GAP-RBF based NR image quality measurement for JPEG coded images

In this paper, we present a growing and pruning radial basis function based no-reference (NR) image quality model for JPEG-coded images. The quality of the images are estimated without referring to their original images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity factors such as edge amplitude, edge length, background activity and background luminance. Image quality estimation involves computation of functional relationship between HVS features and subjective test scores. Here, the problem of quality estimation is transformed to a function approximation problem and solved using GAP-RBF network. GAP-RBF network uses sequential learning algorithm to approximate the functional relationship. The computational complexity and memory requirement are less in GAP-RBF algorithm compared to other batch learning algorithms. Also, the GAP-RBF algorithm finds a compact image quality model and does not require retraining when the new image samples are presented. Experimental results prove that the GAP-RBF image quality model does emulate the mean opinion score (MOS). The subjective test results of the proposed metric are compared with JPEG no-reference image quality index as well as full-reference structural similarity image quality index and it is observed to outperform both.

SPSA algorithms with measurement reuse

Four algorithms, all variants of Simultaneous Perturbation Stochastic Approximation (SPSA), are proposed. The original one-measurement SPSA uses an estimate of the gradient of objective function L containing an additional bias term not seen in two-measurement SPSA. As a result, the asymptotic covariance matrix of the iterate convergence process has a bias term. We propose a one-measurement algorithm that eliminates this bias, and has asymptotic convergence properties making for easier comparison with the two-measurement SPSA. The algorithm, under certain conditions, outperforms both forms of SPSA with the only overhead being the storage of a single measurement. We also propose a similar algorithm that uses perturbations obtained from normalized Hadamard matrices. The convergence w.p. 1 of both algorithms is established. We extend measurement reuse to design two second-order SPSA algorithms and sketch the convergence analysis. Finally, we present simulation results on an illustrative minimization problem.

Faster Algorithms for All-pairs Approximate Shortest Paths in Undirected Graphs

Let G - (V, E) be a weighted undirected graph having nonnegative edge weights. An estimate (delta) over cap (u, v) of the actual distance d( u, v) between u, v is an element of V is said to be of stretch t if and only if delta(u, v) <= (delta) over cap (u, v) <= t . delta(u, v). Computing all-pairs small stretch distances efficiently ( both in terms of time and space) is a well-studied problem in graph algorithms. We present a simple, novel, and generic scheme for all-pairs approximate shortest paths. Using this scheme and some new ideas and tools, we design faster algorithms for all-pairs t-stretch distances for a whole range of stretch t, and we also answer an open question posed by Thorup and Zwick in their seminal paper [J. ACM, 52 (2005), pp. 1-24].

Changes to near-surface region of PTFE during dry sliding against steel

PTFE specimens were slid against an EN24 disc. The unworn and worn surfaces as well as the wear debris were examined by X-ray diffraction. Sliding was found to introduce (i) shrinkage of the unit cell, (ii) enlargement of crystallites and (iii) residual stresses in the slid PTFE surface. No conformational changes in the 157 helix could be observed due to sliding. The wear debris was found to be 1 mgrm thick warped laminates.

Distributed nonlinear optimization algorithms for general network problems

There are a number of large networks which occur in many problems dealing with the flow of power, communication signals, water, gas, transportable goods, etc. Both design and planning of these networks involve optimization problems. The first part of this paper introduces the common characteristics of a nonlinear network (the network may be linear, the objective function may be non linear, or both may be nonlinear). The second part develops a mathematical model trying to put together some important constraints based on the abstraction for a general network. The third part deals with solution procedures; it converts the network to a matrix based system of equations, gives the characteristics of the matrix and suggests two solution procedures, one of them being a new one. The fourth part handles spatially distributed networks and evolves a number of decomposition techniques so that we can solve the problem with the help of a distributed computer system. Algorithms for parallel processors and spatially distributed systems have been described.There are a number of common features that pertain to networks. A network consists of a set of nodes and arcs. In addition at every node, there is a possibility of an input (like power, water, message, goods etc) or an output or none. Normally, the network equations describe the flows amoungst nodes through the arcs. These network equations couple variables associated with nodes. Invariably, variables pertaining to arcs are constants; the result required will be flows through the arcs. To solve the normal base problem, we are given input flows at nodes, output flows at nodes and certain physical constraints on other variables at nodes and we should find out the flows through the network (variables at nodes will be referred to as across variables).The optimization problem involves in selecting inputs at nodes so as to optimise an objective function; the objective may be a cost function based on the inputs to be minimised or a loss function or an efficiency function. The above mathematical model can be solved using Lagrange Multiplier technique since the equalities are strong compared to inequalities. The Lagrange multiplier technique divides the solution procedure into two stages per iteration. Stage one calculates the problem variables % and stage two the multipliers lambda. It is shown that the Jacobian matrix used in stage one (for solving a nonlinear system of necessary conditions) occurs in the stage two also.A second solution procedure has also been imbedded into the first one. This is called total residue approach. It changes the equality constraints so that we can get faster convergence of the iterations.Both solution procedures are found to coverge in 3 to 7 iterations for a sample network.The availability of distributed computer systems — both LAN and WAN — suggest the need for algorithms to solve the optimization problems. Two types of algorithms have been proposed — one based on the physics of the network and the other on the property of the Jacobian matrix. Three algorithms have been deviced, one of them for the local area case. These algorithms are called as regional distributed algorithm, hierarchical regional distributed algorithm (both using the physics properties of the network), and locally distributed algorithm (a multiprocessor based approach with a local area network configuration). The approach used was to define an algorithm that is faster and uses minimum communications. These algorithms are found to converge at the same rate as the non distributed (unitary) case.

DNA Clasping by Mycobacterial HU: The C-Terminal Region of HupB Mediates Increased Specificity of DNA Binding

Background: HU a small, basic, histone like protein is a major component of the bacterial nucleoid. E. coli has two subunits of HU coded by hupA and hupB genes whereas Mycobacterium tuberculosis (Mtb) has only one subunit of HU coded by ORF Rv2986c (hupB gene). One noticeable feature regarding Mtb HupB, based on sequence alignment of HU orthologs from different bacteria, was that HupB(Mtb) bears at its C-terminal end, a highly basic extension and this prompted an examination of its role in Mtb HupB function. Methodology/Principal Findings: With this objective two clones of Mtb HupB were generated; one expressing full length HupB protein (HupB(Mtb)) and another which expresses only the N terminal region (first 95 amino acid) of hupB (HupB(MtbN)). Gel retardation assays revealed that HupBMtbN is almost like E. coli HU (heat stable nucleoid protein) in terms of its DNA binding, with a binding constant (K-d) for linear dsDNA greater than 1000 nM, a value comparable to that obtained for the HU alpha alpha and HU alpha beta forms. However CTR (C-terminal Region) of HupB(Mtb) imparts greater specificity in DNA binding. HupB(Mtb) protein binds more strongly to supercoiled plasmid DNA than to linear DNA, also this binding is very stable as it provides DNase I protection even up to 5 minutes. Similar results were obtained when the abilities of both proteins to mediate protection against DNA strand cleavage by hydroxyl radicals generated by the Fenton's reaction, were compared. It was also observed that both the proteins have DNA binding preference for A: T rich DNA which may occur at the regulatory regions of ORFs and the oriC region of Mtb. Conclusions/Significance: These data thus point that HupB(Mtb) may participate in chromosome organization in-vivo, it may also play a passive, possibly an architectural role.

Algorithms for Colouring Random k-colourable Graphs

The k-colouring problem is to colour a given k-colourable graph with k colours. This problem is known to be NP-hard even for fixed k greater than or equal to 3. The best known polynomial time approximation algorithms require n(delta) (for a positive constant delta depending on k) colours to colour an arbitrary k-colourable n-vertex graph. The situation is entirely different if we look at the average performance of an algorithm rather than its worst-case performance. It is well known that a k-colourable graph drawn from certain classes of distributions can be ii-coloured almost surely in polynomial time. In this paper, we present further results in this direction. We consider k-colourable graphs drawn from the random model in which each allowed edge is chosen independently with probability p(n) after initially partitioning the vertex set into ii colour classes. We present polynomial time algorithms of two different types. The first type of algorithm always runs in polynomial time and succeeds almost surely. Algorithms of this type have been proposed before, but our algorithms have provably exponentially small failure probabilities. The second type of algorithm always succeeds and has polynomial running time on average. Such algorithms are more useful and more difficult to obtain than the first type of algorithms. Our algorithms work as long as p(n) greater than or equal to n(-1+is an element of) where is an element of is a constant greater than 1/4.

Optimal reservoir operation for irrigation of multiple crops using genetic algorithms

This paper presents a genetic algorithm (GA) model for obtaining an optimal operating policy and optimal crop water allocations from an irrigation reservoir. The objective is to maximize the sum of the relative yields from all crops in the irrigated area. The model takes into account reservoir inflow, rainfall on the irrigated area, intraseasonal competition for water among multiple crops, the soil moisture dynamics in each cropped area, the heterogeneous nature of soils. and crop response to the level of irrigation applied. The model is applied to the Malaprabha single-purpose irrigation reservoir in Karnataka State, India. The optimal operating policy obtained using the GA is similar to that obtained by linear programming. This model can be used for optimal utilization of the available water resources of any reservoir system to obtain maximum benefits.

Total risk rating and stability analysis of embankment dams in the Kachchh Region, Gujarat, India

A method for total risk analysis of embankment dams under earthquake conditions is discussed and applied to the selected embankment dams, i.e., Chang, Tapar, Rudramata, and Kaswati located in the Kachchh region of Gujarat, India, to obtain the seismic hazard rating of the dam site and the risk rating of the structures. Based on the results of the total risk analysis of the dams, coupled non-linear dynamic numerical analyses of the dam sections are performed using acceleration time history record of the Bhuj (India) earthquake as well as five other major earthquakes recorded worldwide. The objective of doing so is to perform the numerical analysis of the dams for the range of amplitude, frequency content and time duration of input motions. The deformations calculated from the numerical analyses are also compared with other approaches available in literature, viz, Makdisi and Seed (1978) approach, Jansen's approach (1990), Swaisgood's method (1995), Bureau's method (1997). Singh et al. approach (2007), and Saygili and Rathje approach (2008) and the results are utilized to foresee the stability of dams in future earthquake scenario. (C) 2010 Elsevier B.V. All rights reserved.

Integration-free algorithms for fixed end-point regulator problems

A new formulation is suggested for the fixed end-point regulator problem, which, in conjunction with the recently developed integration-free algorithms, provides an efficient means of obtaining numerical solutions to such problems.

Superconductivity in the 100–120 K region in oxides of the Tl-Ca-Ba-Cu-O system

Oxides with different cation ratios 2122, 2212, 2213 and 2223 in the Ti-Ca-Ba-Cu-O system exhibit onset of superconductivity in the 110–125 K range with zero-resistance in the 95–105 K range. Electron microscopic studies show dislocations, layered morphology and other interesting features. These oxides absorb electromagnetic radiation (9.11 GHz) in the superconducting phase.

Functional Identification of Regulatory Elements within the Promoter Region of Platelet-Derived Growth Factor 2

Human platelet-derived growth factor (PDGF) is composed of two polypeptide chains, PDGF-1 and PDGF-2,the human homolog of the v-sis oncogene. Deregulation of PDGF-2 expression can confer a growth advantage to cells possessing the cognate receptor and, thus, may contribute to the malignant phenotype. We investigated the regulation of PDGF-2 mRNA expression during megakaryocytic differentiation of K562 cells. Induction by 12-O-tetradecanoylphorbol-13-acetate (TPA) led to a greater than 200-fold increase in PDGF-2 transcript levels in these cells. Induction was dependent on protein synthesis and was not enhanced by cycloheximide exposure.In our initial investigation of the PDGF-2 promoter, a minimal promoter region, which included sequences extending only 42 base pairs upstream of the TATA signal, was found to be as efficient as 4 kilobase pairs upstream of the TATA signal in driving expression of a reporter gene in uninduced K562 cells. We also functionally identified different regulatory sequence elements of the PDGF-2 promoter in TPA-induced K562 cells. One region acted as a transcriptional silencer, while another region was necessary for maximal activity of the promoter in megakaryoblasts. This region was shown to bind nuclear factors and was the target for trans-activation in normal and tumor cells. In one tumor cell line, which expressed high PDGF-2 mRNA levels, the presence of the positive regulatory region resulted in a 30-fold increase in promoter activity. However, the ability of the minimal PDGF-2 promoter to drive reporter gene expression in uninduced K562 cells and normal fibroblasts, which contained no detectable PDGF-2 transcripts, implies the existence of other negative control mechanisms beyond the regulation of promoter activity.

Dielectric Properties of Epoxy-Al2O3 Nanocomposite System for Packaging Applications

In recent times, there has been an ever-growing need for polymer-based multifunctional materials for electronic packaging applications. In this direction, epoxy-Al2O3 nanocomposites at low filler loadings can provide an excellent material option, especially from the point of view of their dielectric properties. This paper reports the dielectric characteristics for such a system, results of which are observed to be interesting, unique, and advantageous as compared to traditionally used microcomposite systems. Nanocomposites are found to display lower values of permittivity/tan delta over a wide frequency range as compared to that of unfilled epoxy. This surprising observation has been attributed to the interaction between the epoxy chains and the nanoparticles, and in this paper this phenomenon is analyzed using a dual layer interface model reported for polymer nanocomposites. As for the other dielectric properties associated with the nanocomposites, the nano-filler loading seems to have a significant effect. The dc resistivity and ac dielectric strength of the nanocomposites were observed to be lower than that of the unfilled epoxy system at the investigated filler loadings, whereas the electrical discharge resistant properties showed a significant enhancement. Further analysis of the results obtained in this paper shows that the morphology of the interface region and its characteristics decide the observed interesting dielectric behaviors.

Efficient algorithms for domination and Hamilton circuit problems on permutation graphs

The domination and Hamilton circuit problems are of interest both in algorithm design and complexity theory. The domination problem has applications in facility location and the Hamilton circuit problem has applications in routing problems in communications and operations research.The problem of deciding if G has a dominating set of cardinality at most k, and the problem of determining if G has a Hamilton circuit are NP-Complete. Polynomial time algorithms are, however, available for a large number of restricted classes. A motivation for the study of these algorithms is that they not only give insight into the characterization of these classes but also require a variety of algorithmic techniques and data structures. So the search for efficient algorithms, for these problems in many classes still continues.A class of perfect graphs which is practically important and mathematically interesting is the class of permutation graphs. The domination problem is polynomial time solvable on permutation graphs. Algorithms that are already available are of time complexity O(n2) or more, and space complexity O(n2) on these graphs. The Hamilton circuit problem is open for this class.We present a simple O(n) time and O(n) space algorithm for the domination problem on permutation graphs. Unlike the existing algorithms, we use the concept of geometric representation of permutation graphs. Further, exploiting this geometric notion, we develop an O(n2) time and O(n) space algorithm for the Hamilton circuit problem.

Boundary-layer heights over the monsoon trough region during active and break phases

The thermodynamic structure and the heights of the boundary layer over the monsoon trough region of the Indian southwest monsoon are presented for the active and break phases of the monsoon. Results indicate significant and consistent variation in boundary-layer heights between the active and break phases.