Image modeling based on a 2-D stochastic subspace system identification algorithm

Fitting a causal dynamic model to an image is a fundamental problem in image processing, pattern recognition, and computer vision. In image restoration, for instance, the goal is to recover an estimate of the true image, preferably in the form of a parametric model, given an image that has been degraded by a combination of blur and additive white Gaussian noise. In texture analysis, on the other hand, a model of a particular texture image can serve as a tool for simulating texture patterns. Finally, in image enhancement one computes a model of the true image and the residuals between the image and the modeled image can be interpreted as the result of applying a de-noising filter. There are numerous other applications within the field of image processing that require a causal dynamic model. Such is the case in scene analysis, machined parts inspection, and biometric analysis, to name only a few. There are many types of causal dynamic models that have been proposed in the literature, among which the autoregressive moving average and state-space models (i.e., Kalman filter) are the most commonly used. In this paper we introduce a 2-D stochastic state-space system identification algorithm for fitting a quarter plane causal dynamic Roesser model to an image. The algorithm constructs a causal, recursive, and separable-in-denominator 2-D Kalman filter model. The algorithm is tested with three real images and the quality of the estimated images are assessed.     

Probabilistic linear models for multiresolution estimation in gray-level images

A multiresolution analysis of digital gray-level images is presented. A gray-level multi-scale framework is determined from two main assumptions: the gray scale is binary at the finest spatial resolution, and the gray levels of composed regions are obtained additively. In order to interrelate the gray-level histograms of the same image at different resolutions, probabilistic linear models are developed, which are then applied for estimation. Linear-optimization theory is used as a way of constructing such models. A general procedure for image processing is sketched, based on gray-level estimation. A versatile algorithm for nonlinear filtering is derived. Some examples of prospective applications are given.This work was partially supported by grant TIC91-646 from the DGYCIT of the Spanish Government.     

Rapid Generation of Biologically Relevant Hydrogels Containing Long‐Range Chemical Gradients

Many biological processes are regulated by gradients of bioactive chemicals. Thus, the generation of materials with embedded chemical gradients may be beneficial for understanding biological phenomena and generating tissue‐mimetic constructs. Here a simple and versatile method to rapidly generate materials containing centimeter‐long gradients of chemical properties in a microfluidic channel is described. The formation of a chemical gradient is initiated by a passive‐pump‐induced forward flow and further developed during an evaporation‐induced backward flow. The gradient is spatially controlled by the backward flow time and the hydrogel material containing the gradient is synthesized via photopolymerization. Gradients of a cell‐adhesion ligand, Arg‐Gly‐Asp‐Ser (RGDS), are incorporated in poly(ethylene glycol)‐diacrylate (PEG‐DA) hydrogels to test the response of endothelial cells. The cells attach and spread along the hydrogel material in a manner consistent with the RGDS‐gradient profile. A hydrogel containing a PEG‐DA concentration gradient and constant RGDS concentration is also shown. The morphology of cells cultured on such hydrogel changes from round in the lower PEG‐DA concentration regions to well‐spread in the higher PEG‐DA concentration regions. This approach is expected to be a valuable tool to investigate the cell–material interactions in a simple and high‐throughput manner and to design graded biomimetic materials for tissue engineering applications.     

Propagation Path Loss and Materials Insertion Loss in Indoor Environment at WiMAX Band of 3.3 to 3.6?GHz

The purpose of this study is to characterize the indoor channel for IEEE 802.16 (WiMAX) at 3.3?C3.6?GHz frequency. This work presents a channel model based on measurements conducted in commonly found scenarios in buildings. These scenarios include closed corridor, wide corridor and semi open corridor. Path loss equations are determined using log-distance path loss model and a Rayleigh multipath induced fading, Normal multipath induced fading or a combination of both. A numerical analysis of measurements in each scenario was conducted and the study determined equations that describe path loss for each scenario. Propagation loss is given for 300?MHz bandwidth. This work also represents the insertion loss of different materials and the obstruction loss due the existence of human beings between the transmitting antenna and the receiving one.     

IEEE-Compliant IDCT on FPGA-Augmented TriMedia

This paper presents a TriMedia processor extended with an IDCT reconfigurable design, and assesses the performance gain such an extension has when performing MPEG-2 decoding. We first propose the skeleton of an extension of the TriMedia architecture, which consists of a Field-Programmable Gate Array (FPGA)-based Reconfigurable Functional Unit (RFU), a Configuration Unit managing the reconfiguration of the RFU, and their associated instructions. Then, we address the computation of the 8 × 8 (2-D) IDCT on such extended TriMedia and propose a scheme to implement the 1-D IDCT operation on the RFU. When mapped on an ACEX EP1K100 FPGA from Altera, the proposed 1-D IDCT exhibits a latency of 16 and a recovery of 2 TriMedia@200 MHz cycles, and occupies 45% of the logic cells of the device. By configuring the 1-D IDCT on the RFU at application launch-time, the IEEE-compliant 2-D IDCT can be computed with the throughput of 1/32 IDCT/cycle. This figure translates to an improvement over the standard TriMedia of more than 40% in terms of computing time when 2-D IDCT is carried out in the framework of MPEG-2 decoding. Finally, the proposed reconfigurable IDCT is compared to a number of existing designs.Mihai Sima was born in Bucharest, Romania. He received the MS degree in Electrical Engineering from Politehnica University of Bucharest, and the Ph.D. degree in Electrical Engineering from Delft University of Technology, The Netherlands. He had been with the Microelectronics Company in Bucharest for 3 years, where he was involved in instrumentation electronics for integrated circuit testing. Subsequently, he joined the Telecommunications Department of Politehnica University of Bucharest, where he had been involved in digital signal processing and speech recognition for 6 years. More recently, he had been with the Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, where he worked on reconfigurable architectures for mediaprocessing domain. He is currently an assistant professor with the Department of Electrical and Computer Engineering, University of Victoria, B.C., Canada. His research interests include computer architecture, reconfigurable computing, embedded systems, digital signal processing, and speech recognition.Sorin D. Coofan was born in Mizil, Romania. He received the MS degree in Computer Science from the Politehnica University of Bucharest, Romania, and the Ph.D. degree in Electrical Engineering from Delft University of Technology, The Netherlands. He had worked with the Research & Development Institute for Electronic Components (ICCE) in Bucharest for a decade, being involved in structured design of digital systems, design rule checking of ICs layout, logic and mixed-mode simulation of electronic circuits, testability analysis, and image processing. He is currently an associate professor with the Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, The Netherlands. His research interests include computer arithmetic, parallel architectures, embedded systems, reconfigurable computing, nano-electronics, neural networks, computational geometry, and computer aided design.Jos T.J. van Eijndhoven was born in Roosendaal, The Netherlands. He studied Electrical Engineering at the Eindhoven University of Technology, The Netherlands, obtaining the M.Sc. and Ph.D. degrees in 1981 and 1984, respectively, for a work on piecewise linear circuit simulation. Then, he became a senior research member in the design automation group of the Eindhoven University of Technology. In 1986 he spent a sabbatical period at the IBM Thomas J. Watson Research Laboratory, Yorktown Heights, New York, for research on high level synthesis. In 1998 he joined Philips Research Laboratories in Eindhoven, The Netherlands, to work on the architectural design of programmable multimedia hardware and the associated mapping of media processing applications.Stamatis Vassiliadis was born in Manolates, Samos, Greece. He is a professor with the Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, The Netherlands. He has also served in the faculties of Cornell University, Ithaca, NY, and the State University of New York (S.U.N.Y.), Binghamton, NY.He hadworked for a decade with IBM in the AdvancedWorkstations and Systems laboratory in Austin TX, the Mid-Hudson Valley Laboratory in Poughkeepsie, NY, and the Glendale Laboratory in Endicott, NY. In IBM he was involved in a number of projects regarding computer design, organizations, and architectures and the leadership to advanced research projects. A number of his design and implementation proposals have been implemented in commerciallyavailable systems and processors including the IBM 9370 model 60 computer system, the IBM POWER II, the IBM AS/400 Models 400, 500, and 510, Server Models 40S and 50S, the IBM AS/400 Advanced 36, and the IBM S/390 G4 and G5 computer systems. For his work, he received numerous awards including 23 levels of Publication Achievement Awards, 15 levels of Invention Achievement Awards and an Outstanding Innovation Award for Engineering/Scientific Hardware Design in 1989. In 1990 he has been awarded the highest number of USA patents in IBM, six of his 70 USA patents being rated with the highest patent ranking in IBM.Kees A. Vissers graduated the Delft University of Technology, receiving his M.Sc. in 1980. He started directly with Philips Research Laboratories in Eindhoven where he was involved in highlevel simulation and high-level synthesis. He had been heading the research on hardware/software co-design and system level design for many years, and had a significant contribution to the TriMedia VLIW processor. From 1987 till 1988 he was a visiting researcher at Carnegie Mellon University, Pittsburgh, Pennsylvania, with the group of Don Thomas. He is currently a Research Fellow with University of California at Berkeley, Department of Electrical Engineering and Computer Sciences. His research interests include video processing, embedded media processing systems, and reconfigurable computing.     

A SAED and HREM study of structural defects in brownmillerite,LaBa(x)Sr(1-x)CuGaOy related oxides

The synthesis and microstructural characterization, by means of selected area electron diffraction (SAED) and high resolution electron microscopy (HREM), of the solid solution LaBa(x)Sr(1-x)CuGaO5 (0.1 < or = 5 x < or = 0.9) is reported. Although an average brownmillerite Ima2 structure is proposed for the whole compositional range, SAED and HREM clearly show that structural defects appear as barium content increases.     

Performance evaluation of nonsynchronized initial random access for mobile broadband systems

In this paper, a comparative analysis of the performance of the nonsynchronized initial random access channel in Mobile WiMAX and E-UTRA systems under different conditions (fast fading, multiuser interference) is carried out. The analysis is focused on the correlation properties of the code sequences used in each case. We evaluate their ability to provide low values for false alarm and erroneous detection probabilities (detecting a sequence that has not been transmitted) at the same time as guaranteeing low nondetection probabilities of the effectively transmitted sequences. Results show the promising performance of the E-UTRA scheme, even in high mobility scenarios, where the Doppler effect requires additional considerations to guarantee the correct system operation.     

Fabrication of CdSe‐Nanofibers with Potential for Biomedical Applications

The design and synthesis of nanostructured functional hybrid biomaterials are essential for the next generation of advanced diagnostics and the treatment of disease. A simple route to fabricate semiconductor nanofibers by self‐assembled, elastin‐like polymer (ELP)‐templated semiconductor nanoparticles is reported. Core–shell nanostructures of CdSe nanoparticles with a shell of ELPs are used as building blocks to fabricate functional one‐dimensional (1D) nanostructures. The CdSe particles are generated in situ within the ELP matrix at room temperature. The ELP controls the size and the size‐distribution of the CdSe nanoparticles in an aqueous medium and simultaneously directs the self‐assembly of core–shell building blocks into fibril architectures. It was found that the self‐assembly of core–shell building blocks into nanofibers is strongly dependent on the pH value of the medium. Results of cytotoxicity and antiproliferation of the CdSe‐ELP nanofibers demonstrate that the CdSe‐ELP does not exhibit any toxicity towards B14 cells. Moreover, these are found to be markedly capable of crossing the cell membrane of B14. In contrast, unmodified CdSe nanoparticles with ELPs cause a strong toxic response and reduction in the cell proliferation. This concept is valid for the fabrication of a variety of metallic and semiconductor 1D‐architectures. Therefore, it is believed that these could be used not only for biomedical purposes but for application in a wide range of advanced miniaturized devices.     

Computing the Detection Probability for Small Delay Defects of Nanometer ICs

Interconnect imperfections have become an important issue in modern nanometer technologies. Some of them cause Small Delay Defects (SDDs) which are difficult to detect. Those SDDs not detected during testing may pose a reliability problem. Furthermore, nanometer issues (e.g. process variations, spatial correlations) represent important challenges for traditional delay test methods. In this paper, a methodology to compute the Detection Probability (DP) of resistive open and bridge defects using a statistical timing framework that takes into account process variations and other nanometer issues is proposed. The DP gives the sensitivity of the circuit performance to a given resistance range of the defect. The efficiency issue when analyzing large circuits is alleviated using stratified sampling techniques to reduce the space of possible analyzed defect locations This methodology is applied to some ISCAS benchmark circuits. The obtained results show the feasibility of the proposed methodology. Measures can be taken for those circuits presenting non-acceptable DP in order to improve the test quality.