LSMS 2007

Abstract: In control and systems data modelling refers to finding underlying regularities or relationships from measured data. It is used for pattern recognition and dynamic modelling and is a key supporting technology across a wide range of domains, including the life science. While machine learning, function approximation and statistical modelling, are all used for data modelling, we will confine our attention to computational intelligence, with a focus on neural networks.

To begin our experiences of nonlinear modelling and control since the early 1980s will be briefly introduced. This will cover local and global networks, advanced trainin algorithms, multiple-controller networks, construction techniques, model-based control, learning systems and applications.

Engineering-genes (Eng-genes) a recent computational intelligence technique for dynamical modelling will then be described. Here the underlying physical knowledge is encoded in the neural activation functions or eng-genes. Selection of the dominant eng-genes and combined structural identification and parameter estimation is achieved within a genetic algorithm framework. A new two-stage stepwise identification method will be described for linear-in-the-parameters model built from a (very large) pool of basis functions. This avoids the inherent matrix decomposition in Orthogonal Least Squares, thereby reducing computational complexity and improving model performance. The results of simulation studies of several types of biochemical oscillations, in the form of modelling with a polynomial NARX structrure will be used for illustration.

An acute myocardial inforction (or heart attack) (AMI) is caused by a coronary artery becoming completely obstructed and blood supply being lost to an area of the cardiac tissue. Once the heart cells lose their blood supply, certain chemicals are able to pass through the cell membrane and enter the blood stream. These so-called cardiac markers, have been found to be useful in diagnosing AMI, especially where electrocardiograph (ECG) readings are inconclusive. The final part of the talk will describe results from training Logistic regression and Gaussian mixture model (GMM) classifers to estimate the probability of AMI in patients based opon the concentrations of a panel of cardiac markers.

----------------------------------

Prof George W Irwin

Intelligent Systems and Control

School of Electronics, Electrical Engineering and Computer Science

Queen's University Belfast UK

Professor George Irwin leads the Intelligent Systems and Control Research group and is Director of the University Virtual Engineering Centre at Queen University Belfast. He has been elected Fellow of the Royal Academy of Engineering and Member of the Royal Irish Academy and is a Chartered Engineer, an IEEE Fellow, a Fellow of the IEE and a Fellow of the Institute of Measurement and Control. Prof Irwin��s research covers identification, monitoring, and control, including neural networks, fuzzy neural systems and multivariate statistics and has published over 350 research papers and 12 edited books. He is currently working on wireless networked control systems, fault diagnosis of internal combustion engines and novel techniques for fast temperature measurement and was Technical Director of Anex6 Ltd, a spin out company from his group specialising in process monitoring. He has been awarded a number of prizes including four IEE Premiums, a Best Paper award from the Czech Academy of Sciences and the 2002 Honeywell International Medal from the Institute of Measurement and Control. International recognitions include Honorary Professor at Harbin Institute of Technology and Shandong University, and Visiting Professor at Shanghai University. George Irwin is a former Editor-in-Chief of the IFAC Journal Control Engineering Practice and past chair of the UK Automatic Control Council. He currently chairs the IFAC Publications Committee and serves on the editorial boards of several journals.

===================================

Structural and functional cluster of complex brain networks

J. Kurths, L. Zemanova, and C. Zhou

Abstract: Recent research has revealed a rich and complicated network topology in the cortical connectivity of mammalian brains. A challenging task is to understand the implications of such network structures on the functional organization of the brain activities. This is studied here basing on dynamical complex networks. We investigate synchronization dynamics on the cortico-cortical network of the cat by modelling each node (cortical area) of the network with a sub-network of interacting excitable neurons. We find that the network displays clustered synchronization behaviour and the dynamical clusters coincide with the topological community structures observed in the anatomical network. Our results provide insights into the relationship between the global organization and the functional specialization of the brain cortex.

----------------------------------

Prof. Juergen Kurths

University of Potsdam, Germany

===================================

Development of a Computer-Controlled System for Intracytoplasmic

Sperm Injection with Electro-Activation

Prof. Tong Heng Lee

The National University of Singapore, Singapore

Abstract: In this talk, the development of a computer-controlled system for Intracytoplasmic Sperm Injection (ICSI) with electro-activation is presented. The overall system comprises of a precisely controlled piezo micromanipulation stage integrated to a microinjection workstation, and an electro-activation system capable of automatic medium refresh. The system is comprehensive, comprising of modularly functional components, integrated within a hardware architecture. Experimental and clinical results are provided to verify the effectiveness of the developed system.

----------------------------------

Prof. Tong Heng Lee

The National University of Singapore, Singapore

T. H. Lee received the B.A. degree with First Class Honours in the Engineering Tripos from Cambridge University, England, in 1980; and the Ph.D. degree from Yale University in 1987. He is a Professor in the Department of Electrical and Computer Engineering at the National University of Singapore.

Dr. Lee��s research interests are in the areas of adaptive systems, knowledge-based control, intelligent mechatronics and computational intelligence. He currently holds Associate Editor appointments in the IEEE Transactions in Systems, Man and Cybernetics; Control Engineering Practice (an IFAC journal); the International Journal of Systems Science (Taylor and Francis, London); and Mechatronics journal (Oxford, Pergamon Press).

Dr. Lee was a recipient of the Cambridge University Charles Baker Prize in Engineering. He has also co-authored three research monographs, and holds four patents (two of which are in the technology area of adaptive systems, and the other two are in the area of intelligent mechatronics).

===================================

Neural Network Structures for Adaptation in Engineering Feedback Control Systems

F. L. Lewis

Fellow IEEE, Fellow U.K. Institute of Measurement and Control

Head, Advanced Controls and Sensors Group

Automation and Robotics Research Institute

The University of Texas at Arlington

7300 Jack Newell Blvd. S

Ft. Worth, Texas 76118-7115

http://arri.uta.edu/acs

Abstract: Engineering feedback control systems are responsible for obtaining desired performance from industrial, automotive, robotic, aerospace, and other man-made systems. Included are aircraft autopilots, engine fuel/air mixture and combustion control, ship steering and navigation systems, automated robotic manufacturing cells, spacecraft trajectory control, etc. Control System Theory is a body of theory that deals with the design of feedback controllers; it is heavily rooted in mathematical proofs of stability and performance and provides algorithms for the design of feedback controllers that guarantee such desirable properties. Performance guarantees are the key to acceptance of control structures by the Control Systems Community as well as by private industry.

Control system theory has been based on certain well understood and accepted techniques including adaptive control, robust control, nonlinear systems theory, transfer function methods, state-space methods, etc. During the past several years, it has become more and more clear that methods from the modeling and analysis of life science systems hold out the hope of significantly improving the performance of man-made control systems, and should be added to the control engineer's toolbox of techniques. For instance, in the arena of adaptive control, there has been great interest in artificial neural networks that include dendrite-like weightings, action potential thresholds, and nonlinear processing elements akin to those in the body and axon of the neuron. It has been shown that these ANN, modeled as mathematical processing networks, can extend the capabilities of adaptive controllers by making them applicable for more complex nonlinear systems, and also by greatly improving the system performance.

In this talk we will explore some feedback control structures that are based on biologically inspired systems, showing how they impact the performance and design algorithms of the feedback engineer. Learning and adaptation structures will be developed that improve the performance of controllers and allow their application to complex engineered systems with modeling inaccuracies, vibrational effects, disturbances, and strict performance requirements.

----------------------------------

F. L. Lewis, Ph.D., Fellow IEEE, Fellow U.K. Inst. MC,

Professional Engineer Texas, Chartered Engineer U.K.

Moncrief-O'Donnell Endowed Chair

University Distinguished Scholar Professor

Senior Fellow, Automation & Robotics Research Institute

Head, Advanced Controls & Sensors Group

Automation & Robotics Research Institute

The University of Texas at Arlington

Dr. Lewis was born in W��rzburg, Germany, subsequently studying in Chile and Gordonstoun School in Scotland. He obtained the Bachelor's Degree in Physics/Electrical Engineering and the Master's of Electrical Engineering Degree at Rice University in 1971. He spent six years in the U.S. Navy, serving as Navigator aboard the frigate USS Trippe (FF-1075), and Executive Officer and Acting Commanding Officer aboard USS Salinan (ATF-161). In 1977 he received the Master's of Science in Aeronautical Engineering from the University of West Florida. In 1981 he obtained the Ph.D. degree at The Georgia Institute of Technology in Atlanta, where he was employed as a professor from 1981 to 1990 and is currently an Adjunct Professor. He is a Professor of Electrical Engineering at The University of Texas at Arlington, where he was awarded the Moncrief-O'Donnell Endowed Chair in 1990 at the Automation & Robotics Research Institute. Fellow of the IEEE, Fellow of the U.K. Royal Institute of Measurement & Control, Member of the New York Academy of Sciences. Registered Professional Engineer in the State of Texas and Chartered Engineer, U.K. Engineering Council. Charter Member (2004) of the UTA Academy of Distinguished Scholars and Senior Research Fellow of the Automation & Robotics Research Institute. Has served as Visiting Professor at Democritus University in Greece, Hong Kong University of Science and Technology, Chinese University of Hong Kong, National University of Singapore. Elected Guest Consulting Professor at both Shanghai Jiao Tong University and South China University of Technology.

Current interests include intelligent control, neural and fuzzy systems, wireless sensor networks, nonlinear systems, robotics, condition-based maintenance, micro-electro-mechanical systems (MEMS) control, and manufacturing process control. Author of 5 U.S. patents, 174 journal papers, 32 chapters and encyclopedia articles, 286 refereed conference papers, and 11 books including Optimal Control, Optimal Estimation, Applied Optimal Control and Estimation, Aircraft Control and Simulation, Control of Robot Manipulators, Neural Network Control, High-Level Feedback Control with Neural Networks and the IEEE reprint volume Robot Control. Served/serves on many Editorial Boards including International Journal of Control, Neural Computing and Applications, Optimal Control & Methods, and Int. J. Intelligent Control Systems. Served as Editor for the flagship journal Automatica. Recipient of NSF Research Initiation Grant and continuously funded by NSF since 1982. Since 1991 he has received $6 million in funding from NSF, ARO and other government agencies, including significant DoD SBIR and industry funding. His SBIR program was instrumental in ARRI��s receipt of the US SBA Tibbets Award in 1996. Received Fulbright Research Award, American Society of Engineering Education F.E. Terman Award, three Sigma Xi Research Awards, UTA Halliburton Engineering Research Award, UTA Distinguished Research Award, ARRI Patent Awards, various Best Paper Awards, IEEE Control Systems Society Best Chapter Award (as Founding Chairman of DFW Chapter), and National Sigma Xi Award for Outstanding Chapter (as President of UTA Chapter). Received Outstanding Service Award from the Dallas IEEE Section and selected as Engineer of the year by Ft. Worth IEEE Section. Listed in Ft. Worth Business Press Top 200 Leaders in Manufacturing. Appointed to NAE Committee on Space Station in 1995 and IEEE Control Systems Society Board of Governors in 1996. Selected in 1998 as an IEEE Control Systems Society Distinguished Lecturer. Founding Member of the Board of Governors of the Mediterranean Control Association.

===================================

----------------------------------

Mitsuo UMEZU, PhD

Professor, Chairman of Integrative Bioscience and Biomedical Engineering,

Graduate School of Waseda University, Tokyo ,Japan

I have 30 years experience on the development of artificial hearts, and it is lucky enough for me that two types of artificial hearts, both of which I involved in, have been applied clinically in Japan. Firstly, auxiliary pneumatically-driven pulsatile assist pump was commercialized by Toyobo Company in 1991 based on the fundamental studies by the artificial heart group of the National Cardiovascular Center Research Institute, Osaka and there are over 700 clinical cases in Japan up to now. Bioengineers performed various types of in vitro experiments, such as hydrodynamic tests, hemolysis tests, etc, using our original mock circulatory systems, while huge number of goat experiment were performed towards a development of clinically quality pump. This environment was ideal to validate the data between in vitro and in vivo study. On the other hand, implantable centrifugal type- ventricular assist device project was organized by Dr.Kenji Yamazaki of Tokyo Women's Medical University in 1990 and Sun Medical Company, Waseda University and University of Pittuburgh Medical Center have been supported for the developed of clinical quality ventricular assist pump, called EVAHEART. It has been implanted into 9 human cases in Japan. The first three cases were all discharged and alive. The first patient, whose pump was implanted in May, 2005, has a full-time job, while he drives a car for work everyday. Bioengineers have established a methodology of original in vitro tests to eliminate considerable risk factors, such as fatigue tests, seal leakage tests, etc. These in vitro tests have been proved to be effective and these approaches will reduce a number of animal experiment in the near future.

===================================

Spatial Activity Recognition: A biological inspired model

Professor Svetha Venkatesh

Curtin University of Technology, Perth Western Australia

Abstract: In the pattern recognition community, computer scientists face many open and difficult problems in learning, tracking and classification, and many of these issues arise because of noisy data, imperfect training samples and problem complexity. In this talk, we examine how to solve these open problems with biological principles. Spatial activity recognition in everyday environments is particularly challenging due to these issues. This problem is important in many domains, such as smart homes, large scale urban surveillance and so on. We address the noise issue of spatial recognition with a biologically-inspired chemotactic model that is capable of handling noisy data. The model is based on bacterial chemotaxis, a process that allows bacteria to survive by changing motile behaviour in relation to environmental dynamics. Using chemotactic principles, we propose the chemotactic model and evaluate its classification performance in a smart house environment. We show that the model exhibits high classification accuracy with a diverse dataset and outperforms current models. Importantly, unlike other bottom-up spatial activity recognition models, we show that the chemotactic model is capable of recognising simple interwoven activities, unlike any other computational approach.

----------------------------------

Professor Svetha Venkatesh

Curtin University of Technology, Perth Western Australia

Venkatesh is the Director of the Institute for Multi-Sensor processing and Content Analysis at Curtin University of Technology, Perth Western Australia. The vision of the Institute is to develop a critical mass of expertise in the development of the next generation of tools for large scale pattern recognition, and apply it in the area of intelligent living spaces, content creation, surveillance and process control industries. She has extensive experience in low level vision, pattern recognition and multimedia content analysis, and has made substantial contributions to computer science over the past decade most recently in her development of the field of computational media aesthetics and media creation. She was the recipient of the John Curtin Distinguished Professorship and was elected a fellow of the Australian Academy of Technological Sciences and Engineering and a Fellow of the International Association of Pattern Recognition.

===================================

High throughput imaging for systems neurobiology

Dr. Stephen Wong

Harvard Medical School, USA

Abstract: Optical microscopy and imaging now are indispensable tools in biomedical research. The advances in automation and molecular probes have reached a stage where we can generate many times more high quality, high content data than we are able to analyze. The biologists and clinical researchers currently "eyeball" most images, thus extracting only a fraction of the imbedded data and drawing only general and descriptive conclusions. This talk will present some of the computerized imaging solutions developed in our lab to study neurological disorders and the efficacy of the therapeutics at various levels of biology.

----------------------------------

Dr. Stephen Wong

Harvard Medical School, USA

Stephen TC Wong, Ph.D., PE is the Executive Director of Functional and Molecular Imaging Center, Brigham & Women's Hospital, the Director of HCNR Center for Bioinformatics and an Associate Professor of Radiology, Harvard Medical School. He has over two decades of R&D experience in academia and industry worldwide, including HP, AT&T Bell Labs, Japanese Fifth Generation Computing Project, Royal Philips Electronics, UCSF, and Harvard. His group investigates imaging and bioinformatics techniques for biomarker development, scientific discovery, and personalized medicine. Stephen has published over 200 peer-reviewed papers and 6 patents.

===================================

Biologizing Control Theory

Dr. John L. Casti

IIASA and The Kenos Circle, Vienna, Austria

----------------------------------

Dr. John L. Casti

IIASA and The Kenos Circle, Vienna, Austria

I received my Ph.D. in mathematics under Richard Bellman at the University of Southern California in 1970. I worked at the RAND Corporation in Santa Monica, CA, and served on the faculties of the University of Arizona, NYU and Princeton before becoming one of the first members of the research staff at the International Institute for Applied Systems Analysis (IIASA) in Vienna, Austria. In 1986, I left IIASA to take up a position as a Professor of Operations Research and System Theory at the Technical University of Vienna. I am also a member of the External Faculty of the Santa Fe Institute in Santa Fe, New Mexico, USA, where I worked extensively on the application of biological metaphors to the mathematical modeling of problems in economics, finance and road-traffic networks, as well as on large-scale computer simulations for the study of such networks.

In 2000 I formed two companies in Santa Fe and London, Commodicast, Inc. and SimWorld, Ltd, devoted to the employment of tools and concepts from modern system theory for the solution of problems in business and finance. In early 2005 I returned to Vienna as a Research Fellow at the Wissenschaftzentrum Wien, where I am in the process of establishing a new research division devoted to questions at the interface of the arts/humanities/social sciences, natural sciences, and philosophy/mathematics. In addition, I have co-founded The Kenos Circle with Dr. Michael Zillner, a professional society that aims to make use of complexity science in order to gain a deeper insight into the future than that offered by more conventional statistical tools.

Over the past few years, I have written a numerous articles and seven technical monographs and textbooks on mathematical modeling. In addition, I am the editor of the journals Applied Mathematics & Computation (Elsevier, New York) and Complexity (Wiley, New York). In 1989 my text/reference work Alternate Realities: Mathematical Models of Nature and Man (Wiley, 1989) was awarded a prize by the Association of American Publishers in a competition among all scholarly books published in mathematics and the natural sciences. In 1992, I also published Reality Rules (Wiley, New York), a two-volume text on mathematical modeling.

In addition to these technical volumes, I have written several popular books on science: Paradigms Lost: Images of Man in the Mirror of Science (Morrow, 1989), which addresses several of the most puzzling controversies in modern science, Searching for Certainty: What Scientists Can Know About the Future (Morrow, 1991), a volume dealing with problems of scientific prediction and explanation of everyday events like the weather, stock market price movements and the outbreak of warfare, and Complexification (HarperCollins, 1994), a study of complex systems and the manner in which they give rise to counterintuitive, surprising behavior. I have also written two popular volumes on mathematics: Five Golden Rules: Great Theories of 20th-Century Mathematics---and Why They Matter, and its sequel, Five More Golden Rules (1995, 2000) both published by John Wiley & Sons (New York). My next work of popular science was Would-Be Worlds, a volume on computer simulation and the way it promises to change the way we do science. It was also published by John Wiley & Sons (New York) in1996. In 1998 I published a volume of ``scientific fiction,'' involving Ludwig Wittgenstein, Alan Turing, J.B.S. Haldane, C.P. Snow and Erwin Schrödinger in a dinner-party conversation on the question of the uniqueness of human cognition and the possibility of thinking machines. This book was published under the title The Cambridge Quintet by Little, Brown (UK) in December 1997 and by Addison-Wesley in the US in early 1998.

More recently, my published books include Art & Complexity (Elsevier, Amsterdam, 2003), a volume edited with A. Karlqvist, as well as a short volume on the life of the Austrian logician, Kurt Gödel, the book Gödel: A Life of Logic (Perseus Books, Cambridge, MA, 2002). In the same year I published the volume, The One, True, Platonic Heaven (Joseph Henry Press, Washington, DC, 2003), which addresses in a fictional format the question of the limits to scientific knowledge.

My current research interests have also shifted somewhat to the exploration of questions in the social and behavioral realm and the relationship between social "moods" and their consequent social actions and behaviors. In this direction, my latest book, Zeitgeist: Why We See the Events We Do|and Not See Something Else, addresses the directions and patterns of social causation and their implications for future trends and collective social events, such as styles in popular culture, the outcome of political processes, and even the rise and fall of civilizations.