Applications and Innovations in Intelligent Systems XVI: Proceedings of AI-2008, the Twenty-eighth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence

Applications and Innovations\rin Intelligent Systems XVI......Page 1
Title Page\r......Page 3
ISBN 1848822146......Page 4
APPLICATION PROGRAMME CHAIR’S INTRODUCTION......Page 5
ACKNOWLEDGEMENTS......Page 6
APPLICATION EXECUTIVE PROGRAMME COMMITTEE......Page 7
Table of Contents\r......Page 9
BEST APPLICATION PAPER......Page 12
1 Introduction......Page 13
2 Motivation and Background Knowledge......Page 15
3 Problem Description......Page 17
4.1 The MicroGA Algorithm......Page 18
5 Empirical Evaluation......Page 20
5.2 Network Throughput Results......Page 21
6 Conclusions......Page 25
References......Page 26
MACHINE LEARNING 1......Page 27
1 Introduction......Page 28
2 Micro Workpiece Shape Recognition Task......Page 30
2.1 Permutation Coding Neural Classifier......Page 31
2.2 Results......Page 35
3 Metal Surface Texture Recognition Task......Page 36
3.1 Limited receptive area (LIRA) neural classifier......Page 37
3.2 Results......Page 39
5 Acknowledgment......Page 40
References......Page 41
Recognition of Swallowing Sounds Using Time-Frequency Decomposition and LimitedReceptive Area Neural Classifier......Page 42
1 Introduction......Page 43
2.2.1 STFT......Page 45
2.2.2 CWT......Page 46
2.3 LIRA Neural Classifier......Page 47
2.3.1 Coding Procedure......Page 48
2.3.2 Training procedure......Page 50
3 Results......Page 51
4 Discussion......Page 52
5 Conclusions......Page 53
References......Page 54
1 Introduction......Page 56
1.2 Article Structure......Page 57
2.2 Vegetation – REIP32, REIP49......Page 58
2.5 Data Overview......Page 59
2.6 Fertilization Strategies......Page 60
3.1 Multi-Layer Perceptrons for Modeling......Page 61
3.2 Self-Organizing Maps for Visualization......Page 62
4.2 Results for F330-all......Page 63
4.3 Results for F131-net......Page 66
5.1 Future Work......Page 67
References......Page 68
MACHINE LEARNING 2......Page 70
1 Introduction......Page 71
2.1 Graph Mining......Page 73
2.3 Image Representation......Page 74
3 Proposed Framework......Page 75
3.2 Weighting Scheme......Page 76
3.3 Image Classification......Page 78
4.2 Implementation......Page 79
4.3 Results......Page 80
6 Conclusion......Page 82
References......Page 83
1 Introduction......Page 85
2 Review......Page 87
3.2 Model Library & Machine Learning Module......Page 89
3.3 Graphical User Interface......Page 92
4.1 Evaluation of Performance of Machine Learning Techniques......Page 93
4.2 Evaluation of Functionality......Page 94
4.3 Evaluation of Insight into Decisions......Page 95
5 Commercial Benefits......Page 96
6 Conclusions and Observations......Page 97
References......Page 98
1 Introduction......Page 99
2.1 Ordering......Page 100
3 Distance-based ordering......Page 101
3.1 Formulation......Page 102
3.2.1 Metric learning algorithm......Page 103
3.2.3 Objective function......Page 104
4 Experimental results......Page 105
5 Conclusions......Page 107
References......Page 108
WEB TECHNOLOGIES......Page 109
1 Introduction......Page 110
2 Non-Player Characters......Page 111
3 From Chatbot to Robotar......Page 112
5 Technical Architecture......Page 114
6 Virtual World Challenges......Page 116
7 Turing in a Virtual World......Page 118
References......Page 120
1 Introduction......Page 123
1.1 Use of Ontologies to help find missing concepts / descriptors......Page 124
3 Brain Teasers and Constraint Satisfaction Problems......Page 125
3.2 An overview of Constraint Satisfaction Problems (CSPs)......Page 126
3.3 Non-CSP specialists need help in formulating CSPs......Page 127
3.4 A “manual” solution to a CSP task......Page 128
4 The CSPm System: Design, examples, and evaluation......Page 129
4.2 Evaluation......Page 130
5 The REFINERm System......Page 131
5.1 Using Refiner++......Page 133
6 Conclusions and Further Work......Page 135
References......Page 136
Information Management for Unmanned Systems: Combining DL-Reasoning with Publish/Subscribe\r......Page 137
1 Introduction......Page 138
2.1 Modelling Concept Decoupling......Page 139
2.2 Integrating Concept Decoupling......Page 140
3.1 Basic Description......Page 142
3.2 Service Model......Page 143
3.4 Scenario Implementation and Execution......Page 144
4 Related Work\r......Page 148
5 Conclusions......Page 149
References......Page 150
INTELLIGENT SYSTEMS......Page 151
1 Introduction......Page 152
2 Silog: A user perspective......Page 153
2.1 Enrolment......Page 154
2.2 Verification......Page 155
3 Silog: System Implementation......Page 156
4 Threshold selection......Page 158
5 Silog: System Evaluation......Page 160
References......Page 161
1 Introduction......Page 162
2 Laptop Data Capture......Page 164
3 Web-server Application......Page 165
4 Desktop GIS Application......Page 166
4.1 Adding a New Dynamic Layer......Page 167
4.4 Picking Dynamic Layer Waypoints......Page 168
5 Thermal Image Analysis......Page 169
6 Discussion......Page 170
7 Conclusions & Future Work......Page 171
References......Page 172
1 Introduction......Page 173
2 Conversational Agents in E-Learning......Page 174
3 Motivations for Using Natural Language in E-Learning......Page 176
4 Examples......Page 178
5.1 Conversational Process – Scope, Control and Structure......Page 181
5.2 Technical Issues – Implementation......Page 183
6 Summary......Page 184
References......Page 185
AI IN HEALTHCARE......Page 187
1 Introduction......Page 188
2 Classifier architecture......Page 189
2.1 Data space clustering......Page 191
2.2 Output estimation......Page 192
3 Online feature scoring......Page 193
4 Experimental results......Page 195
References......Page 197
1 Introduction......Page 199
2 HL7 Clinical Document Architecture......Page 200
3 Executing Clinical Practice Guidelines on the Web......Page 205
3.1 Rule Knowledge within Medical Guidelines......Page 206
3.2 Knowledge-Intensive Tasks within Medical Guidelines......Page 207
4 Experimental Validation......Page 209
References......Page 211
1 Introduction......Page 213
2 Problem Formulation......Page 215
3.1 Constraints......Page 216
3.2 Constraint Programming Models......Page 217
4.1.2 Roster construction by Iterative Forward Search......Page 219
4.2 Stage II: Variable Neighborhood Search......Page 220
5 Experimental Results......Page 221
References......Page 224
Appendix B. The list of soft constraints [9]......Page 226
1 Introduction......Page 227
2 Isokinetic Curves Analysis......Page 228
3 The Evolving Fuzzy Neural Network System......Page 230
3.1 The Fuzzy Neural Network Grammar......Page 231
3.2 The Grammar-Guided Genetic Program......Page 233
4.1 Benchmark Datasets......Page 234
4.2 Injury Detection from Isokinetic Curves......Page 237
Acknowledgments.......Page 239
References......Page 240
SHORT PAPERS......Page 241
1 Introduction......Page 242
3 The Genetic Algorithm......Page 243
5 Results......Page 245
Discussion......Page 246
References......Page 247
1 Introduction......Page 248
2.1 Structure of an Electronic-Marketplace......Page 249
2.2 Electronic Marketplace Ontology......Page 250
2.3 Agent Model and Interaction Pattern......Page 251
5 Salient Features......Page 252
References......Page 253
1 Introduction......Page 254
2.1 Robust syntactic analysis......Page 255
2.2 From data to the extraction patterns......Page 256
2.4 Semi automatic generation of ontologies......Page 257
References......Page 259