16th to 19th August 2011
 
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Plenary session
 
"Frontiers in Electronics and Telecommunications"
 
Titles of the talks and corresponding resource persons
 
Title of session 1: Frontiers in Electronics and Telecommunications
   
 
Abstract: An application of  Green industrial and information Systems can be found in our use of "green electronics" to extend product life.
Extending prodcut life is not necessarily the first priority of industrial manufacturers where selling new replacements and new models increases demand.  However a revolution is occurring where increased 
product longevity wins a greater market share and world wide companies such as Roll Royce are finding rich returns by making products more reliable.  From an information systems perspective we already have Error detection and Correction startegies for data reiability and JTAG and Built in Self Test for hardware.  However what about the next steps,  built in self correction for hardware?  Are self fixing systems possible?  Biology seems to prefer this paradigm where limited damage can be healed. Can we design a self repairing systems using smart information systems for the next generation of electronic and electromechanical systems.  If so, then an engine might become much safer, last longer and give a better return. This approach fits the new industrial sales model well that of leasing product functionality by the hour.  There is huge incentive then for the manufacturer to make low cost maintenance its top priority.

  This talk will present three aspects of the above research theme: 
Our new UK ?10M funded Centre for Through Life Engineering Services, enabling such research. 
Smart Communications devices using Holographic Lithography.
Electronic methods for implementing "Self repair" Regenerative Engineering. 
     
 
I have a background in Signal Processing for Engineering. My early training at the Cavendish Laboratory was in Radio Astronomy, Aperture Synthesis and Interferometry. The search to link radio objects to optical galaxies led me to be part of the first teams buidling CCD cameras and the image processing technologies then enabled. Interests which followed include the corretion of atmospheric seeing using liquid crystal phase modulating devices, the synthesis of optical elements and the use of fast processor technologies to perform high
 
speed real time calculations. This work has involved considerable interaction with Industry. Working with the Regional Development Agency: One North East significant Technology Transfer Projects were initiated called ReCET, NeMEC and CENS deploying European funds to assist SMEs take advantage of University Research and generate more economic impact. These projects evolved into a National Faraday Centre and engaged high profile businesses as partners through follow on EPSRC awards such as Agilent, Sharp and Intel. With this substantial corporate experience, opportunities to exploit core EPSRC funded research in the manufacturing sector where there is considerable interest in novel techniques to enable electronic products to repair (heal) themselves. The opportunity for extending this know how on self -fix strategies to encompass electro-mechanical goods with current Industrial sponsors is now a reality through our new ?10m Centre for Through Life Engineering Services in partnership with Cranfield University. Making products last for longer is an example of "Green Electronics" in Smart Systems.
 
Alan is a Professor in Engineering (Electronic Systems) having held many 4x 6 month sabbatical posts at leading International Universities, Stanford, Technion, Cambridge, EPFL.He has held a Fulbright Senior Scholarship at the Leland Stanford Junior University, CA. a Royal Society Visiting Professorship at the Technion and a Royal Society Visiting Scholarship at the Ecole Polytechnic Federal Lausanne. He was Founding Research Director of the EPPIC Faraday (now a Knowledge Transfer Network) partnership for Electronics and Photonics and is a Director of a spin out company.
  Research Interests
Digital signal processing
Optics and image processing
     
  Title of session 2: Radiobots: Towards Self-learning Autonomous Cognitive Radios
     
 
Abstract: For many people, when they see the term cognitive radio the first thing that comes to mind is the dynamic spectrum sharing (DSS). Indeed, DSS seems to be almost synonymous with cognitive radio in communications and signal processing literature. On the other hand, RF antenna/reconfigurable hardware community treats it as an upgrade of an software-defined radios (SDR's). However, for a neutral observer the term cognitive radio naturally would invoke a notion much more broader than either one of these. In recent years, our attempt has been in developing radios that may conform with such a more general interpretation of what really is, or rather can be, a cognitive radio. Based on essentially what true cognition may mean, we define a type of cognitive radio called a Radiobot as "an intelligent wireless communications device that has the ability to reason and learn from the observed RF environment and past actions to self-decide optimal communications mode and can optimally self-reconfigure its hardware to support the selected mode".
 
Radiobots are expected to be autonomous communication devices that has the capability for self-management and truly cognitive learning and reasoning. Ideally, a Radiobot must be able to observe/sense a wide spectrum band much larger than transmission bandwidth required by its communication mode/modes at any given time. It can self-interpret the sensed wide spectrum to determine the properties of its RF environment and characteristics of RF activity in it. Based on these interpretations and its own communications objectives, the Radiobot can then select the best mode of operation and reconfigure its hardware to indeed achieve that chosen mode of operation. Similar to a cognitive being, it can then learn from experience generated by the success or failure of these actions to make better decisions in future. Clearly, this type of cognitive radio need not simply be aimed at achieving dynamic spectrum allocation as is the focus of almost all current work on cognitive radios. A Radiobot can be an autonomous radio that may enable interoperability and multi-mode operability. It can also be used to achieve either cognitive anti-jamming capabilities or to act as a sophisticated jammer itself. In another scenario, a Radiobot can be a means to achieve advanced LPI/LPD communications.
 
Radiobots are expected to be autonomous communication devices that has the capability for self-management and truly cognitive learning and reasoning. Ideally, a Radiobot must be able to observe/sense a wide spectrum band much larger than transmission bandwidth required by its communication mode/modes at any given time. It can self-interpret the sensed wide spectrum to determine the properties of its RF environment and characteristics of RF activity in it. Based on these interpretations and its own communications objectives, the Radiobot can then select the best mode of operation and reconfigure its hardware to indeed achieve that chosen mode of operation. Similar to a cognitive being, it can then learn from experience generated by the success or failure of these actions to make better decisions in future. Clearly, this type of cognitive radio need not simply be aimed at achieving dynamic spectrum allocation as is the focus of almost all current work on cognitive radios. A Radiobot can be an autonomous radio that may enable interoperability and multi-mode operability. It can also be used to achieve either cognitive anti-jamming capabilities or to act as a sophisticated jammer itself. In another scenario, a Radiobot can be a means to achieve advanced LPI/LPD communications.
     
 
Sudharman K. Jayaweera received the B.E. degree in Electrical and Electronic Engineering with First Class Honors from the University of Melbourne, Australia, in 1997. He obtained his M.A. and PhD degrees in Electrical Engineering from Princeton University in 2001 and 2003, respectively. Since 2006 he has been a tenure-track assistant professor at the Department of Electrical and Computer Engineering of the University of New Mexico, USA. He is a senior member of the IEEE. Dr. Jayaweera received the Best Paper Award at the 2006 IEEE Advanced
 
Video and Signal-based Surveillance Conference (AVSS’06), and the Best Technical Paper Award at the 2003 IEEE Wireless Personal Multimedia Conference (WPMC’03). He was awarded an Air Force Summer Faculty Fellowship at the Air Force Research Laboratory (AFRL) Space Vehicles Directorate at the Kirtland Air Force Base for 2009, 2010 and 2011. Currently Dr. Jayaweera serves as the associate editor of EURASIP Journal on Advances in Signal Processing and as a Member of the Editorial Advisory Board of the Open Signal Processing Journal, Bentham Science Publishers. He served as the co-chair of the Software Defined and Cognitive Radios subcommittee of the 2008 IEEE Radio and Wireless Symposium (RWS 08), and the TPC track-chair of the 2010 International Conference on Information and Automation for sustainability (ICIAfS'10). He has served in numerous IEEE conference technical program committees (TPC), including, for example, IEEE GLOBECOM (2006, 2008-2011), IEEE ICC (2010-2012), IEEE ISSSTA 2006, IEEE RWS/RWC (2006- 2008), VTC 2005 and WCNC (2011, 2012). Dr. Jayaweera is the Founder of the Communications and Information Sciences Lab (CISL - www.ece.unm.edu/cisl/) and the co-Founder of the Cognitive Radios Lab (CRL -http://www.ece.unm.edu/cognitive-radio/) at the ECE Department of UNM. He served as the Chair of Signal Processing and Communications Group at the UNM in 2007-2008, and is the Director of the EYES summer internship program for international students since 2007. His current research interests are in cognitive and cooperative radios, wireless mobile and ad-hoc sensor networks, networked-control systems, machine learning, distributed statistical signal processing, smart-grid communications/control/optimization and network information theory.
 
  Title of session 3: Parametric Resonance & Oscillatory Stabilization with Applications to                              MEMS Comb Drives
     
 
Jordan M. Berg received the BSE and MSE in Mechanical and Aerospace Engineering from Princeton University in 1981 and 1984. He received the PhD in Mechanical Engineering and Mechanics, and the MS in Mathematics and Computer Science from Drexel University in 1992. He held postdoctoral appointments at the USAF Wright Laboratory in Dayton, OH, and at the Institute for Mathematics and Its Applications in Minneapolis, MN. Since 1996 he has been at Texas Tech University, where he is Professor of Mechanical Engineering and Co-Director of the Nano Tech Center. His research interests include modeling, simulation,
 
design, and control of nano- and microsystems. As a Fulbright Scholar in 2008 he lectured and conducted research at theUniversity of Ruhuna and University of Peradeniya in Sri Lanka. He currently serves on the Editorial Board of the IEEE/ASME Transactions on Mechatronics and as an officer of the Mechatronics Technical Committee of the Dynamic Systems and Controls Division of ASME. In 2011 he was elected a Fellow of ASME.
     
 
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