The papers in this volume are the refereed application papers presented at AI-2008, the Twenty-eighth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2008.
They present new and innovative applications of artificial intelligence across a wide range of domains; divided into sections on Machine Learning, Web Technologies, Intelligent Systems and AI in Health Care. The volume also includes the text of short papers presented as posters at the conference.
This is the sixteenth volume in the Application and Innovations series, which offers an annual snapshot of the latest applications of artificial intelligence across industry, commerce, education and government.
The Technical Stream papers are published as a companion volume under the title Research and Development in Intelligent Systems XXV.
Author(s): Tony Allen, Tony Allen, Richard Ellis, Miltos Petridis
Edition: 1
Publisher: Springer
Year: 2008
Language: English
Pages: 259
Applications and Innovations
in Intelligent Systems XVI......Page 1
Title Page
......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
......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
......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
......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
