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Prof. Hojjat Adeli

Prof. Andrzej Skowron


Prof. Ruay-Shiung Chang







  
Prof. Hojjat Adeli
Abba G. Liechtenstein Professor
The Ohio State University, USA



Chaos-Wavelet-Neural Network Models for Automated EEG-Based Diagnosis of Neurological Disorders

The author has been advancing a multi-paradigm integrated approach for solution of complicated and intractable dynamic pattern recognition problems. The focus of this keynote lecture is data mining and knowledge discovery from time-series signals obtained from complex phenomena. Novel wavelet-chaos-neural network models are presented for signal processing of brain waves as recorded by electroencephalographs for automated electroencephalogram (EEG)-based diagnosis of neurological disorders such as epilepsy and the Alzheimer’s disease (AD). Through extensive parametric studies and information reuse and integration certain combinations of parameters from the EEG sub-bands were discovered to be effective markers for seizure detection and epilepsy diagnosis. The model can distinguish among healthy, interictal, and ictal EEGs with a high accuracy of 96%, substantially better than practicing neurologists. Other algorithms for diagnosis of the AD and Attention Deficit Hyperactivity Disorder (ADHD) will also be discussed briefly.

About Prof. Hojjat Adeli
Hojjat Adeli received his Ph.D. from Stanford University in 1976 at the age of 26 after receiving his B.S.-M.S. degrees from the University of Tehran in 1973. He has authored over 430 research and scientific publications in various fields of computer science, engineering, applied mathematics, and medicine including 14 books such as Machine Learning - Neural Networks, Genetic Algorithms, and Fuzzy Systems, Wiley, 1995; Neurocomputing for Design Automation, CRC Press, 1998; Wavelets in Intelligent Transportation Systems, Wiley, 2005; and Intelligent Infrastructure – Neural Networks, Wavelets, and Chaos Theory for Intelligent Transportation Systems and Smart Structures, CRC Press, 2009. His most recent book is Automated EEG-based Diagnosis of Neurological Disorders - Inventing the Future of Neurology, CRC Press, 2010. He is the Founder and Editor-in-Chief of Computer-Aided Civil and Infrastructure Engineering, now in 25th year of publication and Integrated Computer-Aided Engineering, now in 17th year of publication, and the Editor-in-Chief of International Journal of Neural Systems. He is the quadruple winner of the OSU College of Engineering Lumley Award for outstanding research accomplishments. In 1998 he received the Distinguished Scholar Award from OSU, the university’s highest research award, “in recognition of extraordinary accomplishment in research and scholarship”. In 2005, he was elected Honorary/Distinguished Member, ASCE: "for wide-ranging, exceptional, and pioneering contributions to computing in civil engineering and extraordinary leadership in advancing the use of computing and information technologies in many engineering disciplines throughout the world.” In 2007, he received the OSU College of Engineering Peter L. and Clara M. Scott Award for Excellence in Engineering Education as well as the Charles E. MacQuigg Outstanding Teaching Award. He is a Fellow of the American Association for the Advancement of Science.
  
Prof. Andrzej Skowron
University of Warsaw, Poland
Introduction to Perception-based Computing
We discuss Perception-based Computing (PbC) in the Wisdom Technology (Wistech) framework. The intuitive nature of wisdom in Wistech can be expressed by the so called wisdom equation metaphorically described by

wisdom = knowledge + adaptive_ judgment + interactions

Interactive Rough-Granular Computing (IRGC) is used as the basic methodology for PbC. Key issue in Granular Computing (GC) is information granulation (IG). IG is used for modeling of human way of data compression and plays a key role in problem solving by human. Due to limited abilities of human organs, human perception is usually imprecise (e.g., boundary between decision classes are vague, values of attributes are granular). Hence, in IRGC the rough set approach in combination with the other soft computing approaches for dealing with imprecise knowledge are used. Computations in IRGC are performed on different kinds of objects, called information granules (such as sensory granules, decision rules or sets of decision rules, classifiers for vague concepts, agents or coalitions of agents). These computations are progressing through interactions between granules. In the discussed approach, methods for modeling of interactions among granules and interactive computations are of great importance. Some granules (e.g., agents) have ability to perceive objects. Perception by such granules is understood here as a process resulting in activation of some parts (e.g., complex concepts) of these granules. This activation is caused by interactions of sensory parts of the granules with distributed environments and other parts of these granules (e.g., granules stored in knowledge networks representing behavioral patterns of observed objects or different components of activated complex granules). The activated parts are used, e.g., for triggering of actions or plans. We discuss how granules such as complex vague concepts can be approximated using domain ontology approximation. This illustrates how the activation of complex granules can be realized, i.e., how, in the discussed model, the perception results are computed. Some applications of the discussed approach in real-life projects such as medical decision support, identification o complex behavioral patterns on the road or sunspot classification are reported.
About Prof. Andrzej Skowron

Andrzej Skowron received the Ph. D. and D. Sci. (habilitation) from the University of Warsaw in Poland. In 1991 he received the Scientific Title of Professor. He is Full Professor in the Faculty of Mathematics, Computer Science and Mechanics at Warsaw University. Andrzej Skowron is the (co)author of more than 350 scientific publications. His areas of expertise include reasoning with incomplete information, approximate reasoning, soft computing methods and applications, rough sets, rough mereology, granular computing, synthesis and analysis of complex objects, intelligent agents, knowledge discovery and data mining, decision support systems, adaptive and autonomous systems. He was the supervisor of more than 20 PhD Thesis. He was also involved in several national and international research and commercial projects related to, e.g., data mining (fraud detection, web mining), control of unmanned vehicles, medical decision support systems and approximate reasoning in distributed environments.


In the period 1995-2009 he was the Editor-in-Chief of Fundamenta Informaticae journal. He is the co-editor-in-chief of the LNCS Transactions on Rough Sets journal published by Springer. He is on Editorial Boards of many others journals including Knowledge Discovery and Data Mining. Andrzej Skowron was the President of the International Rough Set Society from 1996 to 2000. He served or is currently serving on the program committees of more than 100 international conferences and workshops, as program or steering committee member, program chair or co-chair. He has delivered numerous invited talks at international conferences including a plenary talk at the 16-th IFIP World Computer Congress (Beijing, 2000). Throughout his career Andrzej Skowron received many awards for his achievements.

Prof. Ruay-Shiung Chang
Professor, Department of Computer Science and Information Engineering,
National Dong Hwa University
Social Networks: Research and Applications

On September 5, 2010, an opinion article in the Washington Post titled "Facebook and social media offer the potential of peace" appeared. The peace refers to the situation in Mideast. When young generations socialize between themselves using Facebook, MySpace, and/or Tweeter, war is less likely and peace may be possible.

Social media or social networks are changing the world, from how people make friends to how information is disseminated. More than 500 million people use Facebook alone. Of those, 70 percent are outside the United States. MySpace has 122 million monthly active users, and Twitter reports 145 million registered users. With their many users and vast amount of data produced each moment, social networks offer many research challenges in computer science.

For example, different from conventional data types, social media data are multi-model in nature, including content such as images, audio, videos, discussion topics, tags, annotations, hyperlinks, profiles, timestamps, click-throughs, etc. How to make meanings out of these data determines if intelligent applications can be devised.

The omnipresence of Internet makes social networks popular and easily accessible. Will social networks in turn affect the future network architecture? With the advancement of handheld mobile devices, social networks on the move are becoming common. Will mobile and pervasive social networks be any different?

Then there are trust, security, and privacy issues. As you can see, the list of related problems can go on and on and on. In this talk, we will identify some key issues in social network research and present some applications of social networks.

About Prof. Ruay-Shiung Chang
Ruay-Shiung Chang received his B.S.E.E. degree from National Taiwan University in 1980 and his Ph.D. degree in Computer Science from National Tsing Hua University in 1988. He is now a professor in the Department of Computer Science and Information Engineering, National Dong Hwa University. His research interests include Internet, wireless networks, RFID and grid computing. He has published more than 70 peer-reviewed journal papers and numerous international conference papers. He is an editor for International Journal of Internet Protocol Technology, Journal of Internet Technology, and Journal of Convergence Information Technology. Dr. Chang is a member of ACM, a senior member of IEEE, and a founding member of Taiwan Institute of Information and Computing Machinery. Dr. Chang also served on the advisory council for the Public Interest Registry (www.pir.org) from 2004/5 to 2007/4.

  
  
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