COMPOSITIONAL ANALYSIS OF A VACUUM RESIDUE

ABSTRACT

A sample of vacuum residue (VR) was evaluated for its physical and chemical properties. The VR was separated into sixteen fractions according to molecular size distribution on preparative gel permeation chromatography (GPC) columns. Elemental analysis including heteroatoms (N, S) and metal (Ni, V) was carried out on fractions 1 through 9. Molecular weight distribution and number average molecular weight (M¯n) were obtained by analytical GPC for fractions 1 through 11. Forty percent of the VR contains high molecular weight materials (i.e., materials with molecular weights ranging from 1170 to 3920) and 64.3% total vanadium, 62.5% total nickel, 34.1% total sulphur, and 41.6% total nitrogen.     

Efficient 45nm ASIC Architecture for Full-Search Free Intra Prediction in Real-Time H.264/AVC Decoder

The standard H.264/AVC Intra frame encoding process has several data dependent and computational intensive coding methodologies that limit the overall encoding speed. It causes not only a high degree of computational complexity but also an unacceptable delay especially for the real-time video applications. Based on DCT properties and spatial activity analysis, low power hardware architecture for high throughput Full-Search Free (FSF) Intra mode selection and direction prediction algorithm is proposed. The FSF Intra prediction Algorithm significantly reduces the computational complexity and the processing run-time required for the H.264/AVC Intra frame prediction process. The ASIC implementation for the proposed architecture is carried out and synthesizing results are obtained. The heavily tested 45nm ASIC design is able to achieve an operating frequency of 140 MHz while limiting the overall power consumption to 9.01 mW, which nominates our proposed FSF Intra prediction architecture for interactive real-time H.264/AVC mobile video decoders.     

Adaptive energy aware cluster-based routing protocol for wireless sensor networks

Wireless sensor networks (WSNs) have grown excessively due to their various applications and low installation cost. In WSN, the main concern is to reduce energy consumption among nodes while maintaining timely and reliable data forwarding. However, most of the existing energy aware routing protocols incur unbalanced energy consumption, which results in inefficient load balancing and compromised network lifetime. Therefore, the main target of this research paper is to present adaptive energy aware cluster-based routing (AECR) protocol for improving energy conservation and data delivery performance. Our proposed AECR protocol differs from other energy efficient routing schemes in some aspects. Firstly, it generates balance sized clusters based on nodes distribution and avoids random clusters formation. Secondly, it optimizes both intra-cluster and inter-cluster routing paths for improving data delivery performance while balancing data traffic on constructed forwarding routes and at the end, in order to reduce the excessive energy consumption and improving load distribution, the role of Cluster Head (CH) is shifted dynamically among nodes by exploit of network conditions. Simulation results demonstrate that AECR protocol outperforms state of the art in terms of various performance metrics.

     

Degradation of Bi-Directional Single Fiber Transmission in WDM-PON Due to Beat Noise

This paper presents a general formulation for the impact of back-reflection in wavelength division multiplexing-passive optical networks (WDM-PON) access networks. The analysis is applied to various wavelength-independent optical network unit (ONU) configurations such as amplified spontaneous emission (ASE)-locked Fabry-Perot (FP) lasers, reflective semiconductor optical amplifiers or injection locked FP using the downstream signal. The power penalty due to beat noise and its dependence on relative intensity noise, transmitter linewidth, and receiver bandwidth is investigated. The optimal gain at the ONU that minimizes the effect of beat noise is also found. The results show that the power penalty decreases as the linewidth of the the optical line terminal (OLT) and ONU light source increase.     

A New Efficient Block-Matching Algorithm for Motion Estimation

This paper presents a new full-search block-matching algorithm: Multi-stage Interval-based Motion Estimation algorithm (MIME). The proposed algorithm is a block based motion estimation algorithm that utilizes successive elimination technique. We define two approximate functions, as the upper and lower boundaries of the interval that includes the Conventional distortion metric SAD. Each stage in the proposed algorithm; except for the last stage; incorporates low resolution pixels for the boundary functions calculations. The final stage is a full resolution block matching stage. MIME has a high probability of finding the optimal motion vector at any stage of the algorithm. The proposed algorithm reduces the computational complexity by successively eliminating non-candidate blocks from the search window at each stage. This computational reduction leads to enhanced performance in terms of low power consumption and fast motion vector estimation. A low power VLSI implementation of the algorithm is also presented in this paper. Simulation results on benchmark video sequences shows that MIME algorithm eliminates almost 88% of the candidate blocks after only two interval based stages. Hanan Ahmed Hosny Mahmoud obtained the B.Sc. of Computer Science from Faculty of Engineering, University of Alexandria in 1986. She obtained her M.Sc. in Computer Science from Faculty of Engineering, University of Alexandria in 1991. She obtained the M.Sc. in Computer Engineering from University of Louisiana at Lafayette in 1999 and the Ph.D. in Computer Engineering from University of Louisiana at Lafayette in 2001. Currently, she is working as an Assistant Professor in the Faculty of Engineering, University of Alexandria. Sumeer Goel received the B. Tech degree in electronics and communications engineering from Punjab Technical University, Punjab, India, in 2001. He received the M.S. degree in computer engineering from University of Louisiana at Lafayette, Lafayette, LA, in 2003 where he is continuing his education towards Ph.D. degree in computer engineering. His research interests are low-power and high noise tolerance VLSI circuit and architecture design for digital signal processing applications. Mohsen Shaaban received his B.S. degree in electrical engineering and communications from the University of Alexandria, Egypt, in 1998. In 2001, he joined the University of Louisiana at Lafayette (ULL) as a teaching and research assistant at the Center For Advanced Computer Studies (CACS), the VLSI Research Lab. He received his M.S. degree in the field computer engineering from ULL in 2003. Currently, he is pursing his Ph.D. degree in the same field. His research interests include Digital VLSI circuit design, CAD tools and Video processing applications. Magdy A. Bayoumi received the B.Sc. and M.Sc. degrees in electrical engineering from Cairo University, Cairo, Egypt, in 1973 and 1977, the M.Sc. degree in computer engineering from Washington University in St. Louis, MO, in 1981, and the Ph.D. degree in electrical engineering from the University of Windsor, Windsor, ON, Canada, in 1984. Currently, he is the Director of the Center for Advanced Computer Studies (CACS), Department Head of the Computer Science Department, the Edmiston Professor of Computer Engineering, and the Lamson Professor of Computer Science at The Center for Advanced Computer Studies, University of Louisiana at Lafayette, where he has been a faculty member since 1985. He has edited and co-edited three books in the area of VLSI Signal Processing. He was an Associate Editor of the Circuits and Devices Magazine and is currently an Associate Editor of Integration, the VLSI Journal, and the Journal of VLSI Signal Processing Systems. He is a Regional Editor for the VLSI Design Journal and on the Advisory Board of the Journal on Microelectronics Systems Integration. He has one patent pending. His research interests include VLSI design methods and architectures, low power circuits and systems, digital signal processing architectures, parallel algorithm design, computer arithmetic, image and video signal processing, neural networks, and wideband network architectures. Dr. Bayoumi received the University of Louisiana at Lafayette 1988 Researcher of the Year Award and the 1993 Distinguished Professor Award. He was an Associate Editor of the IEEE CIRCUITS AND DEVICES MAGAZINE, the IEEE TRANSACTIONS ON VLSI SYSTEMS, the IEEE TRANSACTIONS ON NEURAL NETWORKS, and the IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS—II: ANALOG AND DIGITAL SIGNAL PROCESSING. From 1991 to 1994, he served on the Distinguished Visitors Program for the IEEE Computer Society, and he is on the Distinguished Lecture Program of the Circuits and Systems Society. He was the Vice President for the technical activities of the IEEE Circuits and Systems Society. He was the Co-chairman of the Workshop on Computer Architecture for Machine Perception in 1993, and is a member of the Steering Committee of this workshop. He was the General Chairman of the 1994 MWSCAS and is a member of the Steering Committee of this symposium. He was the General Chairman for the 8th Great Lake Symposium on VLSI in 1998. He has been on the Technical Program Committee for ISCAS for several years and he was the Publication Chair for ISCAS'99. He was also the General Chairman of the 2000 Workshop on Signal Processing Design and Implementation. He was a founding member of the VLSI Systems and Applications Technical Committee and was its Chairman. He is currently the Chairman of the Technical Committee on Circuits and Systems for Communication and the Technical Committee on Signal Processing Design and Implementation. He is a member of the Neural Network and the Multimedia Technology Technical Committees. Currently, he is the faculty advisor for the IEEE Computer Student Chapter at the University of Louisiana at Lafayette.     

Deep and shallow binding: The assignment operation

Programming languages which use dynamic identification for free variables (i.e., non-local references) are generally implemented with a deep or shallow binding variable access strategy. In this paper, variable access through the binding environment is assumed to be desirable. Given this assumption, it is demonstrated that the act of assigning values to variables may yield unexpected results for some of the binding strategies when functional arguments and results are used. A number of variations of deep and shallow binding strategies are examined along with the modifications necessary to implement the assignment operation in the expected manner.     

Cover Image,Volume 100, Issue 11

The cover image is based on the Research Article The Israeli Palestinian wheat landraces collection: restoration and characterization of lost genetic diversity by Sivan Frankin et al., https://doi.org/10.1002/jsfa.9822 .