Advances in Computational Algorithms and Data Analysis (Lecture Notes in Electrical Engineering)

Advances in Computational Algorithms and Data Analysis (Lecture Notes in Electrical Engineering)
By Sio-Iong Ao, Burghard Rieger, Su-Shing Chen

• Publisher: Springer
• Number Of Pages: 588
• Publication Date: 2008-10-09
• ISBN-10 / ASIN: 140208918X
• ISBN-13 / EAN: 9781402089183

Product Description:

Advances in Computational Algorithms and Data Analysis offers state of the art tremendous advances in computational algorithms and data analysis. The selected articles are representative in these subjects sitting on the top-end-high technologies. The volume serves as an excellent reference work for researchers and graduate students working on computational algorithms and data analysis.

Contents: :
Advances in Computational Algorithms and Data Analysis
Cover
Title Page
Copyright
Contents
Scaling Exponent for the Healthy and Diseased Heartbeat
1.1 Introduction
1.2 Procedure
1.2.1 DFA Methods: Background
1.2.2 DFA Methods
1.2.3 EKG and Finger Pulse
1.3 Results
1.4 Discussion
1.5 Concluding Remarks
CLUSTAG & WCLUSTAG: Hierarchical Clustering Algorithms for Efficient Tag-SNP Selection
2.1 Introduction
2.1.1 Methods for Selecting Tag SNPs
2.1.2 Motivations for Developing Non-block based Tagging Methods
2.2 CLUSTAG: How Tag SNPs are Selected Efficientl
2.2.1 Agglomerative Clustering
2.2.2 Clustering Algorithm with Minimax for Measuring Distances between Clusters, and Graph Algorithm
2.3 Experimental Results of CLUSTAG
2.4 WCLUSTAG: Motivations for Combining Functional
2.4.1 Constructions of the Asymmetric Distance Matrix for Clustering
2.4.2 Handling of the Additional Genomic Information
2.5 WCLUSTAG Experimental Genomic Results
2.6 Result Discussions
The Effects of Gene Recruitment on the Evolvability and Robustness of Pattern-Forming Gene Networks
3.1 Introduction
3.2 Methods and Approaches
3.2.1 The Segmentation Gene Network and its Modeling
3.2.2 Experimental Data for Fitting
3.2.3 GA to Simulate Evolution of Gene Networks
3.3 Results and Discussion
3.3.1 Point Mutations are Enough to Recruit New Genes
3.3.2 Addition and Subtraction of New Genes
3.3.3 Network Redundancy and Evolvability
3.3.4 Redundancy and Robustness of Gene Networks
3.4 Conclusions
Comprehensive Genetic Database of Expressed Sequence Tags for Coccolithophorids
4.1 Introduction
4.2 Relates Work
4.3 Planning
4.3.1 Technology Choice
4.3.2 Front-End Interface
4.3.3 Backend Engine
4.3.4 Database
4.4 Implementation
4.4.1 Database Schema
4.4.2 Front-End
4.4.3 Backend and Database
4.5 Future Work and Conclusion
Hybrid Intelligent Regressions with Neural Network and Fuzzy Clustering
5.1 Introduction
5.2 The Proposed Algorithm
5.2.1 Neural Network Regression Models
5.2.2 Fuzzy Clustering
5.2.3 Hybrid Neural Network and Fuzzy Clustering (NN-FC)
5.3 Experimental Results
5.4 Summary and Discussion
Design of DroDeASys (Drowsy Detection and Alarming System)
6.1 Introduction
6.2 Block Diagram
6.3 Phases of the System
6.3.1 Pre-processing
6.3.2 Processing
6.3.3 Post Processing
6.4 Samples Tested
6.5 Conclusion
The Calculation of Axisymmetric Duct Geometries for Incompressible Rotational Flow with Blockage Effects and Body Forces
7.1 Introduction
7.2 The Design Plane
7.3 The Numerical Algorithm in the Design Plane
7.4 Direct Solution of the Difference Equations
7.5 Axisymmetric Flow in the Presence of Body Forces
7.6 The Blockage Effect: Deriving the Additional Flow Equation
7.7 The Blockage Function k(x,y)
7.8 The Design Plane Counterparts
7.9 Downstream Conditions
7.10 Calculation Procedure
7.11 Prescription of Wall Geometries
7.12 Alternative Solution Using an Integral Formula
7.13 Iterative Solution
7.14 Conclusions
Fault Tolerant Cache Schemes
8.1 Introduction
8.2 Fault Tolerant Caches
8.2.1 Cache Block Disabling
8.2.2 Replacement Using Small Spare Cache
8.2.3 Programmable Decoder (PADded Cache)
8.3 Evaluation and Comparisons
8.3.1 Evaluations
8.3.2 Comparisons
8.4 Conclusion
Reversible Binary Coded Decimal Adders using Toffoli Gates
9.1 Introduction
9.2 BCD Adders
9.2.1 Conventional Decimal Adder
9.2.2 Quick Decimal Adder
9.2.3 Carry Select BCD Adder
9.3 Reversible Implementations Using Toffoli Gates
9.3.1 Reversible Conventional BCD Adder
9.3.2 Reversible QAD Adder
9.3.3 Reversible Carry Select BCD Adder
9.4 Conclusion and Future Work
Sparse Matrix Computational Techniques in Concept Decomposition Matrix Approximation
10.1 Introduction
10.2 Document Clustering and Concept Vectors
10.2.1 Document Clustering
10.2.2 Retrieval Procedure and Research Strategies
10.3 Approximate Least Squares Based Strategies
10.3.1 Computational Procedure
10.3.2 Static Sparsity Pattern (SSP)
10.3.3 Dynamic Sparsity Pattern (DSP)
10.4 Numerical Experiments
10.5 Summary
Transferable E-cheques: An Application of Forward-Secure Serial Multi-signatures
11.1 Introduction
11.2 Basic Schemes made Forward-Secure
11.2.1 Forward Secure ElGamal Signature Scheme
11.2.2 Forward Secure DSA Signature Scheme
11.3 The Forward-Secure Serial Multi-signature Scheme
11.3.1 Forward-Secure Serial Multi-signature Scheme based on Forward-Secure Elgamal Signatures
11.3.2 Forward-Secure Serial Multi-signature Scheme based on Forward-Secure DSA Signatures
11.3.3 Our Model
11.4 Security Analysis
11.4.1 Attacks Aiming to get Private Keys
11.4.2 Attacks for Forging Multi-signatures
11.5 Forward Security of the Proposed Scheme
11.6 Conclusion
A Hidden Markov Model based Speech Recognition Approach to Automated Cryptanalysis of Two Time Pads
12.1 Introduction
12.2 Previous and Related Work
12.2.1 Keystream Reuse
12.2.2 Use of HMMs in Cryptanalysis
12.3 Proposed Approach
12.3.1 HMM Training Phase Modificatio
12.3.2 Recognition Phase Modificatio
12.4 Simulation
12.4.1 Pre-computation Phase
12.4.2 Decoding Phase
12.4.3 Experimental Results
12.5 Future Work and Conclusion
A Reconfigurable and Modular Open Architecture Controller: The New Frontiers
13.1 Introduction
13.2 Original Unimate PUMA 500
13.3 New Hardware Configuratio
13.3.1 Advantages for New PC based PUMA Robot
13.4 Description of the Control Scheme
13.4.1 Effect of Large Gear-Ratios & Friction
13.4.2 Viscous Friction and Inertia
13.5 Software Design for the Controller
13.6 Results
13.7 Discussion & Conclusions
An Adaptive Machine Vision System for Parts Assembly Inspection
14.1 Introduction
14.2 Architecture of an Adaptive Visual Inspection System
14.3 Localization of ROV
14.4 Defect Detection using a Principal Component Analysis
14.5 Online Learning of PCA based Recognition Model
14.5.1 Model Development Phase
14.5.2 Model Execution Phase
14.6 Case Study
14.6.1 System Performance
14.6.2 Comparison with Off-Line Approach
14.6.3 Experiments on Changing Conditions
14.7 Conclusion
Tactile Sensing-based Control System for Dexterous Robot Manipulation
15.1 Introduction
15.2 Optical Three-Axis Tactile Sensor
15.3 Trajectory Generation of Multi-Fingered Humanoid
15.4 Control System Structure
15.5 Experiment and Results
15.6 Conclusions
A Novel Kinematic Model for Rough Terrain Robots
16.1 Introduction
16.1.1 Previous Work
16.1.2 Kinematic Slip
16.1.3 Contribution of this Work
16.2 Analogy Between WMRs and Dextrous Manipulators
16.3 Off-Road Wheeled Mobile Robot Kinematic Model
16.3.1 Wheel/Ground Contact Model
16.3.2 Wheeled Mobile Robot Kinematic Model
16.3.3 Holonomic Constraints and Stabilization
16.3.4 Definitio of Platform Velocities
16.3.5 Forward Kinematics Equations
16.3.6 Adaptability of the Modeling Method
16.4 Results and Discussion
16.4.1 Descending a Steep Hill
16.4.2 Random Terrain
16.5 Conclusion and Future Work
Behavior Emergence in Autonomous Robot Control by Means of Evolutionary Neural Networks
17.1 Introduction
17.2 Khepera Robot
17.3 Neural Networks
17.4 Evolutionary Network Learning
17.5 Experiments
17.6 Analysis of Successful Behaviors
17.7 Conclusions
Swarm Economics
18.1 Introduction
18.2 Swarm Engineering Basics
18.2.1 Definition
18.2.2 Swarm Engineering
18.3 Swarm Engineering Applied to Economic Systems
18.3.1 Vendors and Consumers
18.3.2 Design of Consumer Agents
18.4 Simulation Design
18.4.1 Vendors
18.4.2 Consumers
18.5 Simulation Data
18.5.1 The Effects of
18.5.2 Adding in
18.5.3 Examining (18.29)
18.6 Perturbations of the Economic Swarm
18.7 Discussion and Conclusion
Machines Imitating Humans
19.1 Modern Humanoid Robotics Research
19.2 Human-Robot Interaction (HRI)
19.2.1 Human Robot Collaboration
19.2.2 Nonverbal or Implicit Communication
19.2.3 Multi-person Interaction
19.2.4 Issues in Human Robot Interaction
19.3 Humanlike Appearance
19.4 The Uncanny Valley
19.4.1 Effect of Behavior
19.5 Our Experiment
19.6 Results
19.7 Discussion
19.8 Improving Behavior
19.9 Conclusion
Reinforced ART (ReART) for Online Neural Control
20.1 Introduction
20.2 Related Work
20.3 Reinforced ART (ReART)
20.4 Numerical Evaluation of ReART
20.5 Results and Analysis
20.6 Conclusion
The Bump Hunting by the Decision Tree with the Genetic Algorithm
21.1 Introduction
21.1.1 What is the Bump Hunting?
21.1.2 Trade-Off Curve Between the Pureness Rate and the Capture Rate
21.1.3 Bump Hunting Using the Decision Tree with the Genetic Algorithm
21.1.4 Upper Bound for the Trade-Off Curve by Using the Extreme-Value Statistics
21.1.5 The Bias of the Capture Rates in the Trade-Off Curve
21.2 Objective of the Research
21.3 Customer Data
21.4 Extreme-Value Statistics Approach
21.4.1 1/100 Model Real Data Case: When the Number ofSamplesisSmall
21.4.2 1/10 Model Real Data Case: When the Number of Samples is Large
21.4.3 How to Assess the Trade-Off Curves
21.4.4 Reliability for the Return Period Due to the Number of Initial Seeds
21.5 Concluding Remarks
Machine Learning Approaches for the Inversion of the Radiative Transfer Equation
22.1 Introduction
22.2 Previous Work
22.2.1 Physical Model
22.2.2 Learning RTE Inversion
22.3 Supervised Learning for Temperature Retrieval
22.3.1 Principal Component Analysis (PCA)
22.3.2 Reduced Rank Regression (RRR)
22.3.3 Canonical Correlation Analysis (CCA)
22.3.4 Kernel Canonical Correlation Analysis (KCCA)
22.4 Experiments
22.4.1 Experimental Design
22.4.2 Error description
22.4.3 Results
22.5 Conclusions
Enhancing the Performance of Entropy Algorithm using Minimum Tree in Decision Tree Classifier
23.1 Introduction
23.1.1 Related Works
23.2 Entropy Algorithm Description
23.3 The Proposed Enhanced Entropy Algorithm
23.3.1 The Tree Construction Process
23.3.2 The Decision Tree Classifie (DTC)
23.3.3 Native Bayesian Classifie
23.4 Simulated Results
23.4.1 Performance Analysis of Entropy Algorithm
23.4.2 Performance Analysis of EEA
23.5 Conclusion and Future Works
Numerical Analysis of Large Diameter Butterfly Valve
24.1 Introduction
24.2 Important Aspects of Large Diameter Butterfl Valve
24.2.1 Flow Coefficient
24.2.2 Cavitation Parameters
24.2.3 Hydrodynamic Torque Coeffcient
24.3 Numerical Analysis
24.3.1 Numerical Method
24.3.2 Grid Generation
24.3.3 Boundary Condition
24.4 Result and Discussion
24.5 Conclusion
Axial Crushing of Thin-Walled Columns with Octagonal Section: Modeling and Design
25.1 Simplifie Modeling
25.1.1 Introduction
25.1.2 Axial Resistance
25.1.3 Simplifie Modeling of Thin-Walled Octagonal Column
25.1.4 Analyses and Comparison
25.2 Crashworthiness Design
25.2.1 Introduction
25.2.2 Problem Description
25.2.3 Response Surface Method (RSM) [18]
25.2.4 Design Optimization – Straight Octagonal Columns
25.3 Conclusions
A Fast State Estimation Method for DC Motors
26.1 Introduction
26.2 Motor Model and Estimation Procedure
26.2.1 DC Motor Model
26.2.2 The Procedure of Fast State Estimation
26.3 Simulation
26.3.1 Estimation Application
26.3.2 Control Application
26.4 Summary
Flatness based GPI Control for Flexible Robots
27.1 Introduction
27.2 Model Description
27.2.1 Flexible Beam Dynamics
27.2.2 DC Motor Dynamics
27.2.3 Complete System
27.3 GPI Controller
27.3.1 Outer Loop Controller
27.3.2 Inner Loop Controller
27.4 Experimental Validation
27.4.1 Experimental Setup Description
27.4.2 Outer Loop Design
27.4.3 Inner Loop Design
27.5 Experimental Results
27.6 Conclusions
Estimation of Mass-Spring-Dumper Systems
28.1 Introduction
28.2 Mass-Spring-Damper Model and Identificatio Procedure
28.2.1 Mass-Spring-Damper Model
28.2.2 The Procedure of Algebraic Identificatio
28.3 Simulation Results
28.3.1 Estimation Without Noise in the Measure
28.3.2 Estimation with Noise in the Measure
28.4 Conclusions
MIMO PID Controller Synthesis with Closed-Loop Pole Assignment
29.1 Introduction
29.2 Main Results
29.2.1 Plants with No Poles in
29.2.2 Plants with No Zeros in
29.2.3 Strictly-Proper Plants with No Other Zeros in
29.3 Conclusions
Robust Design of Motor PWM Control using Modeling and Simulation
30.1 Introduction
30.2 Modeling
30.3 Baseline Result
30.4 Determining the Main Factors
30.5 Response Surface Method
30.6 Conclusions
Modeling, Control and Simulation of a Novel Mobile Robotic System
31.1 Introduction
31.2 Dynamics and Control of the Moving Base
31.2.1 Kinematic Equations
31.2.2 Dynamics and Control Law
31.2.3 Simulation Results
31.3 Overall System Simulation System Equations of Motion
31.3.1 System Simulation Results
31.4 Summary
All Circuits Enumeration in Macro-Econometric Models
32.1 Introduction
32.2 Elementary Circuit Theory
32.2.1 Preliminaries and Notations
32.2.2 Circuit Definition and Properties
32.2.3 Enumeration Problems
32.2.4 Backtracking Procedure
32.2.5 Tarjan’s Algorithm
32.2.6 Upper Bounds on Time and Space
32.3 Structure of a Macro-Econometric Model
32.3.1 Graph Properties of the Model
32.4 Circuits of the Digraph
32.5 Edge-Disjoint Circuits
32.6 Conclusion
Noise and Vibration Modeling for Anti-Lock Brake Systems
33.1 Introduction
33.2 Modeling of ABS for Noise and Vibration Study
33.2.1 Noise and Brake Pedal
33.2.2 Motor and Pump
33.2.3 Algorithm: Motor and Valve Control
33.2.4 Low Pressure Accumulator
33.2.5 Brake Pressure
33.2.6 Master Cylinder
33.3 Simulation Scenarios
33.3.1 Evaluating Impact of Motor Speed
33.3.2 Evaluating Impact of Pump Size and Efficienc
33.3.3 Evaluating Impact of ABS Algorithm Calibration
33.3.4 Evaluating Impact of Master Cylinder Design
33.4 Conclusions
Investigation of Single Phase Approximation and Mixture Model on Flow Behaviour and Heat Transfer of a Ferrofluid using CFD Simulation
34.1 Introduction
34.2 Mathematical Formulation
34.3 Numerical Methods
34.4 Results and Discussion
34.5 Conclusion
Two Level Parallel Grammatical Evolution
35.1 Introduction
35.2 Overview of Evolutionary Algorithms
35.3 Parallel Grammatical Evolution
35.4 Parallel Grammatical Evolution with Backward Processing
35.4.1 Backward Processing of the GE
35.4.2 Reduction of the Search Space
35.4.3 Grammatical Evolution
35.4.4 Processing the Grammar
35.4.5 Phenotype to Genotype Projection
35.4.6 Crossover
35.4.7 Mutation
35.4.8 Population Model
35.4.9 Fitness Function
35.4.10 Results of Testing
35.5 Logical Function XOR as a Test Function
35.6 Two-Level Optimization
35.7 Conclusion
References
Genetic Algorithms for Scenario Generation in Stochastic Programming
36.1 Introduction
36.2 Stochastic Programming
36.3 Genetic Algorithms
36.4 Sampling Techniques
36.5 Extreme Scenario Sets
36.6 GA Framework
36.7 The Use in Applications
36.8 Results and Further Research
References
New Approach of Recurrent Neural Network Weight Initialization
37.1 Introduction
37.2 Problems Description
37.2.1 DC Induction Motor Identificatio
37.2.2 Potential Evoked Problem
37.3 Dynamic Analysis
37.3.1 DC Induction Motor Identificatio
37.3.2 Potential Evoked Problem
37.4 Error vs. Dynamic
37.5 Initialization Strategy
37.6 Conclusion
References
GAHC: Hybrid Genetic Algorithm
38.1 Introduction
38.2 Parameter Encoding
38.2.1 Binary Representation of the Task
38.2.2 Hamming Metric
38.2.3 Domain of Definitio
38.3 Implemented HCA
38.3.1 Basic Concept
38.3.2 Transfer Function
38.3.3 Implementation of the Proposed Hill Climbing Algorithm
38.4 Elite Tournament Selection
38.4.1 Background
38.4.2 Evaluation and Analysis
38.5 GAHC
38.5.1 Background
38.5.2 Evaluation and Analysis
38.6 Conclusion
References
Forecasting Inflation with the Influence of Globalization using Artificial Neural Network-based Thin and Thick Models
39.1 Introduction
39.2 Methodology
39.2.1 Theoretical Underpinnings of Artificia Neural Networks
39.2.2 ANN Thin, ANN Thick and Inflatio Models
39.3 Empirical Results and Analysis
39.4 Conclusions
References
Pan-Tilt Motion Estimation Using Superposition-Type Spherical Compound-Like Eye
40.1 Introduction
40.2 The Compound-Like Eye in Computer Vision
40.3 Pan-Tilt Ego-Rotational Motion for One CCD
40.3.1 Pan-Tilt Rotation and Image Transformation
40.3.2 Ego-Rotational Motion of Pan and Tilt
40.4 Ego-Rotational Motion of Superposition Spherical
40.5 Experimental Results
40.5.1 Structure with Unconstrained Length and Width
40.5.2 SSCE Structure with Constrained Length and Width
40.5.3 Discussion
40.6 Conclusion
References
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