fiber-Reinforced Plastics Under Impact Loading

8.1. Introduction
8.2. State-of-the-Art
8.3. Methods of Space Discretization
8.4. Ballistic Trials
8.5. Numerical Simulation
8.5.1. Modelling
8.5.2. Simulation Results
8.5.3. Further Validations
8.6. Conclusions
References

9. How to Improve Driving Perception on an Advanced Dynamic Simulator While Cornering

9.1. Introduction
9.2. Methods
9.2.1. Participants
9.2.2. Experimental Devices
9.2.3. Experimental Scenario
9.2.4. Task
9.2.5. Experimental Design
9.2.6. Data Analysis
9.3. Results
9.3.1. Subjective Analysis
9.3.1.1. Simulator Sickness
9.3.1.2. Realism of Vehicle Behaviour
9.3.1.3. Ease of the Task
9.3.2. Objective Analysis
9.3.2.1. Steering Wheel Reversal Rate
9.3.2.2. Lateral Deviation from the Reference Trajectory
9.4. Discussion of Results
9.4.1. Motion Gains
9.4.1.1. Motion Realism
9.4.1.2. Ease of the Task and Objective Variables
9.5. Conclusion
References

10. Step Climbing Strategy for a Wheelchair

10.1. Introduction
10.1.1. Wheelchair
10.1.2. Related Research of Wheelchair Step Climbing
10.1.3. Purpose of This Chapter
10.2. Theoretical Analysis of Step Climbing for a Wheelchair
10.2.1. Generating the Driving Force to Lift the Front Wheels (Requirement (1))
10.2.2. Avoidance from Tipping over Backward (Requirements (2), (3))
10.2.3. Generating the Driving Force to Lift the Rear Wheels (Requirement (4))
10.2.4. Result of Simulations
10.3. Cooperative Step Climbing Using a Wheelchair and a Robot
10.3.1. Cooperative Step Climbing System
10.3.2. Process of Moving Over a Step
10.4. Theoretical Analysis of Cooperative Step Climbing Using the Wheelchair and the Robot
10.4.1. Requirement of the Manipulator Angles to Avoid Collision and to Grasp the Push Handle
10.4.2. Requirement to Exert Enough Driving Force on the Ground to Climb a Step
10.4.3. Theoretical Analysis of Cooperative Step Climbing Using the Wheelchair and the Robot
10.4.4. Simulation
10.5. Experiment of Cooperative Step Climbing
10.6. Conclusions
Acknowledgments
References

Index