Design of multimedia surveillance systems

This article addresses the problem of how to select the optimal combination of sensors and how to determine their optimal placement in a surveillance region in order to meet the given performance requirements at a minimal cost for a multimedia surveillance system. We propose to solve this problem by obtaining a performance vector, with its elements representing the performances of subtasks, for a given input combination of sensors and their placement. Then we show that the optimal sensor selection problem can be converted into the form of Integer Linear Programming problem (ILP) by using a linear model for computing the optimal performance vector corresponding to a sensor combination. Optimal performance vector corresponding to a sensor combination refers to the performance vector corresponding to the optimal placement of a sensor combination. To demonstrate the utility of our technique, we design and build a surveillance system consisting of PTZ (Pan-Tilt-Zoom) cameras and active motion sensors for capturing faces. Finally, we show experimentally that optimal placement of sensors based on the design maximizes the system performance.

Triplet repeat polymorphism & fragile X syndrome in the Indian context

Mental retardation due to fragile X syndrome is one of the genetic disorders caused by tripler repeat expansion, CGG repeat involved in this disease is known to exhibit polymorphism even among normal individuals. Here we describe the development of suitable probes for detection of polymorphism in CGG repeat at FMR1 locus as well as the diagnosis of fragile X syndrome. Using these methods polymorphism at the FMR1 locus has been examined in 161 individuals. Ninety eight patients with unclassified mental retardation were examined, of whom 7 were found to have the expanded (CGG) allele at the FMR1 locus, The hybridization pattern for two patients has been presented as representative data.

New eight node serendipity quadrilateral plate bending element for thin and moderately thick plates using Integrated Force Method

A new 8-node serendipity quadrilateral plate bending element (MQP8) based on the Mindlin-Reissner theory for the analysis of thin and moderately thick plate bending problems using Integrated Force Method is presented in this paper. The performance of this new element (MQP8) is studied for accuracy and convergence by analyzing many standard benchmark plate bending problems. This new element MQP8 performs excellent in both thin and moderately thick plate bending situations. And also this element is free from spurious/zero energy modes and free from shear locking problem.

Pi-turns in proteins and peptides: Classification, conformation, occurrence, hydration and sequence.

The i + 5-->i hydrogen bonded turn conformation (pi-turn) with the fifth residue adopting alpha L conformation is frequently found at the C-terminus of helices in proteins and hence is speculated to be a "helix termination signal." An analysis of the occurrence of i + 5-->i hydrogen bonded turn conformation at any general position in proteins (not specifically at the helix C-terminus), using coordinates of 228 protein crystal structures determined by X-ray crystallography to better than 2.5 A resolution is reported in this paper. Of 486 detected pi-turn conformations, 367 have the (i + 4)th residue in alpha L conformation, generally occurring at the C-terminus of alpha-helices, consistent with previous observations. However, a significant number (111) of pi-turn conformations occur with (i + 4)th residue in alpha R conformation also, generally occurring in alpha-helices as distortions either at the terminii or at the middle, a novel finding. These two sets of pi-turn conformations are referred to by the names pi alpha L and pi alpha R-turns, respectively, depending upon whether the (i + 4)th residue adopts alpha L or alpha R conformations. Four pi-turns, named pi alpha L'-turns, were noticed to be mirror images of pi alpha L-turns, and four more pi-turns, which have the (i + 4)th residue in beta conformation and denoted as pi beta-turns, occur as a part of hairpin bend connecting twisted beta-strands. Consecutive pi-turns occur, but only with pi alpha R-turns. The preference for amino acid residues is different in pi alpha L and pi alpha R-turns. However, both show a preference for Pro after the C-termini. Hydrophilic residues are preferred at positions i + 1, i + 2, and i + 3 of pi alpha L-turns, whereas positions i and i + 5 prefer hydrophobic residues. Residue i + 4 in pi alpha L-turns is mainly Gly and less often Asn. Although pi alpha R-turns generally occur as distortions in helices, their amino acid preference is different from that of helices. Poor helix formers, such as His, Tyr, and Asn, also were found to be preferred for pi alpha R-turns, whereas good helix former Ala is not preferred. pi-Turns in peptides provide a picture of the pi-turn at atomic resolution. Only nine peptide-based pi-turns are reported so far, and all of them belong to pi alpha L-turn type with an achiral residue in position i + 4. The results are of importance for structure prediction, modeling, and de novo design of proteins.

Structural Investigation of Activated Lattice Oxygen in Ce1-xSnxO2 and Ce1-x-ySnxPdyO2-delta by EXAFS and DFT calculation

Substitution of Sn4+ ion in CeO2 creates activated oxygen in Ce0.8Sn0.2O2 leading to higher oxygen storage capacity compared to Ce0.8Zr0.2O2. With Pd ion substitution in Ce0.8Sn0.2O2,activation of oxygen is further enhanced as observed from the H-2/TPR study. Both EXAFS analysis and DFT calculation reveal that in the solid solution Ceexhibits 4 + 4 coordination, Sri exhibits 4 + 2 + 2 coordination and Pd has 4 + 3 coordination. While the oxygen in the First four coordination with short M-O bonds are strongly held in the lattice, the oxygens in the second and higher coordinations with long M-O bonds are weakly bound, and they are the activated oxygen ill the lattice. Bond valence analysis shows that oxygen with valencies as low its 1.65 are created by the Sn and Pd ion Substitution. Another interesting observation is that H-2/TPR experiment of Ce1-xSnxO2 shows a broad peak starting from 200 to 500 degrees C, while the same reduction is achieved in a single step at similar to 110 degrees C in presence Pd2+ on. Substitution of Pd2+ ion thus facilitates synergistic reduction of the catalyst at lower temperature. We have shown that simultaneous reduction of the Ce4+ and Sr4+ ions by Pd-0 is the synergistic interaction leading to high oxygen storage capacity at low temperature.

Temperature dependent structural properties of nanocrystalline SnS structures

This letter explores the structural behavior of nanocrystalline tin mono sulfide (SnS) structures with respect to temperature (100-600 K). These studies emphasize that the structural properties of SnS nanocrystalline structures depend on the surrounding temperature. The lattice parameters of SnS nanocrystals slightly varied like their microstructures with the increase of temperature. These changes strongly influence the optical properties of SnS nanostructures. On the other hand, the structures exhibited higher strain (similar to 0.44%) than that of microstructured (0.3%) and bulk (0.12%) counterparts. The observed results are discussed under the light of existing concepts and reported.

On-line Dynamic Security Assessment: Determination of Critical Transmission Lines

The main objective of on-line dynamic security assessment is to take preventive action if required or decide remedial action if a contingency actually occurs. Stability limits are obtained for different contingencies. The mode of instability is one of the outputs of dynamic security analysis. When a power system becomes unstable, it splits initially into two groups of generators, and there is a unique cutset in the transmission network known as critical cutset across which the angles become unbounded. The knowledge of critical cutset is additional information obtained from dynamic security assessment, which can be used for initiating preventive control actions, deciding emergency control actions, and adaptive out-of-step relaying. In this article, an analytical technique for the fast prediction of the critical cutset by system simulation for a short duration is presented. Case studies on the New England ten-generator system are presented. The article also suggests the applications of the identification of critical cutsets.

A self-adaptive migration model genetic algorithm for data mining applications

Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

An adaptive decomposition method for video

Scalable video coding (SVC) is an emerging standard built on the success of advanced video coding standard (H.264/AVC) by the Joint video team (JVT). Motion compensated temporal filtering (MCTF) and Closed loop hierarchical B pictures (CHBP) are two important coding methods proposed during initial stages of standardization. Either of the coding methods, MCTF/CHBP performs better depending upon noise content and characteristics of the sequence. This work identifies other characteristics of the sequences for which performance of MCTF is superior to that of CHBP and presents a method to adaptively select either of MCTF and CHBP coding methods at the GOP level. This method, referred as "Adaptive Decomposition" is shown to provide better R-D performance than of that by using MCTF or CRBP only. Further this method is extended to non-scalable coders.

Electrical Properties of Thermal Evaporated Cd1−xMnxS Nanocrystalline Films

Thin films of Cd1−xMnxS (0<=x<=0.5) were deposited on glass substrates by thermal evaporation. All the films were deposited at 300 K and annealed at 373, 473, and 573 K for 1 h in a high vacuum in the range 10−4 Pa. The as-deposited and the annealed films were characterized for composition, structure, and microstructure by using energy-dispersive X-ray, X-ray diffraction, scanning electron microscopy, and atomic force microscopy (AFM). The electrical properties were studied by Hall effect measurement. Electrical conductivity was studied in the temperature range 190–450 K. AFM studies showed that all the films were in nanocrystalline form with grain size varying in the range between 36 and 82 nm. Grain size studies showed a definite increase with annealing temperature. All the films exhibited wurtzite structure of the host material. The lattice parameter varied linearly with composition, following Vegard's law in the entire composition range. Grain size, electrical conductivity, Hall mobility, carrier concentration, and activation energy varied, exhibiting either maxima or minima at x=0.3.

Kernels for large margin time-series classification

In this paper we propose a novel family of kernels for multivariate time-series classification problems. Each time-series is approximated by a linear combination of piecewise polynomial functions in a Reproducing Kernel Hilbert Space by a novel kernel interpolation technique. Using the associated kernel function a large margin classification formulation is proposed which can discriminate between two classes. The formulation leads to kernels, between two multivariate time-series, which can be efficiently computed. The kernels have been successfully applied to writer independent handwritten character recognition.

Low power pipelined TCAM employing mismatch dependent power allocation technique

This paper presents design of a Low power 256x72 bit TCAM in 0.13um CMOS technology. In contrast to conventional Match line (ML) sensing scheme in which equal power is consumed irrespective of match or mismatch, the ML scheme employed in this design allocates less power to match decisions involving a large number of mismatched bits. Typically, the probability of mismatch is high so this scheme results in significant CAM power reduction. We propose to use this technique along with pipelining of search operation in which the MLs are broken into several segments. Since most words fail to match in first segment, the search operation for subsequent segments is discontinued, resulting in further reduction in power consumption. The above architecture provides 70% power reduction while performing search in 3ns.

Localization of handwritten text in documents using moment invariants and Delaunay triangulation

This paper describes an approach based on Zernike moments and Delaunay triangulation for localization of hand-written text in machine printed text documents. The Zernike moments of the image are first evaluated and we classify the text as hand-written using the nearest neighbor classifier. These features are independent of size, slant, orientation, translation and other variations in handwritten text. We then use Delaunay triangulation to reclassify the misclassified text regions. When imposing Delaunay triangulation on the centroid points of the connected components, we extract features based on the triangles and reclassify the text. We remove the noise components in the document as part of the preprocessing step so this method works well on noisy documents. The success rate of the method is found to be 86%. Also for specific hand-written elements such as signatures or similar text the accuracy is found to be even higher at 93%.

Line removal and restoration of handwritten strokes

In document images, we often find printed lines over-lapping with hand written elements especially in case of signatures. Typical examples of such images are bank cheques and payment slips. Although the detection and removal of the horizontal lines has been addressed, the restoration of the handwritten area after removal of lines, persists to be a problem of interest. lit this paper, we propose a method for line removal and restoration of the erased areas of the handwritten elements. Subjective evaluation of the results have been conducted to analyze the effectiveness of the proposed method. The results are promising with an accuracy of 86.33%. The entire Process takes less than half a second for completion on a 2.4 GHz 512 MB RAM Pentium IV PC for a document image.

Entropy based Skew correction of document images

The document images that are fed into an Optical Character Recognition system, might be skewed. This could be due to improper feeding of the document into the scanner or may be due to a faulty scanner. In this paper, we propose a skew detection and correction method for document images. We make use of the inherent randomness in the Horizontal Projection profiles of a text block image, as the skew of the image varies. The proposed algorithm has proved to be very robust and time efficient. The entire process takes less than a second on a 2.4 GHz Pentium IV PC.