CONFERENCE PROGRAM the 6Th IASTED International Conference

CONFERENCE PROGRAM

The 6th IASTED International Conference on Computational Intelligence and Bioinformatics (CIB 2011) & The IASTED International Conference on Modelling, Simulation and Identification (MSI 2011) November 7 - 9, 2011 Pittsburgh, USA LOCATION Wyndham Hotel Pittsburgh – University Place 3454 Forbes Avenue Pittsburgh, Pennsylvania 15213 USA COMPUTATIONAL INTELLIGENCE AND BIOINFORMATICS (CIB 2011)

SPONSOR S. Boytcheva – Bulgarian Academy of Sciences, Bulgaria The International Association of Science and Technology for M.I. Chacon Murguia – Technological Institute of Development (IASTED) Chihuahua, Mexico S.K. Chalup – The University of Newcastle, Australia CONFERENCE CO-CHAIRS Y.M. Cheung – Hong Kong Baptist University, PR China Prof. Taieb Znati – University of Pittsburgh, USA R.B. Chinnam – Wayne State University, USA Prof. Ziv Bar-Joseph – Carnegie Mellon University, USA Y. Crispin – Embry-Riddle Aeronautical University, USA M. das Gracas de Almeida – Federal Center For KEYNOTE SPEAKERS Technological Education of Minas Gerais, Brazil V. Dasigi – Southern Polytechnic State University, USA Prof. Robert F. Murphy – Carnegie Mellon University, A. de Carvalho – University of Sao Paulo, Brazil USA E. del Moral Hernandez – University of Sao Paulo, Brazil Dr. Jaime G. Carbonell - Carnegie Mellon University, USA A. Delgado – National University of Colombia, Colombia

A. Dourado – University of Coimbra Polo II, Portugal TUTORIAL SESSION R.J. Dzeng – National Chiao-Tung University, Taiwan Dr. Isaac Olusegun Osunmakinde – Council for Scientific P. Ekel – Pontifical Catholic Universitry of Minas Gerais, and Industrial Research (CSIR), South Africa Brazil A. Elnagar – University of Sharjah, UAE INTERNATIONAL PROGRAM COMMITTEE T. Elomaa – Tampere University of Technology, Finland MM. Abulaish – Jamia Millia Islamia (Central University), R. Faglia – State University of Brescia, Italy India J.A. Felippe de Souza – University Beira Interior (UBI), G. Agre – Bulgarian Academy of Sciences, Bulgaria Portugal I. Al-Bahadly – Massey University, New Zealand J. Fernandez de Cañete – University of Malaga, Spain G. Angelova – Bulgarian Academy of Sciences, Bulgaria M. Gams – Jozef Stefan Institute, Slovenia D. Arotaritei – University of Medicine and Pharmacy Gr.T. A. Gelbukh – National Polytechnic Institute, Mexico Popa Jassy, Romania J. Ghaboussi – University of Illinois at Urbana-Champaign, N. Belacel – National Research Council Canada, Canada USA J. Berger – Defense Research & Development Canada - J.A. Giampapa – Carnegie Mellon University, USA Valcartier, Canada S.U. Guan – Xian Jiatong-Liverpool University, China U. Bodenhofer – Johannes Kepler University, Austria P. Hartono – Future University-Hakodate, Japan M. Boumedine – University of the Virgin Islands, U.S. C.C. Hung – Southern Polytechnic State University, USA Virgin Islands F. Ionescu – Steinbeis University Berlin, Germany 1

N. Ishii – Aichi Institute of Technology, Japan R. Tadeusiewicz – Akademia Górniczo-Hutnicza University H. Jaddu – Al-Quds University, Israel of Science and Technology, Poland J.G. Juang – National Taiwan Ocean University, Taiwan Y. Tan – Peking University, PR China S. Kanae – Fukui University of Technology, Japan P. Tino – University of Birmingham, UK C. Kemke – University of Manitoba, Canada Z.A. Vale – Polytechnic Institute of Porto, Portugal N. Kemper Valverde – National Autonomous University of S. Veres – University of Southampton, UK Mexico, Mexico A. Verikas – Halmstad University, Sweden T. Kerh – National Pingtung University of Science and H. Wang – Institute of Automation, Chinese Academy of Technology, Taiwan Sciences, PR China B. Kovalerchuk – Central Washington University, USA Z. Wang – Brunel university, UK V. Kvasnicka – Slovak Technical University, Slovakia J. Wu – Zhejiang University, PR China I.S. Lee – Kyungpook National University, Korea L. Xu – Chinese University of Hong Kong, PR China K. Leiviskä – University of Oulu, Finland R.R. Yager – Iona College, USA C. León de Mora – University of Seville, Spain E.E. Yaz – Marquette University, USA D. Liu – University of Illinois, USA W. Yu – National Polytechnic Institute, Mexico Y.S. Lu – National Taiwan Normal University, Taiwan M. Zhang – Christopher Newport University, USA P. Lucas – Radboud University of Nijmegen, S. Zhikun – Beihang University, PR China The Netherlands L. Magdalena – European Centre for Soft Computing, Spain ADDITIONAL PAPER REVIEWERS G.M. Mendez – Technology Institute of Nuevo Leon, Y. Fang – Purdue University, USA Mexico K. Lee – IASTED Calgary, Canada A. Milani – University of Perugia, Italy A. System – IASTED, Canada R. Mitchell – The University of Reading, UK J. Wang – Peking University, China J. Murata – Kyushu University, Japan M. Nallasamy – Box Hill Institute, Australia V. Negru – West University of Timisoara, Romania N. Obeid – University of Jordan, Jordan I.O. Osunmakinde – Council for Scientific and Industrial Research, South Africa S. Ozcelik – Texas A&M University, USA M.M. Polycarpou – University of Cyprus, Cyprus J. Quah – Nanyang Technological University, Singapore S.H. Rubin – Spawar Systems Center, USA J. Shim – Kangnam University, Korea G. Sidorov – Center for Computing Research, National Polytechnical Institute, Mexico J. Sidorova – The Public University of Tarragona, Spain G. Sirakoulis – Democritus University of Thrace, Greece M. Sirola – Aalto University, Finland J. Smieja – Silesian University of Technology, Poland P. Sosnin – Ulianovsk State Technical University, Russia C.Y. Su – Concordia University, Canada L. Sztandera – Philadelphia University, USA

MODELLING, SIMULATION AND IDENTIFICATION (MSI 2011)

SPONSORS F. Ma – University of California at Berkeley, USA The International Association of Science and Technology for P. Mahanti – University of New Brunswick, Canada Development (IASTED) K.L. Man – Xi'an Jiaotong-Liverpool University, PR China • Technical Committee on MSI M. Marčoková – University of Zilina, Slovakia F. Mili – Oakland University, USA CONFERENCE CHAIR K. Möller – Furtwangen University, Germany Prof. Ling Rothrock – Pennsylvania State University, USA L. Monticone – MITRE Corporation, USA E.D. Moreno – Federal University of Sergipe, Brazil J. Navarro-Moreno – University of Jaen, Spain LOCAL ARRANGEMENTS CHAIR J.J. Nieto – University of Santiago de Compostela, Spain Dr. Ajay Ogirala – University of Pittsburgh, USA G. Nikolakopoulos – University of Patras, Greece

A. Ogirala – University of Pittsburgh, USA KEYNOTE SPEAKER J. Otamendi – King Juan Carlos University, Spain Prof. Shane G. Henderson – Cornell University, USA H. Oya – The University of Tokushima, Japan G. Petuelli – South-Westphalia University of Applied INTERNATIONAL PROGRAM COMMITTEE Sciences, Germany J.C. Amaro Ferreira – High Institute of Engineering of C. Pinto – Porto Superior Institute of Engineering, Portugal Lisbon, Portugal M. Pistauer – CISC Semiconductor Design and Consulting C. Angeli – Technological Institute of Piraeus, Greece GmbH, Austria H. Attia – McGill University and National Research Council M. Poboroniuc – The Gheorghe Asachi Technical of Canada, Canada University of Iasi, Romania J. Boaventura – University of Tras-os-Montes and Alto N.H. Rashidi – Virginia State University, USA Douro, Portugal G. Razaqpur – McMaster University, Canada W. Borutzky – Bonn-Rhein-Sieg University of Applied R. Revetria – University of Genoa, Italy Sciences, Germany M. Rodrigues – Sheffield Hallam University, UK P.C. Breedveld – University of Twente, The Netherlands E. Santini – Sapienza University of Rome, Italy B. Dobrucky – University of Zilina, Slovakia D. Schreurs – K.U.Leuven, Belgium D. Dutta – Monash University, Australia B. Shafai – Northeastern University, USA A. Elkamel – University of Waterloo, Canada Y.S. Shmaliy – Guanajuato University, Mexico P. Fishwick – University of Florida, USA B. Singh – Lakehead University, Canada K.A. Folly – University of Cape Town, South Africa R. Snow – Riddle Aeronautical University, USA E. Furutani – Kyoto University, Japan Y.J. Son – University of Arizona, USA G. Fusco – University of Cassino, Italy W. Song – National Tsing Hua University, Taiwan D. Gorgan – Technical University of Cluj-Napoca, Romania J.A. Tenreiro Machado – Porto Superior Institute of G.A. Gravvanis – Democritus University of Thrace, Greece Engineering, Portugal V. Grout – Glyndwr University, UK G.K. Theodoropoulos – Dublin Research Lab, Ireland S.U. Guan – Xian Jiatong-Liverpool University, PR China C. Thorbole – The Engineering Institute, USA K.E. Häggblom – Åbo Akademi University, Finland A. Tornambè – University of Rome Tor Vergata, Italy R. Henriksen – Norwegian University of Science and M. Trabia – University of Nevada, USA Technology, Norway H. Trinh – Deakin University, Australia G. Incerti – University of Brescia, Italy T. Tsubaki – Yokohama National University, Japan B. Joseph – University of South Florida, USA H. Unger – Fern University in Hagen, Germany V. Jotsov – State University in Sofia, Bulgaria J. Vance – The University of Virginia's College at Wise, USA D.N. Kaziolas – Technological Educational Institute of G. Varga – University of Miskolc, Hungary Kavala, Greece J. Vojtesek – Bata University in Zlin, Czech Republic R. Lamanna – Simon Bolivar University, Venezuela Q.G. Wang – National University of Singapore, Singapore M. Lee – Yeungnam University, South Korea K.P. White – University of Virginia, USA M. Lotfalian – University of Evansville, USA D. Xu – Chinese Academy of Science, PR China

M.C. Yagoub – University of Ottawa, Canada PLEASE NOTE E.E. Yaz – Marquette University, USA R. Younsi – Montreal Polytechnical University, Canada  Paper presentations are 15 minutes in length with an H. Yu – Staffordshire University, UK additional 5 minutes for questions. Y.M. Zhang – University of Kentucky, USA  Report to your Session Chair 15 minutes before the Z. Zhang – University of Exeter, UK, USA session is scheduled to begin.  Presentations should be loaded onto the presentation ADDITIONAL PAPER REVIEWERS laptop in the appropriate room prior to your session. G. Andrikopoulos – University of Patras, Greece  End times of sessions vary depending on the J. Arvanitakis – University of Patras, Greece number of papers scheduled. C. Papachristos – University of Patras, Greece M. Saga – University of Zilina, Slovakia

PROGRAM OVERVIEW

Monday, November 7, 2011 Tuesday, November 8, 2011

07:00 – Registration 09:00 – CIB/MSI Keynote Speaker – “Machine Learning (Foyer) Approaches for Systems Biology and Drug Discovery” – Prof. Robert F. Murphy 08:30 – MSI/CIB Welcome Address (Forbes B Room) 09:00 (Forbes B Room) 10:00 – Coffee Break 09:00 – MSI/CIB Keynote Speaker– “Where Should 10:30 (Foyer) Ambulances be Stationed?” – Prof. Shane G. Henderson 10:30 – MSI Session 3 – Energy and Power Systems (Forbes B Room) Modelling II (Forbes B Room) 10:00– Coffee Break 10:30 (Foyer) 12:30 – Lunch Break Self-Catered 10:30 – MSI Session 1 – Energy and Power Systems Modelling I 13:30 – CIB/MSI Keynote Speaker– “Machine Learning (Forbes B Room) Methods for Proteomic Analysis” – Dr. Jaime G. Carbonell 12:10 – Lunch Break (Forbes A Room) Self-Catered 14:30 – Coffee Break 13:30 – MSI Session 2 – Modelling and Simulation 15:00 (Foyer) Methodologies I (Carlow Room - 8th Floor) 15:00 – MSI Session 4 – Environmental Systems Modelling (Chatham Room - 7th Floor) 14:30 – Coffee Break 15:00 (Foyer) 19:00 – Dinner Banquet (Forbes Ballroom) 15:00 – MSI Session 2 Continued (Carlow Room - 8th Floor)

15:00 – CIB Session 1 – Computational Intelligence Algorithms and Optimization (Forbes B Room)

Wednesday, November 9, 2011 Monday, November 7, 2011

9:00 – CIB/MSI Tutorial Session – “Remote Monitoring of 07:00 – REGISTRATION Toxic Gases in Underground Mines: building Location: Foyer knowledge for improving miners’ health and future” – Dr. Isaac Olusegun Osunmakinde 08:30 – 09:00 MSI/CIB WELCOME ADDRESS (Carlow Room - 8th Floor) Location: Forbes B Room

10:00 – Coffee Break 09:00 – MSI/CIB KEYNOTE SPEAKER – “WHERE 10:30 (Foyer) SHOULD AMBULANCES BE STATIONED?” Presenter: Prof. Shane G. Henderson (USA) 10:30 – CIB/MSI Tutorial Session Continued Location: Forbes B Room (Carlow Room - 8th Floor) Ambulance organizations all around the world are facing 12:10 – Lunch Break increasing call volumes, increasing traffic congestion, and Self-Catered shrinking budgets. To keep response times small, many are looking to employ some kind of system-status management 13:10 – MSI Session 5 – Modelling in Biomedicine and (SSM). SSM is the practice of real-time control of the Biomechanics ambulance fleet, using Global Positioning System (GPS) (Forbes A Room) units on the ambulances to track location, and information from the ambulance crews to track status. Available 13:10 – CIB Session 2 – Computational Intelligence Models ambulances are carefully stationed to ensure coverage, while for Learning and Data Mining not requiring too many moves of the ambulance crews. I'll (Carlow Room - 8th Floor) describe my work to help make the location decisions, using a combination of statistics to model inputs, approximate 14:30 – Coffee Break dynamic programming to make stationing decisions in real 15:00 (Foyer) time, simulation optimization to "tune" the approximate dynamic programming algorithm and bounding techniques 15:00 – MSI Session 5 Continued to determine what response times might be achievable in a (Forbes A Room) given city.

15:00 – CIB Session 2 Continued Shane G. Henderson is a professor in, and past director of, (Carlow Room - 8th Floor) the School of Operations Research and Information Engineering at Cornell University. He has previously held 16:00 – MSI Session 6 – Identification positions in Industrial and Operations Engineering at the (Forbes B Room) University of Michigan and in Engineering Science at the University of Auckland. His research interests include 16:20 – MSI Session 7 – Modelling and Simulation discrete-event simulation and simulation optimization, with Methodologies II an emphasis on applications in the emergency services. He has (Forbes A Room) also worked on radiation therapy planning for cancer

treatment, yacht design for match racing in the America's

Cup, and in a kind of technical hobby he has even advised

students in analyzing aspects of the game of Monopoly! He is

the simulation area editor for Operations Research, the current chair of the INFORMS Applied Probability Society, and co-edited both the "Handbook of Simulation" (Elsevier, 2006) and the Proceedings of the 2007 Winter Simulation Conference.

10:00 – 10:30 – COFFEE BREAK 13:30 – MSI SESSION 2 – MODELLING AND Location: Foyer SIMULATION METHODOLOGIES I Chairs: Dr. Nadine Sangster (Trinidad and Tobago) and 10:30– MSI SESSION 1– ENERGY AND POWER Dr. Hazem Kaylani (Jordan) SYSTEMS MODELLING I Location: Carlow Room - 8th Floor Chair: Prof. Bolatbek Utegulov (Kazakhstan) Location: Forbes B Room 755-016 Control Strategy and its Parameters Optimization for 755-003 Outsourcing Production Inventory System Under Slab Hot Delivery and Hot Charge System Production Uncertainty Dispatching and Optimization based on Heat Process Model Xiaofeng Zhu, Le Cao, Fei Liu, and Haixia Wang (PR China) Lijun Liu, Zhi Wen, Fuyong Su, Ruifeng Dou, Xunliang Liu, and Guofeng Lou (PR China) 755-039 A Multi-Purpose Simulation Approach for Digital Factory 755-012 Environments based on Java EE Analysis of Models for Multi-Agent Business Processes Helge Hemmer, Marcus Silber and Wolfgang Kühn (Germany) Formalization Konstantin Aksyonov, Eugene Bykov, Anna Antonova, 755-047 Olga Aksyonova, Ekaterina Sufrygina, and Natalia Goncharova Use of System Dynamics for Modelling the Logistic Facilities (Russia) of an Offshore Supply Base Operated by a Multinational Company 755-024 Francesco Ferri, Piero Giribone, Roberto Revetria, and Optimization of Chemical Enterprise Facility Layout based Alessandro Testa (Italy) on Logistics System State Analysis Tao Zhao, Tao Lin, and Xiaoxin Cheng (PR China) 755-065 Modeling Rough Piston Skirts EHL at Very Low Initial 755-029 Engine Startup Speeds - Pressure Flow Factors Effects Excitation Control Asynchronized Synchronous Syed Adnan Qasim, Mubashir Gulzar, Riaz A. Mufti, and Compensators Remedy for Mains Voltage Fluctuations with M. Afzaal Malik (Pakistan) Sharply Variable Loads Bolatbek Utegulov, Arman Utegulov, Meiram Begentayev, 755-074 Aigul Uakhitova, Serik Zhumazhanov, and Numerical Simulation of Flow Field and Pollutant Nazhmitden Zhakipov, and Gulshat Tleulenova (Kazakhstan) Dispersion in a Long Highway Tunnel Harish Kumar, Krishna M. Singh, and Bhupendra K. Gandhi 755-030 (India) Establishing Ceiling Voltage, Limit Slips and Inertia Constant in a Rotor of Asynchronized Synchronous 755-080 Compensator Bounds Testing Approach to Cointegration: An Examination Bolatbek Utegulov, Arman Utegulov, Meiram Begentayev, of Government Expenditures and Money Supply Aigul Uakhitova, Serik Zhumazhanov, Nazhmitden Zhakipov, Relationships and Dmitry Koftanyuk (Kazakhstan) Mastooreh Eshraghi (Malaysia) and Babak Farjad (Iran)

755-040 12:10 – LUNCH BREAK The Choice of Economic Policy Based on Multi-Criteria Self-Catered Optimization Abdykappar A. Ashimov, Bahyt T. Sultanov, Yuriy V. Borovskiy, Rakhman A. Alshanov, Nikolay Y. Borovskiy, and Bakytzhan A. Aisakova (Kazakhstan)

755-045 753-012 Simulation Tools for Producing Metadata Description Sets Fast and Deterministic Computation of Fixation Probability Covering Simulation-based Content in Evolutionary Graphs Jonathan P. Leidig, Edward A. Fox, and Madhav Marathe Paulo Shakarian and Patrick Roos (USA) (USA) 753-032 755-051 Metaheuristics for the Maximum Parsimony Problem Simulation of Fuzzy System for Control of Complex Plants Karla E. Vazquez-Ortiz and Eduardo Rodriguez-Tello (Mexico) Nadine Sangster and Prakash Persad (Trinidad and Tobago) 753-019 755-056 An Artificial Fish Swarm based Supervised Gene Rank Bit-Packed Damaged Lattice Potts Model Simulations with Aggregation Algorithm for Informative Genes Studies CUDA and GPUs Nan Du, Supriya D. Mahajan, Bindukumar B. Nair, Ken A. Hawick and Mitchell G.B. Johnson (New Zealand) Stanley A. Schwartz, Chiu B. Hsiao, and Aidong Zhang (USA)

755-076 753-029 Simulation based Genetic Algorithm Approach for Comparing Clustering Algorithms based on Structural Integrating Process Planning and Scheduling Similarity Hazem A. Kaylani and Safwan A. Altarazi (Jordan) Nassim Sohaee and Christian V. Forst (USA)

14:30 – 15:00 COFFEE BREAK Location: Foyer

15:00 – MSI SESSION 2 CONTINUED Location: Carlow Room - 8th Floor

15:00 – CIB SESSION 1– COMPUTATIONAL INTELLIGENCE ALGORITHMS AND OPTIMIZATION Chair: Mr. Alan Jennings (USA) Location: Forbes B Room

753-025 Ensemble Decomposition Learning for Optimal Utilization of Implicitly Encoded Knowledge in Biomedical Applications Olga V. Senyukova (Russia) and Valeriy V. Gavrishchaka (USA)

753-017 Multi-Objective Robust Optimization for In Vitro RNA Synthesis Satoru Akama, Masayuki Yamamura, and Takanori Kigawa (Japan)

753-031 Memory-based Motion Optimization for Unbounded Resolution Alan L. Jennings and Raúl Ordóñez (USA) 753-040 Applying Enumerative, Spectral and Hybrid Graph Analyses to Biological Network Data Ken A. Hawick (New Zealand) 8

Tuesday, November 8, 2011 Robert F. Murphy is the Ray and Stephanie Lane Professor of Computational Biology and Director (Department Head) of the Lane Center for Computational Biology in the School 9:00 – CIB/MSI KEYNOTE SPEAKER – “MACHINE of Computer Science at Carnegie Mellon University. He also LEARNING APPROACHES FOR SYSTEMS is Professor of Biological Sciences, Biomedical Engineering, BIOLOGY AND DRUG DISCOVERY” and Machine Learning. He is a Fellow of the American Presenter: Prof. Robert F. Murphy (USA) Institute for Medical and Biological Engineering, and Location: Forbes B Room received an Alexander von Humboldt Foundation Senior

Research Award in 2008. Dr. Murphy has co-edited two Recognition of cells, tissues and organs as complex systems books and three special journal issues on cell imaging, and has with emergent properties has led to the creation of the field of published over 180 research papers. He is Past-President of systems biology, and this complexity has also been manifested the International Society for Advancement of Cytometry, was in a number of prominent drug recalls due to unanticipated named as the first External Senior Fellow of the School of Life side effects. Cutting-edge machine-learning methods have an Sciences in the Freiburg (Germany) Institute for Advanced important role to play in understanding biological systems Studies, and is a member of the National Advisory General and aiding drug development. Cell imaging assays are widely Medical Sciences Council. used in drug development and systems biology, and improved methods to extract detailed information from imaging assays Dr. Murphy’s career has centered on combining fluorescence- are needed. The CellOrganizer project provides tools for based cell measurement methods with quantitative and learning generative models of cell organization directly from computational methods. In the mid 1990’s, his group images and for synthesizing cell images (or other pioneered the application of machine learning methods to representations) from one or more models. Model learning high-resolution fluorescence microscope images depicting captures variation among cells and inputs can be two- or subcellular location patterns. His current research interests three-dimensional static images or movies. Current include image-derived models of cell organization and active components of CellOrganizer can learn models of cell shape, machine learning approaches to experimental biology. nuclear shape, chromatin texture, vesicular organelle size, shape and position, and microtubule distribution. These 10:00 – 10:30 COFFEE BREAK models can be conditional upon each other: for example, for a Location: Foyer given synthesized cell instance, organelle position is dependent upon the cell and nuclear shape of that instance. Major advantages of the generative model approach are that 10:30 – MSI SESSION 3 – ENERGY AND POWER models learned from separate experiments can be combined SYSTEMS MODELLING II into one synthetic cell instance, and that results from different Chairs: Asst. Prof. Iyad Muslih (Jordan) and microscope systems and different experimental conditions can Prof. Bhupendra Gandhi (India) be compared through the framework of the generative model Location: Forbes B Room parameters that describe them. This will be especially 755-032 important for integrating results from diverse studies of the Research on the Relationship Among Electricity effects of drugs and other perturbagens. However, this leads Consumption, Economic Growth and Carbon Emissions in to a second machine learning challenge. Since the number of Inner Mongolia proteins that can be affected is in the tens of thousands, and Guofang Mi, Tao Zhao, and Qiang Dong (PR China) the number of potential therapeutics whose effects we would like to know is at least in the hundreds of thousands, 755-052 exhaustive testing of all compounds on all proteins is not Hybrid Micro-Power Station; Output Power Analysis, Cost feasible. Active machine learning methods, combined with Analysis, and Environmental Impact by Using HOMER generative models, can provide a framework for exploring Modeling Software large perturbagen spaces to find potential therapeutics with high desired activity on a specific target while minimizing Iyad M. Muslih and Yehya N. Abdellatif (Jordan) activity on other targets.

755-057 known for the Maximal Marginal Relevance principle in Energy Optimization Method for Large Natural Gas Supply information retrieval, for derivational analogy in problem Networks solving and for example-based machine translation and for Diego J. Guillen, Lesme A. Corredor, machine learning in structural biology. Overall, he has Marco E. Sanjuán, and Ricardo Lizarazo (Colombia) published some 300 papers and books and supervised over 40 PhD dissertations. Dr. Carbonell has served on multiple 755-068 governmental advisory committees such as the Human Numerical Simulation of Flow through a Francis Turbine Genome Committee of the National Institutes of Health, the Tarun Parashar, Bhupendra K. Gandhi, and Krishna M. Singh Oakridge National Laboratories Scientific Advisory Board, (India) the National Institute of Standards and Technology Interactive Systems Scientific Advisory Board, and the 755-073 German National Artificial Intelligence (DFKI) Scientific A Bond Graph Approach to Hydraulic Hybrid Vehicle Advisory Board. He is also the chairman of Carnegie Speech Muhammad Sajjad S. Malik, Aamer Baqai, and Raja A. Azeem Company, which produces intelligent language tutoring (Pakistan) software.

755-078 14:30 – 15:00 COFFEE BREAK Optimal Array of Energy Farm Buoys Location: Foyer Jung L. Lee, Joo Y. Lee, Jung S. Park, and Jung W. Kim (Korea) 15:00 – MSI SESSION 4 – ENVIRONMENTAL SYSTEMS MODELLING 12:30 – LUNCH BREAK Chair: Prof. Dr. A.K.M. Mohiuddin (Malaysia) Self-Catered Location: Chatham Room - 7th Floor

13:30 – CIB/MSI KEYNOTE SPEAKER – MACHINE 755-007 LEARNING METHODS FOR PROTEOMIC Dynamic Modeling and Vibration Analysis of Airborne ANALYSIS Electronic Cases Presenter: Dr. Jamie G. Carbonell (USA) Fei Xu, Chuanri Li, Xiaoxi Guo, and Tongmin Jiang Location: Forbes A Room (PR China)

Many challenges in structural biology may be addressed by 755-009 existing and emerging machine learning approaches. These Probit Analysis of Landslide Dam Stability in Japan challenges include protein functional family/sub-family Kenneth H. Tiedemann (Canada) classification, inferring secondary, tertiary and quaternary 3D 755-022 structure from 1D sequence, inferring within-species and Brief Analysis of Spatial Clustering of Mexico City Air cross-species (host-pathogen) protein-protein interactions. Pollution Centroids during MILAGRO Campaign The talk addresses machine leaning methods from simple Alejandro Salcido, Ana-Teresa Celada-Murillo, classifiers to linked conditional random fields and their role in-silico bio-informatics, including methods and empirical Susana Carreón-Sierra, and Carlos-Daniel Salcido-Merino results to date. (Mexico) 755-028 Dr. Jaime Carbonell is the Director of the Language Modelling the Optimal Testing Strategies for Preventing Technologies Institute and Allen Newell Professor of Wheat Handling Risks Computer Science at Carnegie Mellon University. He Houtian Ge, James F. Nolan, and Richard S. Gray (Canada) received SB degrees in Physics and Mathematics from MIT, and MS and PhD degrees in Computer Science from Yale 755-038 University. His current research includes machine learning, Agricultural Residue Biomass Resources in Thailand computational proteomics, data mining (primarily in Jerasorn Santisirisomboon and Jaruthat Santisirisomboon healthcare and finance), text mining and machine translation. (Thailand) He recently invented Proactive Machine Learning, including its underlying decision-theoretic framework. He is also 10

755-063 Wednesday, November 9, 2011 Simulation and Models on Control of Pests with Ozone in Greenhouses Plant 09:00 – CIB/MSI TUTORIAL SESSION – REMOTE Rongchang Yuan (PR China), Si Chen (USA), Zhengjiang Li, MONITORING OF TOXIC GASES IN Shengrong Lu, Li Wang, and Haigan Yuan (PR China) UNDERGROUND MINES: BUILDING KNOWLEDGE FOR IMPROVING MINERS’ 755-064 HEALTH AND FUTURE Simulation and Experimental Validation: Waste Cooking Oil Presenter: Dr. Isaac Olusegun Osunmakinde (South Africa) Transesterification using Rushton and Elephant Ear Impellers Location: Carlow Room - 8th Floor A.K.M. Mohiuddin (Bangladesh), Nabeel Adeyemi (Malaysia), Mohamed E.S. Mirghani (Sudan), Abiodun M. Aibinu The steadily rising gas fatality in underground mines and the (Nigeria), Rashid A. Aziz (Malaysia), Firmansyah Firmansyah need to reduce global toxic gas concentration suspended in (Indonesia), and Yohannes T. Anbese (Ethiopia) the air to improve miners’ health and to protect our environment are today’s economical and ecological drivers for 755-008 the emerging consideration of mineral consumption in Probit Analysis of Landslide Dam Stability in Italy mining industry. After a steep increase of contributions, the Kenneth H. Tiedemann (Canada) mine safety-related research is currently entering a mature

phase, in which specific solutions address mining gases 19:00 – DINNER BANQUET challenges. This tutorial will address the challenging issue of Location: Forbes Ballroom static and mobile robot gas sensing in generating knowledge to assist in improving miners’ health and future.

Interestingly, certain algorithms rooted in computational intelligence show increasing performance in generating drivability maps for robot navigation, developing behaviours for robots, and eventually generate knowledge for assisting in reducing miners diseases resulted from toxic gases (e.g. Methane, Carbon monoxide gases, etc.). Specifically, computational algorithms based on Gaussian mixture model (GMM) and expected maximisation (EM), predictive power of k-nearest neighbour (k-NN) and Bayesian Network (BN) models will be presented for addressing the challenges above.

Our tutorial consists of three parts including objectives which are:

(1) Introduction, Motivation, and Preliminaries (10 minutes)

Safety is very important in the mining industry. Underground mine accidents could lead to fatal injuries, sicknesses, diseases, huge economic loss and death of miners. The first part of the tutorial provides an introduction to several lives that have been lost due to toxic mine gases inhalations.

The introduction then lays a solid conceptual foundation towards the purpose of this tutorial, to identify and quantify toxic gases which are extremely prevalent in the underground mines and that cannot be easily detected by human senses.

It introduces key notions of generating knowledge for a better Tutorial Outline: understanding of how a healthy underground mine (1) Introduction, Motivations, and Preliminaries (30 environment is before entering there to work, on the basis of minutes) real-time remote monitoring of the gas levels in different * Origin and Relevance of Improving Miners Health and underground mine areas, and the important relation to static Safety or mobile robot sensing. * Specific Motivations and Health Effects of Toxic Mine Gases (2) Drivability Mapping of Underground Mines for * Recent Gas Injuries, Illness, and Fatalities Autonomous Robots (10 minutes) * Toxic Mine Gases and Health Effects * Hazards Associated with Toxic Mine Gases The second part presents illustrations of a drivability mapping * Existing Measures in Combating Toxic Mine Gases of the inherently unstructured mine terrains captured from a Fatalities 3D SwissRanger camera mounted on a mine safety robot * Introducing a Real-time Remote Monitoring Framework when gas devices are sensing the environment. * Introducing Static and Mobile Robot Sensing

Principles include the SR4000 time-of-flight camera (2) Computational Algorithms to be covered are producing a stream of mine frames projected as a 2.5D, The various computational algorithms/models that will be which are mainly mapped as drivable and non-drivable points covered in this tutorial include: using mixture of Gaussians (GMM) and expected * Gaussian Mixture Models (GMM) and Expected maximization (EM) models based on a hypergraph-type Maximisation (EM) Models model within an entropy textural feature space. * k-Nearest Neighbour (k-NN) Models * Bayesian Network (BN) Models (3) Developing Behaviours for Robots to Autonomously Sense Toxic Gases (10 minutes) (2.1) GMM and Expected Maximisation (EM) Models (5 minutes) The third part of the tutorial provides key strategy to manage the autonomous robot navigation with respect to collision Given a set of data points such as pixels in an image frame, avoidance during mobile sensing of the toxic gases in the the points in the frame seems to be generated in clusters but environments. they are mixed. It is not clear if a meaningful dividing line can be drawn between them by investigating which particular As an important basis for the tutorial outline, this part reveals cluster generates a data point. A family of distributions, P an approach of training a robot to avoid obstacles through called mixtures of Gaussians or Gaussian mixture models are teleoperation and thereafter use the knowledge acquired to well-suited to modelling, say K, clusters or components of develop behaviours for robot to autonomously navigate in data points. The EM model is the maximization algorithm various environmental sensing conditions using the that is iteratively used to find the maximum likelihood computational learning and predictive capabilities of k-NN estimate of GMM parameters until convergence, that is, and Bayesian Network models. The chosen behaviour or when optimal values are reached. navigational direction of the robot determines the control command values of translational and rotational velocities the In this tutorial, we will demonstrate that GMM and EM are robot uses for navigation. quite powerful computational algorithms for detecting drivable and non-drivable regions for mobile robots in the Its excellent performance will suggest a wider application of mines. the behavioural models which learn tasks and command robot successfully without collisions in an unknown environment in (2.2) K-Nearest Neighbour (k-NN) Models (5 minutes) industry. k-NN is a nonparametric instance-based learning as it allows a hypothesis of model complexity to grow with data sizes. K- NN is based on minimum distance from a query instance to all training samples to determine the K-nearest neighbours, which span the entire input space. The Euclidean distance of 12 n-dimensional space is commonly applied for computing the * Bayesian learning and reasoning process to robot behaviour minimum distance in this step. * The k-NN modelling and reasoning process to robot behaviour Prediction of the query instance is taken as majority votes of * Evaluation scheme the K-nearest neighbours. The choice of parameter value k is critical but k-NN is advantageously robust to uncertainty or (5) Sensing Toxic Mine Gases and Predicting Future noisy training samples. There are many variants of k-NN, but Situations (25 minutes) more sophisticated versions can be proposed. * Remote Monitoring Approach and Current Situations of Different Mine Regions In this tutorial, we will demonstrate that k-NN is quite a * A Strategy to Determine an Appropriate Kth-value for powerful computational algorithm for detecting the Predicting Future Gas Concentrations navigational directions for autonomous robots and for * Predicting Future Gas Levels using Forecasting Power of k- predicting the future trends of gases concentrations in the NN Models mines. (6) Demonstration of Remote Monitoring of Toxic Gases (20 (2.3) Bayesian Network Models (5 minutes) minutes) * Participatory sensing Bayesian Network (BN) technology is very useful for * Holistic implementation framework encoding probabilistic knowledge as graphical structures. A * Real-time gas sensing demonstrations Bayesian belief network is formally defined as a directed acyclic graph (DAG) represented as G = {X(G), A(G)}, where Background Knowledge Expected of the Participants X(G) = {X1,…,Xn}, vertices (variables) of the graph G and , set of arcs of G. The network requires discrete random values Intended audience for the tutorial are practitioners and such that if there exists random variables X1, . . ., Xn with scholars in the broad field of computational intelligence, each having a set of some values x1, . . ., xn then, their joint sensor networks, and robotics interested in getting a better probability density distribution is well defined. The Network understanding about the issues related to improving belief technology has been successfully used for reasoning in underground mine safety on gas fatalities. The tutorial will be the areas of power transformer diagnosis, medical diagnoses, organised so as to allow a wide audience to take advantage telecommunication networks, etc. from its content, ranging from graduate students to technologists, researchers, and practitioners willing to start In this tutorial, we will illustrate that BN is a powerful working on safety, computational intelligence, and in the probabilistic model for also detecting the navigational mining industries. directions for autonomous robots in the mines. Dr Isaac O. Osunmakinde is currently a Senior Research (3) Drivability Mapping of Underground Mines for Scientist in the Modelling and Digital Sciences Department Autonomous Robots (30 minutes) at the Council for Scientific and Industrial Research (CSIR), * Various drivability mapping approaches South Africa. By building on a first class B.Sc. (Hons) Degree * Proposed drivability mapping approach in Computer Sciences, a PgDS in Applied Mathematics from * Introduction to hyper-graph models the University of Stellenbosch, and a M.Sc. Degree in * Entropy model in textural feature space Computer Sciences from the University of Cape Town * Mapping with GMM, EM models and drivability (UCT) South Africa in 2006, He received his Ph.D. Degree refinement in Computer Sciences in 2009 (UCT) with a specialisation in * Scoring and evaluation scheme Intelligent Systems. His research interest is in Machine Learning including Intelligent Systems, Pattern Recognition, (4) Developing Behaviours for Robots to Autonomously Field Robotics, Sensor Networks, Probabilistic and Sense Toxic Gases (30 minutes) Mathematical modelling. He is a member of the IEEE * Approaches for developing behaviours for robots Computational Intelligence Society. * Behavioural and collision avoidance modelling (CAM) for robots 10:00 – 10:30 COFFEE BREAK * Perception of ultrasound sensor (US) data Location: Foyer 13

10:30 – CIB/MSI TUTORIAL SESSION CONTINUED 755-070 Location: Carlow Room - 8th Floor Modeling and Animating Three Dimensional Detailed Facial Expressions 12:10 – LUNCH BREAK Alice J. Lin and Fuhua Cheng (USA) Self-Catered 13:10 – CIB SESSION 2 – COMPUTATIONAL 13:10 – MSI SESSION 5 – MODELLING IN INTELLIGENCE MODELS FOR LEARNING AND BIOMEDICINE AND BIOMECHANICS DATA MINING Chair: Mr. Ali Hariri (USA) Chair: Dr. Margaret Miró-Julià (Spain) Location: Forbes A Room Location: Carlow Room - 8th Floor

755-026 753-037 Using Simulation in Medical Communications Training Approximate Computational Intelligence Models and Brian C. Baldwin, William D. Young, Sheilagh M.B. O'Hare, Causality in Bioinformatics Ryan C. Johnson, Aaron M. Lawyer, John N. Gentle, Lawrence J. Mazlack (USA) Aubrey White, and John A. Duncanson (USA) 753-034 755-027 Active Learning for the Prediction of Asparagine/Aspartate Design of State Feedback Controller and Observer for Type Hydroxylation Sites on Proteins ‘I’ Diabetic Patients Festus O. Iyuke, James R. Green, and William G. Willmore Ali M. Hariri and Le Y. Wang (USA) (Canada)

755-034 753-041 Dynamic Analysis and Cascade Movement Simulation of a A Credit Scoring Model based on Strongly-Typed Genetic Pneumatic Muscle Actuator Programming George Andrikopoulos, John Arvanitakis, Stamatis Manesis Rojin Aliehyaei and Shamim Khan (USA) (Greece), and George Nikolakopoulos (Sweden) 753-013 755-043 ANUBIA: An Intelligent Model in Financial Investment A Mathematical Model of Gas Exchange Predicting CO2 Margaret M. Miró-Julià and Ramón Arnau-Gómez (Spain) Response to Respiratory Rate Changes Joern Kretschmer (Germany), Christoph Schranz (Austria), and 753-023 Knut Moeller (Germany) Clustering of Multiple DNA Microarrays through Combination of Particle Swarm Intelligence and K-Means 755-044 Veselka Boeva (Bulgaria), Elena Tsiporkova, and A Behavioral Approach to Neuron Modeling Anna Hristoskova (Belgium) Felix Hutchison (USA) and Yue Yuan (PR China) 753-006 755-046 Classifying Disorders of Prostate using Master-Slave Modeling for Structural Flexibility of Wings in Flapping Configuration of Backpropagation Neural Networks Butterfly Anilkumar Kothalil Gopalakrishnan (Thailand) Kei Sendra, Naoto Yokoyama, Koji Yokoi and Masahiko Kitamura (Japan) 753-043 Multi-Class Classification using Covariance among Binary 755-053 Classifiers and its Application to the Analysis of Tumor Finite Element Modeling of Current Flow from Cochlear Microarrays Implant Stimulation Yuk Yee Leung and Li-San Wang (USA) Phillip Tran, Qing Li, and Paul Carter (Australia)

753-016 755-066 Automatic Extraction of Gene-Disease Association from Bio- Modeling and Identification of a Microcantilever System in Literature using Labeled PPI Data an Unknown Viscous Fluid Hongtao Zhang, Minlie Huang, and Xiaoyan Zhu (PR China) Mohammad N. ElBsat, Edwin E. Yaz, Susan C. Schneider (USA), Isabelle Dufour (France), and Fabien J. Josse (USA) 753-018 Reducer-Order Fuzzy-Observer-based Actuator Fault 16:20 – MSI SESSION 7 – MODELLING AND Reconstruction for a Class of Nonlinear Systems SIMULATION METHODOLOGIES II Dušan Krokavec and Anna Filasová (Slovakia) Chair: Dr. Sayeed Ghani (Pakistan) and Mr. Volkan Ozduran (Turkey) 14:30 – 15:00 COFFEE BREAK Location: Forbes A Room Location: Foyer 755-021 15:00 – MSI SESSION 5 CONTINUED Wavelet based Compress-and-Forward Relay Protocol for Location: Forbes A Room Cooperative Communication in Wireless Sensor Networks Volkan Ozduran and Osman N. Ucan (Turkey) 15:00 – CIB SESSION 2 CONTINUED 755-041 Location: Carlow Room - 8th Floor FEM Simulation of Heat Assisted Roll Bending Process for

Manufacturing Large and Thick High Strength Steel 16:00 – MSI SESSION 6 – IDENTIFICATION Axisymmetric Parts Chair: Prof. Jose Pittol Vera (Venezuela) Tran Hoang Quan (Vietnam), Henri Champliaud (Canada), Location: Forbes B Room Zhengkun Feng (PR China), and Thien-My Dao(Canada) 755-035 Pitch Angle Control of Wind Turbine Generator using 755-055 Disturbance Decoupling with T-S Fuzzy Performance and Call Admission Control of WiMax Taekue Kim, Taehwan Hwang, Seungkyu Park, Sungho Kim, Networks Taesung Yoon, Hokyun Ahn, and Kunpyoung Kwak (Korea) Sayeed Ghani and Muhammad Z. Akram (Pakistan)

755-054 755-071 State-Space Modeling and Identification of Loudspeaker with A Survey on Modeling Approaches for Three Phase Induction Nonlinear Distortion Motors Pascal Brunet and Bahram Shafai (USA) Mohammed Obaid, George Nikolakopoulos, and Thomas Guastafsson (Sweden) 755-058 A Fuzzy Virtual Sensor for Substrate Concentration in a 755-072 Wastewater Treatment Plant Kinematic Modeling and Simulation Studies of a LHD José A. Pittol, Yamitet Sánchez, Rosalba Lamanna (Venezuela), Vehicle under Slip Angles Silvana Revollar (Peru), and Pastora Vega (Spain) Thaker Nayl, George Nikolakopoulos, and Thomas Guastafsson (Sweden) 755-060 The Use of Canopy Clustering within Non-Intrusive Load Monitoring (NILM) ********************************************************* Daniel Carr and Stephen Gardner (UK) IASTED would like to thank you for attending CIB & MSI 2011. Your participation helped make this

international event a success, and we look forward to seeing you at upcoming IASTED events. *********************************************************

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