Modern Approaches in Applied Intelligence 24th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2011, Syracuse, NY, USA, June 28 - July 1, 2011, Proceedings, Part I

• Main Authors: Mehrotra, Kishan G, Mohan, Chilukuri Krishna, Oh, Jae C, Varshney, Pramod K, Ali, Moonis
• Format: eBook
• Language: English
• Published: Berlin, Heidelberg Springer Berlin / Heidelberg 2011
• Edition: 1
• Subjects: Artificial intelligence; Congresses; Industrial applications
• ISBN: 9783642218217; 3642218210

Table of Contents:

• MMP (Maximize Margin Projection) -- SDA (Semi-supervised Discriminate Analysis) -- The Construction of Enhanced Relational Graph -- Build Hierarchical Relational Matrix -- ESDA -- Experimental Results -- Experiment Settings -- Image Retrieval Experiments -- Conclusions -- References -- Prediction-Oriented Dimensionality Reduction of Industrial Data Sets -- Introduction -- Dimensionality Reduction with PCA -- The Role of Intrinsic Dimension -- Principal Component Analysis -- Algorithm -- Experimental Results -- Algorithm Settings -- Drilling Process -- Milling Process -- Discussion -- Summary -- References -- Informative Sentence Retrieval for Domain Specific Terminologies -- Introduction -- Related Works -- Proposed Methods -- System Architecture -- Data Preprocessing -- Candidate Answers Selection -- Term Weighting and Answer Ranking -- Experiments and Results -- Experiment Setup and Evaluation Metric -- Experimental Results and Discussion -- Conclusion and Future Work -- References -- Section 7: Intelligent Techniques for Document Processing -- Factoring Web Tables -- Introduction -- Header Paths -- Algebraic Formulation and Factorization -- Generation of Relational Tables -- Discussion -- References -- Document Analysis Research in the Year 2021 -- Introduction: Setting the Stage -- Document Analysis Research: A Vision of the Future -- Script and Screenplay for the Scenario -- Main Requirements -- Scientific (and Other) Challenges -- Conclusion -- References -- Markov Logic Networks for Document Layout Correction -- Introduction -- Preliminaries -- Learning Layout Correction Theories -- Description Language -- Markov Logic Networks Background -- Experimental Evaluation -- Conclusions -- References -- Extracting General Lists from Web Documents: A Hybrid Approach -- Introduction -- Web Page Layout -- Candidate Generation with Visual Features
• Method -- Time Difference Modeling Method -- Distance to Model -- Proposed Ensemble Prediction Method with Time Difference Model -- Results and Discussion -- Prediction Accuracy -- Estimation of Prediction Accuracy -- Conclusion -- References -- Network Defense Strategies for Maximization of Network Survivability -- Introduction -- Problem Formulation and Notations -- Solution Approach -- Solution Approach for Solving the Inner Problem of (IP 1) -- Solution Approach for Solving (IP 1) -- Computational Experiments -- Experiment Environment -- Computational Experiment of (IP 1) -- Experiment Results of the Inner Problem of (IP 1) -- Experiment Result of (IP 1) -- Conclusion -- References -- PryGuard: A Secure Distributed Authentication Protocol for Pervasive Computing Environment -- Introduction -- Related Works -- The Noise Recognition Attack -- Characteristics -- Overview of PryGuard -- Details of Our Solution -- Conclusions and Future Work -- References -- Section 4: Feature Extraction, Discretization, Clustering, Quantization, and Data Refinement -- A Global Unsupervised Data Discretization Algorithm Based on Collective Correlation Coefficient -- Introduction -- Related Works -- Methodology -- Formal Terminology Definition -- The Descriptions of GUDA-CCC Algorithm -- Key Components in GUDA-CCC -- Artificial Fish-Swarm Algorithm (AFSA) [10] -- Lloyd-Max Scalar Quantization -- Experimental Results -- Conclusion -- References -- A Heuristic Data-Sanitization Approach Based on TF-IDF -- Introduction -- Review of Related Works -- Data Mining Process -- Data Sanitization -- The Proposed Heuristic Approach -- An Example -- Experimental Results -- Conclusion -- References -- Discovering Patterns for Prognostics: A Case Study in Prognostics of Train Wheels -- Introduction -- Methodology -- Symbolizing Time-Series Data
• Searching Patterns from Symbolic Sequences -- Evaluating Patterns -- The Application Domain: Train Wheel Prognostics -- Experiments and Results -- Parameter Settings -- Experiments and Results -- Discussions and Limitations -- Conclusions -- Reference -- Section 5: Applications of Artificial Intelligence -- Automating the Selection of Stories for AI in the News -- Introduction -- Crawling -- Training -- Ranking -- Publishing -- Validation -- SVM Alone -- Adjusted Scores -- Final Test -- Conclusions -- References -- Diagnosability Study of Technological Systems -- Introduction -- System and Faults Modeling -- Normal Model of the System -- Faults Modeling -- Observable Behaviors -- System Behaviors -- Observable Behaviors of the System -- Diagnosability Study of the System -- Faults Characterization -- Diagnosability Study -- Practical Applications -- A Simulation Model Example -- Observable Behaviors Obtained by Simulations -- Results on the Air Line Model -- Conclusions and Perspectives -- References -- Using Ensembles of Regression Trees to Monitor Lubricating Oil Quality -- Introduction -- Experimental Set Up and Data Acquisition -- On-Line Sensor Description -- Data Acquisition -- Ensembles of Regression Trees -- Regression Trees -- Ensemble Methods -- Results and Discussion -- Settings -- Results -- Conclusions -- References -- Section 6: Image Processing and Other Applications -- Image Region Segmentation Based on Color Coherence Quantization -- Introduction -- Generate the CCQ Image -- Salient CCQ Image Region Segmentation -- The Connectivity Factor -- Merge Coherent Regions -- CCQ Image Segmentation -- Experimental Results -- Conclusions -- References -- Image Retrieval Algorithm Based on Enhanced Relational Graph -- Introduction -- Data Dimension Reduction with Graph Embedding -- Problem Definition -- ARE (Augmented Relation Embedding)
• Title Page -- Preface -- Organization -- Table of Contents -- Section 1: Incremental Clustering and Novelty Detection Techniques and Their Application to Intelligent Analysis of Time Varying Information -- Classification Model for Data Streams Based on Similarity -- Introduction -- Description of the Proposal -- Formalization of the Proposal -- Experimentation -- Parameters -- Results -- Conclusions -- References -- Comparison of Artificial Neural Networks and Dynamic Principal Component Analysis for Fault Diagnosis -- Introduction -- DPCA Formulation -- ANN Formulation -- Experimental System -- Results -- Discussion -- Conclusions -- References -- Comparative Behaviour of Recent Incremental and Non-incremental Clustering Methods on Text: An Extended Study -- Introduction -- Clustering Quality Evaluation -- Dataset Analysis -- Estimation of Complexity and Heterogeneity of Datasets -- Results -- Conclusion -- References -- Section 2: Bayesian and Probabilistic Networks -- Fault Diagnosis in Power Networks with Hybrid Bayesian Networks and Wavelets -- Introduction -- Wavelets -- Bayesian Networks -- Framework -- Case Study -- Conclusions -- References -- Learning Temporal Bayesian Networks for Power Plant Diagnosis -- Introduction -- Related Work -- Temporal Nodes Bayesian Networks -- Learning Algorithm -- Interval Learning -- First Approximation: Independent Variables -- Second Approximation: Considering the Network Topology -- Pruning -- Structural Learning -- Application to Power Plant Diagnosis -- Application Domain -- Experiments and Results -- Conclusions and Future Research -- References -- On the Fusion of Probabilistic Networks -- Introduction -- Probabilistic Networks -- Probabilistic Merging -- Aims of the Work -- Fusion of Same-Structure Networks -- Fusion of U-Acyclic Networks -- Adding Variables and Arcs -- Computing the Fused Network
• Handling Sub-normalized Probabilistic Networks -- Conclusions -- References -- Section 3: Methodologies -- Basic Object Oriented Genetic Programming -- Introduction -- Related Work -- An Initial Implementation of OOGP -- Exploiting Reflection in OOGP -- Basic OOGP -- Conceptual Overview -- Algorithm Description -- Experiments -- Results -- Conclusions -- References -- Inferring Border Crossing Intentions with Hidden Markov Models -- Introduction -- Intention Representation and Estimation -- HMM Parameter Learning -- Intention Estimation -- Probabilistic Fusion Approach -- Simulation Results -- Path Prediction -- Conclusion -- References -- A Framework for Autonomous Search in the Ecl^i^ps%^e Solver -- Introduction -- Constraint Programming -- Architecture -- Framework Implementation -- The UPDATE Plug-In -- Conclusion and Future Work -- References -- Multimodal Representations, Indexing, Unexpectedness and Proteins -- Introduction -- Three Modalities of Proteins -- Algorithms and Experiments -- Unexpected Behaviour of the Human Haemoglobin -- Results in Terms of Amino Acid Sequence -- Results in Terms of Topologies -- Results in Terms of Envelopes -- Conclusions -- References -- A Generic Approach for Mining Indirect Association Rules in Data Streams -- Introduction -- Related Work -- A Generic Framework for Indirect Associations Mining -- Proposed Generic Window Model -- Generic Framework for Indirect Association Mining -- The Proposed Generic Algorithm GIAMS -- Theoretical Analyses -- Experimental Results -- Conclusions -- References -- Status Quo Bias in Configuration Systems -- Introduction -- Status Quo Bias in Decision Making -- The RecoMobile Prototype -- Study Design -- Results -- Related Work -- Conclusions -- References -- Improvement and Estimation of Prediction Accuracy of Soft Sensor Models Based on Time Difference -- Introduction
• Pruning with DOM-Tree Features