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Computer, Informatics, Cybernetics and Applications

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1704 Seiten
Englisch
Springer Netherlandserschienen am01.12.20112012
The Conference on Computer, Informatics, Cybernetics and Applications 2011 aims to facilitate an exchange of information on best practices for the latest research advances in the area of computer, informatics, cybernetics and applications, which mainly includes computer science and engineering, informatics, cybernetics, control systems, communication and network systems, technologies and applications, others and emerging new topics.mehr
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E-BookPDF1 - PDF WatermarkE-Book
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Produkt

KlappentextThe Conference on Computer, Informatics, Cybernetics and Applications 2011 aims to facilitate an exchange of information on best practices for the latest research advances in the area of computer, informatics, cybernetics and applications, which mainly includes computer science and engineering, informatics, cybernetics, control systems, communication and network systems, technologies and applications, others and emerging new topics.

Inhalt/Kritik

Inhaltsverzeichnis
1;Computer, Informatics,Cybernetics and Applications;2
1.1;Preface;4
1.2;Contents;6
1.3;Organization;25
1.4;Part ICommunication Technologies andApplications;29
1.4.1;1 Studies on Single Observer Passive Location Tracking Algorithm Based on LMS-PF;30
1.4.1.1;Abstract;30
1.4.1.2;1.1â¦Introduction;30
1.4.1.3;1.2â¦The Particle Filter Brief Introduction;31
1.4.1.4;1.3â¦The Algorithm Based on LMS-PF for Signal Observer Passive Location Tracking;32
1.4.1.4.1;1.3.1 The Algorithm Based on LMS for Single Observer Passive Location Tracking;32
1.4.1.4.2;1.3.2 The Algorithm Based on PF for Single Observer Passive Location Tracking;33
1.4.1.4.3;1.3.3 The Algorithm Based on LMS-PF for Single Observer Passive Location Tracking;34
1.4.1.5;1.4â¦The Signal Observer Passive Location Tracking Eeperiments;35
1.4.1.6;1.5â¦Conclusions and Discussion;36
1.4.1.7;References;36
1.4.2;2 Novel Methods for Extending Optical Code Set for Coherent OCDMA;37
1.4.2.1;Abstract;37
1.4.2.2;2.1â¦Introduction;37
1.4.2.3;2.2â¦Definition;38
1.4.2.4;2.3â¦Differential Algorithm;39
1.4.2.5;2.4â¦Cross Searching Algorithm;42
1.4.2.6;2.5â¦Conclusion;43
1.4.2.7;References;44
1.4.3;3 A Sequential Processing Method for Converted Measurement Kalman Filters Based on Orthogonal Transform;45
1.4.3.1;Abstract;45
1.4.3.2;3.1â¦Introduction;46
1.4.3.3;3.2â¦Block CMKF Algorithm;46
1.4.3.4;3.3â¦Sequential Algorithm Based on Orthogonal Transform;48
1.4.3.5;3.4â¦Simulation Results and Analysis;50
1.4.3.6;References;52
1.4.4;4 Improvement of an ID-Based Threshold Signcryption Scheme;54
1.4.4.1;Abstract;54
1.4.4.2;4.1â¦Introduction;55
1.4.4.3;4.2â¦The Improvement of Fagen Li et al. Scheme;56
1.4.4.4;4.3â¦Security Analysis of Our Improved Scheme;57
1.4.4.5;4.4â¦Conclusion;59
1.4.4.6;Acknowledgment;59
1.4.4.7;References;59
1.4.5;5 Cryptanalysis of an Enhanced Event Signature Protocols for Peer-to-Peer Massively Multiplayer Online Games;61
1.4.5.1;Abstract;61
1.4.5.2;5.1â¦Introduction;61
1.4.5.3;5.2â¦Review of Chan et al. s Event Signature Protocol for P2P MMOGs;62
1.4.5.3.1;5.2.1 Initialization Phase;63
1.4.5.3.2;5.2.2 Signing Phase;63
1.4.5.3.3;5.2.3 Verification Phase;63
1.4.5.3.4;5.2.4 Re-Initialization Phase;64
1.4.5.4;5.3â¦A Replay Attack on Chan et al. s Protocol;64
1.4.5.5;5.4â¦Review of Chun-Ta Li et al. s Enhanced Event Signature Protocol for P2P MMOGs;65
1.4.5.5.1;5.4.1 Initialization Phase;65
1.4.5.5.2;5.4.2 Signing Phase;65
1.4.5.5.3;5.4.3 Verification Phase;66
1.4.5.5.4;5.4.4 Re-Initialization Phase;66
1.4.5.6;5.5â¦Cryptanalysis of Li et al. s Enhanced Protocol;67
1.4.5.7;5.6â¦Discussions;67
1.4.5.8;Acknowledgments;68
1.4.5.9;References;68
1.4.6;6 Design of CAN Bus and Wireless Sensor Based Vehicle Tire Pressure Monitoring System;69
1.4.6.1;Abstract;69
1.4.6.2;6.1â¦Introduction;69
1.4.6.3;6.2â¦The Design of TPMS;70
1.4.6.4;6.3â¦Design of System;71
1.4.6.4.1;6.3.1 Design of Hardware;71
1.4.6.4.1.1;6.3.1.1 TPMS Receivers;71
1.4.6.4.1.2;6.3.1.2 Wireless Sensors;72
1.4.6.4.1.3;6.3.1.3 Low-Frequency Triggers;72
1.4.6.4.1.4;6.3.1.4 TPMS Displayers;73
1.4.6.4.2;6.3.2 Design of System Software;73
1.4.6.4.2.1;6.3.2.1 Software Controlling Policy and Communication Protocol for TPMS Receivers;74
1.4.6.4.2.2;6.3.2.2 Software Controlling Policy and Communication Protocol for Wireless Sensors;74
1.4.6.5;6.4â¦Testing;75
1.4.6.5.1;6.4.1 CAN Bus Communication Test;75
1.4.6.5.2;6.4.2 Test of Wireless Transportation;75
1.4.6.6;6.5â¦Conclusion;76
1.4.6.7;References;77
1.4.7;7 Analysis and Test of the Exposure Synchronization of the Multi-Sensor Aerial Photogrammetric Camera System;78
1.4.7.1;Abstract;78
1.4.7.2;7.1â¦Introduction;78
1.4.7.3;7.2â¦Analysis of Exposure Synchronization of Multi-Sensor System;79
1.4.7.3.1;7.2.1 Exposure Process and Analysis of Asynchronic Error Source;79
1.4.7.3.2;7.2.2 Calculation of the Maximum Exposure Synchronization Difference;80
1.4.7.4;7.3â¦Test of Exposure Asynchronization;81
1.4.7.4.1;7.3.1 Taking Photographs of a Timer with High Accuracy;82
1.4.7.4.2;7.3.2 Using Photodiode Circuit to Capture the Moment when Shutters are Fully Opened;84
1.4.7.5;7.4â¦Conclusion;85
1.4.7.6;References;85
1.4.8;8 Design and Application of Custom RS485 Communication Protocol;86
1.4.8.1;Abstract;86
1.4.8.2;8.1â¦Introduction;86
1.4.8.3;8.2â¦System Background;87
1.4.8.4;8.3â¦Custom Communication Protocols Definition;88
1.4.8.4.1;8.3.1 Set Address Instruction (A4);89
1.4.8.4.2;8.3.2 Communication Test Instruction (A6);90
1.4.8.4.3;8.3.3 Send Information Instruction (AB);90
1.4.8.5;8.4â¦The Mainframe System Programming;91
1.4.8.6;8.5â¦Display Terminal Programming;92
1.4.8.7;8.6â¦Conclusions;93
1.4.8.8;References;94
1.4.9;9 Sensitivity of Neurons Exposed to AC Induction Electric Field;95
1.4.9.1;Abstract;95
1.4.9.2;9.1â¦Introduction;95
1.4.9.3;9.2â¦Model Simplification;96
1.4.9.4;9.3â¦Analysis of Neuronal Sensitivity;97
1.4.9.4.1;9.3.1 Firing Patterns;97
1.4.9.4.2;9.3.2 Sensitivity Under DC Electric Field;98
1.4.9.4.3;9.3.3 Sensitivity Under AC Induction Electric Field;98
1.4.9.5;9.4â¦Conclusions;102
1.4.9.6;References;103
1.4.10;10 Spectra of Discrete Multi-Splitting Waveform Relaxation Methods to Determining Periodic Solutions of Linear Differential-Algebraic Equations;104
1.4.10.1;Abstract;104
1.4.10.2;10.1â¦Introduction;105
1.4.10.3;10.2â¦Spectra of DMSWR Operators and Finite-Difference for Solving MSWR Solutions;106
1.4.10.3.1;10.2.1 Spectra of DMSWR Operators;107
1.4.10.3.2;10.2.2 Finite-Difference for Solving MSWR Solutions;109
1.4.10.4;10.3â¦Numerical Experiments;111
1.4.10.4.1;10.3.1 Example One;111
1.4.10.5;10.4â¦Conclusions;114
1.4.10.6;Acknowledgments;114
1.4.10.7;References;114
1.4.11;11 A Low Power Limiting Amplifier Designed for the RSSI of a 5.8 GHz ETC Receiver;116
1.4.11.1;Abstract;116
1.4.11.2;11.1â¦Introduction;117
1.4.11.3;11.2â¦Systematic Optimization;117
1.4.11.4;11.3â¦Circuit Implementation;120
1.4.11.5;11.4â¦Design Validation;120
1.4.11.6;11.5â¦Conclusion;122
1.4.11.7;Acknowledgments;122
1.4.11.8;References;123
1.4.12;12 A 3rd order Opamp-Based Tunable Low-Pass Filter Design for Data Demodulator of a 5.8 GHz ETC RF Receiver;124
1.4.12.1;Abstract;124
1.4.12.2;12.1â¦Introduction;125
1.4.12.3;12.2â¦Operational Amplifier Design;125
1.4.12.4;12.3â¦Opam-Based 3rd Order Tunable Low-Pass Filter Design;128
1.4.12.5;12.4â¦System Implementation and Validation;129
1.4.12.6;12.5â¦Conclusion;131
1.4.12.7;Acknowledgments;131
1.4.12.8;References;131
1.4.13;13 Sensor Fusion Using Improvement of Resampling Algorithm Particle Filtering for Accurate Location of Mobile Robot;132
1.4.13.1;Abstract;132
1.4.13.2;13.1â¦Introduction;132
1.4.13.3;13.2â¦The Nonlinear Measurement Model Particle Filter;133
1.4.13.3.1;13.2.1 The Divisional Resampling of Particle Filter;133
1.4.13.3.2;13.2.2 The Prediction Stage;134
1.4.13.3.3;13.2.3 Update Stage;135
1.4.13.4;13.3â¦Simulation Results;135
1.4.13.4.1;13.3.1 Improved Particle;135
1.4.13.4.2;13.3.2 Based on Particle Filter Multi-Sensor;138
1.4.13.5;13.4â¦Simulation Results are as Follows;138
1.4.13.6;13.5â¦Conclusion;140
1.4.13.7;References;140
1.5;Part IIIntelligence and Biometrics Technologies;141
1.5.1;14 Sensor Placement Modes for Smartphone Based Pedestrian Dead Reckoning;142
1.5.1.1;Abstract;142
1.5.1.2;14.1â¦Introduction;143
1.5.1.3;14.2â¦Smartphone Based PDR System;144
1.5.1.3.1;14.2.1 Mode Filtering;144
1.5.1.3.2;14.2.2 Footstep Detection;146
1.5.1.3.3;14.2.3 Stride Length Measurement;148
1.5.1.3.4;14.2.4 Heading Determination;149
1.5.1.4;14.3â¦Experimental Results;149
1.5.1.5;14.4â¦Conclusion and Future Work;150
1.5.1.6;References;151
1.5.2;15 A New Methodology of Judging the Observability of the System;152
1.5.2.1;Abstract;152
1.5.2.2;15.1â¦Introduction;152
1.5.2.3;15.2â¦The Correlation Efficient Decomposition to Matrix and the Judgement of the Observability of Linear System;153
1.5.2.4;15.3â¦The Algorithm and Examples Which Judge the Observability of Linear System;155
1.5.2.4.1;15.3.1 The Algorithm Judge the Observability of Linear System ;155
1.5.2.4.2;15.3.2 Example;156
1.5.2.5;References;158
1.5.3;16 Criteria Conditions for Generalized Strictly Diagonally Dominant Matrices;159
1.5.3.1;Abstract;159
1.5.3.2;16.1â¦Introduction;159
1.5.3.3;16.2â¦Definition and Lemma;160
1.5.3.4;16.3â¦Main Result;160
1.5.3.5;References;166
1.5.4;17 Nonlinear Retarded Integral Inequalities for Discontinuous Functions and Its Applications;167
1.5.4.1;Abstract;167
1.5.4.2;17.1â¦Introduction;167
1.5.4.3;17.2â¦Conclusion;168
1.5.4.3.1;17.2.1 A. Conclusion 1;168
1.5.4.3.2;17.2.2 B. Conclusion 2;174
1.5.4.3.3;17.2.3 C. Conclusion 3;175
1.5.4.4;Acknowledgments;176
1.5.4.5;References;176
1.5.5;18 Oscillatory and Asymptotic Behavior of a Second Order Nonlinear Differential Equation with Perturbation;178
1.5.5.1;Abstract;178
1.5.5.2;18.1â¦Introduction;178
1.5.5.3;18.2â¦Oscillatory Behavior;180
1.5.5.4;18.3â¦Asymptotic Behavior;184
1.5.5.5;18.4â¦Example;186
1.5.5.6;References;186
1.5.6;19 A Expanded Binary Tree Method of Automatic River Coding and Algorithm;187
1.5.6.1;Abstract;187
1.5.6.2;19.1â¦Introduction;187
1.5.6.3;19.2â¦The Analysis of River Coding Method;188
1.5.6.4;19.3â¦The Design and Implementation of River Coding Algorithm;190
1.5.6.4.1;19.3.1 The Process of River Coding;190
1.5.6.4.2;19.3.2 The Judgment of Upstream and Downstream;191
1.5.6.4.3;19.3.3 The Steps of River Coding;191
1.5.6.4.4;19.3.4 The Data Structure of River Network Topology;192
1.5.6.4.5;19.3.5 Recursive Code;193
1.5.6.4.6;19.3.6 Algorithm;194
1.5.6.5;19.4â¦Conclusion;194
1.5.6.6;Acknowledgments;195
1.5.6.7;References;195
1.5.7;20 Domain-Specific Ontology Mapping Based on Common Property Collection;197
1.5.7.1;Abstract;197
1.5.7.2;20.1â¦Introduction;197
1.5.7.3;20.2â¦Related Work;198
1.5.7.4;20.3â¦Overview of Mapping Approach;198
1.5.7.5;20.4â¦The Implementation of Ontology Mapping;199
1.5.7.5.1;20.4.1 Definitions;199
1.5.7.5.2;20.4.2 Mapping Rules;199
1.5.7.5.3;20.4.3 Mapping Steps;200
1.5.7.5.3.1;20.4.3.1 Inference Engine;200
1.5.7.5.3.2;20.4.3.2 Ontology Mapping Process;201
1.5.7.6;20.5â¦Analysis;202
1.5.7.7;20.6â¦Experiment;202
1.5.7.8;20.7â¦Discussion;204
1.5.7.9;20.8â¦Conclusions;204
1.5.7.10;Acknowledgments;205
1.5.7.11;References;205
1.5.8;21 Efficient Mobile Electronic Full Declaration System Based on Smart Device;206
1.5.8.1;Abstract;206
1.5.8.2;21.1â¦Introduction;206
1.5.8.3;21.2â¦Paper Preparation;207
1.5.8.4;21.3â¦The Function Module Partition and Hardware Design;208
1.5.8.4.1;21.3.1 The Data Process and Control;208
1.5.8.4.2;21.3.2 The Memory;209
1.5.8.4.3;21.3.3 The LVDS;209
1.5.8.4.4;21.3.4 RFID Data Acquisition;210
1.5.8.4.5;21.3.5 Mobile Internet;210
1.5.8.4.6;21.3.6 Power Management;210
1.5.8.4.7;21.3.7 Embedded Controller;210
1.5.8.5;21.4â¦The Mobile Electronic Full Declaration System Based on Smart Device;211
1.5.8.6;21.5â¦The Applications of Declaration for Exported Commodities;212
1.5.8.7;21.6â¦Summary;213
1.5.8.8;Acknowledgments;213
1.5.8.9;References;214
1.5.9;22 The Predicate System Based on Schweizer--Sklar t-Norm and Its Completeness;215
1.5.9.1;Abstract;215
1.5.9.2;22.1â¦Introduction;215
1.5.9.3;22.2â¦Predicate Formal System \forall {{\bf UL}}^{\ast};216
1.5.9.4;22.3â¦Completeness of \forall {\hbox{UL}}^{\ast};219
1.5.9.5;22.4â¦Conclusion;222
1.5.9.6;Acknowledgments;222
1.5.9.7;References;222
1.5.10;23 Providing Timely Response in Smart Car;224
1.5.10.1;Abstract;224
1.5.10.2;23.1â¦Introduction;224
1.5.10.3;23.2â¦Related Work;225
1.5.10.4;23.3â¦The Architecture of the Smart Car;226
1.5.10.4.1;23.3.1 System Model;227
1.5.10.4.2;23.3.2 Task Model;228
1.5.10.5;23.4â¦The Scheduler;228
1.5.10.6;23.5â¦Performance Evaluation;230
1.5.10.6.1;23.5.1 Test Result;230
1.5.10.7;23.6â¦Conclusion;232
1.5.10.8;Acknowledgments;232
1.5.10.9;References;233
1.5.11;24 A Study of Position Tracking Technology in Indoor Environments for Autonomous Wheelchair Driving;234
1.5.11.1;Abstract;234
1.5.11.2;24.1â¦Introduction;235
1.5.11.3;24.2â¦Position Estimation Method;236
1.5.11.3.1;24.2.1 Triangulation;236
1.5.11.3.2;24.2.2 Position Estimation Using the RSSI;237
1.5.11.4;24.3â¦Realization of Active RFID Module;237
1.5.11.4.1;24.3.1 RF Transmission and Receiving;237
1.5.11.4.2;24.3.2 Micro Controller for the Control;238
1.5.11.4.3;24.3.3 Embodiment of Active RFID Module;239
1.5.11.5;24.4â¦Experiment;239
1.5.11.5.1;24.4.1 Experiment to Estimate the RSSI Value;239
1.5.11.5.2;24.4.2 Position Tracing Experiment in the Test Space;241
1.5.11.6;24.5â¦Conclusion;242
1.5.11.7;Acknowledgments;243
1.5.11.8;References;243
1.5.12;25 Adaptive Regulation of a Class of Nonlinear Systems with Unknown Sinusoidal Disturbances;245
1.5.12.1;Abstract;245
1.5.12.2;25.1â¦Introduction;245
1.5.12.3;25.2â¦System Transformations;246
1.5.12.4;25.3â¦Estimation of Disturbances;249
1.5.12.5;25.4â¦Adaptive Regulation Laws;250
1.5.12.6;25.5â¦Conclusion;253
1.5.12.7;Acknowledgments;253
1.5.12.8;References;253
1.5.13;26 Research on Improved Ant Colony Algorithm for TSP Problem;254
1.5.13.1;Abstract;254
1.5.13.2;26.1â¦Introduction;254
1.5.13.3;26.2â¦Basic Ant Colony Algorithm;255
1.5.13.3.1;26.2.1 Principles;255
1.5.13.3.2;26.2.2 Algorithm Model;255
1.5.13.4;26.3â¦Ant Colony Optimization Algorithm;256
1.5.13.4.1;26.3.1 Algorithm Idea;256
1.5.13.5;26.4â¦Simulation Analysis;258
1.5.13.6;26.5â¦Conclusion;259
1.5.13.7;Acknowledgments;259
1.5.13.8;References;259
1.6;Part IIINetworks Systems and Web Technologies;261
1.6.1;27 Research on Internet of Things Technology;262
1.6.1.1;Abstract;262
1.6.1.2;27.1â¦Introduction;262
1.6.1.3;27.2â¦Internet of Things Architecture;264
1.6.1.4;27.3â¦The Key Technologies in the Internet of Things;265
1.6.1.4.1;27.3.1 RFID Technology;265
1.6.1.4.2;27.3.2 Sensor Network Technology;266
1.6.1.4.3;27.3.3 Embedded Intelligent Technology;267
1.6.1.4.4;27.3.4 Nanotechnology;267
1.6.1.4.5;27.3.5 Cloud Computing Technology;267
1.6.1.5;27.4â¦Development Trends and Prospects;268
1.6.1.6;References;269
1.6.2;28 Hot Topic Detection Research of Internet Public Opinion Based on Affinity Propagation Clustering;270
1.6.2.1;Abstract;270
1.6.2.2;28.1â¦Introduction;270
1.6.2.3;28.2â¦Related Work;271
1.6.2.4;28.3â¦Affinity Propagation;272
1.6.2.5;28.4â¦Hot Topic Detection of IPO Based on Ap Clustering;273
1.6.2.5.1;28.4.1 Data Pretreatment;273
1.6.2.5.2;28.4.2 Similarity Matrix Representation;274
1.6.2.5.3;28.4.3 AP Clustering for IPO;275
1.6.2.5.4;28.4.4 Evaluation Criterion;276
1.6.2.6;28.5â¦Experiment and Discuss;276
1.6.2.7;28.6â¦Conclusions;277
1.6.2.8;Acknowledgment;277
1.6.2.9;References;278
1.6.3;29 TTMP: A Trust-Based Topology Management Protocol for Unstructured P2P Systems;279
1.6.3.1;Abstract;279
1.6.3.2;29.1â¦Introduction;279
1.6.3.3;29.2â¦Related Works;280
1.6.3.4;29.3â¦TTMP Protocol;281
1.6.3.4.1;29.3.1 Overview of TTMP;281
1.6.3.4.2;29.3.2 Trust Model;282
1.6.3.4.2.1;29.3.2.1 Computing Rserv of peer j by peer i;282
1.6.3.4.2.2;29.3.2.2 Computing Rcons of peer i by peer j;283
1.6.3.4.3;29.3.3 Adaptive Topology Management;284
1.6.3.5;29.4â¦Simulation Results;286
1.6.3.6;29.5â¦Conclusions;288
1.6.3.7;References;288
1.6.4;30 Indoor Temperature and Humidity Monitoring System Based on WSN and Fuzzy Strategy;290
1.6.4.1;Abstract;290
1.6.4.2;30.1â¦Introduction;291
1.6.4.3;30.2â¦Monitoring System Design;291
1.6.4.4;30.3â¦Sensor Node Design;292
1.6.4.4.1;30.3.1 Selection of the Embedded Microprocessor;293
1.6.4.4.2;30.3.2 Sensor Selection and Interface Design with Microcontroller;293
1.6.4.4.3;30.3.3 Design of Send and Receive Wireless Data Module;293
1.6.4.4.4;30.3.4 Interface Design Between nRF905 and P89V51RB2;294
1.6.4.4.5;30.3.5 Data Transfer Module;294
1.6.4.5;30.4â¦Fuzzy Control Strategy;294
1.6.4.6;30.5â¦System Software Design;297
1.6.4.7;30.6â¦System Test Results and Analysis;298
1.6.4.8;30.7â¦Summary;299
1.6.4.9;Acknowledgments;299
1.6.4.10;References;299
1.6.5;31 Radioactive Target Detection Using Wireless Sensor Network;300
1.6.5.1;Abstract;300
1.6.5.2;31.1â¦Introduction;300
1.6.5.3;31.2â¦Statistical Method;302
1.6.5.4;31.3â¦Numerical Algorithms;304
1.6.5.5;31.4â¦Simulation Results;306
1.6.5.6;31.5â¦Conclusion;307
1.6.5.7;Acknowledgments;307
1.6.5.8;References;308
1.6.6;32 Optimization of Air Network Applied in the Express Based on Hub-and-Spoke Network: A Case Study of SF Express;309
1.6.6.1;Abstract;309
1.6.6.2;32.1â¦Introduction;309
1.6.6.3;32.2â¦The Model of Hub-and Spoke Network;310
1.6.6.3.1;32.2.1 Put Forward the Hub-and-Spoke Network;310
1.6.6.3.2;32.2.2 Model Assume;310
1.6.6.3.3;32.2.3 Built Model;311
1.6.6.4;32.3â¦The Application of Hub-and-Spoke Network on the Chinese Air Network;312
1.6.6.4.1;32.3.1 The Optimization of Hub-and-spoke Network in Express Air Network;312
1.6.6.4.2;32.3.2 Measure the Real Effectiveness of the Hub-and-Spoke Network;315
1.6.6.5;32.4â¦Conclusion;316
1.6.6.6;Acknowledgment;316
1.6.6.7;References;316
1.6.7;33 Verification and Analysis for Ethernet Protocols with NuSMV;317
1.6.7.1;Abstract;317
1.6.7.2;33.1â¦Introduction;317
1.6.7.3;33.2â¦Modeling CSMA/CD Protocol with NuSMV;318
1.6.7.3.1;33.2.1 Description of Formal Specification;319
1.6.7.3.2;33.2.2 Synchronous Model and Asynchronous Model;322
1.6.7.4;33.3â¦Property Verification;323
1.6.7.5;33.4â¦Traces in NuSMV;324
1.6.7.6;33.5â¦Conclusion;324
1.6.7.7;Acknowledgments;326
1.6.7.8;References;326
1.6.8;34 The Analysis and Modeling on Internet AS-Level Topology Based on K-Core Decomposition;327
1.6.8.1;Abstract;327
1.6.8.2;34.1â¦Introduction;327
1.6.8.3;34.2â¦K-core Decomposition: Main Definitions;328
1.6.8.4;34.3â¦The Distribution on Coreness of the Nodes;329
1.6.8.5;34.4â¦The Linking Trend to Higher Shells;329
1.6.8.6;34.5â¦The Distribution on Links to Higher Shells;331
1.6.8.7;34.6â¦The Modeling Algorithm Based on Coreness;332
1.6.8.8;34.7â¦The Results and Analysis;334
1.6.8.9;34.8â¦Conclusion;335
1.6.8.10;References;335
1.6.9;35 Based on Quasi-IP Address Model of Repeater Coordination;337
1.6.9.1;Abstract;337
1.6.9.2;35.1â¦Introduction;337
1.6.9.3;35.2â¦Model Assumptions;339
1.6.9.4;35.3â¦Symbols;339
1.6.9.5;35.4â¦Coverage of One Repeater;340
1.6.9.6;35.5â¦Number of Users Supported by a Repeater;340
1.6.9.6.1;35.5.1 Differentiation of Repeaters Through the Use of Subaudible Tone;340
1.6.9.6.2;35.5.2 Differentiation of Users Within the Coverage of a Repeater Through the Use of Subaudible Tone;341
1.6.9.6.3;35.5.3 Differentiation of Repeaters and Users Through the Use of Subaudible Voice;341
1.6.9.7;35.6â¦Building a Circular System;342
1.6.9.7.1;35.6.1 Service Area;342
1.6.9.7.2;35.6.2 Calculation Method;342
1.6.9.8;35.7â¦Summary;344
1.6.9.9;References;344
1.6.10;36 Fast Dynamic Mesh Moving Based on Background Grid Morphing;345
1.6.10.1;Abstract;345
1.6.10.2;36.1â¦Introduction;346
1.6.10.3;36.2â¦Dynamic Mesh Moving Based on Delaunay Graph Mapping;347
1.6.10.4;36.3â¦The Ball-Vertex Method;347
1.6.10.5;36.4â¦Boundary Improvement;348
1.6.10.6;36.5â¦The Improved Method Based on Background Grid;349
1.6.10.7;36.6â¦Numerical Examples;350
1.6.10.7.1;36.6.1 Rotation of the Airfoil;350
1.6.10.7.2;36.6.2 Geometries Composed of Segments;351
1.6.10.8;36.7â¦Conclusion;353
1.6.10.9;References;354
1.6.11;37 Research on Network Congestion Control System Based on Continuous Time Model;355
1.6.11.1;Abstract;355
1.6.11.2;37.1â¦Introduction;355
1.6.11.3;37.2â¦The Reasons Caused Network Congestion;356
1.6.11.4;37.3â¦The Modeling of TCP Congestion Control Algorithm;357
1.6.11.5;37.4â¦The Stability Analysis of Congestion Control System;360
1.6.11.6;37.5â¦Summary;361
1.6.11.7;References;361
1.6.12;38 The Realization of OPNET and MATLAB Co-Simulation Based on HLA;362
1.6.12.1;Abstract;362
1.6.12.2;38.1â¦Introduction;362
1.6.12.3;38.2â¦The Mechanism of High Level Architecture;363
1.6.12.4;38.3â¦The Framework and Federates of Co-Simulation;363
1.6.12.4.1;38.3.1 The Framework of Co-Simulation;363
1.6.12.4.2;38.3.2 The OPNET Modeler Federate;363
1.6.12.4.3;38.3.3 The MATLAB Federate;365
1.6.12.5;38.4â¦Example of OPNET and MATLAB s Co-Simulation;366
1.6.12.5.1;38.4.1 The Realization of OPNET Federation;366
1.6.12.5.2;38.4.2 The Realization of OPNET Federation;367
1.6.12.5.3;38.4.3 The Process of Co-Simulation;368
1.6.12.6;Acknowledgments;368
1.6.12.7;References;368
1.7;Part IVData Modeling and ProgrammingLanguages;369
1.7.1;39 Design and Applications of Third Party Integrated Information Security Management System;370
1.7.1.1;Abstract;370
1.7.1.2;39.1â¦Introduction;370
1.7.1.3;39.2â¦Technology Trends at Home and Abroad;371
1.7.1.3.1;39.2.1 Security Risk Analysis Service;371
1.7.1.3.2;39.2.2 Security Evaluation Services;371
1.7.1.3.3;39.2.3 Network Vulnerability Analysis Services;372
1.7.1.3.4;39.2.4 Network Security Incidents Processing Services;372
1.7.1.3.5;39.2.5 Intelligent Decision-Making and Active Defense Services;372
1.7.1.4;39.3â¦Application Design of Information Security Management System;374
1.7.1.4.1;39.3.1 Planning and Design of the System;374
1.7.1.4.2;39.3.2 Whole Framework Design of System;375
1.7.1.5;39.4â¦Conclusion;379
1.7.1.6;Acknowledgments;379
1.7.1.7;References;379
1.7.2;40 A Protocol for a Message System for the Tiles of the Heptagrid, in the Hyperbolic Plane;380
1.7.2.1;Abstract;380
1.7.2.2;40.1â¦Introduction;380
1.7.2.3;40.2â¦The Heptagrid and How To Navigate There;381
1.7.2.4;40.3â¦The Communication Protocol;382
1.7.2.4.1;40.3.1 Absolute and Relative Systems;382
1.7.2.4.2;40.3.2 The Protocol;383
1.7.2.5;40.4â¦The Experiment;385
1.7.2.6;40.5â¦Conclusion;387
1.7.2.7;References;387
1.7.3;41 Monitoring Information System Quality: Between Reality and User Expectation at Bina Nusantara University;389
1.7.3.1;Abstract;389
1.7.3.2;41.1â¦Background;389
1.7.3.3;41.2â¦Methodology;390
1.7.3.4;41.3â¦Theory;390
1.7.3.5;41.4â¦Research Result;392
1.7.3.6;41.5â¦Conclusion;395
1.7.3.7;References;395
1.7.4;42 Ordinal-Set Pair Analysis Prediction Model and Application in Liao River Basin;397
1.7.4.1;Abstract;397
1.7.4.2;42.1â¦Introduction;398
1.7.4.3;42.2â¦Set Pair Analysis Principle;398
1.7.4.4;42.3â¦Annual Runoff Prediction Based on the Ordinal Set Pair Analysis;399
1.7.4.4.1;42.3.1 Annual Runoff Prediction Model Based on the Ordinal Set Pair Analysis;399
1.7.4.4.2;42.3.2 Steps of Annual Runoff Prediction Based on the Ordinal Set Pair Analysis;400
1.7.4.5;42.4â¦Example;401
1.7.4.6;42.5â¦Conclusions;403
1.7.4.7;References;404
1.7.5;43 Integrated RMS Layout and Flow Path Design: Modelling and a Heuristic method;405
1.7.5.1;Abstract;405
1.7.5.2;43.1â¦Introduction;406
1.7.5.3;43.2â¦Integrated Design Modelling;406
1.7.5.4;43.3â¦Integrated Heuristic Design Method;407
1.7.5.4.1;43.3.1 Algorithm Description;407
1.7.5.4.2;43.3.2 The Major Procedures in EMLG;408
1.7.5.5;43.4â¦Computation Cases;409
1.7.5.5.1;43.4.1 Case 1;410
1.7.5.5.2;43.4.2 Case 2 and 3;410
1.7.5.6;43.5â¦Conclusions;412
1.7.5.7;Acknowledgments;412
1.7.5.8;References;412
1.7.6;44 Design and Implementation of Distributed Remote-Reading Water Meter Monitoring System Based on SaaS;414
1.7.6.1;Abstract;414
1.7.6.2;44.1â¦Introduction;414
1.7.6.3;44.2â¦Overall Architecture of the System;415
1.7.6.4;44.3â¦SaaS Pattern and WCF Communication Model;415
1.7.6.5;44.4â¦Design and Implementation of Key Functions in the System;417
1.7.6.5.1;44.4.1 Design and Implementation of the Communication Subsystem;417
1.7.6.5.2;44.4.2 Design and Implementation of Authentication and Authorization;418
1.7.6.5.3;44.4.3 Architecture of Multi-Tenant;419
1.7.6.5.4;44.4.4 Design and Implementation of Data Statistics;419
1.7.6.6;44.5â¦Summary;421
1.7.6.7;References;421
1.7.7;45 Enabling the Traceability of Web Information Access in Laboratory Management via E-CARGO Model;422
1.7.7.1;Abstract;422
1.7.7.2;45.1â¦Introduction;422
1.7.7.3;45.2â¦E-CARGO Model and Related Definitions;423
1.7.7.3.1;45.2.1 E-CARGO Model;423
1.7.7.3.2;45.2.2 Related Definitions;424
1.7.7.4;45.3â¦Problem in Laboratory Information Security Management and the related Algorithms;426
1.7.7.4.1;45.3.1 Algorithm of Harmful Information Reporting;427
1.7.7.4.2;45.3.2 Algorithm for Harmful Information Gathering;428
1.7.7.4.3;45.3.3 Algorithm for Harmful Information Tracing;428
1.7.7.5;45.4â¦Conclusion and Status of Research;429
1.7.7.6;Acknowledgments;429
1.7.7.7;References;429
1.7.8;46 An Improved GVF Snake Model Using Magnetostatic Theory;431
1.7.8.1;Abstract;431
1.7.8.2;46.1â¦Introduction;431
1.7.8.3;46.2â¦Parametric Snake Model;433
1.7.8.4;46.3â¦GVF and MAC Based External Force;434
1.7.8.5;46.4â¦Experimental Results;435
1.7.8.6;46.5â¦Conclusion;438
1.7.8.7;Acknowledgments;439
1.7.8.8;References;439
1.7.9;47 Block Effect Reduction via Model Based Compressive Sensing;441
1.7.9.1;Abstract;441
1.7.9.2;47.1â¦Introduction;441
1.7.9.3;47.2â¦Related Works;442
1.7.9.4;47.3â¦Model Based Compressive Sensing Theory;443
1.7.9.5;47.4â¦Our Approach;444
1.7.9.6;47.5â¦Experimental Results;446
1.7.9.7;47.6â¦Summary;446
1.7.9.8;References;447
1.7.10;48 The Design of Logistics Information Platform for the Yangtze River Delta;449
1.7.10.1;Abstract;449
1.7.10.2;48.1â¦Introduction;449
1.7.10.3;48.2â¦Status of the Yangtze River Delta Logistics;450
1.7.10.4;48.3â¦The requirements of the Logistics Information Platform;450
1.7.10.5;48.4â¦Design logistics platform;451
1.7.10.6;48.5â¦Yangtze River Delta Key Technology Logistics Information Platform;452
1.7.10.7;48.6â¦Summary;454
1.7.10.8;References;455
1.7.11;49 The Case Study for Three Kinds of Mobile Games;456
1.7.11.1;Abstract;456
1.7.11.2;49.1â¦Introduction;457
1.7.11.3;49.2â¦Game Class for Happy Farm Online;458
1.7.11.3.1;49.2.1 Class Design;458
1.7.11.3.2;49.2.2 Game Frameworks;459
1.7.11.3.3;49.2.3 Game Implementations;459
1.7.11.4;49.3â¦Game Class for Plants vs Zombies;461
1.7.11.4.1;49.3.1 Class Design;461
1.7.11.4.2;49.3.2 Game Implementations;463
1.7.11.5;49.4â¦Game Class for Gallant Fighter with Double Blade;464
1.7.11.5.1;49.4.1 Class Design;464
1.7.11.5.2;49.4.2 Gravity Sensing;466
1.7.11.5.3;49.4.3 Game Implementations;466
1.7.11.6;49.5â¦Conclusions and Future Works;467
1.7.11.7;References;467
1.7.12;50 New Methods of Specifying and Modeling Stochastic Concurrent Systems;469
1.7.12.1;Abstract;469
1.7.12.2;50.1â¦Introduction;470
1.7.12.3;50.2â¦Probabilistic Stochastic Automata;470
1.7.12.4;50.3â¦Extended Colored Stochastic Petri Nets;471
1.7.12.4.1;50.3.1 Basic Concepts of ECSPNs;471
1.7.12.4.2;50.3.2 Modeling Methods of ECSPNs;472
1.7.12.4.3;50.3.3 Analysis Methods of ECSPNs;472
1.7.12.5;50.4â¦Generalized Stochastic Extended Bundle Event Structures;473
1.7.12.5.1;50.4.1 Basic Concepts of GSEBEs;473
1.7.12.5.2;50.4.2 Modeling Methods of GSEBESs;474
1.7.12.5.3;50.4.3 Analysis Methods of GSEBESs;474
1.7.12.6;50.5â¦Comparing Between the Two Methods;475
1.7.12.7;50.6â¦Conclusions;475
1.7.12.8;Acknowledgment;476
1.7.12.9;References;476
1.8;Part VDigital Image Processing;477
1.8.1;51 Digital Image Completion Techniques;478
1.8.1.1;Abstract;478
1.8.1.2;51.1â¦Introduction;479
1.8.1.2.1;51.1.1 Problem Description;479
1.8.1.2.2;51.1.2 Evaluation Criterion;479
1.8.1.3;51.2â¦Categories of Image Completion Techniques;480
1.8.1.4;51.3â¦Single Image Based Approaches;481
1.8.1.4.1;51.3.1 Structure Propagation Based Methods;481
1.8.1.4.2;51.3.2 Texture Synthesis Based Methods;482
1.8.1.4.3;51.3.3 Hybrid Methods Based on Structure Propagation and Texture Synthesis;482
1.8.1.4.4;51.3.4 Statistical Learning Based Methods;483
1.8.1.4.5;51.3.5 Interactive Way for Single Image Based Approaches;484
1.8.1.5;51.4â¦Multiple Images Based Approaches;484
1.8.1.6;51.5â¦Future Work;485
1.8.1.7;Acknowledgments;485
1.8.1.8;References;485
1.8.2;52 Application of 2-D Wavelet Transform in Image Compression Based on Matlab;487
1.8.2.1;Abstract;487
1.8.2.2;52.1â¦Introduction;487
1.8.2.3;52.2â¦The Basic Ideal of Wavelet Tranform;488
1.8.2.4;52.3â¦Application of Wavelet Transformation on Image Compression Code;490
1.8.2.5;52.4â¦Experimental Results and Discussion;492
1.8.2.6;52.5â¦Conclusions;493
1.8.2.7;References;495
1.8.3;53 Fingerprint Image Preprocessing Method Based on the Continuous Spectrum Analysis;496
1.8.3.1;Abstract;496
1.8.3.2;53.1â¦Introduction;497
1.8.3.3;53.2â¦Spectrum Analysis Method of Fingerprint Image;498
1.8.3.3.1;53.2.1 The Spectrum Analysis of Different Fingerprint Image Regions;499
1.8.3.3.2;53.2.2 The 3-Dimension Continuous Spectrum of the Fingerprint Image;500
1.8.3.4;53.3â¦Fingerprint Image Segmentation Based on Continuous Spectrum;501
1.8.3.5;53.4â¦The Realization of Fingerprint Image Processing Method;503
1.8.3.6;53.5â¦Experimental Results;503
1.8.3.7;53.6â¦Conclusions and Future Works;506
1.8.3.8;Acknowledgments;506
1.8.3.9;References;506
1.8.4;54 A Zero-Watermarking Algorithm for Digital Map Based on DWT Domain;508
1.8.4.1;Abstract;508
1.8.4.2;54.1â¦Introduction;508
1.8.4.2.1;54.1.1 Grid Map Watermarking Technology;509
1.8.4.2.2;54.1.2 Zero-Watermarking Algorithms;509
1.8.4.3;54.2â¦Zero-Watermarking Algorithm for Grid Map;510
1.8.4.3.1;54.2.1 Embedding Watermarking;510
1.8.4.3.2;54.2.2 Watermark Detection Algorithm;511
1.8.4.4;54.3â¦Experiment;513
1.8.4.5;54.4â¦Conclusion;515
1.8.4.6;Acknowledgments;516
1.8.4.7;References;516
1.8.5;55 A Fault-Tolerance Shortest Routing Algorithm with PDPE on (n, k)-Star Graph for NoC;517
1.8.5.1;Abstract;517
1.8.5.2;55.1â¦Introduction;517
1.8.5.3;55.2â¦(n, k)-Star Graph and Routing;518
1.8.5.3.1;55.2.1 Definitions and Properties of (n, k)-Star;518
1.8.5.3.2;55.2.2 Routing;519
1.8.5.4;55.3â¦Fault-Tolerance Shortest Routing Algorithm with PDPE;519
1.8.5.4.1;55.3.1 Foundation of PDPE Algorithm;519
1.8.5.4.2;55.3.2 The Sorting Rule of Priority of Permutation Elements;520
1.8.5.4.3;55.3.3 PDPE Algorithm;520
1.8.5.4.4;55.3.4 Fault-Tolerance Analysis of PDPE Algorithm;521
1.8.5.5;55.4â¦Simulation;521
1.8.5.6;55.5â¦Conclusion;524
1.8.5.7;References;524
1.8.6;56 A Robust Zero-Watermarking Algorithm for 2D Vector Digital Maps;526
1.8.6.1;Abstract;526
1.8.6.2;56.1â¦Introduction;526
1.8.6.3;56.2â¦The Watermarking Algorithm;527
1.8.6.3.1;56.2.1 Zero-Watermark Generation;528
1.8.6.3.2;56.2.2 Zero-Watermark Extraction;529
1.8.6.4;56.3â¦Experiments and Results;530
1.8.6.5;56.4â¦Conclusions and Future Work;532
1.8.6.6;Acknowledgments;533
1.8.6.7;References;533
1.8.7;57 An Efficient Non-Local Means for Image Denoising;535
1.8.7.1;Abstract;535
1.8.7.2;57.1â¦Introduction;535
1.8.7.3;57.2â¦Method;536
1.8.7.3.1;57.2.1 Non-Local Means;536
1.8.7.3.2;57.2.2 Pre-Classification;537
1.8.7.4;57.3â¦Experimental Results;539
1.8.7.5;57.4â¦Conclusion;542
1.8.7.6;Acknowledgments;542
1.8.7.7;References;542
1.8.8;58 An Efficient Augmented Lagrangian Method for Impulse Noise Removal via Learned Dictionary;543
1.8.8.1;Abstract;543
1.8.8.2;58.1â¦Introduction;543
1.8.8.3;58.2â¦AL Based Dictionary Learning Algorithm;544
1.8.8.3.1;58.2.1 The Sparseness Characteristic of Salt-and-Pepper Noise;544
1.8.8.3.2;58.2.2 The General AL Based Dictionary Learning Framework;545
1.8.8.3.3;58.2.3 An Efficient Inner Solver;546
1.8.8.4;58.3â¦Results;548
1.8.8.5;58.4â¦Conclusion;550
1.8.8.6;Acknowledgments;551
1.8.8.7;References;551
1.8.9;59 Motion Object Segmentation Using Regions Classification and Energy Model;552
1.8.9.1;Abstract;552
1.8.9.2;59.1â¦Introduction;552
1.8.9.3;59.2â¦Spatial Regions Partition;553
1.8.9.4;59.3â¦Initial Regions Classification;554
1.8.9.5;59.4â¦Spatio-Temporal Energy Model for Candidate Regions Selection;554
1.8.9.6;59.5â¦Post-Processing;555
1.8.9.7;59.6â¦Experimental Result;557
1.8.9.8;59.7â¦Conclusions;558
1.8.9.9;References;559
1.8.10;60 A Digital Image Scrambling Method Based on Hopfield Neural Network;560
1.8.10.1;Abstract;560
1.8.10.2;60.1â¦Introduction;560
1.8.10.2.1;60.1.1 Hopfield Neural Network;561
1.8.10.3;60.2â¦Method of Image Processing;561
1.8.10.3.1;60.2.1 Image Block;561
1.8.10.3.2;60.2.2 Image Scrambling Method Based on Hopfield Neural Network;562
1.8.10.4;60.3â¦Simulation Results;563
1.8.10.4.1;60.3.1 Anti-Attacking Test;564
1.8.10.4.2;60.3.2 Noise Attack;564
1.8.10.4.3;60.3.3 JPEG Compression Attack;565
1.8.10.4.4;60.3.4 Cropping Attack;565
1.8.10.5;60.4â¦Conclusion;566
1.8.10.6;References;566
1.8.11;61 Lattice Boltzmann Anisotropic Diffusion Model Based Image Segmentation;567
1.8.11.1;Abstract;567
1.8.11.2;61.1â¦Introduction;568
1.8.11.3;61.2â¦Lattice Boltzmann Model;568
1.8.11.4;61.3â¦Lattice Boltzmann Model for Anisotropic diffusion;570
1.8.11.5;61.4â¦Experimental Analysis;571
1.8.11.5.1;61.4.1 Image Segmentation Algorithm Based on LBADM;571
1.8.11.5.2;61.4.2 Preferences;572
1.8.11.5.3;61.4.3 Experimental Results and Analysis;573
1.8.11.6;61.5â¦Conclusion;574
1.8.11.7;Acknowledgments;574
1.8.11.8;References;574
1.9;Part VIOptimization and Scheduling;576
1.9.1;62 Research on New Distributed Solution Method of Complex System Based on MAS;577
1.9.1.1;Abstract;577
1.9.1.2;62.1â¦Introduction;577
1.9.1.3;62.2â¦Information Agent Formal Description;579
1.9.1.4;62.3â¦Information Agent Task Specification Decomposition Method;580
1.9.1.4.1;62.3.1 Based on GDF Information Agent Task Specification Decomposition Criterion;580
1.9.1.4.2;62.3.2 Based on the BN Task Specification Expressed and Decomposes;581
1.9.1.5;62.4â¦Conclusions;583
1.9.1.6;Acknowledgments;583
1.9.1.7;References;583
1.9.2;63 An Order-Searching Genetic Algorithm for Multi-Dimensional Assignment Problem;585
1.9.2.1;Abstract;585
1.9.2.2;63.1â¦Introduction;585
1.9.2.3;63.2â¦Multi-Dimensional Assignment Model;586
1.9.2.4;63.3â¦Order-Searching Genetic Algorithm;588
1.9.2.4.1;63.3.1 Shortcomings of Order-Searching Algorithm;588
1.9.2.4.2;63.3.2 Genetic Algorithm;588
1.9.2.4.3;63.3.3 Order-Searching Genetic Algorithm;589
1.9.2.5;63.4â¦Simulations;591
1.9.2.5.1;63.4.1 Simulation Model;591
1.9.2.5.2;63.4.2 Simulation Result Analyses;591
1.9.2.6;63.5â¦Conclusions;592
1.9.2.7;Acknowledgments;592
1.9.2.8;References;592
1.9.3;64 The Heuristic Algorithm of Stacking Layer for the Three-Dimensional Packing of Fixed-Size Cargoes;593
1.9.3.1;Abstract;593
1.9.3.2;64.1â¦Introduction;593
1.9.3.3;64.2â¦Problem Definition;594
1.9.3.4;64.3â¦Stacking Layer Method Design;595
1.9.3.4.1;64.3.1 The Concept of Stacking Layer Method;595
1.9.3.4.2;64.3.2 The Two-Step Solving Algorithm for Stacking Layer Method;595
1.9.3.5;64.4â¦Space Utilization Test;597
1.9.3.6;64.5â¦Conclusion;599
1.9.3.7;References;599
1.9.4;65 Research on a Novel Hybrid Optimization Algorithm Based on Agent and Particle Swarm;601
1.9.4.1;Abstract;601
1.9.4.2;65.1â¦Introduction;601
1.9.4.3;65.2â¦Hybrid Optimization Algorithm;602
1.9.4.3.1;65.2.1 MA-PSO Algorithm;603
1.9.4.4;65.3â¦Calculates Example;606
1.9.4.5;65.4â¦Conclusions;608
1.9.4.6;Acknowledgments;608
1.9.4.7;References;608
1.9.5;66 A Novel BCC Algorithm for Function Optimization;610
1.9.5.1;Abstract;610
1.9.5.2;66.1â¦Introduction;610
1.9.5.3;66.2â¦Related Work;611
1.9.5.3.1;66.2.1 BC Algorithm Principle;611
1.9.5.3.2;66.2.2 BCC Algorithm Principle;613
1.9.5.3.3;66.2.3 Chaos Search Strategy;614
1.9.5.4;66.3â¦Algorithm;614
1.9.5.4.1;66.3.1 Overview;614
1.9.5.4.2;66.3.2 Integrating Chaotic Optimization into BCC Algorithm;614
1.9.5.4.3;66.3.3 NBCC Algorithm for Function Optimization Problem;615
1.9.5.5;66.4â¦Numerical Experiments;616
1.9.5.6;66.5â¦Conclusions;617
1.9.5.7;Acknowledgments;617
1.9.5.8;References;617
1.9.6;67 Time--Space Hybrid Markov Model;619
1.9.6.1;Abstract;619
1.9.6.2;67.1â¦Introduction;619
1.9.6.3;67.2â¦Problem Description;620
1.9.6.4;67.3â¦TSHMM Recommendation Algorithm;621
1.9.6.4.1;67.3.1 Time model;621
1.9.6.4.2;67.3.2 Space model;622
1.9.6.4.2.1;67.3.2.0 One-hop and multi-hop model;622
1.9.6.4.2.2;67.3.2.0 One-hop model;622
1.9.6.4.2.3;67.3.2.0 Multi-hop model;622
1.9.6.4.3;67.3.3 TSHMM recommendation algorithm;623
1.9.6.4.4;67.3.4 Discussion;624
1.9.6.5;67.4â¦Experiments;624
1.9.6.6;67.5â¦Conclusion;626
1.9.6.7;References;626
1.9.7;68 Research on Turning Parameters Optimization Based on Genetic Algorithm;627
1.9.7.1;Abstract;627
1.9.7.2;68.1â¦Introduction;627
1.9.7.3;68.2â¦The Objective Functions and Design Variables;628
1.9.7.4;68.3â¦Constraints;628
1.9.7.5;68.4â¦Turning Parameters Optimization;630
1.9.7.5.1;68.4.1 Optimization Result of GA Operation;631
1.9.7.6;68.5â¦Conclusion;632
1.9.7.7;References;633
1.9.8;69 A Power of a Meromorphic Function Sharing 1 IM with Its Derivative;634
1.9.8.1;Abstract;634
1.9.8.2;69.1â¦Introduction;634
1.9.8.3;69.2â¦Some Lemmas;636
1.9.8.4;69.3â¦Proof of Theorem 1;638
1.9.8.5;Acknowledgement;641
1.9.8.6;References;641
1.9.9;70 The Application of Particle Swarm Optimization in Stock Prediction and Analysis;643
1.9.9.1;Abstract;643
1.9.9.2;70.1â¦Introduction;643
1.9.9.3;70.2â¦Stock Prediction and Analysis Means;644
1.9.9.4;70.3â¦The Application of Particle Swarm Optimization on Stock Prediction;645
1.9.9.5;70.4â¦Conclusion;647
1.9.9.6;References;648
1.9.10;71 Research on a Novel Distributed Multi Agent System Plan Method;649
1.9.10.1;Abstract;649
1.9.10.2;71.1â¦Introduction;650
1.9.10.3;71.2â¦Base on Constraint Propagations Distributed-Multi-Agent-Plan;651
1.9.10.4;71.3â¦Arithmetic Distributed-Multi-Agent-Plan (OPS, CaS, I, G);652
1.9.10.5;71.4â¦Conclusion;654
1.9.10.6;Acknowledgment;654
1.9.10.7;References;654
1.9.11;72 A Method of Object Detection Based on Improved Gaussian Mixture Model;656
1.9.11.1;Abstract;656
1.9.11.2;72.1â¦Introduction;657
1.9.11.3;72.2â¦Improved Gaussian Mixture Model;657
1.9.11.3.1;72.2.1 Improved Algorithm Based on Chroma Space;657
1.9.11.3.2;72.2.2 Fast Convergence Algorithm Based on Nearest N-Frame;658
1.9.11.3.3;72.2.3 Algorithm Implementation and Result Analysis;659
1.9.11.4;72.3â¦Conclusion;662
1.9.11.5;References;662
1.9.12;73 A Novel Dynamic Resource Allocation Model Based on MAS Coordination;663
1.9.12.1;Abstract;663
1.9.12.2;73.1â¦Introduction;663
1.9.12.3;73.2â¦MAS Resources Coordinating;664
1.9.12.4;73.3â¦Effectiveness Analyses;666
1.9.12.5;73.4â¦Conclusion;668
1.9.12.6;Acknowledgment;669
1.9.12.7;References;669
1.10;Part VIIEducation and Informatics;670
1.10.1;74 Research on Comprehensive Evaluation of Classroom Teaching Quality Based on Multi-Element Connection Number;671
1.10.1.1;Abstract;671
1.10.1.2;74.1â¦Introduction;671
1.10.1.3;74.2â¦Concept of Set Pair Analysis and Multi-Element Connection Number;672
1.10.1.3.1;74.2.1 Concept of Set Pair Analysis;672
1.10.1.3.2;74.2.2 Concept of Multi-Element Connection Number;673
1.10.1.4;74.3â¦Evaluation Process;674
1.10.1.4.1;74.3.1 Establish Evaluation Index System;674
1.10.1.4.2;74.3.2 Establish the Weight Set;674
1.10.1.4.3;74.3.3 Establish the Evaluation Set;675
1.10.1.4.4;74.3.4 Establish the Evaluation Matrix;675
1.10.1.4.5;74.3.5 First Level Evaluation;676
1.10.1.4.6;74.3.6 Second Level Evaluation;677
1.10.1.4.7;74.3.7 An Analysis of Comprehensive Evaluation Multi-Element Connection Number mu ;677
1.10.1.5;74.4â¦Conclusions;678
1.10.1.6;References;678
1.10.2;75 Program Design of DEA Based on Windows System;679
1.10.2.1;Abstract;679
1.10.2.2;75.1â¦Introduction;679
1.10.2.3;75.2â¦The Algorithm Design of C2R Model and BC2 Model;680
1.10.2.4;75.3â¦The Computer Program Design of C2R Model and BC2 Model;683
1.10.2.4.1;75.3.1 The Structure and Program Design of DEA Software System;683
1.10.2.4.2;75.3.2 The Design of the Input and Output System;686
1.10.2.5;Acknowledgments;687
1.10.2.6;References;687
1.10.3;76 An Incremental and Autonomous Visual Learning Algorithm Based on Internally Motivated Q Learning;688
1.10.3.1;Abstract;688
1.10.3.2;76.1â¦Introduction;689
1.10.3.3;76.2â¦Visual Novelty Based Internal Motivation;690
1.10.3.4;76.3â¦Internally Motivated Q Learning;692
1.10.3.5;76.4â¦Experimental Result and Analysis;694
1.10.3.5.1;76.4.1 Experiment Design;694
1.10.3.5.2;76.4.2 Experimental Result and Analysis;695
1.10.3.6;76.5â¦Conclusion;697
1.10.3.7;Acknowledgments;697
1.10.3.8;References;697
1.10.4;77 Design and Implement of Information System for Water Management Based on SaaS;699
1.10.4.1;Abstract;699
1.10.4.2;77.1â¦Introduction;699
1.10.4.3;77.2â¦Introduction of SaaS;700
1.10.4.4;77.3â¦Design and Implement of Level 3 Maturity Model;700
1.10.4.4.1;77.3.1 Multi-Tenant Data Architecture;700
1.10.4.4.2;77.3.2 Custom Data Model;701
1.10.4.4.3;77.3.3 Configurable Invoice;701
1.10.4.4.4;77.3.4 Configurable User Interface;703
1.10.4.4.4.1;77.3.4.1 Configurable System Menu;703
1.10.4.4.4.2;77.3.4.2 Configurable Page Elements;703
1.10.4.4.5;77.3.5 Configurable Functions;704
1.10.4.5;77.4â¦Conclusions;705
1.10.4.6;References;706
1.10.5;78 Pulse-Based Analysis on Teaching Quality Evaluation;707
1.10.5.1;Abstract;707
1.10.5.2;78.1â¦Introduction;708
1.10.5.3;78.2â¦Emotion, Pulse and Cognition;708
1.10.5.3.1;78.2.1 Emotion and Pulse;708
1.10.5.3.2;78.2.2 Emotion and Cognition;709
1.10.5.4;78.3â¦Pulse Characteristics Parameters;710
1.10.5.4.1;78.3.1 Pulse Position;711
1.10.5.4.2;78.3.2 Pulse Rate;711
1.10.5.4.3;78.3.3 Pulse Presentation;711
1.10.5.5;78.4â¦Teaching Evaluation Model;712
1.10.5.5.1;78.4.1 Emotional Model;712
1.10.5.5.2;78.4.2 Teaching Evaluation Model;714
1.10.5.6;78.5â¦Conclusions;714
1.10.5.7;References;715
1.10.6;79 French Learning Online Platform: French Livehand;716
1.10.6.1;Abstract;716
1.10.6.2;79.1â¦Introduction;716
1.10.6.3;79.2â¦Design and Implementation;717
1.10.6.3.1;79.2.1 ExtJS;717
1.10.6.3.2;79.2.2 Struts2;718
1.10.6.4;79.3â¦Main Functions;718
1.10.6.4.1;79.3.1 Intelligent Word-Searching System;718
1.10.6.4.2;79.3.2 Translation System;718
1.10.6.4.3;79.3.3 Scene System;719
1.10.6.4.4;79.3.4 Grammar System;719
1.10.6.4.5;79.3.5 User Management System;720
1.10.6.5;79.4â¦Conclusion;720
1.10.6.6;References;721
1.10.7;80 Application of Text Data Mining to Education in Long-Distance;722
1.10.7.1;Abstract;722
1.10.7.2;80.1â¦Introduction;722
1.10.7.3;80.2â¦Vector Space Model;723
1.10.7.4;80.3â¦The Recommendation of the Corresponding Web Page Hyperlink Method;724
1.10.7.5;80.4â¦The Recommended Method Based on Cooperation;724
1.10.7.6;80.5â¦Conclusion;727
1.10.7.7;References;727
1.11;Part VIIIFuzzy System and Control;729
1.11.1;81 Adaptive Disturbance Rejection Control of Linear Time Varying System;730
1.11.1.1;Abstract;730
1.11.1.2;81.1â¦Introduction;730
1.11.1.3;81.2â¦Preliminary;731
1.11.1.4;81.3â¦Main Results;733
1.11.1.5;81.4â¦Illustrative Example;735
1.11.1.6;81.5â¦Conclusion;736
1.11.1.7;References;737
1.11.2;82 Nonlinear Predictive Functional Control Based on Support Vector Machine;738
1.11.2.1;Abstract;738
1.11.2.2;82.1â¦Introduction;738
1.11.2.3;82.2â¦Support Vector Machine for Regression;739
1.11.2.4;82.3â¦PFC Based on SVM;740
1.11.2.4.1;82.3.1 Nonlinear Predictive Model Based on SVM;740
1.11.2.4.2;82.3.2 Reference Trajectory;742
1.11.2.4.3;82.3.3 Modeling Error Compensation;742
1.11.2.4.4;82.3.4 PFC Optimal Control law for Step Setpoint;743
1.11.2.4.5;82.3.5 PFC Optimal Control law for Ramp Setpoint;743
1.11.2.4.6;82.3.6 NPFC Control Algorithm Based on SVM;744
1.11.2.5;82.4â¦Simulation Study;745
1.11.2.6;82.5â¦Conclusions;746
1.11.2.7;References;747
1.11.3;83 Analysis and Circuit Simulation of a New Four-Dimensional Lorenz Time-Delay Chaotic System;748
1.11.3.1;Abstract;748
1.11.3.2;83.1â¦Introduction;748
1.11.3.3;83.2â¦Description of System Model;749
1.11.3.3.1;83.2.1 Simulation of the Constructed Time-delay System;749
1.11.3.3.2;83.2.2 Stability Analysis of the New Time-Delay System;750
1.11.3.4;83.3â¦Time-Delay Oscillator Circuit;752
1.11.3.4.1;83.3.1 Design of Chaotic Switching Circuit;752
1.11.3.4.2;83.3.2 Time-Delay Circuit Unit;754
1.11.3.5;83.4â¦Conclusion;755
1.11.3.6;Acknowledgments;755
1.11.3.7;References;756
1.11.4;84 The Design of Adaptive PI Speed Controller for Permanent Magnet Synchronous Motor Servo System;757
1.11.4.1;Abstract;757
1.11.4.2;84.1â¦Introduction;757
1.11.4.3;84.2â¦Mathematical Model of the PMSM;758
1.11.4.4;84.3â¦Identification RBFNN Based on IPSO Algorithm;759
1.11.4.4.1;84.3.1 RBFNN;759
1.11.4.4.2;84.3.2 IPSO Algorithm;760
1.11.4.4.3;84.3.3 Identification RBFNN;761
1.11.4.4.4;84.3.4 Designe of Adaptive Speed Controller Based on RBFNN;762
1.11.4.5;84.4â¦Simulation Results;763
1.11.4.6;84.5â¦Conclusion;764
1.11.4.7;References;764
1.11.5;85 Application of BP Neural Network in Faults Diagnosis of Process Valve Actuator;766
1.11.5.1;Abstract;766
1.11.5.2;85.1â¦Introduction;767
1.11.5.3;85.2â¦Experimental Test Rig;768
1.11.5.3.1;85.2.1 Pneumatic Control Valve;768
1.11.5.3.2;85.2.2 The Set of Available Signals;768
1.11.5.3.3;85.2.3 Control Valve Faults;769
1.11.5.4;85.3â¦BP Neural Network;770
1.11.5.4.1;85.3.1 Network Structure;770
1.11.5.4.2;85.3.2 Network Training;771
1.11.5.5;85.4â¦Results;772
1.11.5.6;85.5â¦Conclusions;773
1.11.5.7;References;774
1.11.6;86 Optimal Detection of Distributed Target with Fluctuating Scatterers;775
1.11.6.1;Abstract;775
1.11.6.2;86.1â¦Introduction;775
1.11.6.3;86.2â¦Problem Formulation;776
1.11.6.4;86.3â¦Binary Integrator;777
1.11.6.5;86.4â¦Optimal Detection Threshold;778
1.11.6.6;86.5â¦Conclusions;781
1.11.6.7;Acknowledgments;781
1.11.6.8;References;781
1.11.7;87 Output Feedback Control for an Active Heave Compensation System;783
1.11.7.1;Abstract;783
1.11.7.2;87.1â¦Introduction;783
1.11.7.3;87.2â¦Problem Formulation;784
1.11.7.4;87.3â¦Adaptive Observer Design;786
1.11.7.5;87.4â¦Controller Design;788
1.11.7.6;87.5â¦Simulation Results;791
1.11.7.7;87.6â¦Conclusions;792
1.11.7.8;Acknowledgments;792
1.11.7.9;References;792
1.11.8;88 Models for Multiple Attribute Decision Making with Intuitionistic Trapezoidal Information;793
1.11.8.1;Abstract;793
1.11.8.2;88.1â¦Introduction;793
1.11.8.3;88.2â¦Preliminaries;794
1.11.8.4;88.3â¦Models for Multiple Attribute Decision Making with Intuitionistic Trapezoidal Fuzzy Information;795
1.11.8.5;88.4â¦Conclusion;796
1.11.8.6;References;797
1.11.9;89 Modeling the Risk Factors in Ergonomic Processes Using Fuzzy Logic;798
1.11.9.1;Abstract;798
1.11.9.2;89.1â¦Introduction;798
1.11.9.3;89.2â¦Literature Survey;799
1.11.9.4;89.3â¦Mathematical Proposition;800
1.11.9.5;89.4â¦Proposed Algorithm;801
1.11.9.5.1;89.4.1 Data Set and Analysis;802
1.11.9.6;89.5â¦Conclusion;802
1.11.9.7;References;803
1.11.10;90 Modified Projective Synchronization of Uncertain Chaotic Systems;804
1.11.10.1;Abstract;804
1.11.10.2;90.1â¦Introduction;804
1.11.10.3;90.2â¦Synchronization Criteria;805
1.11.10.4;90.3â¦Conclusions;809
1.11.10.5;Acknowledgment;809
1.11.10.6;References;809
1.11.11;91 Multi-Agent Based Architecture Supporting Collaborative Product Lightweight Design;810
1.11.11.1;Abstract;810
1.11.11.2;91.1â¦Introduction;811
1.11.11.3;91.2â¦Related Work;812
1.11.11.3.1;91.2.1 Agent and Multi-Agent System;812
1.11.11.3.2;91.2.2 Collaborative Product Lightweight Design Systems;812
1.11.11.4;91.3â¦Generic System Architecture Supporting Collaborative Product Lightweight;812
1.11.11.4.1;91.3.1 Generic System Architecture;812
1.11.11.4.2;91.3.2 CAX Agent;814
1.11.11.5;91.4â¦Operation Process of the System;815
1.11.11.6;91.5â¦Conclusion;816
1.11.11.7;Acknowledgments;817
1.11.11.8;References;817
1.11.12;92 Fuzzy Controller Design with Fault Diagnosis System Condition On-line Monitor Using Neural Network;819
1.11.12.1;Abstract;819
1.11.12.2;92.1â¦Introduction;819
1.11.12.3;92.2â¦Fuzzy Controller Design;821
1.11.12.3.1;92.2.1 Fuzzy Control Strategy;821
1.11.12.3.2;92.2.2 Error Percent Determination;824
1.11.12.4;92.3â¦System Condition On-line Monitor Using Neural Network;825
1.11.12.4.1;92.3.1 Network Structure;825
1.11.12.4.2;92.3.2 Training Data;826
1.11.12.4.3;92.3.3 Network Training;826
1.11.12.5;92.4â¦Practical Implementation;827
1.11.12.6;92.5â¦Conclusions;828
1.11.12.7;References;829
1.12;Part IXForensics, Recognition Technologies andApplications;830
1.12.1;93 Fingerprint Orientation Template Matching Based on Mutual Information;831
1.12.1.1;Abstract;831
1.12.1.2;93.1â¦Introduction;832
1.12.1.3;93.2â¦Mutual Information;833
1.12.1.4;93.3â¦Estimation and Quantization of Fingerprint Orientation;834
1.12.1.5;93.4â¦MI of Fingerprint Orientation;834
1.12.1.6;93.5â¦Fingerprint Matching;836
1.12.1.7;93.6â¦Experimental Results and Conclusion;836
1.12.1.8;References;837
1.12.2;94 Human Action Recognition Algorithm Based on Minimum Spanning Tree;839
1.12.2.1;Abstract;839
1.12.2.2;94.1â¦Introduction;839
1.12.2.3;94.2â¦Human Motion Levels Model;840
1.12.2.3.1;94.2.1 Human Body and Texture Model;840
1.12.2.3.2;94.2.2 Cluster-Based Motion Model of the Relevant Action;841
1.12.2.4;94.3â¦Spanning Tree Algorithm Based on RPC;841
1.12.2.5;94.4â¦Human Actions Recognition Algorithm;843
1.12.2.5.1;94.4.1 The 2D Model Reasoning Based on the RPC;843
1.12.2.5.2;94.4.2 The 3D Human Motion Reasoning;844
1.12.2.5.3;94.4.3 Proposal Function;844
1.12.2.6;94.5â¦Experiment Analysis;845
1.12.2.7;Acknowledgments;846
1.12.2.8;References;846
1.12.3;95 Analysis of Selvi et al. s Identity-Based Threshold Signcryption Scheme;848
1.12.3.1;Abstract;848
1.12.3.2;95.1â¦Introduction;848
1.12.3.3;95.2â¦Preliminaries;850
1.12.3.3.1;95.2.1 Bilinear Pairing;850
1.12.3.3.2;95.2.2 Computational Problems;850
1.12.3.3.3;95.2.3 Identity Based Threshold Signcryption;850
1.12.3.4;95.3â¦Review of Selvi et al. s Identity-Based Threshold Signcryption Scheme;851
1.12.3.5;95.4â¦Cryptanalysis of Selvi et al. s Scheme;852
1.12.3.6;95.5â¦Conclusion;853
1.12.3.7;References;854
1.12.4;96 Analysis of an Authenticated 3-Round Identity-Based Group Key Agreement Protocol;856
1.12.4.1;Abstract;856
1.12.4.2;96.1â¦Introduction;856
1.12.4.3;96.2â¦Paper Preparation;857
1.12.4.3.1;96.2.1 Bilinear Pairing;857
1.12.4.3.2;96.2.2 Computational Problems;858
1.12.4.3.3;96.2.3 Introduction of BR Security Model;858
1.12.4.4;96.3â¦Review of Gang Yao et al. s Protocol;859
1.12.4.5;96.4â¦Cryptanalysis of Gang Yao et al. s protocol;861
1.12.4.6;96.5â¦Conclusions;862
1.12.4.7;Acknowledgments;862
1.12.4.8;References;862
1.12.5;97 Research on ECC Digital Certificate in ATN;864
1.12.5.1;Abstract;864
1.12.5.2;97.1â¦Introduction;864
1.12.5.3;97.2â¦The Application of Digital certificates in the ATN Air-Ground Communication;865
1.12.5.3.1;97.2.1 Key Establishment Phase;865
1.12.5.3.2;97.2.2 Application Service Communication Phase;866
1.12.5.4;97.3â¦A ATN-ECC Structure Digital Certificate;866
1.12.5.5;97.4â¦Certificate Requests, Issue and Compression;867
1.12.5.5.1;97.4.1 Certificate Request;867
1.12.5.5.2;97.4.2 Certificate Issue;868
1.12.5.5.3;97.4.3 Compression Certificate;868
1.12.5.6;97.5â¦Performance Analysis;869
1.12.5.6.1;97.5.1 Size of the Key and Certificate;869
1.12.5.6.2;97.5.2 Computing Time;870
1.12.5.7;97.6â¦Conclusions;871
1.12.5.8;References;871
1.12.6;98 A Robust Method Based on Static Hand Gesture Recognition for Human--Computer Interaction Under Complex Background;873
1.12.6.1;Abstract;873
1.12.6.2;98.1â¦Introduction;873
1.12.6.3;98.2â¦Hand Region Segmentation and Extracting Features;875
1.12.6.3.1;98.2.1 Image Binaryzation by Otsu Algorithm;875
1.12.6.3.2;98.2.2 Find Contours and Calculate Their Area;875
1.12.6.3.3;98.2.3 Extracting Features;876
1.12.6.4;98.3â¦Classifier Construction;876
1.12.6.4.1;98.3.1 Support Vector Machines;877
1.12.6.4.2;98.3.2 Data Set Training;877
1.12.6.4.3;98.3.3 Classifying the Hand Gesture and Non-Hand Gestures;878
1.12.6.5;98.4â¦Experimental Results;879
1.12.6.5.1;98.4.1 Experiments on Testing Samples;879
1.12.6.5.2;98.4.2 Tests on Real-Time;879
1.12.6.6;98.5â¦Conclusion;880
1.12.6.7;Acknowledgment;880
1.12.6.8;References;880
1.12.7;99 Research on Privacy Preserving Based on K-Anonymity;881
1.12.7.1;Abstract;881
1.12.7.2;99.1â¦Introduction;881
1.12.7.3;99.2â¦K-Anonymity Model;882
1.12.7.4;99.3â¦K-Anonymity Model for the Main Algorithm;882
1.12.7.4.1;99.3.1 Generalization and Suppression;882
1.12.7.4.2;99.3.2 The Enhanced K-Anonymity Model;884
1.12.7.4.2.1;99.3.2.1 L-Diversity Model;884
1.12.7.4.2.2;99.3.2.2 ( alpha , k)-Anonymous Model;884
1.12.7.4.2.3;99.3.2.3 ( alpha , L)-Diversification K-Anonymity Model;885
1.12.7.5;99.4â¦Development Trend and Summary;888
1.12.7.6;Acknowledgments;888
1.12.7.7;References;888
1.12.8;100 Existential Forgery Attack Against One Strong Signature Scheme;890
1.12.8.1;Abstract;890
1.12.8.2;100.1â¦Introduction;890
1.12.8.3;100.2â¦Preliminary;892
1.12.8.4;100.3â¦Review of the GMY Strong Signature;893
1.12.8.4.1;100.3.1 Setup;893
1.12.8.4.2;100.3.2 Signing;893
1.12.8.4.3;100.3.3 Verification;894
1.12.8.5;100.4â¦An Existential Forgery to the GMY Strong Signature;895
1.12.8.5.1;100.4.1 The Basic Idea;895
1.12.8.5.2;100.4.2 Attack;896
1.12.8.5.3;100.4.3 Correctness;897
1.12.8.6;100.5â¦Conclusion;898
1.12.8.7;Acknowledgements;898
1.12.8.8;References;898
1.12.9;101 Improved Min-Sum Decoding Algorithm for Moderate Length Low Density Parity Check Codes;899
1.12.9.1;Abstract;899
1.12.9.2;101.1â¦Introduction;899
1.12.9.3;101.2â¦Representation of LDPC Codes;901
1.12.9.3.1;101.2.1 Algebraic Representation;901
1.12.9.3.2;101.2.2 Tanner Graph Representation;901
1.12.9.3.3;101.2.3 LDPC Min-Sum Decoding Algorithm;902
1.12.9.4;101.3â¦Modified Min-Sum Decoding Algorithm;903
1.12.9.4.1;101.3.1 Variable Message Update Conditions;903
1.12.9.4.2;101.3.2 Method for Variable Message Correction;904
1.12.9.4.3;101.3.3 Hardware Implementation and Complexity Analysis;905
1.12.9.5;101.4â¦Simulation Results;905
1.12.9.6;101.5â¦Comparison and Analysis;905
1.12.9.7;101.6â¦Conclusion;906
1.12.9.8;Acknowledgments;907
1.12.9.9;References;907
1.12.10;102 Cryptanalysis of an Authentication Protocol for Session Initiation Protocol;908
1.12.10.1;Abstract;908
1.12.10.2;102.1â¦Introduction;908
1.12.10.3;102.2â¦Review of Chen et al. s Scheme;909
1.12.10.3.1;102.2.1 Setup Phase;910
1.12.10.3.2;102.2.2 Mutual Authentication with Key Agreement Phase;910
1.12.10.4;102.3â¦Weaknesses of Chen et al. s Scheme;911
1.12.10.4.1;102.3.1 Off-line Password Guessing Attack and Forgery Attack;911
1.12.10.4.2;102.3.2 Perfect Forward Secrecy;912
1.12.10.4.3;102.3.3 Other Weakness;912
1.12.10.5;102.4â¦The Proposed Scheme for SIP;912
1.12.10.5.1;102.4.1 Setup Phase;912
1.12.10.5.2;102.4.2 Mutual Authentication with Key Agreement Phase;913
1.12.10.6;102.5â¦Security Analysis;914
1.12.10.6.1;102.5.1 Password Guessing Attack and Smart Card Lost Attack;914
1.12.10.6.2;102.5.2 Replay Attack and Forgery Attack;914
1.12.10.6.3;102.5.3 Denning--Sacco Attack;914
1.12.10.6.4;102.5.4 Known-Key Security and Session Key Security;914
1.12.10.6.5;102.5.5 Perfect Forward Security;915
1.12.10.7;102.6â¦Conclusions;915
1.12.10.8;Acknowledgment;915
1.12.10.9;References;915
1.12.11;103 A Cognitive Model in Biomimetic Pattern Recognition and Its Applications;916
1.12.11.1;Abstract;916
1.12.11.2;103.1â¦Introduction;916
1.12.11.2.1;103.1.1 Face Recognition;917
1.12.11.2.2;103.1.2 Keywords Recognition;917
1.12.11.3;103.2â¦Cognitive Algorithm;917
1.12.11.3.1;103.2.1 Cognitive Model;917
1.12.11.3.2;103.2.2 Cognitive Algorithm;918
1.12.11.3.3;103.2.3 Recognition Algorithm;918
1.12.11.4;103.3â¦Application in Face Recognition;919
1.12.11.4.1;103.3.1 Experiments and Results;919
1.12.11.4.2;103.3.2 Results Analysis;920
1.12.11.5;103.4â¦Application in Keywords Recognition;920
1.12.11.5.1;103.4.1 Experiments and Results;920
1.12.11.5.2;103.4.2 Results Analysis;920
1.12.11.6;103.5â¦Conclusion;922
1.12.11.7;References;923
1.12.12;104 One Way to Enhance the Security of Mobile Payment System Based on Smart TF Card;924
1.12.12.1;Abstract;924
1.12.12.2;104.1â¦Introduction;925
1.12.12.3;104.2â¦Related Works;925
1.12.12.3.1;104.2.1 Identity Authentication Method in Mobile Payment Process;925
1.12.12.3.2;104.2.2 Mechanism of Data Encryption;926
1.12.12.4;104.3â¦Smart TF Card Based Security Improvement Method;927
1.12.12.4.1;104.3.1 Mobile Phone Client System;927
1.12.12.4.1.1;104.3.1.1 Smart Card;927
1.12.12.4.1.2;104.3.1.2 Firmware of Smart Card;927
1.12.12.4.1.3;104.3.1.3 Mobile Phone Software;927
1.12.12.4.2;104.3.2 Double Factor Authentication of User Identity;928
1.12.12.4.3;104.3.3 Two-Way Identity Authentication Protocol;928
1.12.12.5;104.4â¦Implementation of the Method;930
1.12.12.5.1;104.4.1 Internal Structure of Z8D64U Chip;930
1.12.12.5.2;104.4.2 State Transition of Firmware;930
1.12.12.6;104.5â¦Conclusion;932
1.12.12.7;References;932
1.12.13;105 Localization on Discrete Grid Graphs;934
1.12.13.1;Abstract;934
1.12.13.2;105.1â¦Introduction;935
1.12.13.3;105.2â¦Grid Graphs Planning Tasks;935
1.12.13.4;105.3â¦Logical Model;936
1.12.13.5;105.4â¦Robot Experimental Setup;937
1.12.13.6;105.5â¦Summary;940
1.12.13.7;References;940
1.13;Part XElectronic Applications;942
1.13.1;106 The Research of Chinese Q&A System Based on Similarity Algorithm;943
1.13.1.1;Abstract;943
1.13.1.2;106.1â¦Introduction;943
1.13.1.3;106.2â¦The Theoretical Basis of Chinese Question Answering System;944
1.13.1.3.1;106.2.1 HowNet Structure;944
1.13.1.3.2;106.2.2 The Classification of Chinese Question Answering System;944
1.13.1.3.2.1;106.2.2.1 Field Classification;944
1.13.1.3.2.2;106.2.2.2 Characteristics Classification;945
1.13.1.3.3;106.2.3 Characteristics of Chinese Information Processing;945
1.13.1.3.4;106.2.4 Questions Eigenvector Extraction;945
1.13.1.4;106.3â¦Chinese Q&A System Model;945
1.13.1.4.1;106.3.1 Framework of Chinese Q&A System;946
1.13.1.4.2;106.3.2 Questions Pretreatment;946
1.13.1.4.2.1;106.3.2.1 Chinese Word Segmentation and Part-of-Speech Tagging;946
1.13.1.4.2.2;106.3.2.2 Determination of Questions Categories;947
1.13.1.4.2.3;106.3.2.3 The Extraction of Keywords;947
1.13.1.4.2.4;106.3.2.4 Keywords Expansion;947
1.13.1.4.3;106.3.3 Weighted Feature Statements Similarity Calculation;947
1.13.1.4.3.1;106.3.3.1 Words Similarity;947
1.13.1.4.3.2;106.3.3.2 Morphological Similarity;948
1.13.1.4.3.3;106.3.3.3 The Similarity of Trace Word Order;949
1.13.1.4.3.4;106.3.3.4 Structural Similarity;949
1.13.1.4.3.5;106.3.3.5 The Similarity of Sentence Length;949
1.13.1.4.3.6;106.3.3.6 Semantic Similarity;950
1.13.1.4.3.7;106.3.3.7 Sentence Similarity;950
1.13.1.4.4;106.3.4 Answer Extraction;950
1.13.1.4.4.1;106.3.4.1 Track of Sentence Similarity Sorting;950
1.13.1.4.4.2;106.3.4.2 The Mandatory Keywords Filtering Rainfall Distribution;950
1.13.1.4.4.3;106.3.4.3 The Rule Final Answer Extraction Technology;950
1.13.1.5;106.4â¦Experimental Results and Analysis;951
1.13.1.6;106.5â¦Conclusion;951
1.13.1.7;References;952
1.13.2;107 A Model-Driven Method for Service-Oriented Modeling and Design Based on Domain Ontology;953
1.13.2.1;Abstract;953
1.13.2.2;107.1â¦Introduction;953
1.13.2.3;107.2â¦Our Approach;954
1.13.2.4;107.3â¦Domain Modeling;955
1.13.2.5;107.4â¦Mapping and Modeling in PIM Layer;956
1.13.2.6;107.5â¦Mapping and Modeling in PSM Layer;958
1.13.2.7;107.6â¦Conclusion and Future Work;960
1.13.2.8;References;960
1.13.3;108 Design of Three-Dimensional Garage Monitoring System Based on WinCC;961
1.13.3.1;Abstract;961
1.13.3.2;108.1â¦Introduction;962
1.13.3.3;108.2â¦Automatic Three-Dimensional Garage;962
1.13.3.3.1;108.2.1 Working Principles;962
1.13.3.3.2;108.2.2 Monitoring System Constitutes;963
1.13.3.4;108.3â¦Design and Implementation on Monitoring System;963
1.13.3.4.1;108.3.1 The Design of Host Computer Software;963
1.13.3.4.1.1;108.3.1.1 The Abstraction of System Model;963
1.13.3.4.1.2;108.3.1.2 The Program of Model Transformation;964
1.13.3.4.2;108.3.2 The Implementation of Monitoring System;964
1.13.3.5;108.4â¦Communication Realization;965
1.13.3.5.1;108.4.1 Control Panel Setting;965
1.13.3.5.2;108.4.2 Setting of WinCC;965
1.13.3.5.3;108.4.3 The Connection and Realization of the System Communication;966
1.13.3.6;108.5â¦Conclusion;967
1.13.3.7;Acknowledgments;967
1.13.3.8;References;968
1.13.4;109 A Hybrid Modeling Method for Service-Oriented C4ISR Requirements Analysis;969
1.13.4.1;Abstract;969
1.13.4.2;109.1â¦Introduction;969
1.13.4.3;109.2â¦Ontology Definitions;970
1.13.4.4;109.3â¦Modeling Process;972
1.13.4.5;109.4â¦Conclusions and Future Works;976
1.13.4.6;References;976
1.13.5;110 Study on Normalized Operation of Internet Drugs Market;978
1.13.5.1;Abstract;978
1.13.5.2;110.1â¦Introduction;979
1.13.5.3;110.2â¦Regulation Status in Quo of Internet Drugs Market;979
1.13.5.3.1;110.2.1 Current Laws and Regulations;979
1.13.5.3.2;110.2.2 Regulation Status;980
1.13.5.4;110.3â¦Problems in Normalized Operation of Internet Drugs;981
1.13.5.4.1;110.3.1 Related Laws and Regulations of Internet Drugs Transaction are Imperfect;981
1.13.5.4.2;110.3.2 Monitoring Methods of Internet Drugs Information;981
1.13.5.4.3;110.3.3 Lacking of Consumer Privacy Protection Measures;982
1.13.5.5;110.4â¦Countermeasures;982
1.13.5.5.1;110.4.1 Legal System of Internet Drug Transactions Regulation;982
1.13.5.5.2;110.4.2 High-Tech Means for Internet Drug Transaction Regulation;983
1.13.5.5.3;110.4.3 Appropriate Measures to Protect Consumers Privacy;983
1.13.5.5.4;110.4.4 Regulation on Medicines from International Online Pharmacies;983
1.13.5.5.5;110.4.5 Publicity Work;984
1.13.5.6;110.5â¦Conclusions;984
1.13.5.7;References;984
1.13.6;111 Study on Accounting Shenanigan in Universities Using Improved Game Theory;986
1.13.6.1;Abstract;986
1.13.6.2;111.1â¦Introduction;987
1.13.6.3;111.2â¦Accounting Shenanigans in Universities;988
1.13.6.3.1;111.2.1 Jobbery;988
1.13.6.3.2;111.2.2 Organized Crime;988
1.13.6.3.3;111.2.3 Small Private Treasury;989
1.13.6.4;111.3â¦Accounting Shenanigans Analysis via Improved Game Theory;990
1.13.6.4.1;111.3.1 The Evolutionary Game Characteristics of Government and Universities;990
1.13.6.4.2;111.3.2 Dynamic Replication Equation between Government and Universities;990
1.13.6.5;111.4â¦Stability Analysis of Evolutionary Stable Strategy between Government and Universities;991
1.13.6.6;111.5â¦Conclusions;992
1.13.6.7;References;993
1.13.7;112 Improved Iterative Decoding Algorithm for Turbo Codes;994
1.13.7.1;Abstract;994
1.13.7.2;112.1â¦Introduction;994
1.13.7.3;112.2â¦Log-MAP and SOVA;995
1.13.7.3.1;112.2.1 Log-MAP Algorithm;995
1.13.7.3.2;112.2.2 SOVA;996
1.13.7.3.2.1;112.2.2.1 Computing the Accumulative Path Metric;996
1.13.7.3.2.2;112.2.2.2 Computing a Soft Decision Value;996
1.13.7.3.2.3;112.2.2.3 Computing Extrinsic Information Before Updating Soft Decision Value;996
1.13.7.4;112.3â¦Improved Iterative Decoding Algorithm;997
1.13.7.4.1;112.3.1 Complexity Reduction by Combining SOVA and Log-MAP Iterations;997
1.13.7.4.2;112.3.2 Initializing a Priori Input for Log-MAP Iterations by Selecting Extrinsic Output from SOVA Iterations;998
1.13.7.5;112.4â¦Simulations;999
1.13.7.6;112.5â¦Conclusions;1001
1.13.7.7;References;1002
1.13.8;113 Financial Evaluation of the Listed Companies Based on Statistical Analysis Methods;1003
1.13.8.1;Abstract;1003
1.13.8.2;113.1â¦Introduction;1003
1.13.8.3;113.2â¦Methods and Sample Analysis;1004
1.13.8.4;113.3â¦Comprehensive Evaluation;1007
1.13.8.4.1;113.3.1 Factor Analysis Evaluation;1007
1.13.8.4.2;113.3.2 Cluster Analysis and Discriminated Results;1009
1.13.8.4.3;113.3.3 Cluster Statistical Feature;1010
1.13.8.4.4;113.3.4 Cluster Results Evaluation;1010
1.13.8.5;113.4â¦Conclusions;1011
1.13.8.6;References;1011
1.13.9;114 Research of the Timer Granularity Based on Linux;1012
1.13.9.1;Abstract;1012
1.13.9.2;114.1â¦Preface;1013
1.13.9.3;114.2â¦Implementation of Clock Granularity Detailing;1013
1.13.9.3.1;114.2.1 Choice of Optimization Scheme;1013
1.13.9.3.2;114.2.2 Implement of Optimization Scheme;1014
1.13.9.4;114.3â¦Experiment;1016
1.13.9.5;114.4â¦Conclusion;1018
1.13.9.6;Acknowledgements;1018
1.13.9.7;References;1018
1.13.10;115 A New Software to Realize the Optimization of City Sound-Planning;1019
1.13.10.1;Abstract;1019
1.13.10.2;115.1â¦Initial Clue Come from Questing a City Sound Phenomenon;1019
1.13.10.3;115.2â¦Three New Theories to Describe the Interactions Between Neighboring Sound Spaces;1020
1.13.10.4;115.3â¦A New Database to Represent Sound Spaces;1021
1.13.10.5;115.4â¦Realization of the Optimization of City Sound-Planning;1023
1.13.10.6;115.5â¦Prospects;1026
1.13.10.7;References;1026
1.14;Part XIGraphics and Visualizing;1027
1.14.1;116 Automatic Classification and Recognition of Particles in Urinary Sediment Images;1028
1.14.1.1;Abstract;1028
1.14.1.2;116.1â¦Introduction;1028
1.14.1.3;116.2â¦Theoretical Background;1029
1.14.1.4;116.3â¦Algorithm Design;1031
1.14.1.5;116.4â¦Experiment Results;1032
1.14.1.6;116.5â¦Conclusion and Discussion;1034
1.14.1.7;References;1034
1.14.2;117 Ultrasound Strain and Strain Rate Imaging of the Early Sage of Carotid Artery with Type 2 Diabetes Mellitus;1036
1.14.2.1;Abstract;1036
1.14.2.2;117.1â¦Methods;1037
1.14.2.3;117.2â¦Statistical Analysis;1039
1.14.2.4;117.3â¦Results;1039
1.14.2.5;117.4â¦Discussion;1039
1.14.2.6;117.5â¦Conclusion:;1043
1.14.2.7;References;1043
1.14.3;118 Rate Control for Multi-View Video Coding Based on Statistical Analysis and Frame Complexity Estimation;1045
1.14.3.1;Abstract;1045
1.14.3.2;118.1â¦Introduction;1045
1.14.3.3;118.2â¦The Proposed Rate Control Algorithm for MVC;1046
1.14.3.3.1;118.2.1 Target Bit Rate Allocation Scheme for View Level;1047
1.14.3.3.2;118.2.2 Target Bit Rate Allocation Scheme for GOP Level;1049
1.14.3.4;118.3â¦Experiment Results;1050
1.14.3.5;118.4â¦Conclusion and Future Work;1052
1.14.3.6;Acknowledgments;1053
1.14.3.7;References;1053
1.14.4;119 Time-Consistent Preprocessing of Depth Maps for Depth Coding in 3DTV;1054
1.14.4.1;Abstract;1054
1.14.4.2;119.1â¦Introduction;1054
1.14.4.3;119.2â¦Time-Consistent Preprocessing of Depth Map;1055
1.14.4.3.1;119.2.1 Analysis on time-consistency of depth maps;1055
1.14.4.3.2;119.2.2 Analysis on SKIP Mode Distribution in Color Video Coding;1056
1.14.4.3.3;119.2.3 The proposed time-consistent preprocessing algorithm of depth maps;1057
1.14.4.4;119.3â¦Experimental Results and Analyses;1058
1.14.4.5;119.4â¦Conclusion;1061
1.14.4.6;Acknowledgments;1061
1.14.4.7;References;1061
1.14.5;120 A Mixture of Gaussian-Based Method for Detecting Foreground Object in Video Surveillance;1063
1.14.5.1;Abstract;1063
1.14.5.2;120.1â¦Introduction;1063
1.14.5.3;120.2â¦Related Work;1064
1.14.5.4;120.3â¦Mixture of Gaussian Background Modeling Algorithm;1065
1.14.5.5;120.4â¦Statistics-Based Tracking Algorithm;1067
1.14.5.5.1;120.4.1 Object Detector;1067
1.14.5.5.2;120.4.2 Object Tracker;1067
1.14.5.6;120.5â¦Experimental Result;1068
1.14.5.7;120.6â¦Conclusion;1071
1.14.5.8;Acknowledgments;1071
1.14.5.9;References;1071
1.14.6;121 Video Deformation Based on ASM;1073
1.14.6.1;Abstract;1073
1.14.6.2;121.1â¦Introduction;1073
1.14.6.3;121.2â¦ASM;1074
1.14.6.3.1;121.2.1 Shape Model;1074
1.14.6.3.2;121.2.2 Local Texture Model;1076
1.14.6.3.3;121.2.3 Process of Searching Object;1077
1.14.6.3.4;121.2.4 The Result of Video Tracking;1078
1.14.6.4;121.3â¦Deformation Technology Based on Feature Segment;1078
1.14.6.5;121.4â¦Realization of Video Deformation;1079
1.14.6.6;Acknowledgments;1081
1.14.6.7;References;1081
1.14.7;122 An Enhanced Hybrid Image Watermarking Algorithm Using Chaotically Scrambled Technology;1082
1.14.7.1;Abstract;1082
1.14.7.2;122.1â¦Introduction;1082
1.14.7.3;122.2â¦Watermarking Embedding Algorithm;1083
1.14.7.4;122.3â¦Watermarking Detection and Extraction Algorithm;1085
1.14.7.5;122.4â¦Experimental Results and Performance Analysis;1086
1.14.7.6;122.5â¦Conclusion;1088
1.14.7.7;References;1088
1.14.8;123 A Digital Watermarking Technology Based on Wavelet Decomposition;1089
1.14.8.1;Abstract;1089
1.14.8.2;123.1â¦Introduction;1089
1.14.8.3;123.2â¦Embedding Watermarks;1090
1.14.8.4;123.3â¦Watermark Identifying;1092
1.14.8.5;123.4â¦Experiment Result;1092
1.14.8.6;123.5â¦Conclusion;1095
1.14.8.7;Acknowledgments;1095
1.14.8.8;References;1095
1.14.9;124 An Improved Rate Control Algorithm of H.264/AVC Based on Human Visual System;1096
1.14.9.1;Abstract;1096
1.14.9.2;124.1â¦Introduction;1096
1.14.9.3;124.2â¦Analysis of Assessment Effect on Video Quality Produced by Human Visual System;1097
1.14.9.4;124.3â¦Adjust Rule Enactment of Rate-Controls Parameter;1100
1.14.9.5;124.4â¦Experimental Results;1100
1.14.9.6;124.5â¦Conclusion;1101
1.14.9.7;References;1102
1.14.10;125 Contour Lines Extraction from Color Scanned Topographical Maps with Improved Snake Algorithm;1103
1.14.10.1;Abstract;1103
1.14.10.2;125.1â¦Introduction;1103
1.14.10.3;125.2â¦Snake Model;1104
1.14.10.4;125.3â¦Improved Algorithm of Tracking;1104
1.14.10.4.1;125.3.1 Seed Segments Detection;1105
1.14.10.4.2;125.3.2 Internal Energy of Snake Algorithm;1106
1.14.10.4.3;125.3.3 External Energy of Snake Algorithm;1106
1.14.10.4.4;125.3.4 Process of the Snake Algorithm;1108
1.14.10.5;125.4â¦Experiments and Conclusion;1109
1.14.10.6;References;1110
1.14.11;126 The Aberration Characteristics of Wave-Front Coding System for Extending the Depth of Field;1111
1.14.11.1;Abstract;1111
1.14.11.2;126.1â¦Introduction;1111
1.14.11.3;126.2â¦MTF with Aberration;1112
1.14.11.3.1;126.2.1 Wave Aberration;1112
1.14.11.3.2;126.2.2 The Derivation of MTF With Aberration;1112
1.14.11.4;126.3â¦Aberration Characteristics;1113
1.14.11.4.1;126.3.1 MTF with Coma;1114
1.14.11.4.2;126.3.2 MTF with Spherical Aberration;1114
1.14.11.4.3;126.3.3 MTF with Coma and Spherical Aberration;1114
1.14.11.4.4;126.3.4 MTF with Defocus, Coma and Spherical Aberration;1115
1.14.11.5;126.4â¦Conclusion;1116
1.14.11.6;References;1116
1.15;Part XIIGreen Computing;1118
1.15.1;127 Two Improved Nearest Neighbor Search Algorithms for SPH and Their Parallelization;1119
1.15.1.1;Abstract;1119
1.15.1.2;127.1â¦Introduction;1119
1.15.1.3;127.2â¦Basic Principles of SPH;1120
1.15.1.4;127.3â¦Algorithm Description;1121
1.15.1.5;127.4â¦Time Complexity of Algorithm;1123
1.15.1.6;127.5â¦Numerical Simulation and Results Analysis;1124
1.15.1.7;127.6â¦Parallel Implementation;1125
1.15.1.8;127.7â¦Conclusion;1126
1.15.1.9;Acknowledgments;1127
1.15.1.10;References;1127
1.15.2;128 Comprehensive Evaluation of TPL Using Genetic Projection Pursuit Model with AHP in Supply Chain;1128
1.15.2.1;Abstract;1128
1.15.2.2;128.1â¦Introduction;1129
1.15.2.3;128.2â¦Appraisal Target System of TPL Providers;1129
1.15.2.4;128.3â¦Modeling Process of Projection Pursuit Clustering;1131
1.15.2.4.1;128.3.1 Normalization;1131
1.15.2.4.2;128.3.2 Design Weights Preliminary;1132
1.15.2.4.3;128.3.3 Linear Projection;1132
1.15.2.4.4;128.3.4 Fitness of Projection Pursuit;1132
1.15.2.4.5;128.3.5 Optimize Projection Direction;1133
1.15.2.5;128.4â¦GA to Implement the Projection Pursuit Clustering;1133
1.15.2.6;128.5â¦Calculation Case Analysis;1134
1.15.2.7;128.6â¦Conclusion;1136
1.15.2.8;Acknowledgments;1136
1.15.2.9;References;1136
1.15.3;129 A Modified PID Tunning Fitness Function Based on Evolutionary Algorithm;1137
1.15.3.1;Abstract;1137
1.15.3.2;129.1â¦Introduction;1137
1.15.3.3;129.2â¦Fitness Function;1138
1.15.3.3.1;129.2.1 Integral Index Fitness Function on the Basis of Optimal Control;1138
1.15.3.3.2;129.2.2 Fitness Function Based on the Weighted Sum of Some Performance Indexes of System Time Domain Response;1139
1.15.3.3.3;129.2.3 A Universal Fitness Function Based on the System Step-response Index of the System;1139
1.15.3.4;129.3â¦Computer Simulation;1141
1.15.3.5;129.4â¦Conclusion;1145
1.15.3.6;References;1145
1.15.4;130 Analysis of Convergence for Free Search Algorithm in Solving Complex Function Optimization Problems;1147
1.15.4.1;Abstract;1147
1.15.4.2;130.1â¦Introduction;1147
1.15.4.3;130.2â¦Mathematical Model of FS;1148
1.15.4.3.1;130.2.1 Parameter Initialization and Generation of Initial Group;1148
1.15.4.3.2;130.2.2 Search Behavior;1149
1.15.4.3.3;130.2.3 Termination Condition;1149
1.15.4.4;130.3â¦Convergence Proof for FS;1149
1.15.4.4.1;130.3.1 FS Convergence in Continuous Space;1149
1.15.4.4.2;130.3.2 FS Convergence in Discrete Space;1150
1.15.4.5;130.4â¦Experiments;1151
1.15.4.6;130.5â¦Conclusion;1152
1.15.4.7;Acknowledgements;1153
1.15.4.8;References;1153
1.15.5;131 Design of FH Sequences with Given Minimum Gap Based on Logistic Map 1;1154
1.15.5.1;Abstract;1154
1.15.5.2;131.1â¦Introduction;1154
1.15.5.3;131.2â¦Design of Chaotic FH Sequences;1155
1.15.5.4;131.3â¦Performance Analysis and Simulation Experiment;1157
1.15.5.4.1;131.3.1 Frequency Hopping Gap;1158
1.15.5.4.2;131.3.2 Hamming Correlation Property;1159
1.15.5.4.3;131.3.3 Balance Property;1162
1.15.5.4.4;131.3.4 Bit Error Rate;1162
1.15.5.5;131.4â¦Conclusion;1163
1.15.5.6;References;1164
1.15.6;132 Practical Criteria for Generalized Strictly Diagonally Dominant Matrices;1165
1.15.6.1;Abstract;1165
1.15.6.2;132.1â¦Introduction;1165
1.15.6.3;132.2â¦Definition and Lemma;1166
1.15.6.4;132.3â¦Main Result;1167
1.15.6.5;References;1173
1.15.7;133 Research on New Rural Information Service Model of Agricultural Industrial Chain;1174
1.15.7.1;Abstract;1174
1.15.7.2;133.1â¦Introduction;1174
1.15.7.3;133.2â¦Related Articles;1175
1.15.7.4;133.3â¦Agricultural Industrial Chain for the New Service Model;1176
1.15.7.4.1;133.3.1 Come Up with Model;1176
1.15.7.4.2;133.3.2 Model Structure;1177
1.15.7.5;133.4â¦The Key Points of the New Information Service Mode;1177
1.15.7.5.1;133.4.1 The Interaction of Industry Chain;1177
1.15.7.5.2;133.4.2 The Featured Services Function of the Industrial Chain Service Center;1179
1.15.7.5.2.1;133.4.2.1 The Application Capabilities Features of Service Function;1179
1.15.7.5.2.2;133.4.2.2 The Integrated Effect of Service Function on the Industrial Chains;1180
1.15.7.6;133.5â¦Conclusion;1182
1.15.7.7;References;1182
1.15.8;134 Reliability Evaluation Algorithm for Distribution Power System;1184
1.15.8.1;Abstract;1184
1.15.8.2;134.1â¦Introduction;1185
1.15.8.3;134.2â¦New Network Model for Distribution System;1185
1.15.8.4;134.3â¦New Algorithm of Distribution System Reliability Evaluation;1187
1.15.8.5;134.4â¦Experiment;1188
1.15.8.6;134.5â¦Conclude;1190
1.15.8.7;References;1191
1.15.9;135 State-of-the-Art Line Drawing Techniques;1192
1.15.9.1;Abstract;1192
1.15.9.2;135.1â¦Introduction;1192
1.15.9.3;135.2â¦Technical Overview of Line Drawing Methods;1193
1.15.9.4;135.3â¦Image Based Line Drawings;1194
1.15.9.5;135.4â¦3D Model Based Line Drawings;1195
1.15.9.5.1;135.4.1 Image Space Methods;1195
1.15.9.5.2;135.4.2 Object Space Methods;1196
1.15.9.5.3;135.4.3 Hybrid Methods;1197
1.15.9.6;135.5â¦Future Work;1198
1.15.9.7;Acknowledgments;1198
1.15.9.8;References;1198
1.15.10;136 The Cooperation and Competition Mechanism of Supply Chain Based on Evolutionary Game Theory;1201
1.15.10.1;Abstract;1201
1.15.10.2;136.1â¦Introduction;1201
1.15.10.3;136.2â¦The evolutionary Game Model of Supply Chain;1202
1.15.10.3.1;136.2.1 Background and Assumptions;1202
1.15.10.3.2;136.2.2 Payoff Matrix and Replication Dynamics Equations;1203
1.15.10.3.3;136.2.3 System Balance Points;1203
1.15.10.4;136.3â¦Analysis of the model;1205
1.15.10.4.1;136.3.1 The Excess Profits Delta V by Co-Produced;1205
1.15.10.4.2;136.3.2 The Initial Cooperation Costs of Suppliers and Manufacturers;1205
1.15.10.4.3;136.3.3 The Discount Factor of Suppliers and Manufacturers;1206
1.15.10.5;136.4â¦Conclusions and Discussions;1206
1.15.10.6;References;1206
1.15.11;137 A Method of Function Modeling Based on Extenics;1208
1.15.11.1;Abstract;1208
1.15.11.2;137.1â¦Introduction;1208
1.15.11.3;137.2â¦A Method of Function Designing Based on Extenics;1209
1.15.11.3.1;137.2.1 Establish Functional Model;1209
1.15.11.3.1.1;137.2.1.1 Function Decomposing;1209
1.15.11.3.1.2;137.2.1.2 Function Solving;1209
1.15.11.3.1.3;137.2.1.3 Combining Solutions;1210
1.15.11.3.2;137.2.2 Theoretical Basis of Extension Engineering---Extension Theory;1210
1.15.11.3.2.1;137.2.2.1 Introduction of Extension Theory;1210
1.15.11.3.2.2;137.2.2.2 Contains Analysis Theory;1211
1.15.11.3.3;137.2.3 The Relations of the Contain System Method and Functional Modeling;1211
1.15.11.3.4;137.2.4 Optimization Evaluation Method;1212
1.15.11.4;137.3â¦Case Study;1212
1.15.11.4.1;137.3.1 Function Decomposing of the Spring Coiling Machine;1213
1.15.11.4.2;137.3.2 Solving Function;1213
1.15.11.4.2.1;137.3.2.1 Principle Introduction;1213
1.15.11.4.2.2;137.3.2.2 The Solutions of Sub-Functions (see Table 137.1);1215
1.15.11.4.3;137.3.3 Establish a Model Based on Function and Extension;1215
1.15.11.4.4;137.3.4 Excellent Degree Evaluation;1215
1.15.11.5;137.4â¦Summery;1219
1.15.11.6;Acknowledgments;1220
1.15.11.7;References;1220
1.15.12;138 Application of MCR-ALS Computational Method for the Analysis of Interactions Between Copper Ion and Bovine Serum Albumin;1221
1.15.12.1;Abstract;1221
1.15.12.2;138.1â¦Introduction;1222
1.15.12.3;138.2â¦Materials and Methods;1222
1.15.12.3.1;138.2.1 Apparatus;1222
1.15.12.3.2;138.2.2 Materials;1223
1.15.12.3.3;138.2.3 Procedures;1223
1.15.12.3.4;138.2.4 Chemometrics Methods (MCR-ALS);1223
1.15.12.4;138.3â¦Results and Discussion;1225
1.15.12.5;Acknowledgements;1227
1.15.12.6;References;1227
1.15.13;139 Self-Learning Algorithm for Visual Recognition and Object Categorization for Autonomous Mobile Robots;1228
1.15.13.1;Abstract;1228
1.15.13.2;139.1â¦Introduction;1228
1.15.13.3;139.2â¦Principles of Learning and Self-Learning;1230
1.15.13.4;139.3â¦Generation of New Neural Networks;1232
1.15.13.5;139.4â¦Control of the Overall Performance;1233
1.15.13.6;139.5â¦The Overall Mechanism of Functioning of the Algorithm;1234
1.15.13.7;139.6â¦Summary;1234
1.15.13.8;References;1234
1.15.14;140 Time-Complexity of the Algorithm for Physical Ability Test;1235
1.15.14.1;Abstract;1235
1.15.14.2;140.1â¦Introduction;1235
1.15.14.3;140.2â¦Analyzing and Modeling;1236
1.15.14.4;140.3â¦Design of Algorithm;1238
1.15.14.5;140.4â¦Computed Result;1239
1.15.14.6;140.5â¦Time Complexity of Some Approximation Algorithms;1240
1.15.14.7;140.6â¦Summary;1240
1.15.14.8;References;1241
1.16;Part XIIIData Management and Database System;1242
1.16.1;141 A Distributed Keyword Search Algorithm in XML Databases Using MapReduce;1243
1.16.1.1;Abstract;1243
1.16.1.2;141.1â¦Introduction;1243
1.16.1.3;141.2â¦Related Works;1244
1.16.1.4;141.3â¦Problem Model;1245
1.16.1.5;141.4â¦System Structures and Algorithm Models;1247
1.16.1.5.1;141.4.1 Distributed Data Storage Model;1247
1.16.1.5.2;141.4.2 MapReduce-based Search Model;1247
1.16.1.5.3;141.4.3 Indexing Strategies;1249
1.16.1.6;141.5â¦Experiments and Evaluations;1250
1.16.1.7;141.6â¦Conclusions;1251
1.16.1.8;References;1251
1.16.2;142 A Combined Data Mining Method and Its Application in Water Quality Trends Analysis;1253
1.16.2.1;Abstract;1253
1.16.2.2;142.1â¦Introduction;1253
1.16.2.3;142.2â¦Related Work;1254
1.16.2.4;142.3â¦The Combined Method;1254
1.16.2.4.1;142.3.1 Moving Average Smoothing Method;1254
1.16.2.4.2;142.3.2 Reverse Test Method;1255
1.16.2.4.3;142.3.3 Linear Regression Model;1256
1.16.2.4.4;142.3.4 The Combination of Three Methods;1256
1.16.2.4.4.1;142.3.4.1 Long-Term Water Quality Trends Analysis;1256
1.16.2.4.4.2;142.3.4.2 Uniform Seasonal Water Quality Trends Analysis;1256
1.16.2.5;142.4â¦Experiments and Data Analysis;1257
1.16.2.5.1;142.4.1 Experimental Data;1257
1.16.2.5.2;142.4.2 Long-Term Water Quality Trends Analysis of Water Diversion;1257
1.16.2.5.3;142.4.3 Seasonal Water Quality Trends Analysis of Water Diversion;1258
1.16.2.6;142.5â¦Conclusions;1260
1.16.2.7;Acknowldgments;1261
1.16.2.8;References;1261
1.16.3;143 Model of Enterprise Innovation Based on Data Warehousing;1262
1.16.3.1;Abstract;1262
1.16.3.2;143.1â¦Introduction;1262
1.16.3.3;143.2â¦Data Warehouse;1263
1.16.3.4;143.3â¦Measurement of Innovation;1264
1.16.3.5;143.4â¦Data Acquisition;1264
1.16.3.6;143.5â¦Multidimensional Cube Modeling;1265
1.16.3.6.1;143.5.1 Hierarchies Modeling;1266
1.16.3.6.2;143.5.2 Multidimensional Database Modeling;1266
1.16.3.7;143.6â¦OLAP Operations in the Innovation Multidimensional Data Model;1268
1.16.3.8;143.7â¦Conclusion;1269
1.16.3.9;Acknowledgments;1269
1.16.3.10;References;1269
1.16.4;144 Classifying Imbalanced Dataset Using Local Classifier Fusion;1271
1.16.4.1;Abstract;1271
1.16.4.2;144.1â¦Introduction;1271
1.16.4.3;144.2â¦Classification on Imbalanced Distribution;1272
1.16.4.3.1;144.2.1 Algorithm;1272
1.16.4.3.2;144.2.2 Evaluation Measures;1273
1.16.4.4;144.3â¦Local Classifier Fusions for Imbalanced Data;1274
1.16.4.4.1;144.3.1 Inspiration from Feature Space;1274
1.16.4.4.2;144.3.2 Local Model Fusion;1275
1.16.4.5;144.4â¦Experimental Results;1277
1.16.4.6;144.5â¦Conclusion;1278
1.16.4.7;Acknowledgments;1279
1.16.4.8;References;1279
1.16.5;145 Access Frequency Based Energy Efficiency Optimization in Data Centers;1280
1.16.5.1;Abstract;1280
1.16.5.2;145.1â¦Introduction;1281
1.16.5.3;145.2â¦Related Work;1282
1.16.5.4;145.3â¦Access Frequency Based Energy Efficiency Optimization;1283
1.16.5.4.1;145.3.1 Weight Setting Scheme;1284
1.16.5.4.2;145.3.2 Our Redundancy Policies;1285
1.16.5.4.3;145.3.3 Avoiding Hot Spots;1287
1.16.5.5;145.4â¦Conclusion;1287
1.16.5.6;Acknowledgments;1288
1.16.5.7;References;1288
1.16.6;146 Application of Data Mining Technology in Jewelry Design;1289
1.16.6.1;Abstract;1289
1.16.6.2;146.1â¦Introduction;1289
1.16.6.3;146.2â¦Microsoft Time Series Algorithm;1290
1.16.6.3.1;146.2.1 Using Multiple Time Series;1290
1.16.6.3.2;146.2.2 Auto Regression Tree;1291
1.16.6.3.3;146.2.3 Seasonality;1291
1.16.6.3.4;146.2.4 Making Historical Predictions;1292
1.16.6.4;146.3â¦Application of Data Mining Technology for Jewelry Design;1292
1.16.6.4.1;146.3.1 Data Ready;1293
1.16.6.4.2;146.3.2 The Realization of Model;1294
1.16.6.5;146.4â¦Conclusion;1296
1.16.6.6;References;1296
1.16.7;147 Logic Algebra Method for Solving Theoretic Problems of Relational Database;1298
1.16.7.1;Abstract;1298
1.16.7.2;147.1â¦Introduction;1298
1.16.7.3;147.2â¦Preliminary Notions;1299
1.16.7.3.1;147.2.1 Logic Algebra;1299
1.16.7.3.2;147.2.2 Functional Dependency;1300
1.16.7.3.3;147.2.3 Equivalent Theorem;1301
1.16.7.4;147.3â¦Application of Logic Algebra Method;1301
1.16.7.4.1;147.3.1 Determine Minimal Cover;1302
1.16.7.4.2;147.3.2 Determining All Candidate Keys;1302
1.16.7.4.3;147.3.3 Determine Closure of a Set of Attributes;1303
1.16.7.5;147.4â¦Conclusion;1304
1.16.7.6;References;1304
1.16.8;148 Design History Knowledge Management System Based on Product Development Process Management and Its Implementation;1305
1.16.8.1;Abstract;1305
1.16.8.2;148.1â¦Introduction;1306
1.16.8.3;148.2â¦Review;1306
1.16.8.4;148.3â¦Process Based Integrated Framework DHK Management Sytem;1307
1.16.8.5;148.4â¦Acquisition and Management of Design History Knowledge;1308
1.16.8.6;148.5â¦Implementation;1310
1.16.8.7;148.6â¦Summary;1313
1.16.8.8;Acknowledgments;1313
1.16.8.9;References;1313
1.16.9;149 The Application of Series Importance Points (SIP) Based Partition Method on Hydrological Data Processing;1314
1.16.9.1;Abstract;1314
1.16.9.2;149.1â¦Introduction;1314
1.16.9.2.1;149.1.1 Hydrological Time Series;1315
1.16.9.2.2;149.1.2 Time Series Processing Technology;1316
1.16.9.3;149.2â¦Distance of Time Series Data;1317
1.16.9.4;149.3â¦Segmentation Algorithm Based on the Series Important Point;1319
1.16.9.5;149.4â¦The Experiment on Chenglingji s Water Level of Yangtze River;1321
1.16.9.6;149.5â¦Conclusion;1322
1.16.9.7;References;1323
1.16.10;150 A Novel PSO k-Modes Algorithm for Clustering Categorical Data;1324
1.16.10.1;Abstract;1324
1.16.10.2;150.1â¦Introduction;1324
1.16.10.3;150.2â¦K-Modes Algorithm;1326
1.16.10.4;150.3â¦The K--P-Modes Algorithm;1327
1.16.10.4.1;150.3.1 The Data Pre-Processing;1327
1.16.10.4.2;150.3.2 The Encoding and Fitting Function;1328
1.16.10.4.3;150.3.3 K-p-Modes Algorithm;1328
1.16.10.5;150.4â¦Experiments;1330
1.16.10.6;150.5â¦Summary;1330
1.16.10.7;References;1331
1.17;Part XIVE-Commerce and E-Government;1332
1.17.1;151 An Analysis of Influential Factors of Human Resource Allocation in Local Taxation System and the Modeling Approaches;1333
1.17.1.1;Abstract;1333
1.17.1.2;151.1â¦Introduction;1334
1.17.1.3;151.2â¦Research Process and Research Methods;1335
1.17.1.3.1;151.2.1 Make a List of Influential Factors;1335
1.17.1.3.2;151.2.2 Scale the Influential Degree of Each Factor;1335
1.17.1.3.3;151.2.3 Decide the Weight of Influential Factors;1336
1.17.1.4;151.3â¦Types and Index Composition of Influential Factors;1337
1.17.1.4.1;151.3.1 Working Intensity Factors;1337
1.17.1.4.2;151.3.2 Working Difficulty Factors;1338
1.17.1.4.3;151.3.3 Staff Quality Factors;1338
1.17.1.5;151.4â¦The Modeling Approaches of Constructing Human Resource Allocation in Local Taxation System;1339
1.17.1.5.1;151.4.1 Collect Data and Work Out the Influential Factors Sub-Coefficient of Local Taxation Bureaus;1339
1.17.1.5.2;151.4.2 Work Out the Working Difficulty Coefficient of Each Local Taxation Sub-Bureau;1340
1.17.1.5.3;151.4.3 Work Out the Working Intensity Coefficient of Each Local Taxation Sub-Bureau;1340
1.17.1.5.4;151.4.4 Work Out the Human Resource Demand Coefficient of Each Sub-Bureau;1341
1.17.1.5.5;151.4.5 Work Out the Human Resource Allocation Coefficient of Each Sub-Bureau;1341
1.17.1.5.6;151.4.6 Decide the Human Resource Allocation Quantity of Each Sub-Bureau;1342
1.17.1.6;151.5â¦Suggestions on a Scientific Human Resource Allocation in Local Taxation System;1342
1.17.1.7;References;1343
1.17.2;152 Classification Learning System Based on Multi-Objective GA and Frigid Weather Forecast;1344
1.17.2.1;Abstract;1344
1.17.2.2;152.1â¦Introduction;1344
1.17.2.3;152.2â¦Symbol and Algorithm;1345
1.17.2.3.1;152.2.1 Encoding and Decoding;1346
1.17.2.3.2;152.2.2 Definition;1347
1.17.2.3.3;152.2.3 Fitness Vector Function;1348
1.17.2.3.4;152.2.4 Complete Implementation Steps of Algorithm;1348
1.17.2.4;152.3â¦Example Analysis;1349
1.17.2.4.1;152.3.1 Examples Data;1349
1.17.2.4.2;152.3.2 Forecast Chromosomes Output;1350
1.17.2.4.3;152.3.3 Forecast Result Output;1351
1.17.2.5;152.4â¦Conclusion;1352
1.17.2.6;References;1352
1.17.3;153 Empirical Analysis on Choice of Payment Terms in Foreign Capital Acquiring State-Owned Enterprise;1353
1.17.3.1;Abstract;1353
1.17.3.2;153.1â¦The Development of Foreign Capital Acquiring State-Owned Enterprise;1354
1.17.3.2.1;153.1.1 The First Period;1354
1.17.3.2.2;153.1.2 Developing Period;1354
1.17.3.3;153.2â¦Legal Surrounding in Foreign Capital Acquiring State-Owned Enterprises;1354
1.17.3.3.1;153.2.1 Legislation of the First Period;1354
1.17.3.3.2;153.2.2 Legislation in the Development Period;1355
1.17.3.4;153.3â¦Payment Terms of Foreign Capital Acquiring State-Owned Enterprises;1356
1.17.3.4.1;153.3.1 Cash Payment;1356
1.17.3.4.1.1;153.3.1.1 Cash Purchasing Assets;1357
1.17.3.4.1.2;153.3.1.2 Cash Purchasing Shares Right;1357
1.17.3.4.1.3;153.3.1.3 Cash Purchasing Stocks;1357
1.17.3.4.1.4;153.3.1.4 Cash Purchasing Financial Claim;1357
1.17.3.4.1.5;153.3.1.5 Cash Purchasing Debt;1358
1.17.3.4.2;153.3.2 Comprehensive Payment Terms;1358
1.17.3.5;153.4â¦Suggestions;1358
1.17.3.6;Acknowledgments;1359
1.17.3.7;References;1359
1.17.4;154 An Integrated Application of Tourism Planning Based on Virtual Reality Technology and Indicator Assessment;1360
1.17.4.1;Abstract;1360
1.17.4.2;154.1â¦Introduction;1361
1.17.4.3;154.2â¦Study Area;1361
1.17.4.4;154.3â¦Method;1362
1.17.4.4.1;154.3.1 Indicators Description;1362
1.17.4.4.2;154.3.2 VR Environment Assessment;1362
1.17.4.4.3;154.3.3 Experience Information of Virtual Reality Platform;1363
1.17.4.5;154.4â¦Conclusion;1364
1.17.4.5.1;154.4.1 VR Assessment;1364
1.17.4.5.2;154.4.2 Matrix Comparison;1364
1.17.4.6;154.5â¦Promoted STR Planning;1365
1.17.4.7;References;1367
1.17.5;155 A Context Information Management Model for Tour Mobile E-Commerce;1368
1.17.5.1;Abstract;1368
1.17.5.2;155.1â¦Introduction;1368
1.17.5.3;155.2â¦Theory Review;1369
1.17.5.3.1;155.2.1 Context-Aware and Ontology;1369
1.17.5.3.2;155.2.2 Fuzzy Rough Sets;1370
1.17.5.4;155.3â¦Building the Context Information Management Model Based on Ontology;1370
1.17.5.4.1;155.3.1 Classification and Description of Context Information;1370
1.17.5.4.2;155.3.2 Quality Constraint of Context Information;1372
1.17.5.4.3;155.3.3 Building the Multilevel Ontology of Model;1373
1.17.5.5;155.4â¦Applied Example and Analysis;1374
1.17.5.6;References;1377
1.17.6;156 Quantitative Quality Evaluation and Improvement in Incremental Financial Software Development;1378
1.17.6.1;Abstract;1378
1.17.6.2;156.1â¦Introduction;1379
1.17.6.3;156.2â¦Quantitative Software Quality Evaluation;1380
1.17.6.3.1;156.2.1 Quantitative Quality Management Framework;1380
1.17.6.3.2;156.2.2 Indicate the Possible Quality Issues after Increment;1380
1.17.6.3.3;156.2.3 Determine the Quality Status within Increment;1381
1.17.6.4;156.3â¦Quantitative Software Defect Analysis and Quality Improvement;1381
1.17.6.4.1;156.3.1 Quantitative Software Defect Analysis Based on the Summarized Report of Root Cause Analysis;1381
1.17.6.4.2;156.3.2 Quantitative Quality Improvement;1382
1.17.6.5;156.4â¦Case Study in Global IT Corporation;1383
1.17.6.6;156.5â¦Conclusion and Discussion;1385
1.17.6.7;Acknowledgments;1385
1.17.6.8;References;1386
1.17.7;157 Study on Internet Drug Market Access Management;1387
1.17.7.1;Abstract;1387
1.17.7.2;157.1â¦Introduction;1387
1.17.7.3;157.2â¦Status Analysis of Internet Drug Market Body Access;1388
1.17.7.4;157.3â¦Solution Designing of Internet Drug Market Body;1389
1.17.7.5;157.4â¦Continuous Dynamic Monitoring;1392
1.17.7.6;157.5â¦Conclusions;1393
1.17.7.7;Acknowledgment;1393
1.17.7.8;References;1393
1.17.8;158 Study on the Real-Name System Technology for the Ontology of Internet Medicine Market;1394
1.17.8.1;Abstract;1394
1.17.8.2;158.1â¦Introduction;1394
1.17.8.3;158.2â¦Situation and the Main Goal of Internet Real-Name System for the Pharmaceutical Market;1395
1.17.8.4;158.3â¦Related Technology for Real-Name System;1396
1.17.8.5;158.4â¦Market Ontology Real-name System Certification System;1397
1.17.8.6;158.5â¦Conclusion;1400
1.17.8.7;Acknowledgment;1400
1.17.8.8;References;1400
1.17.9;159 The Combined Stock Price Prediction Model based on BP Neural Network and Grey Theory;1401
1.17.9.1;Abstract;1401
1.17.9.2;159.1â¦Introduction;1401
1.17.9.3;159.2â¦The Combined Prediction Model based on BP--GM (1, N);1402
1.17.9.3.1;159.2.1 Combined prediction;1402
1.17.9.3.2;159.2.2 The Combined Stock Price Prediction Model;1404
1.17.9.4;159.3â¦Example Analyses;1405
1.17.9.5;159.4â¦Conclusions;1407
1.17.9.6;Acknowledgment;1407
1.17.9.7;References;1407
1.18;Part XVSocial and Economical Systems;1409
1.18.1;160 Multivariate Curve Resolution with Elastic Net Regularization;1410
1.18.1.1;Abstract;1410
1.18.1.2;160.1â¦Introduction;1411
1.18.1.3;160.2â¦Multivariate Curve Resolution;1411
1.18.1.3.1;160.2.1 MCR Introduction;1411
1.18.1.3.2;160.2.2 Curve Resolution Techniques: MCR Techniques;1412
1.18.1.4;160.3â¦Elastic Net Regulization;1413
1.18.1.5;160.4â¦MCR--LARS Algorithm;1413
1.18.1.5.1;160.4.1 Algorithms Judgement Criterion;1413
1.18.1.5.2;160.4.2 Algorithms Block Diagram;1415
1.18.1.5.3;160.4.3 Algorithms Implementation Details;1415
1.18.1.6;160.5â¦Results and Discussion;1416
1.18.1.7;Acknowledgements;1419
1.18.1.8;References;1419
1.18.2;161 Research about Exoskeleton s Reference Trajectory Generation Based on RBF Neural Network;1421
1.18.2.1;Abstract;1421
1.18.2.2;161.1â¦Introduction;1421
1.18.2.3;161.2â¦Impedance Control of Exoskeleton System;1422
1.18.2.4;161.3â¦RBF Neural Network;1424
1.18.2.5;161.4â¦Model Simulation;1425
1.18.2.5.1;161.4.1 Simulation with Control;1425
1.18.2.5.2;161.4.2 Simulation with Control Based on RBF;1427
1.18.2.6;161.5â¦Conclusion;1430
1.18.2.7;References;1430
1.18.3;162 The Application of Digital Archives Classification with Progressive M-SVM to Wisdom School Building;1432
1.18.3.1;Abstract;1432
1.18.3.2;162.1â¦Introduction;1432
1.18.3.3;162.2â¦Several Conventional Text Categorization Methods;1433
1.18.3.4;162.3â¦The Application of Digital Archives Classification with Progressive M-SVM;1434
1.18.3.5;162.4â¦Specific Steps for Text Classification;1436
1.18.3.6;162.5â¦Experiment Design and Result;1437
1.18.3.7;162.6â¦Summary;1438
1.18.3.8;References;1438
1.18.4;163 Economic Growth Differential Model and Short-Term Economic Growth Momentum;1439
1.18.4.1;Abstract;1439
1.18.4.2;163.1â¦Introduction;1439
1.18.4.3;163.2â¦Economic Growth Differential Model;1440
1.18.4.4;163.3â¦The Reliability Empirical Test of Economic Growth Difference Model;1442
1.18.4.5;163.4â¦The Theoretical Significance of Economic Growth Difference Model;1443
1.18.4.6;163.5â¦Dynamic Analysis of Our Economic Recovery Strategy;1445
1.18.4.7;References;1447
1.18.5;164 A Study of Leading Industries Selection in Comprehensive Cities Based on Factor Analysis;1448
1.18.5.1;Abstract;1448
1.18.5.2;164.1â¦Introduction;1448
1.18.5.3;164.2â¦Establishing the Index System;1449
1.18.5.4;164.3â¦Empirical Study;1449
1.18.5.4.1;164.3.1 Factor Analysis Calculation;1449
1.18.5.4.2;164.3.2 Discussion;1452
1.18.5.5;164.4â¦Conclusions;1453
1.18.5.6;Acknowledgements;1454
1.18.5.7;References;1454
1.18.6;165 A Programme-Oriented Algorithm to Compute Ord(f(x));1455
1.18.6.1;Abstract;1455
1.18.6.2;165.1â¦Introduction;1455
1.18.6.3;165.2â¦Preliminary;1456
1.18.6.4;165.3â¦The General Algorithm for OIP;1458
1.18.6.5;165.4â¦A Programme-Oriented Algorithm for OIP;1460
1.18.6.6;165.5â¦Comparison;1461
1.18.6.7;165.6â¦Conclusion;1463
1.18.6.8;Acknowledgements;1463
1.18.6.9;References;1463
1.18.7;166 Finding the Academic Collaboration Chance in Open Research Community;1464
1.18.7.1;Abstract;1464
1.18.7.2;166.1â¦Introduction;1464
1.18.7.3;166.2â¦Definition of Research Environment;1466
1.18.7.3.1;166.2.1 Research Environment Modeling;1466
1.18.7.3.2;166.2.2 Related Definitions;1466
1.18.7.4;166.3â¦Core Algorithms for Collaboration Chance Finding;1467
1.18.7.4.1;166.3.1 Procedure of Text Similarity Calculation;1468
1.18.7.4.2;166.3.2 Algorithm for Article Similarity Calculation;1468
1.18.7.5;166.4â¦Experiment and Prototype;1470
1.18.7.6;166.5â¦Conclusion and Status of Research;1471
1.18.7.7;Acknowledgment;1472
1.18.7.8;References;1472
1.18.8;167 Analysis of Competition and Cooperation of Ningbo-Zhoushan Port and Shanghai Port;1473
1.18.8.1;Abstract;1473
1.18.8.2;167.1â¦Introduction;1473
1.18.8.3;167.2â¦Comparison of Competitiveness of Ningbo-Zhoushan Port and Shanghai Port;1474
1.18.8.3.1;167.2.1 Geographical Location Condition;1474
1.18.8.3.2;167.2.2 Supply Condition of the Hinterland;1475
1.18.8.3.3;167.2.3 Hardware Condition;1476
1.18.8.3.4;167.2.4 Overall Development Level;1477
1.18.8.4;167.3â¦Analysis of the Two Port s Competition and Cooperation Modes by Studying the Cooperation Mode of Foreign Ports;1478
1.18.8.4.1;167.3.1 Comparison Mode of Cooperation of Foreign Ports;1478
1.18.8.4.2;167.3.2 Port Competition;1478
1.18.8.4.3;167.3.3 Port Cooperation;1479
1.18.8.4.3.1;167.3.3.1 Dislocation Development;1480
1.18.8.4.3.2;167.3.3.2 Policy Support;1480
1.18.8.5;167.4â¦Summary;1480
1.18.8.6;References;1481
1.18.9;168 The Study About Long Memory and Volatility Persistence in China Stock Market Based on Fractal Theory and GARCH Model;1482
1.18.9.1;Abstract;1482
1.18.9.2;168.1â¦Introduction;1482
1.18.9.3;168.2â¦The Study About Long Memory of the Chinese Stock Market;1483
1.18.9.4;168.3â¦Empirical Study about Volatility persistence in China s Stock Market;1485
1.18.9.5;Acknowledgment;1487
1.18.9.6;References;1487
1.18.10;169 Research on Home-Textile Enterprise-Oriented Comprehensive Management Integration Platform and Its Application;1488
1.18.10.1;Abstract;1488
1.18.10.2;169.1â¦Introduction;1489
1.18.10.3;169.2â¦System Architecture Design for Comprehensive Integration Platform;1490
1.18.10.4;169.3â¦The Development and Application of Integrated Platform;1493
1.18.10.5;169.4â¦Summary;1495
1.18.10.6;Acknowledgments;1495
1.18.10.7;References;1495
1.18.11;170 Location-Aware Elderly Personal Safety Checking in Smart Home;1496
1.18.11.1;Abstract;1496
1.18.11.2;170.1â¦Introduction;1497
1.18.11.3;170.2â¦Location Detection of the Elderly;1498
1.18.11.4;170.3â¦Algorithms for the Elderly Personal Safety Checking;1499
1.18.11.5;170.4â¦Case Study;1500
1.18.11.6;170.5â¦Conclusion and Discussion;1501
1.18.11.7;Acknowledgments;1502
1.18.11.8;References;1502
1.18.12;171 Research on Maximum Benefit of Tourist Enterprises Based on the Influence of Scenic Spot Ticket Discount Amount;1504
1.18.12.1;Abstract;1504
1.18.12.2;171.1â¦Proposing the Problems;1505
1.18.12.3;171.2â¦Game-Theory Analysis of the Alliance Based on the Influence of Scenic Spot Tickets Discount Amount;1506
1.18.12.3.1;171.2.1 Profit Function of the Benefit Participants;1506
1.18.12.3.2;171.2.2 Model of Non-cooperation;1507
1.18.12.3.3;171.2.3 Model of Cooperation;1508
1.18.12.4;171.3â¦Benefit Distribution Based on Shapely Value;1508
1.18.12.5;171.4â¦Conclusion;1509
1.18.12.6;References;1509
1.19;Part XVIWeb Service and Data Mining;1510
1.19.1;172 A Fuzzy Multi-Criteria Group Decision Making Approach for Hotel Location Evaluation and Selection;1511
1.19.1.1;Abstract;1511
1.19.1.2;172.1â¦Introduction;1511
1.19.1.3;172.2â¦Some Preliminary Concepts;1512
1.19.1.4;172.3â¦A Fuzzy Multi-Criteria Approach;1513
1.19.1.5;172.4â¦An Example;1516
1.19.1.6;172.5â¦Conclusion;1519
1.19.1.7;References;1520
1.19.2;173 Using Online Self-Adaptive Clustering to Group Web Documents;1521
1.19.2.1;Abstract;1521
1.19.2.2;173.1â¦Introduction;1522
1.19.2.3;173.2â¦Paper Preparation;1522
1.19.2.4;173.3â¦Experimental Study;1525
1.19.2.5;173.4â¦Results Analysis and Conclusions;1527
1.19.2.6;References;1528
1.19.3;174 An Order-Based Taxonomy for Text Similarity;1529
1.19.3.1;Abstract;1529
1.19.3.2;174.1â¦Introduction;1530
1.19.3.3;174.2â¦An Order-based Taxonomy for Text Similarity;1530
1.19.3.4;174.3â¦Category 1: Order-Sensitive Similarity;1531
1.19.3.5;174.4â¦Category 2: Order-Insensitive Similarity;1532
1.19.3.6;174.5â¦Category 3: Order-Semi-Sensitive Similarity;1533
1.19.3.7;174.6â¦Conclusion;1534
1.19.3.8;Acknowledgments;1535
1.19.3.9;References;1535
1.19.4;175 Distributed Intrusion Detection System Using Autonomous Agents Based on DCOM;1536
1.19.4.1;Abstract;1536
1.19.4.2;175.1â¦Introduction;1536
1.19.4.3;175.2â¦System Architecture;1537
1.19.4.4;175.3â¦Agent Design with Alert Correlation;1538
1.19.4.5;175.4â¦Implementation;1539
1.19.4.6;175.5â¦Results;1540
1.19.4.7;175.6â¦Conclusion;1541
1.19.4.8;References;1542
1.19.5;176 A Method for Uncertain Linguistic Multiple Attribute Decision Making and Its Application;1543
1.19.5.1;Abstract;1543
1.19.5.2;176.1â¦Introduction;1543
1.19.5.3;176.2â¦Preliminaries;1544
1.19.5.4;176.3â¦A Method for Uncertain Linguistic Multiple Attribute Decision Making and its Application to Supplier Selection;1545
1.19.5.5;176.4â¦Conclusion;1547
1.19.5.6;References;1547
1.19.6;177 Web2.0 Environment of Personal Knowledge Management Applications;1548
1.19.6.1;Abstract;1548
1.19.6.2;177.1â¦The Concept of Personal Knowledge Management;1548
1.19.6.3;177.2â¦Personal Knowledge Management in Web2.0 Times;1549
1.19.6.4;177.3â¦Personal Knowledge Management Skills;1549
1.19.6.4.1;177.3.1 Knowledge Acquisition;1549
1.19.6.4.2;177.3.2 Knowledge Storage;1550
1.19.6.4.3;177.3.3 Knowledge Sharing;1550
1.19.6.4.4;177.3.4 Knowledge Utilization;1550
1.19.6.5;177.4â¦Personal Knowledge Management Tools.;1551
1.19.6.5.1;177.4.1 Social Book Mark;1551
1.19.6.5.2;177.4.2 RSS;1552
1.19.6.5.3;177.4.3 TAG;1552
1.19.6.5.4;177.4.4 Personal Portal (Personal Information Portal);1552
1.19.6.5.4.1;177.4.4.1 Network Summary and Article Collection Network;1552
1.19.6.5.5;177.4.5 BLOG;1553
1.19.6.5.5.1;177.4.5.1 Blogs in the Application of Individual Knowledge Management;1553
1.19.6.6;177.5â¦Conclusion;1554
1.19.6.7;References;1554
1.19.7;178 Semantic Web and Its Applications;1556
1.19.7.1;Abstract;1556
1.19.7.2;178.1â¦Introduction;1556
1.19.7.3;178.2â¦Key Technologies;1557
1.19.7.3.1;178.2.1 XML and XMLS;1558
1.19.7.3.2;178.2.2 RDF and RDFS;1559
1.19.7.3.3;178.2.3 Ontologies;1559
1.19.7.3.4;178.2.4 OWL;1560
1.19.7.3.5;178.2.5 Logic and Inference: Rules;1560
1.19.7.4;178.3â¦Applications;1561
1.19.7.4.1;178.3.1 Business-to-Business Electronic Commerce;1561
1.19.7.4.2;178.3.2 E-Learning;1561
1.19.7.4.3;178.3.3 Semantic Web Search;1562
1.19.7.4.4;178.3.4 Data Integration;1562
1.19.7.5;178.4â¦Future;1563
1.19.7.6;References;1563
1.19.8;179 A Semantics-Based Web Service Matching Framework and Approach;1564
1.19.8.1;Abstract;1564
1.19.8.2;179.1â¦Introduction;1564
1.19.8.3;179.2â¦Web Service Matching Framework;1565
1.19.8.4;179.3â¦Semantics-Based Web Service Matching Approach;1566
1.19.8.4.1;179.3.1 Category Match of Semantic Web Service;1566
1.19.8.4.2;179.3.2 Semantic Web Service Function Information Match;1566
1.19.8.5;179.4â¦Improved Calculation of Semantic Similarity;1568
1.19.8.5.1;179.4.1 Calculation of Distance-Based Semantic Similarity;1568
1.19.8.5.2;179.4.2 Calculation of Property-Based Semantic Similarity;1570
1.19.8.5.3;179.4.3 Calculation of Integrated Semantic Similarity;1570
1.19.8.6;179.5â¦Experiments;1570
1.19.8.7;179.6â¦Conclusion;1571
1.19.8.8;References;1572
1.19.9;180 Using Integrated Technology to Achieve Three-Dimensional WebGIS System in Park Planning;1573
1.19.9.1;Abstract;1573
1.19.9.2;180.1â¦Questions;1573
1.19.9.3;180.2â¦Problem-Solving;1574
1.19.9.3.1;180.2.1 The Three-Dimensional WebGIS System and CAD System Data Sharing;1574
1.19.9.3.2;180.2.2 Build and Publish Web Three-Dimensional Model;1575
1.19.9.4;180.3â¦The Specific Process to Achieve Three-Dimensional WebGIS Function;1576
1.19.9.4.1;180.3.1 The Realization of Web-Driven Three-Dimensional Scene and Three-Dimensional Model Visualization;1576
1.19.9.4.2;180.3.2 The Realizations on Multiple Three-Dimensional Scene Sightseeing Modes;1576
1.19.9.4.3;180.3.3 Three-Dimensional Spatial Query and Measurement;1577
1.19.9.4.4;180.3.4 Other Three-dimensional Spatial Analysis Function;1578
1.19.9.5;180.4â¦Conclusion;1579
1.19.9.6;References;1580
1.19.10;181 Hierarchical Base-k Chord Based on Semantic Networks;1581
1.19.10.1;Abstract;1581
1.19.10.2;181.1â¦Introduction;1582
1.19.10.3;181.2â¦Related Work;1583
1.19.10.3.1;181.2.1 Base-k Chord;1583
1.19.10.4;181.3â¦Hierarchical Base-k Chord;1585
1.19.10.4.1;181.3.1 Structure of Hierarchical Base-k Chord;1585
1.19.10.4.2;181.3.2 Finger Table;1586
1.19.10.5;181.4â¦Routing;1587
1.19.10.6;181.5â¦Simulations;1588
1.19.10.7;181.6â¦Conclusions;1590
1.19.10.8;Acknowledgments;1590
1.19.10.9;References;1590
1.19.11;182 Enterprises Application Integration Framework Based on Web Services and Its Interfaces;1592
1.19.11.1;Abstract;1592
1.19.11.2;182.1â¦Introduction;1592
1.19.11.3;182.2â¦Analysis of the Traditional EAI;1593
1.19.11.3.1;182.2.1 Classification and Characteristics of EAI;1593
1.19.11.3.2;182.2.2 Traditional Methods of EAI;1594
1.19.11.4;182.3â¦Design a Framework and its Interfaces of EAI Based on WEB Service;1594
1.19.11.4.1;182.3.1 Architecture of WEB Service;1595
1.19.11.4.2;182.3.2 Design of a EAI Framework Based on WEB Service;1595
1.19.11.4.3;182.3.3 Interface Design Principle of WEB Service in the EAI Framework;1597
1.19.11.4.4;182.3.4 Implementation of Interfaces in the EAI Framework Based on WEB Service;1598
1.19.11.5;182.4â¦Compared with Traditional EAI Method;1598
1.19.11.6;182.5â¦Conclusion;1599
1.19.11.7;Acknowledgments;1599
1.19.11.8;References;1600
1.19.12;183 The Automatic Classification 3D Point Clouds Based Associative Markov Network Using Context Information;1601
1.19.12.1;Abstract;1601
1.19.12.2;183.1â¦Introduction;1602
1.19.12.3;183.2â¦Previous Work;1602
1.19.12.4;183.3â¦Associative Markov Random Fields;1603
1.19.12.4.1;183.3.1 Definitions;1604
1.19.12.4.2;183.3.2 Learning;1604
1.19.12.4.3;183.3.3 Inference;1605
1.19.12.5;183.4â¦Experiments;1606
1.19.12.6;183.5â¦Conclusion;1607
1.19.12.7;Acknowledgments;1607
1.19.12.8;References;1608
1.20;Author Index;1609mehr

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