Using Ontology for Providing Content Recommendation Based on Learning Styles inside E-Learning - repository civitas UGM
Proceedings
Second International Conference
on
Artificial Intelligence, Modelling, and Simulation
Madrid, Spain 18–20 November 2014
Technical Sponsors, Patrons, Promoters, and Supporters
IEEE Region 8
IEEE Spain Section
Asia Modelling and Simulation Section
UK Simulation Society
European Simulation Council (EUROSIM)
European Council for Modelling and Simulation (ECMS)
University Polytechnic of Madrid (UPM)
University of Kingston, UK
University of Liverpool, UK
University of Malaysia in Sabah (UMS)
University of Malaysia in Pahang (UMP)
University of Malaysia in Perlis (UniMaP)
University of Technology Malaysia (UTM)
University of Technology Mara (UiTM)
Institute of Technology Bandung (ITB)
University of Science Malaysia (USM)
Machine Intelligence Research Labs (MIR Labs)
Nottingham Trent University, UK
Los Alamitos, California
Washington- • Tokyo
Copyright © 2014 by The Institute of Electrical and Electronics Engineers, Inc.
All rights reserved.
Copyright and Reprint Permissions: Abstracting is permitted with credit to the source. Libraries may photocopy
beyond the limits of US copyright law, for private use of patrons, those articles in this volume that carry a code at
the bottom of the first page, provided that the per-copy fee indicated in the code is paid through the Copyright
Clearance Center, 222 Rosewood Drive, Danvers, MA 01923.
Other copying, reprint, or republication requests should be addressed to: IEEE Copyrights Manager, IEEE Service
Center, 445 Hoes Lane, P.O. Box 133, Piscataway, NJ 08855-1331.
The papers in this book comprise the proceedings of the meeting mentioned on the cover and title page. They reflect
the authors’ opinions and, in the interests of timely dissemination, are published as presented and without change.
Their inclusion in this publication does not necessarily constitute endorsement by the editors, the IEEE Computer
Society, or the Institute of Electrical and Electronics Engineers, Inc.
IEEE Computer Society Order Number E5395
BMS Part Number CFP1415V-CDR
ISBN 978-1-4799-7599-0
Additional copies may be ordered from:
IEEE Computer Society
IEEE Service Center
IEEE Computer Society Customer Service Center 445 Hoes Lane Asia/Pacific Office 10662 Los Vaqueros Circle P.O. Box 1331 Watanabe Bldg., 1-4-2 P.O. Box 3014 Piscataway, NJ 08855-1331 Minami-Aoyama
Los Alamitos, CA 90720-1314 Tel: + 1 732 981 0060 Minato-ku, Tokyo 107-0062 Tel: + 1 800 272 6657 Fax: + 1 732 981 9667 JAPAN Fax: + 1 714 821 4641 http://shop.ieee.org/store/ Tel: + 81 3 3408 3118 http://computer.org/cspress customer-service@ieee.org Fax: + 81 3 3408 3553 csbooks@computer.org tokyo.ofc@computer.org
Individual paper REPRINTS may be ordered at: <reprints@computer.org>
Editorial production by Lisa O’Conner
Cover art production by Mark Bartosik
I E E E C o m p u t e r S o c i e t y
Conference Publishing Services (CPS)
http://www.computer.org/cps
2014 Second International
Conference on Artificial
Intelligence, Modelling
and Simulation
AIMS 2014
Table of Contents
Welcome Message from the Chairs..........................................................................................................xii
Conference Organization..........................................................................................................................xiii
International Program Committee ...........................................................................................................xiv
International Reviewers.............................................................................................................................xv
Technical Sponsors, Patrons, Promoters,and Supporters..........................................................................................................................................xvi
Keynote AddressKeynote 1: Feature Selection in Data-Driven Systems Modelling ................................................................1
Qiang Shen
Keynote 2: Challenges in Handling and Processing Huge Data ..................................................................2
Hermann Hessling Track 01.A Artificial Intelligence Study of Performance of Several Techniques of Fault Diagnosis for Induction
Motors in Steady-State with SVM Learning Algorithms ................................................................................3
J. Burriel Valencia, M. Pineda Sanchez, J. Martinez Roman, R. Puche Panadero, and A. Sapena Baño
Simulation of Human Opinions about Calligraphy Aesthetic ........................................................................9
Ana Pérez, Eduardo Cermeño, and Juan Alberto Sigüenza
Expert Diagnosis Systems for Network Connection Problems ...................................................................15
RajaaAldeen Khalid and Rafah Jassim
Topology-Aware Simulated Annealing ........................................................................................................19
Said Kerrache and Hafida Benhidour
Skinning Analysis of a Mapping Algorithm in Higher Dimensions ..............................................................25
Mustafa Youldash and John Rankin
Track 02.B. Neural Networks and Fuzzy Systems Consolidation of the IFM with the JSSP through Neural Networks as Model
for Software Projects ..................................................................................................................................33
Pandelis Ipsilandis, Dimitrios Tselios, and Vassilis C. Gerogiannis Classification of Working Memory Impairment in Children Using
Electroencephalograph Signal at the Prefrontal Cortex ..............................................................................39
S.Z. Mohd Tumari and R. Sudirman
Designing ANFIS with Self-Extraction of Rules ..........................................................................................44
Lamine Thiaw, Gustave Sow, Oumar Ba, and Salif Fall
An Approach to Represent Time Series Forecasting via Fuzzy Numbers .................................................51
Atakan Sahin, Tufan Kumbasar, Engin Yesil, M. Furkan Doýdurka, and Onur Karasakal Track 03.C Evolutionary Computation
Towards Deterministic Network Coding in Hierarchical Networks ..............................................................57
Oana Graur and Werner Henkel
Steps Towards Decentralized Deterministic Network Coding ....................................................................63
Oana Graur and Werner Henkel On the Improvement of Elite Swimmers Velocity Identification by Using Neural
Network Associated to Multiobjective Optimization ....................................................................................69
Elcio A. Bardeli Jr., Luciano F. da Cruz, Helon V.H. Ayala, Roberto Z. Freire, and Leandro dos S. Coelho A Wind Driven Approach Using Lévy Flights for Global Continuous
Optimization ................................................................................................................................................75
Emerson Hochsteiner de Vasconcelos Segundo, Anderson Levati Amoroso, Viviana Cocco Mariani, and Leandro dos Santos Coelho
Shapes Extraction Method by Genetic Algorithm with Local Search Method .............................................81
Mitsukuni Matayoshi
A Semi-Supervised Multi-view Genetic Algorithm ......................................................................................87
Gergana Lazarova and Ivan Koychev Track 06.F Bioinformatics and Bioengineering
Moments Invariant for Expression Invariant Thermal Human Recognition ................................................92
Naser Zaeri Movement Analysis for Surgical Skill Assessment and Measurement
of Ergonomic Conditions .............................................................................................................................97
O. Weede, F. Möhrle, H. Wörn, M. Falkinger, and H. Feussner
Track 11.K Intelligent Systems and Applications Exploring Experts Decisions in Concrete Delivery Dispatching Systems Using
Bayesian Network Learning Techniques ..................................................................................................103
Mojtaba Maghrebi and S. Travis Waller
A Comparative Analysis on Home Automation Techniques .....................................................................109
Mirza Qutab Baig, Junaid Maqsood, Muhammad Haris Bin Tariq Alvi, and Tamim Ahmed Khan Spreading Activation Approach for Social Recommendations: The Case
of Microblogging Services .........................................................................................................................115
Xi Kong, Lennart Weller, Susanne Boll, and Wilko Heuten System Failure Prediction through Rare-Events Elastic-Net Logistic
Regression ................................................................................................................................................120
José M. Navarro, G. Hugo A. Parada, and Juan C. Dueñas Eye-Gaze Tracking Method Driven by Raspberry PI Applicable in Automotive
Traffic Safety .............................................................................................................................................126
Ovidiu Stan, Liviu Miclea, and Ana Centea Parameter-Based Mechanism for Unifying User Interaction, Applications
and Communication Protocols ..................................................................................................................131
Jie Song, Silvia Calatrava Sierra, Jaime Caffarel Rodríguez, Jorge Martín Perandones, Guillermo del Campo Jiménez, Jorge Olloqui Buján, Rocío Martínez García, and Asunción Santamaría Galdón
Track 14.N Control of Intelligent Systems and Control Intelligence Balancing Control of Robot Gymnast Based on Discrete-Time Linear
Quadratic Regulator Technique ................................................................................................................137
H.G. Kamil, E.E. Eldukhri, and M.S. Packianather Track 16.P Robotics, Cybernetics, Engineering, Manufacturing and Control Validating the Camera and Light Simulation of a Virtual Reality Testbed
by Means of Physical Mockup Data ..........................................................................................................143
Thomas Steil and Jürgen Roßmann Mobile Robot Performance in Robotics Challenges: Analyzing a Simulated
Indoor Scenario and Its Translation to Real-World ...................................................................................149
Francisco Rodríguez Lera, Fernando Casado García, Gonzalo Esteban, and Vicente Matellán
Synergetic Control of a Mobile Robot Group ............................................................................................155
Gennady Veselov, Andrey Sklyrov, Alexey Mushenko, and Sergey Sklyrov
Track 19.S Image, Speech, and Signal Processing
Modified Back Projection Kernel Based Image Super Resolution ............................................................161
Pejman Rasti, Iiris Lüsi, Armen Sahakyan, Andres Traumann, Anastasia Bolotnikova, Morteza Daneshmand, Rudolf Kiefer, Alvo Aabloo, Gholamreza Anbarjafar, Hasan Demirel, and Cagri Ozcinar
User’s Gaze Tracking System and Its Application Using Head Pose Estimation .....................................166
Hyunduk Kim, Myoung-Kyu Sohn, Dong-Ju Kim, and Nuri RyuGeometric Feature-Based Face Normalization for Facial Expression
Recognition ...............................................................................................................................................172
Dong-Ju Kim, Myoung-Kyu Sohn, Hyunduk Kim, and Nuri RyuQualitative Evaluation of Full Body Movements with Gesture Description
Language ..................................................................................................................................................176
Tomasz Hachaj and Marek R. Ogiela
Scene Text Recognition Based on Positional Relation between Closed Curves .....................................182
Yuji Waizumi and Kazuyuki TanakaStudying the Effects of 2D and 3D Educational Contents on Memory Recall
Using EEG Signals, PCA and Statistical Features ...................................................................................187
Saeed Bamatraf, Hatim Aboalsamh, Muhammad Hussain, Hassan Mathkour, Emad-Ul-Haq Qazi, Aamir Malik, and Hafeezullah AminInsertion of Impairments in Test Video Sequences for Quality Assessment
Based on Psychovisual Characteristics ....................................................................................................193
J.P. López, J.A. Rodrigo, D. Jiménez, and J. M. MenéndezFeature Based Encryption Technique for Securing Forensic Biometric Image
Data Using AES and Visual Cryptography ...............................................................................................199
Quist-Aphetsi Kester, Laurent Nana, Anca Christine Pascu, Sophie Gire, J.M. Eghan, Nii Narku Quaynor, Robert A. Baffour, Daniel Michael Okwabi Adjin, Yeboah-Boateng Eo, Isaac Hanson, and Osei K. DarkwaTrack 19.S1 Natural Language Processing/Language Technologies Specification Model of Paragraph Summarization by Verbal Relationships:
Objective, Cause, Consequence, Concurrence ........................................................................................205
Trung Tran and Dang Tuan Nguyen
Track 20.T Industry, Business, Management, Human Factors, and Social Issues A Modeling Approach for IT Governance Basics Application on IT Projects
and IT Goals .............................................................................................................................................211
Rabii El Ghorfi, Mohamed Ouadou, Driss Aboutajdine, and Mohamed El Aroussi Human Resource Assessment in Software Development Projects Using Fuzzy
Linguistic 2-Tuples ....................................................................................................................................217
Vassilis C. Gerogiannis, Elli Rapti, Anthony Karageorgos, and Panos Fitsilis Track 21.U Energy, Power, Transport, Logistics, Harbour, Shipping and Marine Simulation
A Simulation Study of the Hamada to Zawiyah Crude Oil Pipeline in Libya .............................................223
Awad Shamekh, Jonathan Theakston, and Salah Masheiti
Exergy Analysis of a 210 MW Unit at 1260 MW Thermal Plant in India ...................................................228
Varun Goyal, Rajasekhar Dondapati, Rakesh Dang, and S.K. Mangal Design and Comparison of Feasible Control Systems for VSC-HVDC
Transmission System ...............................................................................................................................234
Boyang Shen, Sheng Wang, Lin Fu, and Jun Liang Verification of a Synchronous Machine Model for Stator Ground Fault
Simulation Through Measurements in a Large Generator .......................................................................240
A. Bermejo, C.A. Platero, F. Blázquez, F. Blánquez, and E. Rebollo Online Tool for Benchmarking of Simulated Intervention Autonomous Underwater Vehicles: Evaluating Position Controllers in Changing Underwater
Currents ....................................................................................................................................................246
Javier Pérez, Jorge Sales, Raúl Marín, and Pedro J. Sanz Communality Performance Assessment of Electricity Load Management
Model for Namibia .....................................................................................................................................252
Godwin Norense Osarumwense Asemota Track 22.V Parallel, Distributed, and Software Architectures and Systems Architecture of Real-Time Database in Cloud Environment for Distributed
Systems ....................................................................................................................................................258
Sebastijan Stoja, Srđjan Vukmirović, Bojan Jelačić, Darko Čapko, and Nikola Dalčeković Simulating a Multi-core x8664 Architecture with Hardware ISA Extension
Supporting a Data-Flow Execution Model ................................................................................................264
Nam Ho, Antoni Portero, Marcos Solinas, Alberto Scionti, Andrea Mondelli, Paolo Faraboschi, and Roberto Giorgi
Attack Prediction Models for Cloud Intrusion Detection Systems .............................................................270
Hisham A. Kholidy, Abdelkarim Erradi, and Sherif AbdelwahedTrack 23.W Internet Modelling, Semantic Web, and Ontologies Using Ontology for Providing Content Recommendation Based on Learning
Styles inside E-learning ............................................................................................................................276
Sri Suning Kusumawardani, Robertus Sonny Prakoso, and Paulus Insap Santosa Track 24.X Mobile/Ad Hoc Wireless Networks, Mobicast, Sensor Placement, Target Tracking Novel Location Tracking Energy Efficient Model for Robust Routing
over Wireless Sensor Networks ................................................................................................................282
Fatma Almajadub and Khaled Elleithy
Prevention of Wormhole Attacks in Wireless Sensor Networks ...............................................................287
Dema Aldhobaiban, Khaled Elleithy, and Laiali Almazaydeh
A Fully Functional Shopping Mall Application—SHOPPING EYE ............................................................292
K.M.D.M. Karunarathna, H.M.D.A. Weerasingha, M.M Rumy, M.M Rajapaksha, D.I De Silva, and N. Kodagoda Performance Analysis of a Grid Based Route Discovery in AODV Routing
Algorithm for MANET ................................................................................................................................297
Abderezak Touzene and Ishaq Al-Yahyai “Smart Ships”: Mobile Applications, Cloud and Bigdata on Marine Traffic
for Increased Safety and Optimized Costs Operations .............................................................................303
Alejandro García Dominguez A Potential Game Approach Towards Distributive Interference Management
in OFDMA-Based Femtocell Networks .....................................................................................................309
Adnan Shahid, Saleem Aslam, Hyung Seok Kim, and Kyung Geun Lee
Location-Based Services with iBeacon Technology .................................................................................315
Markus Koühne and Jürgen Sieck
Track 25.Y Performance Engineering of Computer and Communication
SystemsStudy of Energy Saving in Carrier-Ethernet Network ...............................................................................322
Rihab Maaloul, Lamia Chaari, and Bernard Cousin Achieving Better Performance Using a New Variable LMS Algorithm Equalizer
for Systems-Based OFDM ........................................................................................................................329
Ziba Reza-zadeh Razlighi and Saeed Ghazi-Maghrebi
Ultra-Wideband Antenna for RFID Underground Oil Industry Application ................................................333
Maged Aldhaeebi, Khalid Jamil, and Abdel R. Sebak
Analysis of VoIP over LTE End-to-End Performances in Congested Scenarios ......................................339
Alessandro VizzarriTrack 26.Z Circuits, Sensors, and Devices Detecting and Minimizing Bad Posture Using Postuino among Engineering
Students ....................................................................................................................................................344
Reem Alattas and Khaled Elleithy
A New Approach for the Differential Spectrum Using the Frobenius Norm ..............................................350
Gelson Cruz, Jonas Kunzler, Rodrigo Lemos, Diego Burgos, Hugo Silva, and Yroá Ferreira
Author Index ............................................................................................................................................355
Welcome Message from the Chairs
We are very pleased to welcome our colleagues from Europe, Asia and other parts of the world to our second international
conference on Artificial Intelligence, Modelling and Simulation 2014 (AIMS2014), held in Madrid, Spain. It follows last
year’s outstandingly successful (with 83 published papers) first international conference held in Kota Kinabalu, Sabah,
Malaysia, 3 – 5 December 2013. The second such event internationally we are hopeful that its outstanding technical content
contributed by leading researchers in the field from numerous countries and research laboratories in both university and
industry worldwide will ensure its continued success. The conference Program Committee has organized an exciting and
balanced program comprising presentations from distinguished experts in the field, and important and wide-ranging
contributions on state-of-the-art research that provides new insights into the latest innovations in computational intelligence,
mathematical and analytical modelling and computer simulation of a diverse range of topics in science, engineering and
technology. No plans have yet been finalized for the location of next year’s event, but it would be appropriate to choose
another interesting location in suitable location in either South East Asia or Europe. The main themes addressed by this conference are: Artificial Intelligence- Neural Networks & Fuzzy Systems Evolutionary Computation • Bioinformatics and Bioengineering • Intelligent Systems and Applicaitons • Control of Intelligent Systems and Control Intelligence
- Robotics, Cybernetics, Engineering, Manufacturing and Control • Image, Speech and Signal Processing • Natural Language Processing/Language Technologies • Industry, Business, Management, Human Factors and Social Issues • Energy, Power, Transport, Logistics, Harbour, Shipping and Marine Simulation
- Parallel, Distributed and Software Architectures and Systems • Internet Modelling, Semantic Web and Ontologies • Mobile/Ad hoc wireless networks, mobicast, sensor placement, target tracking
- Performance Engineering of Computer & Communication Systems • Circuits, Sensors and Devices •
AIMS 2014 is technically co-sponsored with patrons, promoters and supports including IEEE Region 8, Asia Modelling and
Simulation Section, UK Simulation Society, European Simulation Council (EUROSIM), European Council for Modelling
and Simulation (ECMS), University Polytechnic of Madrid (UPM), University of Kingston, UK, University of Liverpool,
UK, University of Malaysia in Sabah (UMS), University of Malaysia in Pahang (UMP), University of Malaysia in Perlis
(UniMaP), University of Technology Malaysia (UTM), University of Technology Mara (UiTM), Institute of Technology
Bandung (ITB), University of Science Malaysia (USM), Machine Intelligence Research Labs (MIR Labs) and Nottingham
Trent University, UK. AIMS2014 proved to be very popular and received submissions from over 20 countries. The
conference program committee had a very challenging task of choosing high quality submissions. Each paper was peer
reviewed by several independent referees of the program committee and, based on the recommendation of the reviewers, 61
papers were finally accepted for publication. The papers offer stimulating insights into emerging modelling and simulation
techniques for intelligent and hybrid intelligent systems and systems that employ intelligent methodologies. We express our
sincere thanks to the keynote speakers, authors, track chairs, program committee members, and additional reviewers who
have made this conference a success. Finally, we hope that you will find the conference to be a valuable resource in your
professional, research, and educational activities whether you are a student, academic, researcher, or a practicing
professional. Enjoy!
David Al-Dabass, Gregorio Romero, Emilio Corchado, Ismail Saad, Alessandra Orsoni, Athanasios Pantelous
General, Conference and Program Chairs
Conference Organization
Conference Chair
Gregorio Romero, University Polytechnic of Madrid, Spain
Honorary Conference Co-Chairs
Emilio Corchado, University of Burgos, Spain
Ismail Saad, University of Malaysia in Sabah, Malaysia
Alessandra Orsoni, University of Kingston, UK
Program Chairs and Honorary Program Co-Chairs
Athanasios Pantelous, University of Liverpool
Zuwairie Ibrahim, University of Malaysia in Pahang (UMP)
Dr Adam Brentnall, Queen Mary, London University, UK
Local Arrangements Chair
Gregorio Romero, University Polytechnic of Madrid, Spain
General Chairs
David Al-Dabass, Nottingham Trent University, UK
Ajith Abraham, Norwegian University of Science and Technology, Norway
International Program Committee Jasmy Yunus Rosni Abdullah Shamin Ahmad Khalid Al-Begain David Al-Dabass Mikulas Alexik Saleh Al-Jufout Ferda Nur Alpaslan Shamsudin Amin Eduard Babulak Arijit Bhattacharya Leon Bobrowski Irfan Syamsuddin Vesna Bosilj-Vuksic Fabian Böttinger Jadranka Bozikov Felix Breitenecker Agostino Bruzzon Piers Campbell Theodoros Kostis Hüseyin K. Çakmak Richard Cant Andrejs Romanovs Vlatko Ceric Sanjay Chaudhary Yuehui Chen Russell Cheng Sung-Bae Cho Emilio Corchado Alan Crispin Andrzej Dzielinski Mohammad Essaaidi Ford Lumban Gaol Fengge Gao Xiaohong Gao Xiao-Zhi Gao Crina Grosan Antonio Guasch
Otávio Noura Teixeira Sadiq Hussain Min-Shiang Hwang Zuwairie Ibrahim Kunio Igusa Hisao Ishibuchi Gerrit Janssens Andras Javor Er Meng Joo Kai Juslin Esko Juuso Nikolaos Karadimas Helen Karatza Arpad Kelemen Marzuki Khalid Dong-hwa Kim Mario Koeppen Issakki Kosonen Kambiz Badie Vincent Lee Hongbo Liu Xiangrong Liu Franco Maceri Emelio Jimenez Macias Mahdi Mahfouf Rashid Mehmood Yuri Merkuryev Galina Merkuryeva Zhou Mingtao Farshad Moradi Gaius Mulley Atulya Nagar Gaby Neumann Leonid Novitski Osamu Ono Alessandra Orsoni
Jeng-Shyang Pan Athanasios Pantelous Charles Patchett P. Pichappan Miguel Angel Piera Henri Pierreval D K Pra Marius Radulescu Fazal Rehman Marco Remondino Olaf Ruhle Paramasivan Saratchandran Kazunori Sato Peter Schwartz Janos Janosy Rohit Sharma Igor Skrjanc Miroslav Snorek Mo Song Mojca Indihar Stemberger K.G. Subramanian R K Subramanian Vassilis Tsoulkas Pandian Vasant Carlos Martin Vide Siegfried Wassertheurer Roland Wertz Wolfgang Wiechert Edward Williams Zhang Yi Rubiyah Yusof Daniela Zaharie Richard Zobel Borut Zupancic
International Reviewers Dayang Norhayati Abg Jawawi Ajith Abraham Mohammad Nazir Ahmad David Al-Dabass Dhiya Al-Jumeily David Aldabass Mikulas Alexik Belal Alhaija Konar Amit Bagus Arthaya Mohsen Askari Eduard Babulak Kambiz Badie Gurvinder-Singh Baicher Arijit Bhattacharya Nurmin Bolong Hueseyin Cakmak Richard Cant Andre Carvalho Brijesh Chaurasia Sung-Bae Cho Jamal Dargham Giuseppe De Francesco Jiri Dvorsky Andrzej Dzielinski Muhammad H Fazli Fauadi G Ganesan Ford Gaol Ida Giriantari Visvasuresh Victor Govindaswamy Sami Habib Aboul Ella Hassanien JERBI Houssem Elisati Hulu Min-Shiang Hwang Zuwairie Ibrahim Nauman Israr Gerrit Janssens Emilio Jimenez Macias S. D. Katebi Dong-hwa Kim Petia Koprinkova-Hristova
Ku Ruhana Ku-Mahamud Satya Kumara Nooritawati Md Tahir Rashid Mehmood Galina Merkuryeva Durgesh Mishra Veronica Moertini Siti Zaiton Mohd Hashim Salwani Mohd. Daud Atulya Nagar Atul Negi Gaby Neumann Alessandra Orsoni Kama Azura Othman Athanasios Pantelous Charles Patchett Gillian Pearce Mirjana Pejic-Bach Evtim Peytchev Raja Kamil Raja Ahmad Arshin Rezazadeh Norlaili Safri Ignatius Sandy Ali Selamat Ajay Singh Fadzilah Siraj Mo Song Rubita Sudirman Dedy Suryadi Irfan Syamsuddin Otavio Teixeira Jason Teo Kenneth Teo Geetam Tomar Martin Tunnicliffe Ijaz Uddin Shekhar Verma Farrah Wong Jasmy Yunus Richard Zobel
Technical Sponsors, Patrons, Promoters and Supporters
IEEE Region 8
IEEE Sain Srection Asia Modelling and Simulation Section UK Simulation Society European Simulation Council (EUROSIM)
European Council for Modelling and Simulation (ECMS) University Polytechnic of Madrid (UPM) University of Kingston, UK University of Liverpool, UK
University of Malaysia in Sabah (UMS) University of Malaysia in Pahang (UMP) University of Malaysia in Perlis (UniMaP) University of Technology Malaysia (UTM)
University of Technology Mara (UiTM) Institute of Technology Bandung (ITB) University of Science Malaysia (USM) Machine Intelligence Research Labs (MIR Labs)
Nottingham Trent University, UK
2014 Second International Conference on Artificial Intelligence, Modelling and Simulation
Keynote Speaker-1
Feature Selection in Data-Driven Systems Modelling
Prof Qiang Shen
Director, Institute of Mathematics, Physics and Computer Science
Aberystwyth University, Wales, UK.
Email: qqs@aber.ac.uk
Feature selection (FS) addresses the problem of selecting those system descriptors that are most
predictive of a given outcome. Unlike other dimensionality reduction methods, with FS the original
meaning of the features is preserved. This has found application in tasks that involve datasets
containing very large numbers of features that might otherwise be impractical to model and process
(e.g., large-scale image analysis, text processing and Web content classification).This talk will focus on the development and application of FS mechanisms based on rough and
fuzzy-rough theories. Such techniques provide a means by which data can be effectively reduced
without the need for user-supplied information. In particular, fuzzy-rough feature selection (FRFS)
works with discrete and real-valued noisy data (or a mixture of both). As such, it is suitable for
regression as well as for classification. The only additional information required is the fuzzy partition
for each feature, which can be automatically derived from the data. FRFS has been shown to be a
powerful technique for data dimensionality reduction. In introducing the general background of FS, this
talk will first cover the rough-set-based approach, before focusing on FRFS and its application to real-
world problems. The talk will conclude with an outline of opportunities for further development.Speaker’s Biography Professor Qiang Shen received a PhD in Knowledge-Based Systems and a DSc in Computational Intelligence. He holds the Established Chair of Computer Science and is Director of the Institute of Mathematics, Physics and Computer Science at Aberystwyth University. He is a Fellow of the Learned Society of Wales, a UK REF 2014 panel member for Computer Science and Informatics, and a long-serving Associate Editor of two IEEE flagship Journals (IEEE Transactions on Cybernetics and IEEE Transactions on Fuzzy Systems). He has chaired and given keynotes at numerous international conferences.
Professor Shen’s current research interests include: computational
intelligence, reasoning under uncertainty, pattern recognition, data mining, and their real-world
applications for intelligent decision support (e.g., crime detection, consumer profiling, systems
monitoring, and medical diagnosis). He has authored 2 research monographs and over 340 peer-
reviewed papers, including an award-winning IEEE Outstanding Transactions paper. Qiang has served
as the first supervisor of over 40 PDRAs/PhDs, including one UK Distinguished Dissertation Award
winner.
2014 Second International Conference on Artificial Intelligence, Modelling and Simulation
Keynote Speaker-2
Challenges in Handling and Processing Huge Data
Prof Hermann-Hessling
Hochschule für Technik und Wirtschaft Berlin
10313 Berlin
hessling@htw-berlin.de
Data-intensive computing is considered as the fourth paradigm in science. The term “data-intensive
computing” did not establish in other communities although they are also confronted with enormous
amounts of data. Nowadays, Big Data refers to data sets that are too large, too complex, too distributed
for analysing them by conventional methods. One strategy for handling Big Data is known as “software
to the data” which is applicable when it is more efficient to bring the analysis tools to the data than,
vice versa, to apply traditional methods where, for example, all data are collected at some place and
analysed there.The data production rate is expected to increase exponentially for the time being. This is particularly
true in science where the resolution power of experiments is steadily improving. Sooner or later it has
to be taken into account that it is not feasible to store all data anymore. A new era is on the horizon:
Huge Data.Huge Data have to be pre-analysed during the data-taking period in order to extract a sufficiently
small subset of data that is worth to be analysed in more detail later on. An effective and efficient pre-
selection in real-time or near-realtime is most critical for successfully handling Huge Data. This is
made more challenging if during the pre-analysis that has to be done in parallel, intermediate results
have to be exchanged. The talk considers selected challenges of Huge Data. Some examples from different scientific communities are presented.Speaker’s Biography Hermann Heßling studied Physics at the Universities of Münster, Göttingen and Hamburg. He received the Ph.D. (Dr. rer. nat) in Theoretical Physics and was appointed a postdoctoral research fellow at Deutsches Elektronen-Synchrotron (DESY) Hamburg (1993-1996). Subsequently, he continued his work with a computer communicaitons and networking company and accepted in 1999 an offer from the University of Applied Sciences Hof as a Professor of Operating Systems. Since 2000 he has been professor of Applied Informatics at the University of Applied Sciences HTW Berlin.
Using Ontology for Providing Content Recommendation Based on Learning Styles inside
E-Learning
Sri Suning Kusumawardani, Robertus Sonny Prakoso, Paulus Insap Santosa
HEORETICAL
2014 Second International Conference on Artificial Intelligence, Modelling and Simulation
Felder-Silverman Learning Style Model (FSLSM) is learning style model that built and developed based on experience and environment in engineering education [1]. There are four dimensions in this model. Every student will have preference on each dimension. These four dimensions in Felder-Silverman Learning Style Model are.
B. Felder-Silverman Learning Style Model
The ontology for modelling learning tree inside e- Learning can be used for creating personalized e-Learning [7]. Another work is using ontology for generating student activity report inside from the activity log inside Moodle- based e-Learning [8]. This research combines these two concepts that is using ontology and giving recommendation inside e-Learning. More specific, this research use ontology as the main knowledge-based that the e-Learning used for giving content recommendation.
There are some related works on e-Learning that giving recommendation function inside e-Learning based on students’ learning style. The developed system to detect students’ learning styles based on their choices inside a search engine in e-Learning, and then used this information to give a recommendation in search result [5]. Another work in personalized e-Learning is developed recommendation system inside e-Learning based on students’ learning style and record of the students’ activity in e-Learning [6]. Both works were using Felder-Silverman Learning Style Model as learning style model in the e-Learning.
A. Related Works
OUNDATION
F
II. T
Department of Electrical Engineering and Information Technology
Learning styles model that used in this research is Felder- Silverman Learning Style Model. This learning style model is more suitable for being implemented in adaptive e- Learning because it covers more psychological aspect than other models [3]. Moreover, kinds of e-Learning contents and features are picked from Moodle-based e-Learning, so this knowledge based will be implemented on Moodle-based e-Learning. This knowledge based will be represented as an ontology. We choose ontology as knowledge representation because it is readable and understandable, not only by human but also by machine [4].
Refer to the above descriptions, a mapping from characteristics of each category on learning styles to the appropriate contents and features is needed. This mapping will be used for deciding in which learning style category a student fall, and which contents are appropriate to this student. This research is focused on developing knowledge based of learning styles characteristics and appropriate contents on e-Learning.
As the growth of information and communication technology, now there are many features and content types inside e-Learning that used as learning materials and communication models between teacher and students. This variety of features and content types can be used for accommodating many types of learning styles. It will be better for the students if they get a recommendation of contents and features in e-Learning that appropriate to their learning styles.
Today, there are many supporting facilities that can be used in learning and teaching. One of these facilities that begin to be widely used is e-Learning. E-Learning is one of the supporting facilities in learning that considered as an effective method for learning [2].
Learning style is used to classify students based their preference to receive and process information [1]. In conventional learning, the students should get different treatment that fits their learning style. However, it’s difficult for the teacher to teach in many ways and match all learning styles of the students because of their limitation and ability in teaching.
NTRODUCTION Every student has a preference in learning process.
Keywords-ontology; e-Learning; learning style; Felder- Silverman Learning Style Model