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The Resource Active Media Technology : 9th International Conference, AMT 2013, Maebashi, Japan, October 29-31, 2013, Proceedings

Active Media Technology : 9th International Conference, AMT 2013, Maebashi, Japan, October 29-31, 2013, Proceedings

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Active Media Technology : 9th International Conference, AMT 2013, Maebashi, Japan, October 29-31, 2013, Proceedings
Title
Active Media Technology
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9th International Conference, AMT 2013, Maebashi, Japan, October 29-31, 2013, Proceedings
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Language
eng
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MiAaPQ
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non fiction
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dictionaries
Active Media Technology : 9th International Conference, AMT 2013, Maebashi, Japan, October 29-31, 2013, Proceedings
Label
Active Media Technology : 9th International Conference, AMT 2013, Maebashi, Japan, October 29-31, 2013, Proceedings
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http://libproxy.rpi.edu/login?url=https://ebookcentral.proquest.com/lib/rpi/detail.action?docID=3101107
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Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
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multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface -- Organization -- Table of Contents -- Invited Paper -- Interactive Rough-Granular Computing in Wisdom Technology -- 1 Introduction -- 2 Complex Granules and Physical World -- 3 Risk Managemant in IIS -- 4 Conclusions and Future Research -- References -- Active Computer Systems, Interactive Systems, and Application of AMT Based Systems -- Vision-Based User Interface for Mouse and Multi-mouse System -- Introduction -- 2 Related Works -- 3 Methodology -- 4 Implementation -- 5 User Experiments -- 6 Conclusion and Future Direction -- References -- An Automated Musical Scoring System for Tsugaru Shamisen by Multi-agent Method -- 1 Introduction -- 2 Automatic Scoring System -- 2.1 Composition of Equ uipment -- 2.2 Comparison betwe een the Western Scores and Shamisen Scores (Bun nka Tablature) -- 2.3 Indications of the M Musical Instrument (Tsugaru Shamisen) -- 3 Electronic Sham misen -- 4 Automatic Notation Process -- 4.1 Automatic Notation Process -- 4.2 Issues with Notation Particular to Shamisen -- 4.3 Shamisen Scale or T Tsubo Decipherment Process by Multi-agent System m -- 5 Experiment d and Validation by the Test Model -- 5.1 Shamisen Acoustic Source Frequency Analysis -- 5.2 Application of s This Research -- 5.3 Review of the Expe eriment Results -- 6 Conclusion -- References -- Visualization of Life Patterns through Deformation of Maps Based on Users' Movement Data -- 1 Introduction -- 2 Related Work -- 3 Spatiotemporal Maps Generation System -- 3.1 System Configuration -- 3.2 Features of the Spatiotemporal Maps -- 4 PrototypeSystem -- 4.1 Collection and Storage of Movement Data -- 4.2 Creating Sparial Scales and Time Scales and Generating Nodes -- 4.3 Map Deformation -- 4.4 Demonstration -- 5 Conclusions and Future Work -- References -- Wi-Fi RSS Based Indoor Positioning Using a Probabilistic Reduced Estimator -- 1 Introduction
  • 2 Assumptions and Models -- 3 Probabilistic Reduced Estimation Algorithms -- 4 Simulations and Evaluation -- 5 Conclusions and Discussions -- References -- Identifying Individuals' Footsteps Walking on a Floor Sensor Device -- 1 Introduction -- 2 Related Work -- 3 Foot Motion Tracking Using Particle Filter Framework -- 3.1 Application Scenarios -- 3.2 Foot Tracking with Two-Phase Particle Filters -- 4 Extension for Application of the System to Interactive Application Environments -- 4.1 Application of Walker's Alias Method to Particle Filter Processing -- 4.2 Identifying Pairs of Footsteps -- 5 Conclusions -- References -- Detection and Presentation of Failure of Learning from Quiz Responses in Course Management Systems -- 1 Introduction -- 2 Data Mining of Quiz Responses -- 3 Determination of Failure of Learning -- 3.1 Determination for the Class -- 3.2 Determination for Individual Students -- 4 Presentation of Failure of Learning -- 5 Evaluation -- 5.1 Objective -- 5.2 Method -- 5.3 Results -- 5.4 Discussion -- Factor Analysis of Failure of Learning. -- 6 Conclusion -- References -- Gamification of Community Policing: SpamCombat -- 1 Introduction -- 2 Literature Review -- 2.1 Community Policing -- 2.2 Gamification -- 2.3 Behavioral Intention to Adopt -- 3 SpamCombat: Design Overview -- 4 Methodology -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- Tackling the Correspondence Problem Closed-Form Solution for Gesture Imitation by a Humanoid's Upper Body -- 1 Introduction -- 2 The Correspondence Problem -- 3 Proposed Solution -- 3.1 ExternalMapping -- 3.2 Learner's Mapping -- 4 Evaluation -- 5 Conclusions -- References -- Active Media Machine Learning and Data Mining Techniques -- Learning and Utilizing a Pool of Features in Non-negative Matrix Factorization -- 1 Introduction -- 2 Non-negative Matrix Factorization
  • 2.1 Representation Learning with NMF -- 2.2 Preprocessing of Data -- 2.3 Incorporation of Additional Constraints -- 2.4 Post-processing of Learned Representation -- 3 Evaluation -- 3.1 Experimental Setting -- 3.2 Results for Balanced Data -- 3.3 Results for Imbalanced Data -- 4 Discussion -- 5 Concluding Remarks -- References -- Theoretical Analysis and Evaluation of Topic Graph Based Transfer Learning -- 1 Introduction -- 2 Theoretical Analysis of a Transfer Learning Method -- 2.1 Topic Graph Based NMF for Transfer Learning -- 2.2 Theoretical Analysis of TNT -- 3 Evaluations -- 3.1 Experimental Settings -- 3.2 Performance Evaluations -- 3.3 Discussions -- 4 Concluding Remarks -- References -- Selective Weight Update for Neural Network - Its Backgrounds -- 1 Introduction -- 2 Incremental Learning by Chaos Neural Network -- 2.1 Incremental Learning -- 2.2 Pattern Recognition by Chaos Neural Network -- 2.3 Correlation between Associative Memory and Patterns -- 2.4 Correlation on Chaos Neural Network -- 3 Recognition of Combinational Patterns -- 4 VSF-Network and Selective Weight Updating -- 4.1 Learning Procedure -- 4.2 SelectingWeights Updating -- 5 Experiment and Result -- 6 Conclution -- References -- Toward Robust and Fast Two-Dimensional Linear Discriminant Analysis -- 1 Introduction -- 2 Related Work -- 3 Robust and Fast Two-Dimensional Linear Discriminant Analysis -- 3.1 Preliminaries -- 3.2 Two-Dimensional Linear Discriminant Analysis -- 3.3 Robust Calculation of 2DLDA -- 3.4 Fast Calculation of 2DLDA -- 4 Evaluation -- 4.1 Experimental Setting -- 4.2 Evaluations of Approximate Decomposition -- 4.3 Comparisons with Two-Dimensional Methods -- 5 Concluding Remarks -- References -- Research on the Algorithm of Semi-supervised Robust Facial Expression Recognition -- 1 Introduction -- 2 Our Approach -- 2.1 The Principle of TrAdaBoost
  • 2.2 The Principle of Our Approach -- 3 Simulations and Experiments -- 3.1 Experimental Setting -- 3.2 Comparisons and Analysis -- 4 Conclusion -- References -- Identification of K-Tolerance Regulatory Modules in Time Series Gene Expression Data Using a Biclustering Algorithm -- 1 Introduction -- 2 Related Work -- 3 Definitions -- 4 Algorithms -- 4.1 Preprocessing Step -- 4.2 Suffix Trees and CCC-Biclusters -- 4.3 Postprocessing Step: K-Tolerance Clustering Process -- 4.4 K-CCC-Biclustering: A Biclustering Algorithm for Finding and Report All Maximal K-CCC-Biclusters -- 4.5 Complexity Analysis of K-CCC-Biclustering -- 5 Experimental Results -- 6 Conclusions -- References -- Ranking Cricket Teams through Runs and Wickets -- 1 Introduction -- 2 Cricket Teams Ranking -- 2.1 ICC Cricket Teams Ranking System -- 2.2 Team-Index (T-Index) -- 2.3 TeamRank (TR) -- 2.4 Weighted Team Rank (WTR) -- 2.5 Unified Weighted Team Rank (UWTR) -- 3 Experimental -- 3.1 Dataset -- 3.2 Results and Discussions -- 4 Related Work -- 5 Conclusions -- References -- Information and Rough Set Theory Based Feature Selection Techniques -- 1 Introduction -- 2 Background -- 2.1 Information Theory -- 2.2 Rough Set Theory -- 3 Fitness Functions -- 3.1 Paired Mutual Information -- 3.2 Group Mutual Information -- 3.3 Probabilistic Rough Set Approximations -- 4 Experimental Results -- 5 Discussion -- 6 Conclusion -- References -- Developing Transferable Clickstream Analytic Models Using Sequential Pattern Evaluation Indices -- 1 Introduction -- 2 Generation of Sequential Patterns and Sequential Pattern Evaluation Indices -- 2.1 Sequential Pattern Generating Algorithms -- 2.2 Defining Sequential Pattern Evaluation Indices -- 3 Construction of Predictive Models Based on Sequential Pattern Evaluation Indices by Considering Transferring Models
  • 3.1 A Method for Constructing Clickstream Prediction Models Based on Sequential Patterns and Their Evaluation Indices -- 3.2 Transferring the PredictiveModels Based on Sequential Pattern Evaluation Indices to Other Datasets -- 4 Experiment -- 4.1 Generating Sequential Patterns on PeriodicalWeb Clickstream Dataset -- 4.2 Evaluating the Availability for Predicting Web Clickstream Results Based on Sequential Pattern Evaluation Indices -- 4.3 Evaluating Availability for Transferring the Web Clickstream Predictive Models to Other Period -- 5 Conclusion -- References -- Customer Rating Prediction Using Hypergraph Kernel Based Classification -- 1 Introduction -- 2 The Proposed Method -- 3 Experiments -- 3.1 Experimental Setup -- 3.2 Results and Discussion -- 4 Conclusion -- References -- AMT for Semantic Web, Social Networks, and Cognitive Foundations -- Preference Structure and Similarity Measure in Tag-Based Recommender Systems -- 1 Introduction -- 2 The Qualitative Description for Similarity -- 3 The Quantitative Description for Similarity -- 4 The Strategy of Recommendation -- 5 Results and Analysis -- 6 Conclusion -- References -- Semantically Modeling Mobile Phone Data for Urban Computing -- 1 Introduction -- 2 Foundation and State of the Art -- 2.1 Foundation -- 2.2 State of the Art -- 3 Overview of Our System -- 4 Ontology Modeling -- 5 Examples -- 6 Conclusions -- References -- Action Unit-Based Linked Data for Facial Emotion Recognition -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Facial Action Unit State -- 3.2 Action Unit-Based Linked Data -- 4 Experimental Results -- 4.1 Experimental Environment -- 4.2 Method Using Artificial Neural Network -- 4.3 Method Using Support Vector Machine -- 4.4 Method Using Action Unit-Based Linked Data -- 5 Conclusion and Future Works -- References
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