April 6-8, 2016 - Saint Julian's, Malta
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2024-12-03 02:39
A System of Autonomous Vehicles: Modeling, Diagnostics, Prognostics, Localization, Navigation and Cloud-Based Control
Prof. Mo Jamshidi, Ph.D., DEgr.
Lutcher Brown Endowed Professor
The University of Texas, USA
With the advent of the Internet in mid-1990’s people of the world got connected. System of systems (or cyber-physical systems) have been advocated within US military and US aerospace industry for over 10 years. System of Systems (SoS) are integration of independent operatable and non-homogeneous legacy systems to achieve a higher goal than the sum of the parts. SoS is a generalization of Internet where people, machines or machines and machines are now connected.For the past half century or so, large amount of data has been accumulating in all aspects of our lives. Advances in sensor technology, the Internet, wireless communication, and inexpensive memory have all contributed to an explosion of “Big Data”.
The objective of this presentation is to describe the fundamental problems addressed for a system of autonomous vehicles (airborne, land and undersea). Issues like modeling, diagnostic, prognostics, big data analytic, control, testing, evaluation and outreach all will be discussed. A UTSA open stack cloud infrastructure is also being used to do most compute-intensive tasks.
Bio-Sketch
Mo M. Jamshidi (Fellow IEEE, Fellow ASME, A. Fellow-AIAA, Fellow AAAS, Fellow TWAS, Fellow NYAS) received BS in EE, Oregon State University, Corvallis, OR, USA in 1967, the MS and Ph.D. degrees in EE from the University of Illinois at Urbana-Champaign, IL, USA in June 1969 and February 1971, respectively. He holds honorary doctorate degrees from University of Waterloo, Canada, 2004 and Technical University of Crete, Greece, 2004. Currently, he is the Lutcher Brown Endowed Chaired Professor at the University of Texas, San Antonio, TX, USA. He has been an advisor to NASA (including 1st MARS Mission), USAF, USDOE and EC/EU (Brussels). He has over 730 technical publications including 68 books (11 text books), research volumes, and edited volumes in English and a few foreign languages. He is the Founding Editor or co-founding editor or Editor-in-Chief of 5 journals including IEEE Control Systems Magazine and the IEEE Systems Journal. He is an Honorary Professor at three Chinese Universities (Nanjing and Xi’an), Deakin University (Australia), Birmingham University and Loughbrough University (UK), and Obuda University (Hungary). In October 2005 he was awarded the IEEE’s Norbert Weiner Research Achievement Award. He is a member of the University of the Texas System Chancellor’s Council since 2011. He is currently involved in research on system of systems engineering with emphasis on cloud computing, robotics, UAVs, biological and sustainable energy systems. He has over 6600 citations on Scholar Google.
Network Based Control and Filtering in a Unified Framework
Prof. Huijun Gao
Professor and director of the Research Institute of Intelligent Control and Systems
Harbin Institute of Technology, Harbin, China
With rapid developments of information technology, network-based control has been widely used in industrial processes. However, various network-induced constraints such as transmission delays, packet dropouts/disorder and quantization, also bring great challenges to conventional control theories. On the other hand, in order to improve the efficiency and gain more profit, the two-layer network-based feedback control scheme has shown its great advantages over the traditional one-layer network-based one in operational control of industrial processes. The talk will first introduce some elegant approaches to network-based control and estimation problems. And then a novel two-layer network-based architecture for operational control of industrial processes will be discussed. It will be shown that under the proposed framework, the overall optimal operational control of industrial processes can be achieved.
Bio-Sketch
Huijun Gao received his Ph.D. degree in control science and engineering from Harbin Institute of Technology, China, in 2005. He was a Research Associate with the Department of Mechanical Engineering, The University of Hong Kong, from November 2003 to August 2004. From October 2005 to October 2007, he carried out his postdoctoral research with the Department of Electrical and Computer Engineering, University of Alberta, Canada. Since November 2004, he has been with Harbin Institute of Technology, where he is currently a Professor and director of the Research Institute of Intelligent Control and Systems.
Prof. Gao’s research interests include network-based control, robust control/filtering theory and their engineering applications. He have (co-)authored 3 monographs, and published more than 300 papers in international journals and peer-reviewed conferences, among which, more than 100 papers are published in IEEE Transactions and Automatica. His scientific papers have been cited for more than 3000 and 10000 times according to Web of Science and Google Scholar, respectively.
He is an IEEE Fellow and received the IES David Irwin Early Career Award. He is Co-Editor-in-Chief of IEEE Transactions on Industrial Electronics and Associate Editor of Automatica, IEEE Transactions on Control Systems Technology, IEEE Transactions on Cybernetics, IEEE/ASME Transactions on Mechatronics etc. Prof. Gao is an IEEE Industrial Electronics Society (IES) Administration Committee (AdCom) member.
He is among the top 17 (15th position is shared by 3 people) listed in Thomson Reuters 2014, The World’s Most Influential Scientific Minds.
Risks-Forcast@People-in-Clouds: Big data based Clouds Healthcare and Risk Forecasting based on Subjective Intelligence
Prof. Hamido Fujita
Director of Intelligent Software Systems
Iwate Prefectural University, Japan
and
Editor-in-Chief: http://yannakakis.net/, Elsevier
In decision making most approaches are taking into account objective criteria, however the subjective correlation among decision makers provided as preference utility is necessary to be presented to provide confidence preference additive among decision makers reducing ambiguity and produce better utility preferences measurement for subjective criteria among decision makers. Most models in Decision support systems are assuming criteria as independent. Therefore, these models are ranking alternatives based on objective data analysis. Also, different type of data (time series, linguistic values, interval data, etc.) imposes some difficulties to do decision making using classical multi criteria decision making models.
Sophisticated machine learning methods to estimate or extract emotions from the content created by users has been developed including support vector machines, Bayesian networks, maximum entropy approaches and concept level analysis of natural language text, supported by combinations of common-sense reasoning. These approaches are mainly based on language text processing with sufficient documents, which is usually in-large is not available.
We think subjectivness is related to the contextual form of criteria. Uncertainty of some criteria in decision making is also considered as other important aspect These draw backs in decision making are major research challenges that are attracting wide attention, like on big data analysis for risk prediction, medical diagnosis and other applications that are in practice more subjective to user situation and its knowledge related context. Subjectivity would be examined based on correlations between different contextual structures that is reflecting the framework of personal context, for example in nearest neighbor based correlation analysis fashion. Some of the attributes incompleteness also may lead to affect the approximation accuracy. Attributes with preference-ordered domain relations properties become one aspect in ordering properties in rough approximations.
The Virtual Doctor System (VDS) developed by my group is a system assisting human doctor who is practicing medical diagnosis in real situation and environment. The interoperability is represented by utilizing the medical diagnosis cases of medical doctor, represented in machine executable fashion based on human patient interaction with virtual avatar resembling a real doctor. VDS is practiced as a virtual avatar interacting with the human patient based on physical views and mental view analysis. In this talk I outline our VDS system and then discuss related issues in subjective decision making in medical domain. Using fuzzy reasoning techniques in VDS, it has been shown that it is possible to provide better precision in circumstances that is related to partial known data and uncertainty on the acquisition of medical symptoms.
Bio-Sketch
Hamido Fujita is professor at Iwate Prefectural University (IPU), Iwate, Japan, as a director of Intelligent Software Systems. He is the Editor-in-Chief of Knowledge-Based Systems, Elsevier of impact factor (2.97) for 2014. He received Doctor Honoris Causa from O’buda University in 2013, and a title of Honorary Professor from O’buda University, Budapest, Hungary in 2011. He received Honorary scholar from University of Technology Sydney, Australia on 2012. He is Adjunct professor to Stockholm University, Sweden, University of Technology Sydney, National Taiwan Ocean University and others. He has supervised PhD students jointly with University of Laval, Quebec, Canada; University of Technology, Sydney, Australia; Oregon State University (Corvallis), University of Paris 1 Pantheon-Sorbonne, France and University of Genoa, Italy. He has four international Patents in Software System and Several research projects with Japanese industry and partners. He is vice president of International Society of Applied Intelligence. He has given many keynotes in many prestigious international conferences on intelligent system and subjective intelligence. He headed a number of projects including Intelligent HCI, a project related to Mental Cloning as an intelligent user interface between human user and computers and SCOPE project on Virtual Doctor Systems for medical applications.
Real machine scheduling problems with metaheuristics
Prof. Rubén Ruiz
Polytechnic University of Valencia, Spain
Real scheduling problems found in industry are as varied and heterogeneous as the nature of the different products manufactured. One can expect that if the manufacturing process of an LCD panel and a ceramic tile have little in common, scheduling algorithms for solving those problems need to be also radically different. However, designing ad-hoc scheduling methods for each manufacturing problem is extremely time consuming. Such scheduling algorithms, even if successful, are hardly a viable choice as continuous changes in products, machines, tooling, processes, methodologies, etc. might render them quickly obsolete. On the contrary, simple metaheuristics without too much problem-specific knowledge and working on a solution representation abstraction are basically problem agnostic. Effective metaheuristics still produce state-of-the-art results most of the time and can result in good solutions for instances of realistic size in a matter of minutes. In this presentation, we will introduce simple metaheuristics based on the Iterated Greedy (IG) principles. These methods are inherently simple with very few parameters. They are easy to code and results are easy to reproduce. We will show that for all tested problems so far they show state-of-the-art performance despite their simplicity. Special emphasis will be put on realistic scheduling problems coming from several industrial applications. We will move from flowshops to real hybrid flexible flowline problems with several side constraints. We will defend the choice of simpler, yet good performing approaches over complicated metaphor-based algorithms in a solid attempt to close the long-standing research gap between the theory and the practice of scheduling.
Bio-Sketch
Rubén Ruiz is Full Professor of Statistics and Operations Research at the Polytechnic University of Valencia, Spain. He is co-author of more than 60 papers in International Journals and has participated in presentations of more than a hundred papers in national and international conferences. He is editor of the Elsevier’s journal Operations Research Perspectives (ORP) and co-editor of the JCR-listed journal European Journal of Industrial Engineering (EJIE). He is also associate editor of other important journals like TOP or Applied Mathematics and Computation as well as member of the editorial boards of several journals most notably European Journal of Operational Research and Computers and Operations Research. He is the director of the Applied Optimization Systems Group (SOA, http://soa.iti.es) at the Instituto Tecnológico de Informática (ITI, http://www.iti.es) where he his or has been principal investigator of several public research projects as well as privately funded projects with industrial companies. His research interests include scheduling and routing in real life scenarios.
Agility issues in supply chain management
Prof. Chengbin Chu
Director/Chair Professor of Supply Chain Management
CentraleSupélec, Université Paris-Saclay, France
In this talk, we discuss increasingly important agility issues in supply chain management. Especially we present major concerns of practioners and the gap between their expectations and academic research, identify some interesting topics for academic research. To illustrate, we address a reallife problem in flexible quantity contrating between a supplier and a manufacturer.
Bio-Sketch
Games: AI's Long-Standing Friend and (Final) Frontier.
Prof. Georgios N. Yannakakis
Director of the Institute of Digital Games
University of Malta, Malta
Why games offer the ideal arena for AI? Alternatively, how can AI help us make better games? Is it possible, for instance, that AI understands how we feel, think and react and, in turn, automatically design new games for us? Can those computationally designed games be considered creative? What happens when we design together with our AI? Do we merely co-design or can a machine truly foster our creativity as human designers?
In this talk I will address the above questions by positioning computer games as the ideal application domain for AI for the unique features they offer. For that purpose, I will identify a number of key creative facets in modern game development and discuss their required orchestration for a successful game product. I will also focus on the study of player emotion and will detail the key phases for efficient game-based affect interaction. Advanced methods for player experience modeling, game adaptation, procedural content generation, and computational game creativity will be showcased via a plethora of game projects developed at the Institute of Digital Games, University of Malta.
Bio-Sketch
Georgios N. Yannakakis (http://yannakakis.net/) is the Director of the Institute of Digital Games, University of Malta (UoM). He received the PhD degree in Informatics from the University of Edinburgh in 2005. Prior to joining the Institute of Digital Games, UoM, in 2012 he was an Associate Professor at the Center for Computer Games Research at the IT University of Copenhagen. He does research at the crossroads of artificial intelligence, computational creativity, affective computing, advanced game technology, and human-computer interaction. He pursues research concepts such as user experience modeling and procedural content generation for the design of personalized interactive systems for entertainment, education, training and health. He has published over 180 journal and conference papers in the aforementioned fields and his work has been cited broadly. His research has been supported by numerous national and European grants and has appeared in Science Magazine and New Scientist among other venues. He is an Associate Editor of the IEEE Transactions on Affective Computing and the IEEE Transactions on Computational Intelligence and AI in Games. He has been the General Chair of key conferences in the area of game artificial intelligence (IEEE CIG 2010) and games research (FDG 2013). He is a Senior Member of IEEE.Facial Animation and Speech Synchronization in MPEG-4
Prof. Abdennour El Rhalibi
Professor of Entertainment Computing
Head of Strategic Projects
Head of Computer Games Research Group at the Protect Centre
School of Computer Science
Liverpool John Moores University, UK
In this talk, Prof. Abdennour El Rhalibi will present an overview of his research in game technologies at LJMU. He will present some recent projects developed with BBC R&D, on game middleware development and in facial animation. In particular he will introduce a novel framework for coarticulation and speech synchronization for MPEG-4 based facial animation. The system, known as Charisma, enables the creation, editing and playback of high resolution 3D models; MPEG-4 animation streams; and is compatible with well-known related systems such as Greta and Xface. It supports text-to-speech for dynamic speech synchronization. The framework also enables real-time model simplification using quadric-based surfaces. The coarticulation approach provides realistic and high performance lip-sync animation, based on Cohen-Massaro's model of coarticulation adapted to MPEG-4 facial animation (FA) specification. He will also discuss some experiments which show that the coarticulation technique gives overall good results when compared to related state-of-the-art techniques.
Bio-Sketch
Abdennour El Rhalibi is Professor of Entertainment Computing and Head of Strategic Projects at Liverpool John Moores University. He is Head of Computer Games Research Lab at the Protect Research Centre. He has over 22 years' experience doing research and teaching in Computer Sciences. Abdennour has worked as lead researcher in three EU projects in France and in UK. His current research involves Game Technologies and Applied Artificial intelligence. Abdennour has been leading for six years several projects in Entertainment Computing funded by the BBC and UK based games companies, involving cross-platform development tools for games, 3D Web-Based Game Middleware Development, State Synchronisation in Multiplayer Online Games, Peer-to-Peer MMOG and 3D Character Animation. Abdennour has published over 160 publications in these areas. Abdennour serves in many journal editorial boards including ACM Computer in Entertainment and the International Journal of Computer Games Technologies. He has served as chair and IPC member in over 100 conferences on Computer Entertainment, AI and VR. Abdennour is member of many International Research Committees in AI and Entertainment Computing, including IEEE MMTC IG: 3D Rendering, Processing and Communications (3DRPCIG), IEEE Task Force on Computational Intelligence in Video Games and IFIP WG 14.4 Games and Entertainment Computing. Sophisticated machine learning methods to estimate or extract emotions from the content created by users has been developed including support vector machines, Bayesian networks, maximum entropy approaches and concept level analysis of natural language text, supported by combinations of common-sense reasoning. These approaches are mainly based on language text processing with sufficient documents, which is usually in-large is not available.
Event-Triggered Control for Output Consensus of Heterogeneous Linear Multi-Agent Systems
Prof. Gang Feng
Chair Professor
City University of Hong Kong, Hong Kong, China
In this talk distributed even-triggered control algorithms will be presented for output consensus of heterogeneous multi-agent systems with general linear dynamics, with the objective to reduce the number of controller updates and communication exchanges. It is shown that the output consensus problem can be solved by the proposed event-triggered control algorithms if a necessary and sufficient condition is satisfied. Then a self-triggered control scheme is also developed, where continuous monitoring of measurement errors can be avoided. The feasibility of both proposed control schemes is discussed by excluding Zeno behavior. It is also shown that agents are able to achieve output consensus with significant reduction of the number of triggering events, controller updates and communication transmission. As a result, energy can be saved and the lifespan of the agents can be prolonged. A numerical example is given to illustrate the effectiveness of the proposed control schemes.
Bio-Sketch
Gang Feng received the B.Eng and M.Eng. Degrees in Automatic Control from Nanjing Aeronautical Institute, China in 1982 and in 1984 respectively, and the Ph.D. degree in Electrical Engineering from the University of Melbourne, Australia in 1992. Professor Feng was a Lecturer in Royal Melbourne Institute of Technology, 1991 and a Senior Lecturer/Lecturer, University of New South Wales, 1992-1999. He has been with City University of Hong Kong since 2000 where he is now a Chair Professor of Mechatronic Engineering. He was also a ChangJiang Chair Professor at Nanjing University of Science and Technology, awarded by Ministry of Education. He has received Alexander von Humboldt Fellowship, the IEEE Transactions on Fuzzy Systems Outstanding Paper Award, the Best Paper Award of IEEE International Conference on Neural Networks and Signal Processing and the Best Theoretical Paper Award in the Second World Congress on Intelligent Control and Automation. He is an author of one research monograph entitled “Analysis and Synthesis of Fuzzy Control Systems: A Model Based Approach”, and over 200 SCI indexed papers including over 100 in IEEE Transactions. His research interests include intelligent systems and control, networked control systems, and multi-agent systems and control.Professor Feng is a fellow of IEEE. He has been an Associate Editor of IEEE Trans. Automatic Control, IEEE Trans. on Fuzzy Systems, Mechatronics, IEEE Trans. Systems, Man, & Cybernetics, Journal of Systems Science and Complexity, and Journal of Control Theory and Applications.