Mastorakis / Mladenov / Kontargyri Proceedings of the European Computing Conference

Volume 2
1. Auflage 2010
ISBN: 978-0-387-85437-3
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 28, 732 Seiten

Reihe: Lecture Notes in Electrical Engineering

The European Computing Conference offers a unique forum for establishing new collaborations within present or upcoming research projects, exchanging useful ideas, presenting recent research results, participating in discussions and establishing new academic collaborations, linking university with the industry. Engineers and Scientists working on various areas of Systems Theory, Applied Mathematics, Simulation, Numerical and Computational Methods and Parallel Computing present the latest findings, advances, and current trends on a wide range of topics. This proceedings volume will be of interest to students, researchers, and practicing engineers.

Autoren/Hrsg.

Mladenov, Valeri

Mastorakis, Nikos

Kontargyri, Vassiliki T.

Inhaltsverzeichnis

1;Contents;6
2;Contributors;13
3;Part 1: Computer Applications in Power Systems;24
3.1;Wind Energy Production Forecasting;25
3.1.1;1.1 Introduction;25
3.1.2;1.2 Related Work;26
3.1.3;1.3 Theoretical Approach;26
3.1.3.1;1.3.1 Neural Networks;26
3.1.3.2;1.3.2 Quasi-Newton Method for Training the Neural Network;27
3.1.3.3;1.3.3 Genetic Algorithm for Training the Neural Network;28
3.1.4;1.4 Computational Results;29
3.1.4.1;1.4.1 Parameter Selection;29
3.1.4.2;1.4.2 Network Parameter Issues;29
3.1.4.3;1.4.3 Data Series Partitioning;30
3.1.4.4;1.4.4 Learning and Training;31
3.1.4.5;1.4.5 Out of Sample Evaluation;31
3.1.5;1.5 Conclusion and Further Research;33
3.1.6;References;34
3.2;Operation Management on Autonomous Power System;36
3.2.1;2.1 Introduction;36
3.2.2;2.2 Algorithm Implementation;37
3.2.2.1;2.2.1 Load and wind power forecasting;37
3.2.2.2;2.2.2 Unit Commitment;38
3.2.2.3;2.2.3 Economic Dispatch;39
3.2.2.4;2.2.4 Dynamic Security Assessment;40
3.2.3;2.3 Operation Management;41
3.2.3.1;2.3.1 Data Entry;41
3.2.3.2;2.3.2 Unit Commitment;41
3.2.3.3;2.3.3 Dynamic Security Assessment;43
3.2.3.4;2.3.4 Preventive Security Assessment;43
3.2.4;2.4 Conclusion;44
3.2.5;References;45
3.3;A Low-Power Portable H.264/AVC Decoder Using Elastic Pipeline;46
3.3.1;3.1 Introduction;46
3.3.2;3.2 Conventional Pipeline Architecture;47
3.3.3;3.3 Elastic Pipeline Architecture;48
3.3.3.1;3.3.1 Concept;48
3.3.3.2;3.3.2 Feedback-Type Voltage/Frequency Control Algorithm;48
3.3.3.3;3.3.3 Architecture;50
3.3.4;3.4 Experimental Results;51
3.3.4.1;3.4.1 Test Sequence;51
3.3.4.2;3.4.2 The Optimum Number of Slots Per Frame;51
3.3.4.3;3.4.3 Power Saving;52
3.3.5;3.5 Summary;53
3.3.6;References;53
4;Part 2: Computational Techniques and Algorithms;54
4.1;Computational Methods for Detecting Types of Nonlinear Dynamics;55
4.1.1;4.1 Introduction;55
4.1.2;4.2 Mathematical Framework Presentation;56
4.1.2.1;4.2.1 Model Presentation;56
4.1.2.2;4.2.2 The Householder QR Factorization for a Matrix $\textbf{\textit{A}} \in R^2 xR^2$;57
4.1.3;4.3 Implementation Methods for Numerical Simulations;59
4.1.3.1;4.3.1 Implementation Method Used to Detect the Behavior Type of System (4.1);59
4.1.3.2;4.3.2 Implementation Method Used to Calculate the Lyapunov Exponents, Using Householder QR Factorization;63
4.1.4;4.4 Numerical Simulations;65
4.1.5;4.5 Conclusion;67
4.1.6;References;67
4.2;The Worm Cutter Tool Profiling Based on Discreet Surfaces Representation;69
4.2.1;5.1 Introduction;69
4.2.2;5.2 The Rack-Gear Tool Profiling;70
4.2.3;5.3 Reference Systems and Generation Movements;71
4.2.4;5.4 The Primary Peripheral Surface of the Worm Cutter;73
4.2.4.1;5.4.1 The Intermediary Surface Family in the Reference System of the Worm Cutter Primary Peripheral Surface;73
4.2.4.2;5.4.2 The Enwrapping Condition;74
4.2.4.3;5.4.3 The Characteristic Curve of the Conjugated Surfaces;74
4.2.4.4;5.4.4 Primary Peripheral Surface of the Worm Cutter;75
4.2.5;5.5 The Software for the Rolling Generating Tool Profiling (RGTP);75
4.2.6;5.6 Applications;80
4.2.7;5.7 Conclusions;81
4.2.8;References;82
4.3;Suggesting Correct Words Algorithms Developing in FarsiTeX;83
4.3.1;6.1 Introduction;83
4.3.2;6.2 Algorithms of Suggesting Correct Words;85
4.3.2.1;6.2.1 On an Incorrect Word;85
4.3.3;6.3 Increasing Speed;86
4.3.4;6.4 Memory Usage Problems;86
4.3.4.1;6.4.1 Using Static Functions;86
4.3.4.2;6.4.2 Using Multi Files;87
4.3.4.3;6.4.3 The Roots of the Farsi Words Instead of the Whole Words;87
4.3.5;6.5 Implementation Results;88
4.3.6;6.6 Other Techniques and Conclusion;88
4.3.7;6.7 Appendix;89
4.3.8;References;90
4.4;On the Analytical and Numerical Computation in Mechanical Modeling;92
4.4.1;7.1 Introduction About Coding;92
4.4.2;7.2 Notions on the Set of Polynomials;93
4.4.3;7.3 A Theorem of Division;93
4.4.4;7.4 A New Definition of Euclidean Ring;94
4.4.5;7.5 The Model of Thin Plates and Coding;94
4.4.6;7.6 Conclusion;96
4.4.7;References;96
4.5;Real Genetic Algorithm for Traveling Salesman Problem Optimization;98
4.5.1;8.1 Introduction;98
4.5.2;8.2 Encoding Schemes of GA;99
4.5.3;8.3 Example: A Real Problem of Solid Waste Routing;100
4.5.4;8.4 GA Optimization;102
4.5.4.1;8.4.1 Coding;102
4.5.4.2;8.4.2 Fitness;102
4.5.4.3;8.4.3 Selection, Crossover and Mutation;103
4.5.5;8.5 Results;104
4.5.6;8.6 Conclusion;106
4.5.7;References;107
4.6;The COTECOMO: COnstractive Test Effort COst MOdel;108
4.6.1;9.1 Introduction;109
4.6.2;9.2 Attributes Affecting Software/System Test Effort;111
4.6.2.1;9.2.1 Conventional Approach to Test Effort Estimation;111
4.6.2.2;9.2.2 The Selection of the Sizing and Estimation Methodologies;112
4.6.2.2.1;9.2.2.1 Sizing and Estimation Methodologies;113
4.6.2.2.2;9.2.2.2 Characteristics of the Cost Estimation;114
4.6.2.2.3;9.2.2.3 General Advantages of Estimation Methodologies:;114
4.6.2.3;9.2.3 The Software Test Effort Models - Critical Review;115
4.6.2.3.1;9.2.3.1 Industry Case Studies;116
4.6.2.4;9.2.4 Adaptive Cyclic Pairwise Rejection Rules of Estimation Model Candidates Using performance measures (ACPREPM);117
4.6.2.4.1;9.2.4.1 Adaptive Cyclic Pairwise Rejection of Estimation Model;119
4.6.3;9.3 COTECOMO Methodology;120
4.6.3.1;9.3.1 Test Effort Estimation Using System Test Points: A New Metric for Practitioners;121
4.6.3.2;9.3.2 Software/System Test Point (STP) Evaluation;124
4.6.4;9.4 COTECOMO Effort Estimation Procedure and Case Study Results;125
4.6.5;9.5 Conclusion and Future Work;128
4.6.6;References;128
4.7;A Semantics of Core Computational Model for ODP Specifications;130
4.7.1;10.1 Introduction;130
4.7.2;10.2 Related Work;131
4.7.3;10.3 The RM-ODP;132
4.7.3.1;10.3.1 The RM-ODP Foundations Part;132
4.7.3.2;10.3.2 The RM-ODP Computational Language;133
4.7.4;10.4 The Syntax Domain;134
4.7.5;10.5 Semantics Domain;136
4.7.6;10.6 Meaning Function;136
4.7.7;10.7 Conclusion;138
4.7.8;References;139
4.8;Computer Simulation Via Direct Modeling;141
4.8.1;11.1 Introduction;141
4.8.2;11.2 Background;142
4.8.2.1;11.2.1 The DiCOMO General Scheme as Applied to Continuous Media;142
4.8.2.2;11.2.2 IC Simulation Algorithms;144
4.8.2.3;11.2.3 The Molecular Binding Simulation;148
4.8.2.4;11.2.4 DiCOMO Approach Compatibility with the Sun’s Fortress Object-Oriented Language for Parallelization;149
4.8.3;11.3 Conclusions;149
4.8.4;References;150
4.9;Image Segmentation with Improved Artificial Fish Swarm Algorithm;151
4.9.1;12.1 Introduction;151
4.9.2;12.2 The Artificial Fish Swarm Algorithm;152
4.9.2.1;12.2.1 The Artificial Fish;152
4.9.2.2;12.2.2 Five Basic Behaviors of AF;152
4.9.2.3;12.2.3 The Improved Adaptive Step Length in AFSA;153
4.9.3;12.3 Image Segmentation by Improved AFSA;154
4.9.3.1;12.3.1 The Multi-Threshold Image Segmentation;154
4.9.3.2;12.3.2 The Parameter Selection and Results;154
4.9.4;12.4 Discussion and Conclusion;155
4.9.4.1;12.4.1 Discussion;155
4.9.4.2;12.4.2 Conclusion;155
4.9.5;References;156
4.10;Propagation of Elastic-Plastic Waves in Bars;157
4.10.1;13.1 Introduction;157
4.10.2;13.2 Problem Formulation;157
4.10.3;13.3 Approximation Study;161
4.10.4;13.4 Numerical Example;164
4.10.5;13.5 Conclusions;167
4.10.6;References;167
4.11;Shahyat Algorithm as a Clustering Method;169
4.11.1;14.1 Introduction;169
4.11.2;14.2 Description of Shahyat Algorithm;170
4.11.2.1;14.2.1 Finding the Candidate Centers Without Differentiating from Heat Function;171
4.11.2.2;14.2.2 Selecting C Main Centers from T+1 Candidate Centers;172
4.11.3;14.3 Solving a Clustering Problem by Shahyat Algorithm;172
4.11.4;14.4 Specifications of Shahyat Algorithm;175
4.11.5;14.5 Iris Data;176
4.11.6;14.6 Conclusion;178
4.11.7;References;178
4.12;A Modified Electromagnetism-Like Algorithm Based on a Pattern Search Method;179
4.12.1;15.1 Introduction;179
4.12.2;15.2 Electromagnetism-Like Algorithm;180
4.12.3;15.3 Hooke and Jeeves Pattern Search Method;182
4.12.4;15.4 Numerical Results;182
4.12.5;15.5 Conclusions;185
4.12.6;References;185
4.13;Latency Hiding and Adaptability for Parallel Iterative Algorithms;186
4.13.1;16.1 Introduction;186
4.13.2;16.2 Parallel Iterative Reconstruction Methods;187
4.13.3;16.3 Adaptability;188
4.13.4;16.4 Results;189
4.13.5;16.5 Discussion and Conclusions;191
4.13.6;References;192
4.14;Clustering the Linearly Inseparable Clusters;193
4.14.1;17.1 Introduction;193
4.14.2;17.2 Description of the Algorithm;194
4.14.3;17.3 Iris Data;196
4.14.4;17.4 Conclusion;198
4.14.5;References;199
4.15;A Top-Down Minimization Algorithm for Non-Deterministic Systems;200
4.15.1;18.1 Introduction;200
4.15.2;18.2 Method Presentation;201
4.15.3;18.3 Conclusions;204
4.15.4;References;205
5;Part 3: Natural Phenomena and Computer Models;206
5.1;Multi-Layer Finite Volume Solution of Wind Induced Basin Flow;207
5.1.1;19.1 Introduction;207
5.1.2;19.2 Governing Equations;208
5.1.3;19.3 Numerical Formulation;210
5.1.4;19.4 Artificial Viscosity;211
5.1.5;19.5 Boundary Condition;212
5.1.6;19.6 Verification Test;212
5.1.7;19.7 Conclusions;214
5.1.8;References;214
5.2;NASIR Heat Generation and Transfer Solver for RCC Dams;216
5.2.1;20.1 Introduction;216
5.2.2;20.2 Governing Equations;217
5.2.3;20.3 Numerical Solutions;220
5.2.4;20.4 Domain Discretization;221
5.2.5;20.5 Verification of Solution;222
5.2.6;20.6 Applications to a Typical Case;224
5.2.7;20.7 Conclusions;224
5.2.8;References;226
5.3;Water Hammer Modeling Using 2nd Order Godunov Finite Volume Method;227
5.3.1;21.1 Introduction;227
5.3.2;21.2 Governing Equations;228
5.3.3;21.3 Formulation of Finite Volume Schemes for Water Hammer;229
5.3.4;21.4 Boundary Conditions;231
5.3.4.1;21.4.1 Upstream Head-Constant Reservoir;232
5.3.4.2;21.4.2 Fully Closed Downstream Valve;232
5.3.5;21.5 Time Integration;233
5.3.6;21.6 Numerical Results and Discussion;233
5.3.7;21.7 Conclusions;234
5.3.8;References;235
5.4;Simulation of Wind Pressure on Two Tandem Tanks;236
5.4.1;22.1 Introduction;236
5.4.2;22.2 Governing Equations;237
5.4.3;22.3 Numerical Method;238
5.4.4;22.4 Application of the Model;240
5.4.5;22.5 Discussion;244
5.4.6;References;244
5.5;Tropical Cyclone Forecaster Integrated with Case-Based Reasoning;246
5.5.1;23.1 Introduction;246
5.5.2;23.2 Problem Formulation;247
5.5.3;23.3 Development of CBR Intensity Prediction Model;250
5.5.3.1;23.3.1 Case Representation;250
5.5.3.2;23.3.2 Building a Case Store;250
5.5.3.3;23.3.3 Case Retrieval;250
5.5.4;23.4 Results and Discussion;251
5.5.5;23.5 Conclusion and Future Work;252
5.5.6;References;252
6;Part 4: Knowledge Engineering, Decision Rules and Data Bases;253
6.1;Toward an Understanding of Knowledge Reuse in an On-Line Environment;254
6.1.1;24.1 Introduction;254
6.1.1.1;24.1.1 Statement of Research Problem;255
6.1.1.2;24.1.2 Purposes of the Study;255
6.1.2;24.2 Literature Review;255
6.1.2.1;24.2.1 Knowledge Reuse as a Process;255
6.1.2.2;24.2.2 Meta-Cognitive Knowledge;256
6.1.2.3;24.2.3 Meta-Cognitive Regulation;256
6.1.2.4;24.2.4 Meta-Cognitive Strategies;257
6.1.3;24.3 Theory Frame;259
6.1.3.1;24.3.1 Intention of Knowledge Reuse;259
6.1.3.2;24.3.2 Meta-Cognitive Intention of Knowledge Reuse;262
6.1.3.3;24.3.3 Behavior of Knowledge Reuse;263
6.1.4;24.4 Research Method;263
6.1.4.1;24.4.1 Data Collection;263
6.1.4.2;24.4.2 Measurement of Constructs;263
6.1.4.3;24.4.3 Scale Validation Method;263
6.1.5;24.5 Data Analysis and Results;264
6.1.5.1;24.5.1 Samples;264
6.1.5.2;24.5.2 Measurement Equations;265
6.1.5.3;24.5.3 Structural Equations;267
6.1.5.4;24.5.4 Conclusion;268
6.1.6;References;268
6.2;Handling Contradictions in Knowledge Discovery Applications;269
6.2.1;25.1 What’s Wrong with Contradictions?;269
6.2.2;25.2 Correcting Classical Logic’s Mistake?;270
6.2.3;25.3 A Different Approach - Knowledge Bases and Presence Values;271
6.2.4;25.4 Conclusion;275
6.2.5;Appendix: Indicative Results for LM4;276
6.2.6;References;282
6.3;A Cooperative Distributed Query-Processing Approach;283
6.3.1;26.1 Introduction;283
6.3.1.1;26.1.1 Transparency Types;284
6.3.2;26.2 Traditional DDBMS;285
6.3.3;26.3 Co-operative and Dynamic DDBMS;285
6.3.3.1;26.3.1 Architecture;285
6.3.3.1.1;26.3.1.1 Client;286
6.3.3.1.2;26.3.1.2 Distributed Query Service Provider;286
6.3.3.1.3;26.3.1.3 Data Dictionary Service Provider;286
6.3.3.1.4;26.3.1.4 Local Query Service Provider (LQSP);286
6.3.3.2;26.3.2 Distributed Execution Plan Strategy;287
6.3.3.3;26.3.3 Communication Overview;287
6.3.3.3.1;26.3.3.1 DQSP Process;288
6.3.3.3.2;26.3.3.2 DDSP Process;289
6.3.3.3.3;26.3.3.3 LQSP Process;289
6.3.3.4;26.3.4 Query Processing Example;289
6.3.4;26.4 Conclusion;292
6.3.5;References;293
6.4;Estimating Join and Projection Selectivity Factors;294
6.4.1;27.1 Introduction;294
6.4.2;27.2 Related Work;295
6.4.3;27.3 Data Distribution Approximation by Orthogonal Series;297
6.4.4;27.4 Join Selectivity Estimation;297
6.4.5;27.5 Projection Selectivity Estimation;301
6.4.6;27.6 Conclusions;303
6.4.7;References;303
6.5;Decision Rules: A Metamodel to Organize Information;305
6.5.1;28.1 Introduction;305
6.5.2;28.2 Problem Formulation;306
6.5.2.1;28.2.1 The Output for a Decision-Model;306
6.5.2.2;28.2.2 The Ideology of Knowledge Representation;307
6.5.3;28.3 Problem Solution;309
6.5.3.1;28.3.1 An Example to Justify the Solution;311
6.5.4;28.4 Conclusions;313
6.5.5;References;313
6.6;A Computerized Solution for the Financial Diagnose of the SMEs;315
6.6.1;29.1 Introduction;315
6.6.2;29.2 Problem Formulation;317
6.6.2.1;29.2.1 Testing the Enterprise Liquidity Ratio;317
6.6.2.2;29.2.2 Testing the Enterprise’s Profitableness;317
6.6.2.3;29.2.3 Inferring the Recommendations;319
6.6.3;29.3 Problem Solution;320
6.6.3.1;29.3.1 The System’s Variables;320
6.6.3.2;29.3.2 Logic Blocks;321
6.6.3.3;29.3.3 Command Blocks;322
6.6.3.4;29.3.4 Testing the Computerized Solution and Displaying the Results;323
6.6.4;29.4 Conclusion;324
6.6.5;References;324
6.7;DELP System: Tracking Deadlocks and Phantoms in Databaseas;325
6.7.1;30.1 Introduction;325
6.7.2;30.2 Related Work;326
6.7.3;30.3 System Description;326
6.7.4;30.4 Experiments and Results;327
6.7.4.1;30.4.1 Deadlock Occurrences;328
6.7.4.2;30.4.2 Phantom Occurrences;328
6.7.5;30.5 Conclusions;329
6.7.6;References;330
6.8;Concurrency Control for Multilevel Secure Distributed Real-Time Databases;331
6.8.1;31.1 Introduction;331
6.8.2;31.2 Review of Literature;332
6.8.3;31.3 Computing Complexity;334
6.8.3.1;31.3.1 Secure Concurrency Control Protocol;335
6.8.3.2;31.3.2 Concurrency Control Algorithm;338
6.8.4;31.4 Simulation Results;340
6.8.5;31.5 Conclusion;342
6.8.6;References;343
6.9;A New Framework for Nondeterministic Multi-valued System Minimization;344
6.9.1;32.1 Introduction;344
6.9.2;32.2 Minimization Tools;345
6.9.3;32.3 The Proposed Principles of Minimization;346
6.9.4;32.4 Network Minimization of Nondeterministic Tables with Correlated Outputs;347
6.9.5;32.5 Conclusions;348
6.9.6;References;349
7;Part 5: Web-Based Applications;350
7.1;Thread Pool-Based Improvement of the Mean-Value Analysis Algorithm;351
7.1.1;33.1 Introduction;351
7.1.2;33.2 Backgrounds and Related Work;353
7.1.3;33.3 Improving MVA Based on Thread Pool Investigation;354
7.1.4;33.4 Applying Improved MVA Algorithm in Different ASP.NET Environments;356
7.1.4.1;33.4.1 Experimental Configurations;356
7.1.4.2;33.4.2 Performance Prediction with the Improved MVA Algorithm;357
7.1.4.3;33.4.3 Experimental Validation;358
7.1.5;33.5 Conclusions and Future Work;362
7.1.6;References;362
7.2;Security Enhancements for Web-Based Applications;364
7.2.1;34.1 Introduction;364
7.2.1.1;34.1.1 Hidden Fields;365
7.2.1.2;34.1.2 Cookies;366
7.2.2;34.2 Building Blocks;367
7.2.2.1;34.2.1 Digest Algorithms;367
7.2.2.2;34.2.2 Digests and HTML Forms;367
7.2.2.3;34.2.3 The HMAC Standard;367
7.2.3;34.3 Proposed Approach;369
7.2.4;34.4 Implementation;370
7.2.5;34.5 Conclusions;376
7.2.6;References;376
7.3;Description and Discovery of Web Applications in Grid;377
7.3.1;35.1 Introduction;377
7.3.2;35.2 The Project Scenario and Resource’s Provider Challenges;378
7.3.2.1;35.2.1 Grid Services, Grid Resources and Web Services-Based Application;379
7.3.2.2;35.2.2 Solution Proposed for Application Description and Discovery: Mapping of WSDL Artifacts and UDDI Data Model;380
7.3.3;35.3 A Semantic Description for Resources;381
7.3.3.1;35.3.1 Web Application Description Enrichment with OWL-S Language and its Application to Discovery Task;382
7.3.4;35.4 Conclusions;384
7.3.5;References;384
7.4;An Approach to Treat the User’s Preferences About Personal Data;385
7.4.1;36.1 Introduction;385
7.4.2;36.2 Current Web Privacy Treatment;386
7.4.3;36.3 Web Privacy Controlled by User;387
7.4.4;36.4 Case Study;388
7.4.5;36.5 Conclusions;390
7.4.6;References;390
7.5;Ssort: Peak Analysis for Efficient String Sorting;391
7.5.1;37.1 Introduction;391
7.5.2;37.2 Algorithm Description;392
7.5.3;37.3 Algorithm;393
7.5.4;37.4 Result Analysis;398
7.5.5;37.5 Further Work;399
7.5.6;37.6 Conclusion;400
7.5.7;References;400
7.6;Parametric Studies for the AEC Domain Using InteliGrid Platform;401
7.6.1;38.1 Introduction;401
7.6.2;38.2 InteliGrid Architecture Components;402
7.6.3;38.3 Use Case: Parametric Studies in Civil Engineering;404
7.6.4;38.4 Conclusion;406
7.6.5;References;406
7.7;An Auction-Based Resource Allocation Strategy with a Proportional Share Model for Economic-Based Grid Systems;408
7.7.1;39.1 Introduction;408
7.7.2;39.2 Related Works;409
7.7.3;39.3 Proposed Algorithm;410
7.7.4;39.4 Experimental Results;411
7.7.5;39.5 Concluding Remarks;412
7.7.6;References;412
8;Part 6: Advances in Computer Science and Applications;414
8.1;Propagation in Cylindrical Inset Dielectric Guide Structures;415
8.1.1;40.1 Introduction;415
8.1.2;40.2 Formulation;416
8.1.3;40.3 Numerical Results;418
8.1.4;40.4 Conclusions;419
8.1.5;References;419
8.2;On the Damage in Nonlinear Mesoscopic Materials;421
8.2.1;41.1 Introduction;421
8.2.2;41.2 Basic Micropolar Equations;422
8.2.3;41.3 Proposed Model for the Interface;422
8.2.4;41.4 Degradation and Failure of the Interface;424
8.2.5;41.5 Conclusions;424
8.2.6;References;425
8.3;Diagnosis of Robotized Assembling Systems;427
8.3.1;42.1 Introduction;427
8.3.2;42.2 Modelling the Robot Assembled Process: Assembly Supervisor Petri Nets;429
8.3.3;42.3 SE - Functions for Basic Configurations of ASPN;431
8.3.4;42.4 Design and Implementation Method;433
8.3.5;42.5 Conclusion;434
8.3.6;References;435
8.4;Open Architecture Systems for MERO Walking Robots Control;437
8.4.1;43.1 Introduction;437
8.4.2;43.2 Robot Position Control;439
8.4.3;43.3 Conclusions and Results;441
8.4.4;References;443
8.5;Mass Transfer Analysis in the Case of the EFG Method;444
8.5.1;44.1 Introduction;444
8.5.2;44.2 Problem Formulation;445
8.5.3;44.3 Numerical Results;447
8.5.4;44.4 Conclusions;454
8.5.5;References;454
8.6;Information System Architecture for Data Warehousing;455
8.6.1;45.1 Introduction;455
8.6.2;45.2 Federated Databases and Data Warehouses;456
8.6.3;45.3 Architecture Extension with Temporal Elements;457
8.6.4;45.4 Conclusion;460
8.6.5;References;460
8.7;Dimensional Dynamics Identification of Reconfigurable Machine Tools;462
8.7.1;46.1 Introduction;462
8.7.2;46.2 Algorithm for Online Identification of the Dimensional Dynamics;463
8.7.3;46.3 Experimental Research;467
8.7.4;46.4 Conclusions;467
8.7.5;References;468
8.8;Compaction-Induced Deformation on Flexible Substrate;469
8.8.1;47.1 Introduction;469
8.8.2;47.2 Materials and Method;471
8.8.3;47.3 Results and Discussion;476
8.8.4;47.4 Conclusions;479
8.8.5;References;480
8.9;Robust and Accurate Visual Odometry by Stereo;481
8.9.1;48.1 Introduction;481
8.9.2;48.2 The Visual Odometry Algorithm;482
8.9.2.1;48.2.1 Feature Extraction and Tracking;483
8.9.2.2;48.2.2 Motion Estimation;483
8.9.2.3;48.2.3 Cyclic Correction;485
8.9.3;48.3 Experimental Results;485
8.9.3.1;48.3.1 Equipment and Setup;485
8.9.3.2;48.3.2 Test Results;488
8.9.4;48.4 Concluding Remarks;489
8.9.5;References;489
8.10;Financial Auditing in an E-Business Environment;491
8.10.1;49.1 Introduction;491
8.10.2;49.2 Impacts of e-Business on Audit Missions and Auditors;492
8.10.2.1;49.2.1 Knowledge of the Client’s Business and Planning Mission;493
8.10.2.2;49.2.2 Evaluating Audit Risks in E-Business;494
8.10.2.3;49.2.3 Specific Controls in Auditing E-Business;497
8.10.3;49.3 Solutions for an Efficient Financial Auditing in E-Business;498
8.10.4;49.4 Conclusion;499
8.10.5;References;500
8.11;Reputed Authenticated Routing Ad-Hoc Networks Protocol;501
8.11.1;50.1 Introduction;501
8.11.2;50.2 Security Analysis of ARAN;502
8.11.3;50.3 The Proposed Reputation System Scheme: Reputed-ARAN;503
8.11.4;50.4 Simulation;507
8.11.5;50.5 Conclusion and Future Directions;509
8.11.6;References;510
8.12;Quantum Mechanical Analysis of Nanowire FETs;511
8.12.1;51.1 Introduction;511
8.12.2;51.2 Device Structure and Approach;512
8.12.3;51.3 Results;514
8.12.4;51.4 Conclusion;515
8.12.5;References;515
9;Part 7: Software Tools and Programming Languages;517
9.1;Impact of Quality Factors on the Success of Software Development;518
9.1.1;52.1 Introduction;518
9.1.2;52.2 The Distinguishing Characteristics;519
9.1.2.1;52.2.1 Abstraction;519
9.1.2.2;52.2.2 Encapsulation;519
9.1.2.3;52.2.3 Inheritance;520
9.1.3;52.3 Software Quality Factors;520
9.1.3.1;52.3.1 Flexibility;520
9.1.3.2;52.3.2 Maintainability;520
9.1.3.3;52.3.3 Reliability;520
9.1.3.4;52.3.4 Usability;521
9.1.4;52.4 An Illustrative Case Study Problem;521
9.1.5;52.5 Comparing the Two Methodologies;521
9.1.5.1;52.5.1 Preliminary Results;521
9.1.5.1.1;52.5.1.1 Reliability Results;522
9.1.5.1.2;52.5.1.2 Maintainability Results;522
9.1.5.1.3;52.5.1.3 Flexibility Results;522
9.1.5.1.4;52.5.1.4 Usability Results;523
9.1.5.2;52.5.2 Discussions;523
9.1.5.2.1;52.5.2.1 Differences in Reliability;523
9.1.5.2.2;52.5.2.2 Differences in Maintainability;524
9.1.5.2.3;52.5.2.3 Differences in Flexibility;525
9.1.5.2.4;52.5.2.4 Differences in Usability;525
9.1.6;52.6 Conclusions;526
9.1.7;Refrences;526
9.2;Sisal 3.2 Language Structure Decomposition;528
9.2.1;53.1 Introduction;528
9.2.2;53.2 The Compound Node Select;530
9.2.3;53.3 The Compound Node Forall;530
9.2.4;53.4 Decomposition of the Case Expression;531
9.2.5;53.5 Decomposition of the multidimensional Loops;532
9.2.6;53.6 Decomposition of the Array Element Selection;533
9.2.7;53.7 Array Element Replacement with a Singlet List Selection Construction;534
9.2.8;53.8 Array Element Replacement With a Scalar Replacement Construction;534
9.2.9;53.9 Array Element Replacement with Array Replacement Construction;535
9.2.10;53.10 Decomposition of the Where Expression;536
9.2.11;53.11 Decomposition of the Vector Operations;537
9.2.12;53.12 Conclusion;537
9.2.13;References;538
9.3;An Embedded Application for Driverless Metro Train;539
9.3.1;54.1 Introduction;539
9.3.2;54.2 Experimental Set Up of Train Control System;540
9.3.2.1;54.2.1 Hardware;541
9.3.3;54.3 Hardware Implementation;542
9.3.3.1;54.3.1 The Resulting Hardware;542
9.3.4;54.4 Simulations;542
9.3.4.1;54.4.1 Assembly Code (written on UMPS Version 2.1);543
9.3.5;54.5 Challenges;544
9.3.6;54.6 Conclusion and Future Scope of this Model;544
9.3.7;References;545
9.4;A Post-mortem JavaSpaces Debugger;546
9.4.1;55.1 Introduction;546
9.4.2;55.2 Background;547
9.4.2.1;55.2.1 JavaSpaces;547
9.4.2.2;55.2.2 Jini;547
9.4.2.3;55.2.3 Weak Unstable Predicates;548
9.4.2.4;55.2.4 Strong Unstable Predicates;550
9.4.3;55.3 JSD Architecture;550
9.4.3.1;55.3.1 Predicate Detection Language;551
9.4.4;55.4 JSD Example;552
9.4.5;55.5 Conclusion;553
9.4.6;References;554
9.5;Stochastic Numerical Simulations Using C#;555
9.5.1;56.1 Introduction;555
9.5.2;56.2 Numerical Solutions of SDEs;556
9.5.3;56.3 Numerical Experiments Using C#;557
9.5.4;References;560
9.6;Visualization and Analyses of Multi-Dimensional Data Sets Using OLAP- A Case Study of a Student Administration System;561
9.6.1;57.1 Introduction;561
9.6.2;57.2 Design of OLAP Cubes;562
9.6.3;57.3 Case Study;565
9.6.4;57.4 Conclusion;565
9.6.5;References;565
9.7;Design of a Computer-Based Triangle Chess Machine;566
9.7.1;58.1 Introduction;566
9.7.2;58.2 Implementation;568
9.7.3;58.3 Conclusions;570
9.7.4;References;570
9.8;A Taxonomy Model for Analyzing Project-Based Learning Using Analytical Hierarchy Process (AHP): A Case Study of Design of a Beer Company Website in an Elementary School;571
9.8.1;59.1 Introduction;571
9.8.2;59.2 The AHP Procedure;572
9.8.3;59.3 Experimental Setup and Results;575
9.8.4;59.4 Conclusions;575
9.8.5;References;576
9.9;A Framework of Mixed Model of a Neural Network and Boolean Logic for Financial Crisis Prediction;577
9.9.1;60.1 Introduction;577
9.9.2;60.2 The Framework;578
9.9.3;60.3 Methodologies;580
9.9.4;60.4 Conclusions;581
9.9.5;References;581
9.10;Chinese Document Clustering Using Self-Organizing Map-Based on Botanical Document Warehouse;582
9.10.1;61.1 Introduction;582
9.10.2;61.2 Related Works;583
9.10.2.1;61.2.1 Dealing With Unstructured Documents;583
9.10.2.2;61.2.2 Self Organizing Map Algorithm;584
9.10.2.3;61.2.3 Users’ Information Need;585
9.10.3;61.3 Methodology;585
9.10.4;61.4 Results;586
9.10.4.1;61.4.1 Discussion;586
9.10.4.2;61.4.2 Evaluation;587
9.10.5;61.5 Conclusion;588
9.10.6;References;588
9.11;Linear Discriminant Analysis in Ottoman Alphabet Character Recognition;590
9.11.1;62.1 Introduction;590
9.11.2;62.2 The Preprocessing;591
9.11.3;62.3 The Feature Extraction;592
9.11.3.1;62.3.1 Principle Components Analysis;593
9.11.3.2;62.3.2 Linear Discriminant Analysis;593
9.11.4;62.4 Classification;594
9.11.5;62.5 Experimental Results;595
9.11.6;62.6 Conclusion;596
9.11.7;References;596
9.12;User Requirements Engineering and Management in Software Development;597
9.12.1;63.1 Introduction;597
9.12.2;63.2 Stakeholders’ Interests;598
9.12.3;63.3 Requirements are Interrelated;598
9.12.4;63.4 The Need for Requirements Management;599
9.12.5;63.5 Accelerating Development;601
9.12.6;63.6 Requirements Development and Management;602
9.12.7;63.7 Strategies and Best Practices for Better User Requirements Management;603
9.12.8;63.8 Traditional vs. Novel Approach to RM;604
9.12.9;63.9 Assessing Return on Investment;606
9.12.10;63.10 Conclusion;607
9.12.11;References;607
9.13;SSAF - A Tool for Active Filter Synthesis;609
9.13.1;64.1 Introduction;609
9.13.2;64.2 Program’s Structure and Algorithm;610
9.13.3;64.3 SSAF Program - Implementation and Operation;613
9.13.4;64.4 Conclusion;614
9.13.5;References;615
10;Part 8: Theoretical Approaches in Information Science;616
10.1;On the Complexity of the Auxetic Systems;617
10.1.1;65.1 Introduction;617
10.1.2;65.2 Structural Complexity;618
10.1.3;65.3 Computing Complexity;619
10.1.4;65.4 Case Study and Conclusions;620
10.1.5;References;621
10.2;New Verification of Reactive Requirement for Lyee Method;623
10.2.1;66.1 Introduction;623
10.2.2;66.2 Lyee Methodology and Requirement;624
10.2.3;66.3 Reactive Systems;625
10.2.3.1;66.3.1 Composition of Reactive System;625
10.2.3.2;66.3.2 Reactive System on Lyee Specification;625
10.2.4;66.4 Verification Lyee Requirement by Temporal Logic;627
10.2.4.1;66.4.1 Verification by Temporal Logic;628
10.2.4.2;66.4.2 Example;629
10.2.4.3;66.4.3 Proof of Example;631
10.2.5;66.5 Discussions;633
10.2.5.1;66.5.1 Shared Variable and Common Variable;633
10.2.5.2;66.5.2 Classification of Condition and Fairness;633
10.2.5.3;66.5.3 Expression as a Design Rule;633
10.2.6;66.6 Conclusion;634
10.2.7;References;635
10.3;A Tree Derivation Procedure for Multivalent and Paraconsistent Inference;636
10.3.1;67.1 Valid Arguments;636
10.3.2;67.2 Tree Construction;636
10.3.3;67.3 Multivalent Tree Construction;638
10.3.3.1;67.3.1 Multiple Tree Derivation Scheme;641
10.3.3.2;67.3.2 Single Tree Derivation Scheme;641
10.3.4;67.4 Appendix: Matrices for Epsilon 442;642
10.3.5;References;642
10.4;On the Feedback Stabilization of Matrix;643
10.4.1;68.1 Introduction;643
10.4.2;68.2 Numerical Stabilization of Polynomial and Matrix;646
10.4.3;68.3 Feedback Stabilization of Interval Controllable Canonical Form;647
10.4.4;68.4 Single Feedback Stabilization;653
10.4.5;68.5 Feedback Stabilization of Hessenberg Form;655
10.4.6;68.6 Conclusion;660
10.4.7;References;660
10.5;Maxwell Geometric Dynamics;661
10.5.1;69.1 Variational Problem in Electrodynamics;661
10.5.2;69.2 Ibragimov-Maxwell Lagrangian;662
10.5.3;69.3 Ibragimov-Udriscedilte-Maxwell Lagrangian;663
10.5.4;69.4 Udriscedilte-Maxwell Lagrangian;664
10.5.5;69.5 Discrete Maxwell geometric dynamics;665
10.5.6;69.6 Von Neumann Analysis;667
10.5.7;69.7 Open Problems;670
10.5.8;69.8 Conclusions;670
10.5.9;References;671
10.6;Fractional Right Ideals;672
10.6.1;References;677
10.7;A Distributed Approach for Concurrent Password Recovery of Archived Files;678
10.7.1;71.1 Introduction;678
10.7.2;71.2 Encrypted-Compressed Zip Archive Files;679
10.7.2.1;71.2.1 Brute Force Attack;679
10.7.2.2;71.2.2 Dictionary Attack;680
10.7.3;71.3 Distributed Password Recovery;680
10.7.3.1;71.3.1 Achieving Data Independency for Brute Force Attack;682
10.7.3.2;71.3.2 Achieving Data Independency for Dictionary Attack;682
10.7.3.3;71.3.3 Coding and Performance Issues;683
10.7.4;71.4 Conclusion;683
10.7.5;References;685
10.8;Solutions for an Integral-Differential Equation;686
10.8.1;72.1 Introduction;686
10.8.2;72.2 Problem Formulation;687
10.8.3;72.3 Numerical Method;691
10.8.4;72.4 Conclusions;694
10.8.5;References;695
10.9;Development of Genetic Algorithms and C-Method for Optimizing a Scattering by Rough Surface;696
10.9.1;73.1 Introduction;696
10.9.2;73.2 Compute the Reflectivity;697
10.9.3;73.3 Synthesis with Genetic Algorithms;698
10.9.4;73.4 Application;699
10.9.5;73.5 Conclusions;700
10.9.6;References;700
11;Author Index;701
12;Subject Index;704