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Advanced Computational Methods for Knowledge Engineering.pdf
Preface
Organization
Contents
Part I: Mathematical Programming and Optimization: Theory, Methods and Software
A Cutting Plane Approach for Solving Linear Bilevel Programming Problems
1 Introduction
2 Solving Linear BLP Problems
3 Numerical Example
4 Conclusion
References
A Direct Method for Determining the Lower Convex Hull of a Finite Point Set in 3D
1 Introduction
2 Preliminaries
3 Lower Convex Hull of a Finite Point Set in 3D
4 Algorithm for Determining the Lower Convex Hull of a Finite Point Set
4.1 Determining Lower Facets
4.2 Main Algorithm and Correctness
5 Numerical Experiments
5.1 Determining the Lower Convex Hull of a Finite Point Set in 3D
5.2 Application for Computing Voronoi Diagrams on a Sphere
References
A Hybrid Intelligent Control System
Based on PMV Optimization for Thermal
Comfort in Smart Buildings
1 Introduction
2 Problem Description
2.1 Building Thermal Model
2.2 Thermal Comfort
3 ProposedMethod
4 Experimentation
5 Conclusion
References
DC Approximation Approach
for 0-minimization in Compressed Sensing
1 Introduction
2 DC Programming and DCA
3 DC Approximation Approach for Solving Problem (1)
4 NumericalExperiments
5 Conclusions
References
DC Programming and DCA Approach
for Resource Allocation Optimization
in OFDMA/TDD Wireless Networks
1 Introduction
2 Problem Statement
3 A Global Optimization Based on DC Programming Approach
3.1 DC Reformulation
3.2 DCA for Solving Problem (7)
4 Computational Experiments
References
DC Programming and DCA for a Novel
Resource Allocation Problem in Emerging Area
of Cooperative Physical Layer Security
1 Introduction and Related Works
2 A Novel Resource Allocation Problem in the Emerging Area of Cooperative Physical Layer Security
3 DC Programming and DCA for Solving the Problem (6)
3.1 A Brief Introduction of DC Programming and DCA
3.2 DC Programming and DCA for the Problem (6)
4 Numerical Results
4.1 Datasets
4.2 Setting Parameters and Stopping Criteria
4.3 Numerical Results and Comments
5 Conclusions
References
Scheduling Problem for Bus Rapid Transit Routes
1 Introduction
2 Optimization Model of BRT Systems
3 A GA-Based Solution Method
4 A Case Study in Hanoi
5 Conclusions
References
Part II:
Operational Researchand Decision Making
Application of Recently Proposed
Metaheuristics to the Sequence Dependent TSP
1 Introduction
2 Background
2.1 Simulated Annealing
2.2 Artificial Bee Colony
2.3 Migrating Birds Optimization
3 Neighbor Functions
4 Experimental Setup, Results and Discussion
4.1 Parameter Fine Tuning
4.2 Determining Best Performing Neighbor Functions
5 Summary, Conclusions and Future Work
References
Comparative Study of Extended Kalman Filter and Particle Filter for Attitude Estimation in Gyroless Low Earth Orbit Spacecraft
1 Introduction
2 Nonlinear Mathematical Model of the Observer
3 Nonlinear Estimation Algorithms
3.1 Extended Kalman Filter
3.2 Particle Filter
4 Result and Discussion
5 Conclusions
References
Graph Coloring Tabu Search
for Project Scheduling
1 Introduction
2 Problem (P1)
2.1 Presentation of the Problem
2.2 Graph Coloring Model Based on the k-GCP
2.3 Tabu Search
2.4 Results
3 Problem (P2)
3.1 Presentation of the Problem
3.2 Graph Coloring Model Based on the Multi-coloring Problem
3.3 Tabu Search
3.4 Results
4 Problem (P3)
4.1 Presentation of the Problem
4.2 Graph Coloring Model Based on the Mixed GCP
4.3 Tabu Search
4.4 Results
5 Conclusion
References
Quality of the Approximation
of Ruin Probabilities Regarding to Large Claims
1 Introduction
2 Strong Stability of a Univariate Classical Risk Model
2.1 Description of the Model
2.2 Strong Stability of a Univariate Classical Risk Model
3 Simulation Based Study
3.1 Algorithm
3.2 Simulated Distributions
3.3 Numerical and Graphical Results
3.4 Discussion of Results
4 Conclusion
References
Part III: Machine Learning, Data Security,
and Bioinformatics
An Improvement of Stability
Based Method to Clustering
1 Introduction
2 The Bootstrap Technique
2.1 An Algorithm Based on Bootstrap for Clustering
2.2 DC Programming and DCA
2.3 Experiments with Bootstrap Techinique and DCA
3 An Improvement of Stability Based Method
4 Testing with Large Number of Dimensions and/or Large Number of Clusters
5 Conclusion
References
A Method for Building a Labeled Named Entity
Recognition Corpus Using Ontologies
1 Introduction
2 Phenotype Named Entity Recognition
2.1 Phenotype Corpora
2.2 Maximum Entropy Model with Beam Search
3 Building Annotated Corpora
3.1 Phenotype Knowledge Resources
3.2 Building Process
3.3 Error Analysis
4 Result and Discussion
5 Conclusion
References
A New Method of Virus Detection Based on Maximum Entropy Model
1 Introduction
2 Model of Virus Detection Systems
3 Developing the Method of Virus Detection Based on MEM
3.1 Extracting Virus Feature
3.2 Applying Maximum Entropy Model for Detecting Virus
3.3 Training Phase
3.4 Phase of Detection Virus
4 Experiment
4.1 Program and Experimental Data
4.2 Experimental Result and Evaluation
5 Conclusion and Future Work
References
A Parallel Algorithm for Frequent Subgraph Mining
1 Introduction
2 Related Work
3 Multi-core Processor Architecture
4 gSpan Algorithm
5 Proposed Algorithms
5.1 Parallel Mining Frequent Subgraphs with Independent Branch Strategy
5.2 Example
6 Experiments
7 Conclusions and Future Work
References
Combining Random Sub Space Algorithm and Support Vector Machines Classifier for Arabic Opinions Analysis
1 Introduction
2 Related Works
3 Random Sub Space
4 System Architecture
4.1 The Arabic Corpus Construction and Manual Pre-treatment
4.2 Features Extraction
4.3 RSS-SVM Hybrid Classifier
5 Analysis of Resu ults
6 Conclusion
References
Efficient Privacy Preserving Data Audit in Cloud
1 Introduction
2 The Three-Parties Auditing Model
2.1 System Model
3 Proposed Method
3.1 Description
3.2 Correctness
4 Analysis
4.1 Storage Overhead, Communication Cost and Computation Complexity
4.2 Security
4.3 Comparison to the State-of-Art Schemes
5 Conclusion
References
Incremental Mining Class Association Rules Using Diffsets
1 Introduction
2 Related Work
2.1 Basic Concepts
2.2 Mining Class Association Rules
2.3 Mining Association Rules from Incremental Datasets
2.4 Mining Class Association Rules from Incremental Datasets
3 A Method for Updating CARs in Incremental Dataset Using Diffsets
3.1 CAR-Incre-Diff Algorithm
3.2 An Illustrative Example
4 Experiments
5 Conclusions and Future Work
References
Mathematical Morphology on Soft Sets
for Application to Metabolic Networks
1 Introduction
2 Lattice Structures on Soft Sets
3 Morphological Operators on Soft Sets
4 Mathematical Morphology on Metabolical Networks
5 Morphological Dilation Dualities
6 Conclusions
References
Molecular Screening of Azurin-Like Anticancer Bacteriocins from Human Gut Microflora Using Bioinformatics
1 Introduction
2 Methods
2.1 Selection of the Human Gut Microbiome
2.2 Identification of Probable Bacteriocins from Human Gut Microbiome
2.3 Screening of Potentially Anticancer Bacteriocins
3 Results
3.1 Identification of Probable Bacteriocins from Human Gut Microbiome
3.2 Screening of Potentially Anticancer Bacteriocins
4 Discussions
References
Non-linear Classification of Massive Datasets with a Parallel Algorithm of Local Support Vector Machines
1 Introduction
2 Support Vector Machines
3 Parallel Algorithm of Local Support Vector Machines
4 Evaluation
5 Discussion on RelatedWorks
6 Conclusion and Future Works
References
On the Efficiency of Query-Subquery Nets withRight/Tail-Recursion Elimination in Evaluating Queries to Horn Knowledge Bases
1 Introduction
2 Preliminaries
3 QSQ-Nets with Right/Tail-Recursion Elimination
4 Preliminary Experiments
5 Conclusions
References
Parallel Multiclass Logistic Regression for Classifying Large Scale Image Datasets
1 Introduction
2 Logistic Regression for Two-Class Problems
3 Extentions of Logistic Regression to Large Number of Classes
3.1 Balanced Batch of Logistic Regression
3.2 Parallel LR-BBatch-SGD Training
4 Evaluation
4.1 Datasets
4.2 Classificaton Results
5 Conclusion and Future Works
References
Statistical Features for Emboli Identification Using Clustering Technique
1 Introduction
1.1 Limitation of Classification Technique
2 Methodology
2.1 k-Means Algorithm
2.2 Features Extraction
3 Result and Discussion
3.1 Experimental Setup
3.2 Statistical Analysis
3.3 Results
3.4 Discussion
4 Conclusion
References
Twitter Sentiment Analysis
Using Machine Learning Techniques
1 Introduction
2 Related Works
3 Our Approach
3.1 Pre-processing of Data
3.2 Feature Extraction
3.3 Classification Model
4 Experiments and Evalutions
4.1 Experiments
4.2 Evalutions
5 Conclusions
References
Video Recommendation Using Neuro-Fuzzy on Social TV Environment
1 Introduction
2 User Behaviors-Based CF Using Neuro-Fuzzy Network
2.1 ProfileModeling
2.2 Content-Based Filtering Using Neuro-Fuzzy Network
3 Experiments
3.1 Data Set
3.2 EvaluationMethods
3.3 Evaluation Results
4 Conclusion
References
Part IV:
Knowledge Information System
A Two-Stage Consensus-Based Approach for Determining Collective Knowledge
1 Introduction
2 Preliminaries
2.1 Collective of Knowledge States
2.2 Consensus Choice
2.3 Knowledge of Collective
2.4 Quality of Collective Knowledge
3 The Proposed Method
4 Experiments and Evaluation
4.1 Experimental Results
4.2 Experimental Evaluation
5 Conclusions
References
Context in Ontology for Knowledge Representation
1 Introduction
2 Related Works
3 Ontology Metamodel
4 Context
4.1 Usage and Utility
4.2 Integration to the Ontology Model
5 Conclusion
References
Designing a Tableau Reasoner
for Description Logics
1 Introduction
2 Tableaux with Global Caching
3 Design Principles
3.1 Avoiding Costly Recomputations by Caching
3.2 Memory Management
3.3 Search Strategies
4 Some Other Optimization Techniques
4.1 Delaying Time-Consuming Subtasks
4.2 Converting TBoxes
4.3 Ontology Classification
5 Conclusions
References
Granular Floor Plan Representation
for Evacuation Modeling
1 Introduction
2 The Evacuation Process
3 Our Goal: Desired Fire Scene Representation
4 Geometric Network Construction
5 Conclusions and Future Work
References
Integrated Assessment Model on Global-Scale Emissions of Air Pollutants
1 Introduction
2 Related Work
3 GAINS-IAM Concepts
3.1 GAINS-IAM Global Emission Concepts
3.2 GAINS IAM Data Model
3.3 Specifying GAINS IAM Data Cubes
4 Implementing Results of the GAINS-IAM Data Model
4.1 Global Activity Pathway Data
4.2 Global Emission Data Cube
5 Conclusion
References
Query-Subquery Nets with Stratified Negation
1 Introduction
2 Preliminaries
3 Query-Subquery Nets with Stratified Negation
4 Preliminary Experiments
5 Conclusions
References
Part V:
Software Engineering
Distributed Hierarchy of Clusters
in the Presence of Topological Changes
1 Introduction
1.1 Related Works
1.2 Model and Problem Statement
2 Algorithm
2.1 Clustering
2.2 Virtual Nodes
2.3 Hierarchical Clustering
3 Example
4 Conclusion and Perspectives
References
Native Runtime Environment
for Internet of Things
1 Introduction
2 Related Work
3 Design
3.1 VMXL4 Microkernel
3.2 VMXPOSIX Native Runtime Environment
4 Implementation
4.1 Functions for File Operations
4.2 fork() System Call
4.3 Standard Input Implementation
5 Experimental Evaluation
5.1 File Operations Test Scenario
5.2 fork() System Call Test Scenario
5.3 Standard Input Test Scenario
6 Conclusion and Further Work
References
Searching for Strongly Subsuming Higher Order Mutants by Applying Multi-objective Optimization Algorithm
1 Introduction
2 HOMs Classification
3 Identify HOMs Based on Objective and Fitness Functions
4 Experimental Evaluation
4.1 Research Questions
4.2 Software under Test and Supporting Tool
4.3 Multi-objective Optimization Algorithm
4.4 Results and Analysis
5 Conclusion and Future Work
References
Some Practical Aspects
on Modelling Server Clusters
1 Introduction
2 System Modelling
3 Performance Measures
4 Simulation Experiments
5 Conclusion
References
Author Index
Advances in Intelligent Systems and Computing 358
Hoai An Le Thi
Ngoc Thanh Nguyen
Tien Van Do Editors
Advanced
Computational
Methods for
Knowledge
Engineering
Proceedings of 3rd International Conference
on Computer Science, Applied Mathematics
and Applications - ICCSAMA 2015
Advances in Intelligent Systems and Computing
Volume 358
Series editor
Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland
e-mail: kacprzyk@ibspan.waw.pl
About this Series
The series “Advances in Intelligent Systems and Computing” contains publications on theory,
applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all
disciplines such as engineering, natural sciences, computer and information science, ICT, eco-
nomics, business, e-commerce, environment, healthcare, life science are covered. The list of top-
ics spans all the areas of modern intelligent systems and computing.
The publications within “Advances in Intelligent Systems and Computing” are primarily
textbooks and proceedings of important conferences, symposia and congresses. They cover sig-
nificant recent developments in the field, both of a foundational and applicable character. An
important characteristic feature of the series is the short publication time and world-wide distri-
bution. This permits a rapid and broad dissemination of research results.
Advisory Board
Chairman
Nikhil R. Pal, Indian Statistical Institute, Kolkata, India
e-mail: nikhil@isical.ac.in
Members
Rafael Bello, Universidad Central “Marta Abreu” de Las Villas, Santa Clara, Cuba
e-mail: rbellop@uclv.edu.cu
Emilio S. Corchado, University of Salamanca, Salamanca, Spain
e-mail: escorchado@usal.es
Hani Hagras, University of Essex, Colchester, UK
e-mail: hani@essex.ac.uk
László T. Kóczy, Széchenyi István University, Gy˝or, Hungary
e-mail: koczy@sze.hu
Vladik Kreinovich, University of Texas at El Paso, El Paso, USA
e-mail: vladik@utep.edu
Chin-Teng Lin, National Chiao Tung University, Hsinchu, Taiwan
e-mail: ctlin@mail.nctu.edu.tw
Jie Lu, University of Technology, Sydney, Australia
e-mail: Jie.Lu@uts.edu.au
Patricia Melin, Tijuana Institute of Technology, Tijuana, Mexico
e-mail: epmelin@hafsamx.org
Nadia Nedjah, State University of Rio de Janeiro, Rio de Janeiro, Brazil
e-mail: nadia@eng.uerj.br
Ngoc Thanh Nguyen, Wroclaw University of Technology, Wroclaw, Poland
e-mail: Ngoc-Thanh.Nguyen@pwr.edu.pl
Jun Wang, The Chinese University of Hong Kong, Shatin, Hong Kong
e-mail: jwang@mae.cuhk.edu.hk
More information about this series at http://www.springer.com/series/11156
Hoai An Le Thi · Ngoc Thanh Nguyen
Tien Van Do
Editors
Advanced Computational
Methods for Knowledge
Engineering
Proceedings of 3rd International Conference
on Computer Science, Applied Mathematics
and Applications – ICCSAMA 2015
A
B
C
Editors
Hoai An Le Thi
LITA - UFR MIM
University of Lorraine - Metz
France
Ngoc Thanh Nguyen
Institute of Informatics
Wrocław University of Technology
Wrocław
Poland
Tien Van Do
Department of Networked Systems
Budapest University of Technology
and Services
and Economics
Budapest
Hungary
ISSN 2194-5357
Advances in Intelligent Systems and Computing
ISBN 978-3-319-17995-7
DOI 10.1007/978-3-319-17996-4
ISSN 2194-5365
ISBN 978-3-319-17996-4
(eBook)
(electronic)
Library of Congress Control Number: 2015937023
Springer Cham Heidelberg New York Dordrecht London
c Springer International Publishing Switzerland 2015
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the
material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broad-
casting, reproduction on microfilms or in any other physical way, and transmission or information storage
and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known
or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
does not imply, even in the absence of a specific statement, that such names are exempt from the relevant
protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this book
are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the
editors give a warranty, express or implied, with respect to the material contained herein or for any errors or
omissions that may have been made.
Printed on acid-free paper
Springer International Publishing AG Switzerland is part of Springer Science+Business Media
(www.springer.com)
Preface
This volume contains the extended versions of papers presented at the 3th Inter-
national Conference on Computer Science, Applied Mathematics and Applications
(ICCSAMA 2015) held on 11-13 May, 2015 in Metz, France. The conference is co-
organized by Laboratory of Theoretical and Applied Computer Science (University of
Lorraine, France), Analysis, Design and Development of ICT systems (AddICT) Lab-
oratory (Budapest University of Technology and Economics, Hungary), Division of
Knowledge Management Systems (Wroclaw University of Technology, Poland), School
of Applied Mathematics and Informatics (Hanoi University of Science and Technology,
Vietnam), and in cooperation with IEEE SMC Technical Committee on Computational
Collective Intelligence.
The aim of ICCSAMA 2015 is to bring together leading academic scientists, re-
searchers and scholars to discuss and share their newest results in the fields of Computer
Science, Applied Mathematics and their applications. These two fields are very close
and related to each other. It is also clear that the potentials of computational methods
for knowledge engineering and optimization algorithms are to be exploited, and this is
an opportunity and a challenge for researchers.
After the peer review process, 36 papers have been selected for including in this vol-
ume. Their topics revolve around Computational Methods, Optimization Techniques,
Knowledge Engineering and have been partitioned into 5 groups: Mathematical Pro-
gramming and Optimization: theory, methods and software; Operational Research and
Decision making; Machine Learning, Data Security, and Bioinformatics; Knowledge
Information System; and Software Engineering.
It is observed that the ICCSAMA 2013, 2014 and 2015 clearly generated a signif-
icant amount of interaction between members of both communities on Computer Sci-
ence and Applied Mathematics, and we hope that these discussions have seeded future
exciting development at the interface between computational methods, optimization and
engineering.
The materials included in this book can be useful for researchers, Ph.D. and graduate
students in Optimization Theory and Knowledge Engineering fields. It is the hope of
the editors that readers can find many inspiring ideas and use them to their research.
Many such challenges are suggested by particular approaches and models presented in
VI
Preface
individual chapters of this book. We would like to thank all authors, who contributed to
the success of the conference and to this book. Special thanks go to the members of the
Steering and Program Committees for their contributions to keeping the high quality
of the selected papers. Cordial thanks are due to the Organizing Committee members
for their efforts and the organizational work. Finally, we cordially thank Prof. Janusz
Kacprzyk and Dr. Thomas Ditzinger from Springer for their supports.
March 2015
Hoai An Le Thi
Ngoc Thanh Nguyen
Tien Van Do
Organization
ICCSAMA 2015 is co-organized by Laboratory of Theoretical and Applied Computer
Science (University of Lorraine, France), Analysis, Design and Development of ICT
systems (AddICT) Laboratory (Budapest University of Technology and Economics,
Hungary), Division of Knowledge Management Systems (Wroclaw University of Tech-
nology, Poland), School of Applied Mathematics and Informatics (Hanoi University
of Science and Technology, Vietnam), and in cooperation with IEEE SMC Technical
Committee on Computational Collective Intelligence.
Organizing Committee
Conference Chair
Hoai An Le Thi
LITA–University of Lorraine, France
Conference Co-Chair
Ngoc Thanh Nguyen
Tien Van Do
Publicity Chair
Wroclaw University of Technology, Poland
Budapest University of Technology and
Economics, Hungary
Hoai Minh Le
LITA–University of Lorraine, France
Members
Hoai Minh Le
Quang Thuy Le
University of Lorraine, France
Hanoi University of Science and Technology,
Vietnam
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