Keynote Speakers

Dr. Sankar K. Pal
Dr. Hamid R. Arabnia
Dr. Jinan Fiaidhi
Dr. Sabah Mohammed

Dr. Gerald Schaefer


Prof. Sankar K. Pal,
Indian Statistical Institute, Kolkata, India  
F-granulation, Generalized Rough Entropy and Granular Mining: Uncertainty Analysis and Challenges in Soft Computing Framework?

Fuzzy sets and Rough sets provide two different paradigms for uncertainty analysis and machine intelligence. The problems of their judicious integration, under rough-fuzzy computing, as a stronger paradigm for granular computing and uncertainty handling in real life decision-making, are addressed. Generalized rough sets and entropy measures involving the concept of fuzziness in granules as well as in sets are defined using both equivalence and tolerance relations. Significance of fuzzy-granulation (or f-granulation), different applications of granules, and certain emerging issues in their performance are explained. Different basic tasks considered include: case generation, classification/ clustering, and measuring image ambiguities. The characteristics of granules used therein are highlighted. Rough-fuzzy cases generated with variable reduced dimension are useful for mining data sets with large dimension and size. Class dependent fuzzy granulation coupled with neighborhood rough set based feature selection is efficient in modeling overlapping classes. Rough-fuzzy clustering, which provides a balanced mixture between hard and fuzzy partitioning, has merits both in terms of computation time and performance. Image ambiguity measures using generalized rough entropy take both the fuzziness in boundary regions, and the rough resemblance among nearby gray levels and nearby pixels, into account. Accordingly, the uncertainty in image analysis is better handled with generalization, resulting in superior performance. The talk concludes with mentioning the future directions of research, domains of possible applications, challenging issues, and the relevance of the said framework to natural computing.

About Dr. Sankar K. Pal 

Sankar K. Pal (www.isical.ac.in/~sankar) is a Distinguished Scientist of the Indian Statistical Institute and a former Director. Currently, he is also a J.C. Bose Fellow of the Govt. of India. He founded the Machine Intelligence Unit and the Center for Soft Computing Research: A National Facility in the Institute in Calcutta. He received a Ph.D. in Radio Physics and Electronics from the University of Calcutta in 1979 (Work carried out at Indian Statistical Institute, Calcutta), and another Ph.D. in Electrical Engineering along with DIC from Imperial College, University of London in 1982. He joined his Institute in 1975 as a CSIR Senior Research Fellow where he became a Full Professor in 1987, Distinguished Scientist in 1998 and the Director for the term 2005-10.

He worked at the University of California, Berkeley and the University of Maryland, College Park in 1986-87; the NASA Johnson Space Center, Houston, Texas in 1990-92 & 1994; and in US Naval Research Laboratory, Washington DC in 2004. Since 1997 he has been serving as a Distinguished Visitor of IEEE Computer Society (USA) for the Asia-Pacific Region, and held several visiting positions in Italy, Poland, Hong Kong and Australian universities.

Prof. Pal is a Fellow of the IEEE, USA, the Academy of Sciences for the Developing World (TWAS), Italy, International Association for Pattern recognition, USA, International Association of Fuzzy Systems, USA, and all the four National Academies for Science/Engineering in India. He is a co-author of fifteen books and more than three hundred research publications in the areas of Pattern Recognition and Machine Learning, Image Processing, Data Mining and Web Intelligence, Soft Computing, Neural Nets, Genetic Algorithms, Fuzzy Sets, Rough Sets and Bioinformatics.

He has received the 1990 S.S. Bhatnagar Prize (which is the most coveted award for a scientist in India), and many prestigious awards in India and abroad including the 1999 G.D. Birla Award, 1998 Om Bhasin Award, 1993 Jawaharlal Nehru Fellowship, 2000 Khwarizmi International Award from the Islamic Republic of Iran, 2000-2001 FICCI Award, 1993 Vikram Sarabhai Research Award, 1993 NASA Tech Brief Award (USA), 1994 IEEE Trans. Neural Networks Outstanding Paper Award (USA), 1995 NASA Patent Application Award (USA), 1997 IETE-R.L. Wadhwa Gold Medal, the 2001 INSA-S.H. Zaheer Medal, 2005-06 Indian Science Congress-P.C. Mahalanobis Birth Centenary Award (Gold Medal) for Lifetime Achievement, 2007 J.C. Bose Fellowship of the Government of India and 2008 Vigyan Ratna Award from Science & Culture Organization, West Bengal.

Prof. Pal is/ was an Associate Editor of IEEE Trans. Pattern Analysis and Machine Intelligence (2002-06), IEEE Trans. Neural Networks [1994-98 & 2003-06], Neurocomputing (1995-2005), Pattern Recognition Letters (1993-2011), Int. J. Pattern Recognition & Artificial Intelligence, Applied Intelligence, Information Sciences, Fuzzy Sets and Systems, Fundamenta Informaticae, LNCS Trans. On Rough Sets, Int. J. Computational Intelligence and Applications, IET Image Processing, J. Intelligent Information Systems, and Proc. INSA-A; Editor-in-Chief, Int. J. Signal Processing, Image Processing and Pattern Recognition; a Book Series Editor, Frontiers in Artificial Intelligence and Applications, IOS Press, and Statistical Science and Interdisciplinary Research, World Scientific; a Member, Executive Advisory Editorial Board, IEEE Trans. Fuzzy Systems, Int. Journal on Image and Graphics, and Int. Journal of Approximate Reasoning; and a Guest Editor of IEEE Computer.

  
Prof. Hamid R. Arabnia,
University of Georgia, Athens, Georgia, USA
A Bio-Inspired Reconfigurable Communication Topology - Progress Report

The two major issues in the formulation and design of parallel multiprocessor systems are algorithm design and architecture design. The parallel multiprocessor systems should be so designed so as to facilitate the design and implementation of the efficient parallel algorithms that exploit optimally the capabilities of the system. From an architectural point of view, the system should have low hardware complexity, be capable of being built of components that can be easily replicated, should exhibit desirable cost-performance characteristics, be cost effective and exhibit good scalability in terms of hardware complexity and cost with increasing problem size. In distributed memory multiprocessor systems, the processing elements can be considered to be nodes that are connected together via an interconnection network. In order to facilitate algorithm and architecture design, we require that the interconnection network have a low diameter, the system be symmetric and each node in the system have low degree of connectivity. Further, it is also desirable that the system configuration and behavior be amenable to a suitable and tractable mathematical description. The requirement of network symmetry ensures that each node in the network is identical to any other, thereby greatly reducing the architecture and algorithm design effort. For most symmetric network topologies, however, the requirements of low degree of connectivity for each node and low network diameter are often conflicting. Low network diameter often entails that each node in the network have a high degree of connectivity resulting in a drastic increase in the number of inter-processor connection links. A low degree of connectivity on the other hand, results in a high network diameter which in turn results in high inter-processor communication overhead and reduced efficiency of parallelism. Reconfigurable networks attempt to address this tradeoff. In a reconfigurable network each node has a fixed degree of connectivity irrespective of the network size. The network diameter is restricted by allowing the network to reconfigure itself into different configurations. In general, a reconfigurable system needs to satisfy the following criteria in order to be considered practically viable: (a) In each configuration the nodes in the network should have a fixed degree of active connectivity irrespective of network size, (b) The network diameter should be kept low via the reconfiguration mechanism and (c) The hardware for the reconfiguration mechanism (i.e. switch) should be of reasonable complexity. In this presentation, we discuss our design of a reconfigurable network topology that is targeted at medical applications; however, others have found a number of interesting properties about the network that makes it ideal for applications in computational biology as well as information engineering. We present some results and discuss our ongoing work in this area; we will also present a particular variation to our original reconfigurable network which is nature/biology inspired and our recent results.


About Dr. Hamid R. Arabnial 

Hamid R. Arabnia received a Ph.D. degree in Computer Science from the University of Kent (Canterbury, England) in 1987. Arabnia is currently a Full Professor of Computer Science at University of Georgia (Georgia, USA), where he has been since October 1987. His research interests include Parallel and distributed processing techniques and algorithms, interconnection networks, and applications (in particular, in image processing, medical imaging, bioinformatics, and other computational intensive problems). Dr. Arabnia is Editor-in-Chief of The Journal of Supercomputing (one of the oldest journals in Computer Science) published by Springer and is Associate Editor of IEEE Transactions on Information Technology in Biomedicine (2007-2010). He is also on the editorial and advisory boards of over 35 other journals. He is the founding chair of World Congress in Computer Science, Computer Engineering, and Applied Computing (WORLDCOMP). Dr. Arabnia has received a number of awards, including, The Johns Hopkins University National Search in recognition of his contributions to the national program for enhancing the quality of life for people with disabilities through the application of computing technology (signatories: co-directors of the National Search and President of Johns Hopkins U.) In 2006, he received the Distinguished Service Award in recognition and appreciation of his contributions to the profession of computer science and his assistance and support to students and scholars from all over the world; this award was presented to him on June 26, 2006 by Professor Barry Vercoe (Massachusetts Institute of Technology / MIT). In 2007, Dr. Arabnia received an "Outstanding Achievement Award in Recognition of His Leadership and Outstanding Research Contributions to the Field of Supercomputing". This award was presented to him at Harvard University Medical School (signatories: Lawrence O. Hall, President of IEEE/SMC; Zhi-Pei Liang, Vice President of IEEE/EMB; Jack. Y. Yang, General Chair of IEEE BIBE and Harvard University; Mary Qu Yang, Chair of Steering Committee, IEEE BIBE and NIH). Dr. Arabnia is an elected Fellow, Int'l Society of Intelligent Biological Medicine (ISIBM) and is on the Advisory Board of IEEE Technical Committee on Scalable Computing (TCSC). He was recently nominated for Outstanding Service award by IEEE Computer Society Technical Committee on Parallel Processing (TCPP); Prof. Albert Zomaya won the award.

Dr. Arabnia has published extensively in journals and refereed conference proceedings. He has over 300 publications (journals, proceedings, editorship) in his area of research. He has been a PI/Co-PI on over $7 Million externally funded projects/initiatives and on over $100K internally funded projects. He has also contributed projects for justification for equipment purchase (grant proposals worth over $4 Million - awarded). During his tenure as Graduate Coordinator/Director of Computer Science (August 2002 - January 2009), Dr. Arabnia secured the largest level of funding in the history of the department for supporting the research and education of graduate students (PhD, MS).

Dr. Arabnia has delivered numerous number of keynote lectures at international conferences; most recently at (since September 2008): The 14th IEEE International Conference on Parallel and Distributed Systems (ICPADS'08, Australia); International Conference on Future Generation Communication and Networking (FGCN 2008 / IEEE CS, Sanya); The 10th IEEE International Conference on High Performance Computing and Communications (HPCC-08, Dalian), ... He has also delivered a number of "distinguished lectures" at various universities.


Prof. Jinan Fiaidhi,
Department of Computer Science Lakehead University, Ontario-Canada

Situated Learning for Social Networking through Opinion Mining

The notion of “community” and the relationship among individual members within a community plays an essential role in the identification of the new form of e-learning. Researchers like Mayes and de Freitas (2007) presented situated learning theory as a fundamental perspective to further discipline our understanding of learning in Web 2.0 environments. This theory suggests that the social interaction plays a fundamental role in the process of cognitive development. Learning in the new age of social networking (e.g. personal blogs, Twitter, Face book) open new opportunities and challenges for learners to actively use the emerging information technologies to seek out and understand the opinions of others as well as to exchange their ideas and finding about learning issues. This presentation identifies opinion mining and sentiment analysis as one of the major elements for implementing an ideal situated learning environment. Actually, opinion mining and sentiment analysis deals with the computational treatment of opinion, sentiment, and subjectivity in text messages exchanged through social networking media like Twitter. In this new area of elearning, opinions need to be considered as a first-class object.

About Dr. Jinan Fiaidhi

Dr. Jinan Fiaidhi is a full Professor and the Graduate Coordinator with the Department of Computer Science, Lakehead University, Ontario, Canada since late 2001. She is also an Adjunct Research Professor with the University of Western Ontario. She received her graduate degrees in Computer Science from Essex University (PgD 1983) and Brunel University (PhD, 1986).
During the period (1986-2001), Dr. Fiaidhi served at many academic positions (e.g. University of Technology (Asso. Prof and Chairperson), Philadelphia University (Asso. Prof), Applied Science University (Professor), Sultan Qaboos University (Asso. Prof.). Dr. Fiaidhi research is focused on mobile and ubiquitous learning utilizing the emerging technologies (e.g. Cloud Computing, Calm Computing, Mobile Learning, Personal Learning Environment, Social Networking, Enterprise Mashups, and Semantic Web). Dr. Fiaidhi research is supported by the major research granting associations in Canada (e.g. NSERC, CFI).

Dr. Fiaidhi is a Professional Software Engineer of Ontario (PEng), Senior Member of IEEE, member of the British Computer Society (MBCS) and member of the Canadian Information Society (CIPS) holding the designate of ISP. Dr. Fiaidhi has intensive editorial experience (e.g. Editor-in-Chief of the International Journal of Software Engineering and Its Applications (IJSEIA), Editor of IEEE IT-Pro, Associate EiC of the Journal of Emerging Technologies in Web Intelligence). More information on her publications and news can be found at her Web page: http://flash.lakeheadu.ca/~jfiaidhi

Prof. Sabah Mohammed,
Department of Computer Science Lakehead University, Ontario-Canada
Intrusion Detection for Public Health Security

Public health security and bioterrorism preparedness is a key driver in the effort to strengthen global public health security. Unanimously agreed upon by the World Health Assembly (WHO) on May 23, 2005, the regulations that include commitments to improve capacity for disease prevention, detection, and response. This agreement provides standards for addressing national public health threats that have the potential to become global emergencies. Its success will rely on the capacity and performance of national public health systems and their capacity to enforce public health services and prevent unauthorized intruders. This presentation surveys some important intruder detection technologies used in public health. In particular it focuses on intruder prevention using state of art machine learning approaches.

About Dr. Sabah Mohammed
Dr. Sabah Mohammed started his career during 1977 as a Multimedia Maintenance Engineer working for Canon and Sony following his hobby in Electronics, although he completed his bachelor degree in Mathematics (HBSc 1977). From July 1979 he started his graduate studies where he received his degrees in Computer Science from Glasgow University-UK (PgD 1980, MPhil 1981) and from Brunel University-UK (PhD 1986). Since late 2001, Dr. Mohammed is a full Professor of Computer Science at Lakehead University. Formerly, from 1986-1995, Dr. Mohammed was an Assistant/Associate Professor of Computer Science at various universities including (BU, Amman University, Philadelphia University, Applied Science University and HCT). Sabah is interested in intelligent systems that have to operate in large, nondeterministic, cooperative, survivable, adaptive or partially known domains. Although his research is inspired by his PhD work on the employment of some Brain Activity-Structures based techniques for decision making (planning and learning) that enable processes (e.g. agents, mobile objects) and collaborative processes to act intelligently in their environments to timely achieve the required goals, Sabah extended his research vision to include constructivism and focus more on the nature of knowledge. Since knowledge is created by people and influenced by their values and culture, Sabah research stated to shift more towards net centric systems (e.g. Cloud Computing, Social Networking and Enterprise Systems, Web-Based Systems). During the last nine years, Sabah research is focused on developing ubiquitous healthcare systems that enable sharing securely knowledge and data in an effective way. In particular sharing Electronic Health Record (EHRs) over the Web is one of the very challenging problems that Sabah tries to solve. Sabah believes that finding good solutions for sharing EHRs requires approaches that cut across many different fields (e.g. Semantic Web, Web 2.0, Web 3.0, Ubiquitous Computing, Medical Informatics, XML Security and Artificial Intelligence).. He published several research articles in an attempt to promote EHRs interoperability and sharing. Recently he edited and authored a notable book on Ubiquitous Health and Medical Informatics: The Ubiquity 2.0 and Beyond? by IGI Global that will be published during April 2010.

Dr. Mohammed professional career includes many achievements. He is the Editor-in-Chief of three international journals ( Journal of Emerging Technologies in Web Intelligence (JETWI), the International Journal of? Education and Learning (IJEL) and the International Journal of Multimedia & Ubiquitous Engineering (IJMUE)). He was a Visiting Scholar at the Math and Computer Science, Laurentian University (Winter 2008). He is a Professional Software Engineer of Ontario (P.Eng.) and Canada Information Processing Professional (ISP). Dr. Mohammed is an active member of Canada’s e-Health Interoperability group (http://www.simbioses.ca/ehealth/) and the coordinator on Northern Ontario Web Intelligence Research Group (NOWI http://www2.cs.uregina.ca/~wi/). Besides being an active member of the Department of Computer Science here at Lakehead University, Dr. Mohammed is among the core faculty members of both the Lakehead University Bioinformatics and BioTechnology programs. Moreover, Dr. Mohammed is an Adjunct Research Professor with the University of Western Ontario. More recently, Dr. Mohammed joined the core members of the BioTechnology PhD program.

His membership in these programs enables him to supervise good number of MSc and PhD students. Actually, Dr. Mohammed is passionate about helping students and young researchers to get a good start in their careers. His teaching involves many important courses in Computer Science including: Mobile Programming, Artificial Intelligence, Programming Languages and Object-Oriented Design and Methodologies. During 2006, Dr. Mohammed was the recipient of the Contribution to Teaching Award. Dr. Mohammed has also some notable administrative services as he chaired three Computer Science and Information Systems departments including (Philadelphia University-Jordan (1995-1997), Applied Science University-Jordan (1997-2000), HCT-Sultanate of Oman (2000-2001)). Dr. Mohammed published more than 90 refereed articles, chapters in books and three textbooks. He supervised more than 20 Masters Students and one PhD student. More on Dr. Mohammed career and publications can be found at his webpage (http://flash.kakeheadu.ca/~mohammed).


Prof. Gerald Schaefer,
Department of Computer Science,
Loughborough University

Intuitive image database browsing systems

Image communication and image database management are becoming increasingly important due to ease of image capture, introduction of photo sharing websites and the resulting rapid growth of image collections. In my talk, I will show that image browsers, that are based on principles from content-based image rerieval (CBIR), provide an in an interesting alternative to retrieval-based approaches. I will introduce the basic approaches to similarity-based image browsing, and present some of the image browsers that we have developed in our group. These are designed for interactive exploration of large image collections based on the principles that visually similar images are located close to each other thus helping user navigation, and that large datasets are handled through a hierarchical approach.

About Dr. Gerald Schaefer
Gerald Schaefer gained his PhD in Computer Vision from the University of East Anglia. He worked at the Colour & Imaging Institute, University of Derby (1997-1999), in the School of Information Systems, University of East Anglia (2000-2001), in the School of Computing and Informatics at Nottingham Trent University (2001-2006), and in the School of Engineering and Applied Science at Aston University (2006-2009) before joining the Department of Computer Science at Loughborough University where he leads the Vision, Imaging and Autonomous Systems Research Division. His research interests are mainly in the areas of colour image analysis, image retrieval, physics-based vision, medical imaging, and computational intelligence. He has published extensively in these areas with a total publication count exceeding 300. He is a member of the editorial board of more than a dozen international journals, reviews for over 80 journals and served on the programme committee of more than 250 conferences. He has been invited as keynote or tutorial speaker to more than 40 conferences, is the organiser of various international workshops and special sessions at conferences, and the editor of several books, conference proceedings and special journal issues.

  

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