The true indicator of performance in applications such as imaging and printing is the quality of the resulting image as perceived by a human observer. Image quality assessment algorithms try to obviate the need for a human observer by providing an objective measure of subjective image quality. In this talk I will describe a new framework for quantifying distortions in color images. Starting with the observation that human judgements of image quality are relatively insensitive to small changes in the viewing or imaging conditions, I will motivate the need for a signal representation that is spatially adaptive. In particular, I will exploit the fact that distortions along some directions in the vector space corresponding to the full set of color image pixel values are less perceptible than others, and that these directions generally depend on the content of the original image. This adaptive signal representation is then used to develop an image quality metric that is correlated well with human perception of color images subjected to a variety of different common distortions.

The fields of computer graphics, image processing and computer vision are inherently intertwined. Solutions to problems in one field are often influenced by methods from another. In this talk I will present examples of the blurring boundaries between the 3 fields which I have encountered while solving problems in medical visualization and information visualization, and during the development of interactive graphics applications.

Mr. Clement is a 1998 graduate from the LSU ECE Department. The talk will provide students with an overview on the type of work they can expect to perform should they choose to pursue a career in power distribution. The presentation is geared towards students interested in the power generation and distribution; however, it may also provide insight to the industry (EPC) for the students not interested in power.

Nanostructured materials lie at the heart of the fundamental advances in efficient energy storage/conversion in which surface process and transport kinetics place determining roles. To develop high-rate intercalation electrodes for energy storage devices such as lithium-ion rechargeable batteries, facile solution processing methods are employed to achieve a variety of nanostructured electrodes, including nanotube arrays of titanium oxide obtained via anodization of titanium foil. All the nanostructured electrodes demonstrate higher Li-ion intercalation capacities and better kinetics compared to the thin film electrode, due to the higher surface area and the shorter diffusion distance. In addition, to enhance the cycling life of lithium-ion battery electrodes, ultra-thin and highly-conformal surface coatings are deposited onto electrodes by using the atomic layer deposition (ALD) technique. The ALD-coated cathodes show significantly enhanced cycleability than bare cathodes, because the high-quality ALD coatings protect the cathode materials from dissolution during electrochemical cycling. Moreover, the thickness of ALD coatings can be accurately tuned at atomic scale by varying ALD growth cycles. Therefore, the cycling performance of ALD-coated cathodes can be easily optimized by controlling the coating thickness precisely.

Dr. Ying (Jane) Wang is an Assistant Professor in the Department of Mechanical Engineering at Louisiana State University since August 2008. Prior to that, she worked as a Postdoc Fellow in Materials Science at Northwestern University from 2006 to 2008. She received her Ph.D. degree in Materials Science and Engineering at University of Washington, a M.A. degree in Chemistry at Harvard University, and a B.S. degree in Chemical Physics from University of Science and Technology of China (USTC). Dr. Wang's research focuses on nanomaterials synthesis for energy applications such as lithium-ion batteries, solar cells, and oil spill cleanup. She has published 37 refereed journal articles and conference proceedings, 6 book chapters, and co-authored one book on nanomaterials and nanostructures. Her recent awards include Ralph E. Powe Junior Faculty Enhancement Award in 2010 and LSU Dean's Scholarship Award in 2011.

In recent years, modern graphics processing units have been widely adopted in high performance computing areas to solve large scale computation problems. The leading GPU manufacturers Nvidia and ATI have introduced series of products to the market. While sharing many similar design concepts, GPUs from these two manufacturers differ in several aspects on processor cores and the memory subsystem. In this paper, we conduct a comprehensive study to characterize the architectural differences between Nvidia's Fermi and ATI's Cypress and demonstrate their impact on performance. Our results indicate that these two products have diverse advantages that are reflected in their performance for different sets of applications. In addition, we also compare the energy efficiencies of these two platforms since power/energy consumption is a major concern in the high performance computing.

Ying Zhang received the bachelor's and master's degree in electronics and information engineering from Huazhong University of Science and Technology, China, in June 2006 and June 2008, respectively. He joined the the Department of Electrical and Computer Engineering, Louisiana State University as a PhD student in Fall 2008. His research interests include GPU performance characterization, energy-efficient computing, and reliable processor design.

The main idea in this work is to design and analyze a symmetric key generation algorithm whereby we can strengthen wireless network security. Our main goal is generating a sequence of highly secure secret keys based on an ARQ based transmission mechanism that relies on the statistical independence of channel errors between the attacker and legitimate users. This leads to some information loss for the adversary which allows us to constantly extract keys by using universal Hashing techniques from communication process, about which we can make sure that adversary's knowledge remains negligible. More specifically, the key generation algorithm is analyzed and designed in a way that targeted security as well as the required throughput and synchronization goals for the transmission are achieved. Simulation results show that the designed algorithm achieves the desired requirements for both system security and throughput.

Yahya S. Khiabani received his B.S.E.E. and M.S.E.E degrees from University of Tabriz, Iran, in 2003 and 2007. He was admitted as a PHD student in Louisiana state university, ECE department, in 2009 and granted Economic Development Assistantship (EDA) to work on security algorithms in wireless networks under advisory of Dr. Shuangqing Wei. As a PHD student his research is focused on information theoretic based security and anti-eavesdropping algorithms in wireless networks including physical layer secrecy and cryptography.

We consider the problem of spectrum sensing in cognitive radios when the receiver of the secondary user (SU) is equipped with a multi-antenna system. Using an estimate of the cross-correlation among the signals received at different antenna elements, we propose a blind detection method which assumes no prior knowledge of the signaling scheme used by the primary user (PU), the noise power, or the channel path coefficients. The cross-correlation among the received signals is a result of the correlation among the channel path coefficients from the PU transmitter to different antenna elements of the secondary receiver. The detection and false alarm probabilities of the proposed algorithms are evaluated using an asymptotic analysis and the results are compared to simulation results. It is shown that the proposed methods outperform several recently-proposed blind sensing techniques for cognitive radios using multiple antennas.

This presentation will focus on the real-time digital controller design for Networked Control System (NCS). NCSs are spatially distributed systems in which communications between sensors, actuators and controllers are realized through a shared digital communication network. Networked control can effectively reduce wiring, and achieve low installation cost, ease of maintenance, and flexibility in reconfiguration. Its advantages are further demonstrated with the ever increasing complexity of control system structures. For the real-time networked control system, a serious challenge is the inevitable and unpredictable delay and data loss due to shared communication channel, which may degrade the performance or even destabilize the system. So far, research efforts are mainly within single loop systems. For multiple interconnected systems over shared communication channels that work together in a distributed fashion towards common goals, the controller design methodologies to achieve satisfied performances under real-time conditions have not been fully explored. This research is to integrate control theory, mathematical modeling, embedded system, and cybernetics together to obtain a physical implementation for various applications involving cyber-physical system, power system, etc.

Yongpeng Zhang received his BS degree in Automatic Control from Xi'an University of Technology in 1994, MS degree in Automation from Tianjin University in 1999, and PhD degree in Electrical Engineering from University of Houston in 2003. After one year post-doctoral research, he was appointed as the Tenure-Track Assistant Professor in Engineering Technology Dept at Prairie View A&M University in 2004 Fall, where he received promotion as the Tenured Associate Professor from 2010 Fall. His research interests include control system, mechatronics, motor drive, power electronics, and real-time embedded system design. As the Principal Investigator for multiple grants sponsored by US Army Research Office, NSF, and industry (Emerson, 3M), his accumulated research funding has been 1 million US dollars.

In-band spectrum sensing protocols require that the secondary users periodically suspend their transmission periods and sense the channel in order to determine whether the primary user has emerged or not. Recently a new technique was introduced by the name of spectrum monitoring in which receiver statistics at the secondary user are used to detect the emergence of the primary user in the in-band channel. In this approach, referred to as spectrum monitoring, the secondary user does not need to suspend its transmission period in order to monitor the channel. This results in increased channel utilization for the secondary users and reduced detection delay for the primary users. In this talk I will present a new performance analysis of the spectrum monitoring technique in AWGN channel. The closed form formulas for channel utilization and detection delay using two Markov chain models will be presented. The limits of performance for a system using joint spectrum sensing/spectrum monitoring will be discussed and an optimization problem will be solved to maximize channel utilization with a constraint on detection delay.

Erfan Soltanmohammadi was born in Karaj, Iran, in 1984. He received the bachelor degree in electrical engineering from KNTU (Khaje Nasir University of Technology), Tehran Iran, in 2007 and the master degree from AUT (Amirkabir University of Technology), Tehran Iran, in 2010. He is a Graduate Research/Teaching Assistant and a Ph.D. candidate with the Department of Electrical and Computer Engineering, LSU. His research interests include cognitive radios, wireless sensor Networks.

We study a kinematic model that is suitable for control design for high level formation flight of UAVs. We design controllers that give robust global tracking for a wide class of reference trajectories in the sense of input-to-state stability while satisfying given amplitude and rate constraints on the inputs. We illustrate our work in simulations.

Aleksandra Gruszka received her MS in applied probability and mathematical statistics from Uniwersytet Wroclawski in Poland, and is a doctoral candidate in systems and controls in the LSU mathematics department. Her research lies at the interface of applied mathematics and control engineering, focusing on the design of controllers for nonlinear models that ensure good controller performance under uncertainty in the sense of input-to-state stability and other important criteria. She received a Best Presentation in the Session award at the 2011 American Control Conference, and was selected as one of the 12 US graduate students who will present their research in the Association for Women in Mathematics sessions at the 2012 Joint Mathematics Meetings. She has served as a referee for the Asian Journal of Control and for Automatica.