Keynote Speeches

  The first ever World Happiness Report has been published recently by the United Nations, it reflects a new worldwide demand for more attention to happiness as criteria for government policy. This also calls upon science and technology in both natural and social domains to be developed for promoting a happy and healthy lifestyle in our modern society.
  To meet such a world trend, the Orange Technology research has been first proposed in National Cheng Kung University in Taiwan. The Orange Technology refers to a newly evolved interdisciplinary research area for integration and innovation of health, happiness, and care technologies. The research scope includes computer science, electrical engineering, biomedical engineering, psychological/physiological science, cognitive science, and social science. The representative color of Orange Technology originates from a harmonic fusion of red (representing brightness of health and happiness) and yellow (representing warming care). Instead of emphasizing the relations between environments and humans, as proposed by green technology, the objective of Orange Technology will explore the innovative technologies to bring more health, happiness, warming care, and more mental wellness to the society. So far, we have developed many new models for the Orange Technology such as the H2O model, 3D model of happiness, SEE-H methodology H-POS for service engineering and Happiness informatics for the detection, measurement and feedback of the happiness emotion.
  The Happiness Informatics Research is also newly proposed accompanying with Orange technology. It will first sense the happiness behavior of the human being to get the happiness signals such as EEG brain signals, smiling sound signals & smiling face images etc. Then the information technology such as pattern recognition technique will be applied to detect & measure the happiness degree of the behavior based on the input signals. Finally the system will give the suitable positive feedback to improve the happiness degree of the user. Several interesting examples will be demonstrated in this speech.

  Prof. Jhing-Fa Wang is currently the President in Tajen University, Chair & Distinguished Professor in the Department of Electrical Engineering, National Cheng Kung University (NCKU). He got his bachelor and master degree from NCKU in Taiwan and Ph. D. from Stevens Institute of Technology USA in 1973, 1979 and 1983 respectively. He is the formal chair of IEEE Tainan Section in 2005-2009, the Coordinator of Section/Chapter, IEEE Region 10 in 2011-2012 & the Industry Liaison-Coordinater of IEEE Region 10 in 2009-2011. He was elected as IEEE Fellow in 1999 for his contribution on:"Hardware and Software Co-design on Speech Signal Processing", He was also the general Chair of ISCAS 2009.
  He received Outstanding Research Awards and Outstanding Researcher Award from National Science Council in 1990, 1995, 1997, and 2006 respectively. He also received Outstanding Industrial Awards from ACER and Institute of Information Industry and the Outstanding Professor Award from Chinese Engineer Association, Taiwan in 1991 and 1996 respectively. He also received the culture service award from Ministry of Education, Taiwan in 2008, Distinguished Scholar Award of KT Li from NCKU in 2009, IEEE Tainan Section Best Service Award in 2011 & Innovation Education Award in 2013 Seoul International Invention Fair.
  Prof. Wang was also invited to give the Keynote Speeches in PACLIC 12 in Singapore, 1998, UWN 2005 in Taipei, WirlessCom 2005 in Hawaii, IIH-MSP2006 in Pasadena, USA, ISM2007 in Taichung, PCM 2008 in Tainan, 2011 ICAST in Dalian, China, 2011 ICSPCC in Xi'an, China & Keer2012 in Penghu, Taiwan respectively. He also served as an associate editor on IEEE Transactions on Neural Network and IEEE Transactions on VLSI System and Editor in Chief on International Journal of Chinese Engineering from 1995 to 2000.
  Prof. Wang's research area is mainly on multimedia signal processing including speech signal processing, image processing, and VLSI system design. Concerning about the publication, he has published about one hundred & forty journal papers on IEEE, SIAM, IEICE, IEE and about three hundreds international conference papers since 1983. Prof. Wang recently has explored the research on Orange Technology. Orange Technology refers to a newly evolved interdisciplinary research area for integration and innovation of health, happiness, and care technologies. The objective of Orange Technology is to bring more health, happiness and warming care to the society.

  Recent advances in technological equipment, like digital cameras, smart-phones, etc., have led to an increase of the available digital media, e.g., videos, captured every day. Moreover, the amount of data captured for professional media production (e.g., movies, special effects, etc) has dramatically increased and diversified using multiple sensors (e.g., 3D scanners, multi-view cameras, very high quality images, motion capture, etc), justifying the digital media analysis as a big data analysis problem. As expected, most of these data are acquired in order to describe human presence and activity and are exploited either for monitoring (visual surveillance and security) or for personal use and entertainment. Basic problems in human centered media analysis are face recognition, facial expression recognition and human activity recognition. According to YouTube statistics http://www.youtube.com/yt/press/statistics.html, 100 hours of video are uploaded by the users every minute. Such a data growth, as well as the importance of visual information in many applications, has necessitated the creation of methods capable of automatic processing and decision making when necessary. This is why a large amount of research has been devoted in the analysis and description of digital media in the last two decades.
  In this keynote a short overview on recent research efforts for digital media analysis and description using computational intelligence methods will be given. Computational intelligence methods are very powerful in analyzing, representing and classifying digital media content through various architectures and learning algorithms. Both unsupervised and supervised algorithms can be used for digital media feature extraction. The specific problem that will be used as a case study for digital media analysis is the human-centered video analysis for activity and identity recognition.

  Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) received the Diploma and PhD degree in Electrical Engineering, both from the Aristotle University of Thessaloniki, Greece. Since 1994, he has been a Professor at the Department of Informatics of the same University. He served as a Visiting Professor at several Universities. His current interests are in the areas of image/video processing, intelligent digital media, machine learning, human centered interfaces, affective computing, computer vision, 3D imaging and biomedical imaging. He has published over 749 papers, contributed in 39 books in his areas of interest and edited or (co-)authored another 9 books. He has also been an invited speaker and/or member of the program committee of many scientific conferences and workshops. In the past he served as Associate Editor or co-Editor of eight international journals and General or Technical Chair of four international conferences (including ICIP2001). He participated in 68 R&D projects, primarily funded by the European Union and is/was principal investigator/researcher in 40 such projects. He has 17900+ citations (Source Publish and Perish), 6250+ (Scopus) to his work and h-index 64+ (Source Publish and Perish), 38+ (Scopus).
  IOANNIS PITAS received the Diploma of Electrical Engineering in 1980 and the PhD degree in Electrical Engineering in 1985, both from the University of Thessaloniki, Greece. Since 1994 he has been a Professor at the Department of Informatics, University of Thessaloniki, Greece. From 1980 to 1993 he served as Scientific Assistant, Lecturer, Assistant Professor, and Associate Professor in the Department of Electrical and Computer Engineering at the same University. He lead funded research in CERTH/ITI. He is an IEEE fellow (2007), IEEE Distinguished Lecturer (2012) and EURASIP fellow (2013). He is ranked at the 13th position internationally in the area 'Multimedia' in Microsoft Academic Search. University of Thessaloniki is ranked 2nd in Europe (after EPFL) and 36th in the world, in the area 'Multimedia' in Microsoft Academic Search, primarily due to the R&D efforts of the AIIA lab headed by Prof. Pitas. He served as Visiting Professor and ASI fellow at the University of British Columbia, Canada, as Visiting Professor at Yonsei University, Korea, at Ecole Polytechnique Federale de Lausanne, Switzerland, at Tampere University of Technology, Finland, as Visiting Assistant Professor at the University of Toronto and as a Visiting Research Associate at the University of Toronto, Canada and at the University of Erlangen-Nuernberg, Germany. He was Chair of the School of Graduate Studies, Head of the MSc specialization on Digital Media and Head of the AIIA lab, at the Department of Computer Science, University of Thessaloniki, Greece. His current interests are in the areas of image/video processing, intelligent digital media, machine learning, human centered interfaces, affective computing, computer vision, 3D imaging and biomedical imaging. He has published over 749 papers, contributed in 39 books and authored, co-authored, edited, co-edited 9 books in his area of interest. He is the co-author of the books '3D image processing algorithms' (Wiley 2000), 'Nonlinear Digital Filters: Principles and Applications' (Kluwer, 1990). He is the author of the books 'Digital Video and Television' (Createspace/Amazon 2013), 'Digital image processing algorithms and applications' (Wiley 2000), 'Digital Image Processing Algorithms' (Prentice Hall, 1993), 'Digital Television and digital video processing' (in Greek 2010), 'Digital image processing' (in Greek, 1999). He is the editor of the book 'Parallel Algorithms and Architectures for Digital Image Processing, Computer Vision and Neural Networks' (Wiley, 1993) and co-editor of the book 'Nonlinear Model-Based Image/Video Processing and Analysis' (Wiley 2000). Dr Pitas has been member of the European Community ESPRIT Parallel Action Committee. He had 10 academic occupation and visits in universities abroad. He co-organized 14 special sessions in conferences, 8 special issues in scientific journals. He is/was editor in 22 journals. He gave 55 invited lectures, was member of the program committee of more than 257 scientific conferences and workshops and was chair of more than 39 conference sessions. He supervised 18 completed PhD theses. He was reviewer in 52 scientific journals, 290 conferences, 36 R&D funding agencies and 4 publishers. He participated in 24 national and international committees and he had a major role in the organization of 16 conferences. He participated in 68 R&D projects, is/was principal investigator/researcher in 40 competitive R&D projects, mostly funded by the European Union. He is/was Associate Editor of the IEEE Transactions on Circuits and Systems, IEEE Transactions on Neural Networks, IEEE Transactions on Image processing, IJIG Journal, IEICE, Circuits Systems and Signal Processing (CSSP), co-editor of Multidimensional Systems and Signal Processing, member of the editorial board of 14 journals and guest editor in 8 special journal issues. He was chair of the 1995 IEEE Workshop on Nonlinear Signal and Image Processing (NSIP95). He was technical chair of the 1998 European Signal Processing Conference. He was the general chair of IEEE ICIP2001. He was co-chair of the 2003 International workshop on Rich media content production. He was technical co-chair of the 2003 Greek Informatics conference (EPY). He was general co-chair of the 2013 IEEE IVMSP workshop on '3D image/video technologies and applications', 10-12/6/2013, Seoul, Korea. He was chair of the TC on Digital Signal Processing of the IEEE Circuits and Systems Society. He was vice-chair of the TC on image processing and multidimensional signal processing of the IEEE Signal Processing Society. He was member of the National Research Council of Greece. He has received the 2009 best cited author award by Aristotle University of Thessaloniki (8500+ citations in 2009). The number of citations to his work by third authors is 17900+ (Publish or Perish), 6250+ (Scopus). His h-index is 64+, (source Publish or Perish), 38+ (Scopus), date: February 2014.

  Understanding modern data communication networks such as the Internet involves collection and analysis of data collected from deployed networks. It also calls for development of various tools for analysis of such datasets. Collected traffic data are used for characterization and modeling of network traffic, analysis of Internet topologies, and prediction of network anomalies.
  In this talk, I will describe collection and analysis of real-time traffic data using special purpose hardware and software tools. Analysis of such collected datasets indicates a complex underlying network infrastructure that carries traffic generated by a variety of the Internet applications. Data collected from the Internet routing tables is used to analyze Internet topologies and to illustrate the existence of historical trends in the development of the Internet. The Internet traffic data are also used to classify and detect network anomalies such as Internet worms, which affect performance of routing protocols and may greatly degrade network performance. Various statistical and machine learning techniques are used to classify test datasets, identify the correct traffic anomaly types, and design anomaly detection mechanisms.

  Ljiljana Trajkovic received the Dipl. Ing. degree from University of Pristina, Yugoslavia, in 1974, the M.Sc. degrees in electrical engineering and computer engineering from Syracuse University, Syracuse, NY, in 1979 and 1981, respectively, and the Ph.D. degree in electrical engineering from University of California at Los Angeles, in 1986.
  She is currently a Professor in the School of Engineering Science at Simon Fraser University, Burnaby, British Columbia, Canada. From 1995 to 1997, she was a National Science Foundation (NSF) Visiting Professor in the Electrical Engineering and Computer Sciences Department, University of California, Berkeley. She was a Research Scientist at Bell Communications Research, Morristown, NJ, from 1990 to 1997, and a Member of the Technical Staff at AT&T Bell Laboratories, Murray Hill, NJ, from 1988 to 1990. Her research interests include high-performance communication networks, control of communication systems, computer-aided circuit analysis and design, and theory of nonlinear circuits and dynamical systems.
  Dr. Trajkovic serves as President (2014 - 2015) of the IEEE Systems, Man, and Cybernetics Society and served as Vice President Publications (2012 - 2014 and 2010 - 2011), as Vice President Long-Range Planning and Finance (2008 - 2009), and as a Member at Large of its Board of Governors (2004 - 2006). She served as 2007 President of the IEEE Circuits and Systems Society. She was a member of the Board of Governors of the IEEE Circuits and Systems Society (2001 - 2003 and 2004 - 2005). She is Chair of the IEEE Circuits and Systems Society joint Chapter of the Vancouver/Victoria Sections. She was Chair of the IEEE Technical Committee on Nonlinear Circuits and Systems (1998). She was Technical Program Co-Chair of ISCAS 2005 and served as Technical Program Chair and Vice General Co-Chair of ISCAS 2004. She served as an Associate Editor of the IEEE Transactions on Circuits and Systems (Part I) (2004 - 2005 and 1993 - 1995), the IEEE Transactions on Circuits and Systems (Part II) (1999 - 2001 and 2002 - 2003), and the IEEE Circuits and Systems Magazine (2001 - 2003). She was a Distinguished Lecturer of the IEEE Circuits and Systems Society (2010 - 2011 and 2002 - 2003). She is a Fellow of the IEEE.

Professor C. L. Philip Chen

  This talk discusses a new neural-fuzzy network architecture in which a traditional neuro-fuzzy system is transformed into an equivalent fully connected three layer neural network, namely, the Fully Connected Neuro-Fuzzy Inference Systems (F-CONFIS). The F-CONFIS differs from traditional neural networks by its dependent and repeated weights between input layer and hidden layer and can be considered as the variation of a kind of multilayer neural network. Therefore, an efficient learning algorithm for F-CONFIS to cope these repeated weights is derived. Furthermore, a dynamic learning rate is proposed for neuro-fuzzy systems via F-CONFIS where both premise (hidden) and consequent portions should be considered. Several simulation results indicate that the proposed approach achieves much better accuracy and fast convergence. In addition the bounded capacity for the learning for a fuzzy neural network via the proposed F-CONFIS and its applications will be discussed.

   C. L. Philip Chen, Ph.D, FIEEE FAAAS. Dean and Chair Professor Faculty of Science and Technology, The University of Macau. Editor-in-Chief, IEEE Transactions on Systems, Man, and Cybernetics: Systems,2014 - ,http://www.ieeesmc.org/publications/index.html . Junior Past President, IEEE Systems, Man, and Cybernetics Society (2014-2015), http://www.ieee.org.
   C. L. Philip Chen received his M.S. degree from the University of Michigan, Ann Arbor, Michigan, U.S.A. in 1985, and his Ph.D. degree from Purdue University, West Lafayette, Indiana, U.S.A., in 1988, both degrees in Electrical Engineering. He was with Wright State University, Department of Computer Science and Engineering, from 1989 to 2002 as an assistant, an associate, and a full professor before he joined the University of Texas, San Antonio, where he has been a Professor and Chair of the Department of Electrical and Computer Engineering, the Associate Dean for Research and Graduate Studies of the College of Engineering. Since 2010, he is Chair Professor and the Dean of Faculty of Science and Technology, University of Macau. (http://www.fst.umac.mo/index.php)
   Dr. Chen has been a visiting research scientist, at the Materials Directorate, Wright Laboratory, Wright-Patterson Air Force Base. He has been a senior research fellow sponsored by the National Research Council, National Academy of Sciences. He is a Chair professor of National Chung-Hsing University, Taiwan, 2009-2011, the HiaTien Chair Professor in Dalian University of Technology, China since 2011, and an Honorary Professor in Obuda University, Hungary since 2011. He also has been a research faculty fellow at NASA Glenn Research Center for several years. His research interests and projects, supported by the NSF, Air Force Office Scientific Research and the U.S. Air Force, Office of Naval Research, NASA, and State of Ohio, include computer networking, intelligent systems, neural networks, fuzzy- neural systems, robotics, and CAD/CAM. His current research areas include design computational intelligent systems, networking, and video data indexing, retrieval, and communications; and a research project funded by the NASA Glenn Research Center on data mining on aircraft flight and maintenance data, aircraft engine life prediction, life extending control, diagnosis and prognosis, and health monitoring. As a result of his research contribution and academic recognition, he was elected to a Fellow of the IEEE (www.ieee.org) and AAAS (American Association for the Advancement of Science,www.aaas.org). Dr. Chen has been involving in professional service for more than twenty years. He has served as a member of organizing committee for many IEEE conferences under different capacities, including IEEE International Conference on Robotics and Automation, IEEE WCCI, IEEE Int'l Conf. on Intelligent Robotics and Systems (IROS), IEEE Int'l Conf. on SMC, IEEE Int'l Conf. on System of Systems. Notably, he also has been a Conference Co-Chair of the International Conference on Artificial Neural Networks in Engineering (ANNIE), 1995 and 1996; the Program Co-Chairs of 2006 IEEE/SMC Int'l Conference on System of Systems Engineering (SoSE);a Program Co-Chair of 2008 & 2010 ICMLC, General Co-Chair of 2008 IEEE Int'l Conference on Secure Systems Integration and Reliability Improvement (SSIRI 2008); General Chair of 2009 and Program Chair of 2014 of IEEE Int'l Conf. On Systems, Man, and Cybernetics (SMC); General Chair (Co-Chair) of 2011 (2012) IEEE Int’l Conference on Systems Science and Engineering; and General Co-Chair of 2014 International Conference on Medical Biometrics (ICMB) and as a Co-Chair of several international conferences held in Europe.
   Currently, he is the Jr. Past President of IEEE SMC Society (2014-2015) and has been the President of IEEE SMC Society (2012-2013), Vice President on Conferences and Meetings and President-Elect, Vice President on Technical Activities in Systems Science and Engineering, a member of Board of Governors, the Treasurer; and serves as a Distinguished Lecturer, an Associate Editor of IEEE Transactions on SMC-C (2006-) and IEEE Systems Journal (2008-2010). He is the founding faculty advisor of the IEEE Computer Society Student Chapter while at Wright State University; the founding Chair of IEEE SMCS Central Texas Section; founding Co-Chair of IEEE SMCS Macau Chapter, and founding co-chairs of three SMCS Technical Committees (SoS, Enterprise Information Systems, and Information Assurance). With this recognition, he received Outstanding Contribution Award three times from IEEE SMCS in 2008, 2010, and 2013. Dr. Chen is a member of Tau Beta Pi and Eta Kappa Nu honor societies and has been the faculty advisor for Tau Beta Pi Engineering honor society. In addition, he is an ABET (Accreditation Board of Engineering and Technology Education) Program Evaluator for Computer Engineering, Electrical Engineering, and Software Engineering programs.