Lecture Notes in Artificial Intelligence 9978

Subseries of Lecture Notes in Computer Science

LNAI Series Editors

Randy GoebelUniversity of Alberta, Edmonton, Canada

Yuzuru TanakaHokkaido University, Sapporo, Japan

Wolfgang WahlsterDFKI and Saarland University, Saarbrücken, Germany

LNAI Founding Series Editor

Joerg SiekmannDFKI and Saarland University, Saarbrücken, Germany

More information about this series at http://www.springer.com/series/1244

Van-Nam Huynh • Masahiro InuiguchiBac Le • Bao Nguyen LeThierry Denoeux (Eds.)

Integrated Uncertaintyin Knowledge Modellingand Decision Making5th International Symposium, IUKM 2016Da Nang, Vietnam, November 30 – December 2, 2016Proceedings

123

EditorsVan-Nam HuynhJapan Advanced Institute of Scienceand Technology

Nomi, IshikawaJapan

Masahiro InuiguchiGraduate School of Engineering ScienceOsaka UniversityToyonaka, OsakaJapan

Bac LeUniversity of ScienceHo Chi Minh CityVietnam

Bao Nguyen LeDuy Tan UniversityDa NangVietnam

Thierry DenoeuxUniversité de Technologie de CompiègneCompiègneFrance

ISSN 0302-9743 ISSN 1611-3349 (electronic)Lecture Notes in Artificial IntelligenceISBN 978-3-319-49045-8 ISBN 978-3-319-49046-5 (eBook)DOI 10.1007/978-3-319-49046-5

Library of Congress Control Number: 2016955999

LNCS Sublibrary: SL7 – Artificial Intelligence

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Preface

This volume contains the papers that were presented at the 5th International Sympo-sium on Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM2016) held in Da Nang, Vietnam, from November 30 to December 2, 2016.

The IUKM symposia aim to provide a forum for the exchange of research resultsand ideas, and experiences in application among researchers and practitioners involvedwith all aspects of uncertainty modelling and management. Previous editions of theconference were held in Ishikawa, Japan (originally under the name of InternationalSymposium on Integrated Uncertainty Management and Applications – IUM 2010),Hangzhou, China (IUKM 2011), Beijing, China (IUKM 2013), and Nha Trang,Vietnam (IUKM 2015).

IUKM 2016 was jointly organized by Duy Tan University (Da Nang, Vietnam),Japan Advanced Institute of Science and Technology (JAIST), and Belief Functionsand Applications Society (BFAS).

The organizers received 78 submissions. Each of which was peer reviewed by atleast two members of the Program Committee. While 35 papers were accepted after thefirst round of reviews, 22 others were conditionally accepted and underwent a rebuttalstage in which authors were asked to revise their paper in accordance to the reviews,and prepare an extensive response addressing the reviewers’ concerns. The finaldecision was made by the program chairs. Finally, 57 papers were accepted for pre-sentation at IUKM 2016 and publication in the proceedings. Invited talks presented atthe symposium are also included in this volume.

As a follow-up of the symposium, a special volume of the International Journal ofApproximate Reasoning is anticipated to include a small number of extended papersselected from the symposium as well as other relevant contributions received inresponse to subsequent open calls. These journal submissions will go through a freshround of reviews in accordance with the journal’s guidelines.

The IUKM 2016 symposium was partially supported by the National Foundation forScience and Technology Development of Vietnam (NAFOSTED) and Duy TanUniversity. The IUKM 2016 best student paper award was sponsored by Elsevier. Weare very thankful to Dr. Gia-Nhu Nguyen and his local organizing team from Duy TanUniversity for their hard work and efficient services and for the wonderful localarrangements.

We would like to express our appreciation to the members of the Program Com-mittee for their support and cooperation in this publication. We are also thankful toAlfred Hofmann, Anna Kramer, and their colleagues at Springer for providing ameticulous service for the timely production of this volume. Last, but certainly not the

least, our special thanks go to all the authors who submitted papers and all the attendeesfor their contributions and fruitful discussions that made this conference a greatsuccess.

December 2016 Van-Nam HuynhMasahiro Inuiguchi

Bac LeBao N. Le

Thierry Denoeux

VI Preface

Organization

General Co-chairs

Bao N. Le Duy Tan University, Da Nang, VietnamThierry Denoeux University of Technology of Compiègne, France

Honorary Co-chairs

Michio Sugeno European Center for Soft Computing, SpainHung T. Nguyen New Mexico State University, USA;

Chiang Mai University, ThailandCo C. Le Duy Tan University, Da Nang, VietnamSadaaki Miyamoto University of Tsukuba, Japan

Program Co-chairs

Van-Nam Huynh JAIST, JapanMasahiro Inuiguchi University of Osaka, JapanBac Le University of Science, VNU-Ho Chi Minh, Vietnam

Local Arrangements Chair

Gia-Nhu Nguyen Duy Tan University, Da Nang, Vietnam

Publication and Financial Chair

Van-Hai Pham Pacific Ocean University, Nha Trang, Vietnam

Program Committee

Byeong-Seok Ahn Chung-Ang University, KoreaYaxin Bi University of Ulster, UKBernadette

Bouchon-MeunierUniversité Pierre et Marie Curie, France

Lam Thu Bui Le Quy Don Technical University, VietnamHumberto Bustince Universidad Publica de Navarra, SpainTru Cao Ho Chi Minh City University of Technology, VietnamFabio Cuzzolin Oxford Brookes University, UKTien-Tuan Dao University of Technology of Compiègne, FranceBernard De Baets Ghent University, BelgiumYong Deng Xian Jiaotong University, China

Thierry Denoeux University of Technology of Compiègne, FranceSebastien Destercke University of Technology of Compiègne, FranceKarim El Kirat University of Technology of Compiègne, FranceZied Elouedi LARODEC, ISG de Tunis, TunisieTomoe Entani University of Hyogo, JapanLluis Godo IIIA - CSIC, SpainFernando Gomide University of Campinas, BrazilPeijun Guo Yokohama National University, JapanEnrique Herrera-Viedma University of Granada, SpainMarie-Christine Ho

Ba ThoUniversity of Technology of Compiègne, France

Katsuhiro Honda Osaka Prefecture University, JapanTzung-Pei Hong National University of Kaohsiung, TaiwanVan Nam Huynh JAIST, JapanMasahiro Inuiguchi Osaka University, JapanRadim Jirousek University of Economics, Czech RepublicJanusz Kacprzyk Polish Academy of Sciences, PolandGabriele Kern-Isberner Technische Universität Dortmund, GermanyEtienne Kerre Ghent University, BelgiumLaszlo T. Koczy Budapest University of Technology and Economics,

HungaryVladik Kreinovich University of Texas at El Paso, USARudolf Kruse University of Magdeburg, GermanyYasuo Kudo Muroran Institute of Technology, JapanYoshifumi Kusunoki Osaka University, JapanJonathan Lawry University of Bristol, UKAnh-Cuong Le Ton Duc Thang University, VietnamBac Le University of Science, VNU-Ho Chi Minh, VietnamChurn-Jung Liau Academia Sinica, Taipei, TaiwanChin-Teng Lin National Chiao-Tung University, TaiwanJun Liu University of Ulster, UKWeiru Liu Queen’s University Belfast, UKAnitawati Mohd

LokmanUniversiti Teknologi MARA (UiTM) Malaysia

Tieju Ma East China University of Science and Technology, ChinaCatherine K. Marque University of Technology of Compiègne, FranceLuis Martinez University of Jaen, SpainRadko Mesiar Slovak University of Technology in Bratislava, SlovakiaTetsuya Murai Hokkaido University, JapanCanh Hao Nguyen Kyoto University, JapanThanh Binh Nguyen Duy Tan University, Vietnam; IIASA, AustriaLe Minh Nguyen JAIST, JapanHung Son Nguyen University of Warsaw, PolandXuan Hoai Nguyen Hanoi University, VietnamThanh Hien Nguyen Ton Duc Thang University, VietnamAkira Notsu Osaka Prefecture University, Japan

VIII Organization

Vilem Novak Ostrava University, Czech RepublicNikhil Pal Indian Statistical Institute, IndiaIrina Perfilieva Ostrava University, Czech RepublicTuan Phung-Duc Tokyo Institute of Technology, JapanZengchang Qin Beihang University, ChinaYasuo Sasaki JAIST, JapanHirosato Seki Osaka University, JapanDominik Slezak University of Warsaw and Infobright Inc., PolandNoboru Takagi Toyama Prefectural University, JapanYongchuan Tang Zhejiang University, ChinaPhantipa

ThipwiwatpotjanaChulalongkorn University, Thailand

Vicenc Torra University of Skovde, SwedenSeiki Ubukata Osaka University, JapanBay Vo HUTECH, VietnamGuoyin Wang Chongqing University of Posts and Telecom., ChinaThanuka

WickramarathneUniversity of Massachusetts, USA

Zeshui Xu Sichuan University, ChinaHong-Bin Yan East China University of Science and Technology, ChinaChunlai Zhou Renmin University of China

Local Organizing Committee

Viet Hung Dang Duy Tan University, Da Nang, VietnamVan Son Phan Duy Tan University, Da Nang, VietnamPhung Hoi Phan Duy Tan University, Da Nang, VietnamThanh Duong Nguyen Duy Tan University, Da Nang, VietnamDuc Man Nguyen Duy Tan University, Da Nang, VietnamThoai My Ho Duy Tan University, Da Nang, VietnamNgoc Trung Dang Duy Tan University, Da Nang, VietnamVu Tien Truong Duy Tan University, Da Nang, VietnamDac Nhuong Le Hai Phong University, Hai Phong, Vietnam

Organization IX

Sponsoring Institutions

The National Foundation for Science and TechnologyDevelopment of Vietnam (NAFOSTED)

Duy Tan University, Da Nang, Vietnam

Japan Advanced Institute of Science and Technology

X Organization

Invited Speakers

Machine Learning Applications:Past, Present and Future

Hiroshi Mamitsuka

Kyoto University, Kyoto, Japan

Short biography: Dr. Hiroshi Mamitsuka is a Professor of Bioinformatics Center,Institute for Chemical Research, Kyoto University, being jointly appointed as a Pro-fessor of School of Pharmaceutical Sciences of the same university. Also currently he isa FiDiPro (Finland Distinguished Professor Program) Professor of Department ofComputer Science, Aalto University, Finland. His present research interest includes avariety of aspects of machine learning and diverse applications, primarily cellular- ormolecular-level biology, chemistry and medical sciences. He has published more than100 scientific papers, including those appearing in top-tier conferences or journals inmachine learning and bioinformatics, such as ICML, KDD, ISMB, Machine Learning,Bioinformatics, etc. Also he has served program committee member of numerousconferences and associate editor of several well-known journals of the related fields.Prior to joining Kyoto University, he worked in industry for more than ten years,mainly data analytics in business sectors, for example, customer/revenue churn, web-access pattern, campaign management, collaborative filtering, recommendation engine,etc. So after moving to Kyoto University, he has worked as research advisor on datamining of several enterprises.

Summary: Machine learning is data-driven and so application-driven technologyalways seeking real problems. Interestingly in the beginning, techniques currentlyconsidered as part of machine learning, were developed in other domains mainly. Atypical example is hidden Markov model (HMM), which was extensively studied forspeech recognition while not necessarily in machine learning community. HMM is nowtechnically well matured and commonly used not only for speech but in many otherapplications including biological sequence alignment. This type of “machine learning”can be found in classical applications, such as natural language processing, computervision and pattern recognition. Currently, due to the era of Internet, big data and bigscience, machine learning applications are much broader, covering numerous fields,such as science, engineering, economics and other many aspects of our society. Par-ticularly commercial or business-oriented applications are weighted more, being part ofor data mining itself. The question is on future. In this talk, I’d like to review the pastand present applications of machine learning, and also shed light on possible andpromising future applications, which are already gradually coming out.

On Evidential Measures of Supportfor Reasoning with Integrated Uncertainty

Hung T. Nguyen

New Mexico State University, Las Cruces, USAChiang Mai University, Chiang Mai, Thailand

Short biography: Prof. Hung T. Nguyen received the BS degree (1967) fromUniversity of Paris XI, the Master degree (1968) from University of Paris VI, and thePhD degree (1975) from University of Lille (France), all in Mathematics. Afterspending several years at the University of California, Berkeley and the University ofMassachusetts, Amherst, he joined the faculty of Mathematical Sciences, New MexicoState University (USA), where he is currently a Professor Emeritus. He is also anAdjunct Professor of Economics, Chiang Mai University, Thailand, and was on theLIFE Chair on Fuzzy Theory at Tokyo Institute of Technology (Japan) during 1992-1993, Distinguished Visiting Lukacs Professor of Statistics at Bowling Green StateUniversity, Ohio, in 2002, Distinguished Fellow of the American Society of Engi-neering Education (ASEE), Fellow of the International Fuzzy Systems Association(IFSA). He has published 16 books, 6 edited books and more than 100 papers. Dr.Nguyen’s current research interests include Fuzzy Logics and their Applications,Random Set Theory, Risk Analysis, and Casual Inference in Econometrics.

Summary: In view of the recent ban of the use of P-values in statistical inference, sincethey are not qualified as information measures of support from empirical evidence, wewill not only take a closer look at them, but also embark on a panorama of morepromising ingredients which could replace P-values for statistical science as well as forany fields involving reasoning with integrated uncertainty. These ingredients includethe recently developed theory of Inferential Models, the emergent Information Theo-retic Statistics, and of course Bayesian statistics. One main focus of our analysis ofinformation measures is its logical aspect where emphasis will be placed upon con-ditional (event) logic, probability logic, possibility distributions, and some fuzzy sets.

Autonomous Systems: Many Possibilitiesand Challenges

Akira Namatame

National Defense Academy of Japan, Yokosuka, JapanAsian Office of Aerospace Research & Development (AOARD),

US Air Force Research Laboratory (AFRL)

Short biography: Dr. Akira Namatame is Professor emeritus of National DefenseAcademy, Japan. He is now Scientific Advisor, Asian Office of Aerospace Research &Development of US Air Force Research Laboratory. His research interests includemulti-agent systems, complex networks, artificial intelligence, computational socialscience, and game theory. In the past ten years, he has given over 35 invited talks, andover 15 tutorial lectures in international conferences and workshops, and academicinstitutions. He has organized more that 30 international conferences and workshops,and special sessions. He is the editor-in-chief of Springer’s Journal of EconomicInteraction and Coordination (JEIC), editor in Modeling and Simulation Society Letter.He has published more than 300 refereed scientific papers, together with eight books onmulti-agent systems, agent modeling and network dynamics, collective systems andgame theory. More detail information can be obtained through http://www.nda.ac.jp/*nama.

Summary: Our lives have been immensely improved by decades of automationtechnologies. Most manufacturing equipment, home appliance, cars and other physicalsystems are somehow automated. We are more comfortable, more productive and saferthan ever before. Without automation, they are more troublesome, more time con-suming, less convenient, and far less safe. Systems that can change their behavior inresponse to unanticipated events during operation are called autonomous. Autonomoussystems generally are those that take actions automatically under certain conditions.They can be thought of as self-governing systems capable of acting on their own withinprogrammed boundaries. Depending on a system’s purposes and required actions,autonomy may occur at different scales and degrees of sophistication. The capability ofsuch autonomous systems and their domains of application have expanded significantlyin recent years. These successes have also been accompanied by failures that com-pellingly illustrate the real technical difficulties associated with seemingly naturalbehavior specification for truly autonomous systems. The autonomous technology alsoholds the potential for enabling entirely new capabilities in environments where directhuman control is not physically possible. For all of these reasons, autonomous systemstechnology is as an important element of its science and technology vision and a criticalarea for future development.

Autonomy is a growing field of research and application. Specialized robots inhazardous environments and medical application under human supervisory control forspace and repetitive industrial tasks have proven successful. However, research in areas

of self-driving cars, intimate collaboration with humans in manipulation tasks, humancontrol of humanoid robots for hazardous environments, and social interaction withrobots is at initial stages. Autonomous systems are in their infancy and are capable onlyof performing well-defined tasks in predictable environments. Advances in technolo-gies enabling autonomy are needed for these systems to respond to new situations incomplex, dynamic environments. Research on autonomy includes many challengingproblems and has the potential to produce solutions with positive social impact. Itsinterdisciplinary nature also requires that researchers in the field understand theirresearch within a broader context. In this talk, I will discuss autonomous technologiesthat promise to make humans more proficient in addressing such needs. The currentstatus of autonomy research is reviewed, and key current research challenges for thehuman factors community are described. I will also present a unified treatment ofautonomous systems, identify key themes, and discuss challenge problems that arelikely to shape the science of autonomy.

XVI A. Namatame

Fuzzy Co-clustering and Applicationto Collaborative Filtering

Katsuhiro Honda

Osaka Prefecture University, Sakai, Japan

Short biography: Katsuhiro Honda is a professor of the Department of ComputerScience and Intelligent Systems, Graduate School of Engineering, Osaka PrefectureUniversity, Japan. His research interests include hybrid techniques of fuzzy clusteringand multivariate analysis, data mining with fuzzy data analysis, and neural networks.He has published more than 100 scientific papers, including those appearing in suchjournals as IEEE Transactions on Fuzzy Systems, International Journal of ApproximateReasoning, etc. He received the Outstanding Book Award (2010), the Best PaperAward (2002, 2011, 2012) and so on from the Japan Society for Fuzzy Theory andIntelligent Informatics, and delivered a tutorial lecture at the 2004 IEEE InternationalConference on Fuzzy Systems.

Summary: Cooccurrence information analysis became more popular in many web-based system analysis such as document analysis or purchase history analysis. Ratherthan the conventional multivariate observations, each object is characterized by itscooccurrence degrees with various items, and the goal is often to extract co-clusterstructures among objects and items, such that mutually familiar object-item pairs forma co-cluster. A typical application of co-cluster structure analysis can be seen in col-laborative filtering (CF). CF is a basic technique for achieving personalized recom-mendation in various web services by considering the similarity of preferences amongusers. In this talk, I’d like to introduce a fuzzy co-clustering model, which is motivatedfrom a statistical co-clustering model, and demonstrate its applicability to CF tasksfollowing a brief review of the CF framework.

Contents

Invited Papers

On Evidential Measures of Support for Reasoning with IntegratedUncertainty: A Lesson from the Ban of P-values in Statistical Inference. . . . . 3

Hung T. Nguyen

Fuzzy Co-Clustering and Application to Collaborative Filtering . . . . . . . . . . 16Katsuhiro Honda

Evidential Clustering: A Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24Thierry Denœux and Orakanya Kanjanatarakul

Uncertainty Management and Decision Support

Non-uniqueness of Interval Weight Vector to Consistent Interval PairwiseComparison Matrix and Logarithmic Estimation Methods. . . . . . . . . . . . . . . 39

Masahiro Inuiguchi

Sequential Decision Process Supported by a Compositional Model . . . . . . . . 51Radim Jiroušek and Lucie Váchová

A Theory of Modeling Semantic Uncertainty in Label Representation . . . . . . 64Zengchang Qin, Tao Wan, and Hanqing Zhao

A Probability Based Approach to Evaluation of New Energy Alternatives . . . 76Hong-Bin Yan

Minimax Regret Relaxation Procedure of Expected Recourse Problemwith Vectors of Uncertainty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

Thibhadha Saraprang and Phantipa Thipwiwatpotjana

Bottom Up Review of Criteria in Hierarchically Structured DecisionProblem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

Tomoe Entani

A Two-Stage Fuzzy Quality Function Deployment Model for ServiceDesign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

Hong-Bin Yan, Shaojing Cai, and Ming Li

Usages of Fuzzy Returns on Markowitz’s Portfolio Selection . . . . . . . . . . . . 124Tanarat Rattanadamrongaksorn, Jirakom Sirisrisakulchai,and Songsak Sriboonjitta

A Flood Risk Assessment Based on Maximum Flow Capacity of CanalSystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136

Jirakom Sirisrisakulchai, Napat Harnpornchai,Kittawit Autchariyapanitkul, and Songsak Sriboonchitta

Soft Clustering and Classification

Generalizations of Fuzzy c-Means and Fuzzy Classifiers . . . . . . . . . . . . . . . 151Sadaaki Miyamoto, Yoshiyuki Komazaki, and Yasunori Endo

Partial Data Querying Through Racing Algorithms . . . . . . . . . . . . . . . . . . . 163Vu-Linh Nguyen, Sébastien Destercke, and Marie-Hélène Masson

Fuzzy DA Clustering-Based Improvement of Probabilistic Latent SemanticAnalysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175

Takafumi Goshima, Katsuhiro Honda, Seiki Ubukata, and Akira Notsu

Exclusive Item Partition with Fuzziness Tuning in MMMs-Induced FuzzyCo-clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185

Takaya Nakano, Katsuhiro Honda, Seiki Ubukata, and Akira Notsu

A Hybrid Model of ARIMA, ANNs and k-Means Clustering for TimeSeries Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195

Warut Pannakkong, Van Hai Pham, and Van-Nam Huynh

The Rough Membership k-Means Clustering . . . . . . . . . . . . . . . . . . . . . . . 207Seiki Ubukata, Akira Notsu, and Katsuhiro Honda

Instance Reduction for Time Series Classification by ExploitingRepresentative Characteristics using k-means . . . . . . . . . . . . . . . . . . . . . . . 217

Vo Thanh Vinh, Hien T. Nguyen, and Tin T. Tran

A New Fault Classification Scheme Using Vibration Signal Signaturesand the Mahalanobis Distance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230

Jaeyoung Kim, Hung Nguyen Ngoc, and Jongmyon Kim

Machine Learning for Social Media Analytics

Estimating Asymmetric Product Attribute Weights in Review Mining . . . . . . 245Wei Ou, Anh-Cuong Le, and Van-Nam Huynh

Deep Bi-directional Long Short-Term Memory Neural Networksfor Sentiment Analysis of Social Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255

Ngoc Khuong Nguyen, Anh-Cuong Le, and Hong Thai Pham

Linguistic Features and Learning to Rank Methods for Shopping Advice . . . . 269Xuan-Huy Nguyen and Le-Minh Nguyen

XX Contents

An Evidential Method for Multi-relational Link Prediction in UncertainSocial Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280

Sabrine Mallek, Imen Boukhris, Zied Elouedi, and Eric Lefevre

Detecting Thai Messages Leading to Deception on Facebook . . . . . . . . . . . . 293Panida Songram, Atchara Choompol, Paitoon Thipsanthia,and Veera Boonjing

Answer Validation for Question Answering Systems by Using ExternalResources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305

Van-Tu Nguyen and Anh-Cuong Le

Optimizing Selection of PZMI Features Based on MMAS Algorithmfor Face Recognition of the Online Video Contextual AdvertisementUser-Oriented System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317

Bao Nguyen Le, Dac-Nhuong Le, Gia Nhu Nguyen, and Do Nang Toan

Phrase-Based Compressive Summarization for English-Vietnamese . . . . . . . . 331Tung Le, Le-Minh Nguyen, Akira Shimazu, and Dinh Dien

Improve the Performance of Mobile Applications Based on CodeOptimization Techniques Using PMD and Android Lint. . . . . . . . . . . . . . . . 343

Man D. Nguyen, Thang Q. Huynh, and T. Hung Nguyen

Biomedical and Image Applications

Clustering of Children with Cerebral Palsy with Prior BiomechanicalKnowledge Fused from Multiple Data Sources . . . . . . . . . . . . . . . . . . . . . . 359

Tuan Nha Hoang, Tien Tuan Dao, and Marie-Christine Ho Ba Tho

Co-Simulation of Electrical and Mechanical Models of the Uterine Muscle . . . 371Maxime Yochum, Jérémy Laforêt, and Catherine Marque

Computing EHG Signals from a Realistic 3D Uterus Model:A Method to Adapt a Planar Volume Conductor . . . . . . . . . . . . . . . . . . . . . 381

Maxime Yochum, Pamela Riahi, Jérémy Laforêt, and Catherine Marque

Ant Colony Optimization Based Anisotropic Diffusion Approach forDespeckling of SAR Images. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389

Vikrant Bhateja, Abhishek Tripathi, Aditi Sharma, Bao Nguyen Le,Suresh Chandra Satapathy, Gia Nhu Nguyen, and Dac-Nhuong Le

A Fusion of Bag of Word Model and Hierarchical K-Means++in Image Retrieval. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 397

My Kieu, Khai Dinh Lai, Tam Duc Tran, and Thai Hoang Le

Contents XXI

Accelerating Envelope Analysis-Based Fault DiagnosisUsing a General-Purpose Graphics Processing Unit . . . . . . . . . . . . . . . . . . . 409

Viet Tra, Sharif Uddin, Jaeyoung Kim, Cheol-Hong Kim,and Jongmyon Kim

The Marker Detection from Product Logo for Augmented RealityTechnology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 421

Thummarat Boonrod, Phatthanaphong Chomphuwiset,and Chatklaw Jareanpon

Data Mining and Application

An Approach to Decrease Execution Time and Difference for Hiding HighUtility Sequential Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435

Minh Nguyen Quang, Ut Huynh, Tai Dinh, Nghia Hoai Le, and Bac Le

Modeling Global-scale Data Marts Based on Federated Data WarehousingApplication Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 447

Ngoc Sy Ngo and Binh Thanh Nguyen

How to Select an Appropriate Similarity Measure: Towards a Symmetry-Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 457

Ildar Batyrshin, Thongchai Dumrongpokaphan, Vladik Kreinovich,and Olga Kosheleva

A Convex Combination Method for Linear Regression with Interval Data . . . 469Somsak Chanaim, Songsak Sriboonchitta, and Chongkolnee Rungruang

A Copula-Based Markov Switching Seemingly Unrelated RegressionApproach for Analysis the Demand and Supply on Sugar Market . . . . . . . . . 481

Pathairat Pastpipatkul, Nisit Panthamit, Woraphon Yamaka,and Songsak Sriboochitta

The Best Copula Modeling of Dependence Structure Among Gold, OilPrices, and U.S. Currency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493

Pathairat Pastpipatkul, Paravee Maneejuk, and Songsak Sriboonchitt

Modeling and Forecasting Interdependence of the ASEAN-5 Stock Marketsand the US, Japan and China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 508

Krit Lattayaporn, Jianxu Liu, Jirakom Sirisrisakulchai,and Songsak Sriboonchitta

XXII Contents

Statistical Methods

Need for Most Accurate Discrete Approximations Explains Effectivenessof Statistical Methods Based on Heavy-Tailed Distributions . . . . . . . . . . . . . 523

Songsak Sriboonchitta, Vladik Kreinovich, Olga Kosheleva,and Hung T. Nguyen

A New Method for Hypothesis Testing Using Inferential Modelswith an Application to the Changepoint Problem. . . . . . . . . . . . . . . . . . . . . 532

Son Phuc Nguyen, Uyen Hoang Pham, Thien Dinh Nguyen,and Hoa Thanh Le

Confidence Intervals for the Ratio of Coefficients of Variationin the Two-Parameter Exponential Distributions . . . . . . . . . . . . . . . . . . . . . 542

Patarawan Sangnawakij, Sa-Aat Niwitpong, and Suparat Niwitpong

Simultaneous Fiducial Generalized Confidence Intervals for All Differencesof Coefficients of Variation of Log-Normal Distributions . . . . . . . . . . . . . . . 552

Warisa Thangjai, Sa-Aat Niwitpong, and Suparat Niwitpong

Confidence Intervals for Common Variance of Normal Distributions . . . . . . . 562Narudee Smithpreecha, Sa-Aat Niwitpong, and Suparat Niwitpong

Confidence Intervals for Common Mean of Normal Distributionswith Known Coefficient of Variation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 574

Sukritta Sodanin, Sa-Aat Niwitpong, and Suparat Niwitpong

Pair Trading Rule with Switching Regression GARCH Model . . . . . . . . . . . 586Kongliang Zhu, Woraphon Yamaka, and Songsak Sriboonchitta

Econometric Applications

An Empirical Confirmation of the Superior Performance of MIDASover ARIMAX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 601

Tanaporn Tungtrakul, Natthaphat Kingnetr, and Songsak Sriboonchitta

Modelling Co-movement and Portfolio Optimization of Goldand Global Major Currencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 612

Methas Rattanasorn, Jianxu Liu, Jirakom Sirisrisakulchai,and Songsak Sriboonchitta

Does Asian Credit Default Swap Index Improve Portfolio Performance? . . . . 624Chatchai Khiewngamdee, Woraphon Yamaka,and Songsak Sriboonchitta

A Copula-Based Stochastic Frontier Model and Efficiency Analysis:Evidence from Stock Exchange of Thailand . . . . . . . . . . . . . . . . . . . . . . . . 637

Phachongchit Tibprasorn, Somsak Chanaim, and Songsak Sriboonchitta

Contents XXIII

Economic Growth and Income Inequality: Evidence from Thailand . . . . . . . . 649Paravee Maneejuk, Pathairat Pastpipatkul, and Songsak Sriboonchitta

Thailand’s Export and ASEAN Economic Integration: A Gravity Modelwith State Space Approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 664

Pathairat Pastpipatkul, Petchaluck Boonyakunakorn,and Songsak Sriboonchitta

Volatility Hedging Model for Precious Metal Futures Returns. . . . . . . . . . . . 675Roengchai Tansuchat, Paravee Maneejuk, and Songsak Sriboonchitta

What Firms Must Pay Bribes and How Much? An Empirical Study of Smalland Medium Enterprises in Vietnam . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 689

Thi Thuong Vu and Chon Van Le

Analysis of Agricultural Production in Asia and Measurement of TechnicalEfficiency Using Copula-Based Stochastic Frontier Quantile Model. . . . . . . . 701

Varith Pipitpojanakarn, Paravee Maneejuk, Woraphon Yamaka,and Songsak Sriboonchitta

Statistical and ANN Approaches in Credit Rating for VietnameseCorporate: A Comparative Empirical Study . . . . . . . . . . . . . . . . . . . . . . . . 715

Hung Nguyen and Tung Nguyen

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 727

XXIV Contents