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.

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.

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.

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