ELISA: An Estimated Load Information Scheduling Algorithm for Distributed Computing Systems

In this paper, we present a decentralized dynamic load scheduling/balancing algorithm called ELISA (Estimated Load Information Scheduling Algorithm) for general purpose distributed computing systems. ELISA uses estimated state information based upon periodic exchange of exact state information between neighbouring nodes to perform load scheduling. The primary objective of the algorithm is to cut down on the communication and load transfer overheads by minimizing the frequency of status exchange and by restricting the load transfer and status exchange within the buddy set of a processor. It is shown that the resulting algorithm performs almost as well as a perfect information algorithm and is superior to other load balancing schemes based on the random sharing and Ni-Hwang algorithms. A sensitivity analysis to study the effect of various design parameters on the effectiveness of load balancing is also carried out. Finally, the algorithm's performance is tested on large dimensional hypercubes in the presence of time-varying load arrival process and is shown to perform well in comparison to other algorithms. This makes ELISA a viable and implementable load balancing algorithm for use in general purpose distributed computing systems.

A.c. conductivity studies on the silver molybdo-arsenate glassy system

A new quaternary fast-ion conducting silver molybdo-arsenate [Agl-Ag2O-(MoO3 + As2O5)] (SMA) glassy system has been prepared using the melt-quenching technique for various dopant salt (Agl) concentrations by fixing the formers (MoO3 + As2O5) composition and the modifier (Ag2O) to formers (M/F) ratio. The prepared compounds were characterized by X-ray diffraction. The impedance measurements were made on different Agl compositions of the SMA glasses as a function of frequency (6.5 Hz-65 kHz) and temperature (303-343 K), using the Solatron frequency-response analyser(model 1250). The bulk conductivity and the appropriate physical model (equivalent circuit) of the SMA glass were obtained from the impedance analysis. The a.c. conductivity was calculated for different Agl compositions of SMA glasses at various temperatures and the obtained a.c. conductivity results were analysed using Jonscher's Universal Law. The conduction mechanism for the highest conducting SMA glassy compound has been explained using the diffusion path model.

A Quasi-Newton Adaptive Algorithm for Generalized Symmetric Eigenvalue Problem

In this paper, we first recast the generalized symmetric eigenvalue problem, where the underlying matrix pencil consists of symmetric positive definite matrices, into an unconstrained minimization problem by constructing an appropriate cost function, We then extend it to the case of multiple eigenvectors using an inflation technique, Based on this asymptotic formulation, we derive a quasi-Newton-based adaptive algorithm for estimating the required generalized eigenvectors in the data case. The resulting algorithm is modular and parallel, and it is globally convergent with probability one, We also analyze the effect of inexact inflation on the convergence of this algorithm and that of inexact knowledge of one of the matrices (in the pencil) on the resulting eigenstructure. Simulation results demonstrate that the performance of this algorithm is almost identical to that of the rank-one updating algorithm of Karasalo. Further, the performance of the proposed algorithm has been found to remain stable even over 1 million updates without suffering from any error accumulation problems.

Fabrication and evaluation of 1 Ah silver/metal hydride cells

Silver/metal hydride (Ag/MH) cells of about 1 Ah capacity have been fabricated and their discharge characteristics at different rates of discharge, faradaic efficiency, cycle life and a.c. impedance have been evaluated. These cells comprise metal-hydride electrodes prepared by employing similar to 60 mu m powder of an AB(2)-Laves phase alloy of nominal composition Zr0.5Ti0.5V0.6Cr0.2Ni1.2 with PTFE binder on a nickel-mesh substrate as the negative plates and commercial-grade silver electrodes as the positive plates. The cells are positive limited and exhibit two distinct voltage plateaus characteristic of two-step reduction of AgO to Ag during their low rates of discharge between C/20 and C/10. This feature is, however, absent when the cells are discharged at C/5 rate. On charging the cells to 100% of their capacity, the faradaic efficiency is found to be 100%. The impedance of the Ag/MH cell is essentially due to the impedance of the silver electrodes, since MH electrodes offer negligible impedance. The cells may be subjected to a large number of charge-discharge cycles with little deterioration.

Antibacterial Applications of Silver Nanoparticles Synthesized by Aqueous Extract of Azadirachta Indica (Neem) Leaves

Silver nanoparticles are known to have bactericidal effects. A new generation of dressings incorporating antimicrobial agents like silver nanoparticles is being formulated to reduce or prevent infections. The particles can be incorporated in materials and cloth rendering them sterile. Recently, it was found that aqueous silver ions can be reduced by aqueous extract of plant parts to generate extremely stable silver nanoparticles in water. Apart from being environmentally friendly process, use of Neem leaves extract might add synergistic antibacterial effect of Neem leaves to the biosynthesized nanoparticles. With this hypothesis the biosynthetic production of silver nanoparticles by aqueous extract of Neem leaves and its bactericidal effect in cotton cloth against E. Coli were studied in this work. Silver nanoparticles were synthesized by short term (1 day) and long term (21 days) interaction of Neem extract (20% w/v) and 0.01 M AgNO3 solution in 1:4 mixing ratio. The synthesized particles were characterized by UV visible spectroscopy, transmission electron microscopy, and incorporated into cotton disks by (i) centrifuging the disks with liquid broth containing nanoparticles, (ii) in-situ coating process during synthesis, and (iii) coating with dried and purified nanoparticles. The antibacterial property of the nanoparticles coated cotton disks was studied by disk diffusion method. The effect of consecutive washing of the coated disks with distilled water on antibacterial property was also investigated. This work demonstrates the possible use of biologically synthesized silver nanoparticles by its incorporation in cloths leading them to sterilization.

PocketMatch: A new algorithm to compare binding sites in protein structures

Recognizing similarities and deriving relationships among protein molecules is a fundamental requirement in present-day biology. Similarities can be present at various levels which can be detected through comparison of protein sequences or their structural folds. In some cases similarities obscure at these levels could be present merely in the substructures at their binding sites. Inferring functional similarities between protein molecules by comparing their binding sites is still largely exploratory and not as yet a routine protocol. One of the main reasons for this is the limitation in the choice of appropriate analytical tools that can compare binding sites with high sensitivity. To benefit from the enormous amount of structural data that is being rapidly accumulated, it is essential to have high throughput tools that enable large scale binding site comparison. Results: Here we present a new algorithm PocketMatch for comparison of binding sites in a frame invariant manner. Each binding site is represented by 90 lists of sorted distances capturing shape and chemical nature of the site. The sorted arrays are then aligned using an incremental alignment method and scored to obtain PMScores for pairs of sites. A comprehensive sensitivity analysis and an extensive validation of the algorithm have been carried out. A comparison with other site matching algorithms is also presented. Perturbation studies where the geometry of a given site was retained but the residue types were changed randomly, indicated that chance similarities were virtually non-existent. Our analysis also demonstrates that shape information alone is insufficient to discriminate between diverse binding sites, unless combined with chemical nature of amino acids. Conclusion: A new algorithm has been developed to compare binding sites in accurate, efficient and high-throughput manner. Though the representation used is conceptually simplistic, we demonstrate that along with the new alignment strategy used, it is sufficient to enable binding comparison with high sensitivity. Novel methodology has also been presented for validating the algorithm for accuracy and sensitivity with respect to geometry and chemical nature of the site. The method is also fast and takes about 1/250(th) second for one comparison on a single processor. A parallel version on BlueGene has also been implemented.

A new intelligent algorithm for online voltage stability assessment and monitoring

This paper presents a new approach for assessing power system voltage stability based on artificial feed forward neural network (FFNN). The approach uses real and reactive power, as well as voltage vectors for generators and load buses to train the neural net (NN). The input properties of the NN are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The performance of the trained NN is investigated on two systems under various voltage stability assessment conditions. Main advantage is that the proposed approach is fast, robust, accurate and can be used online for predicting the L-indices of all the power system buses simultaneously. The method can also be effectively used to determining local and global stability margin for further improvement measures.

A Jacobian-Based Algorithm for Planning Attitude Maneuvers Using Forward and Reverse Rotations

Algorithms for planning quasistatic attitude maneuvers based on the Jacobian of the forward kinematic mapping of fully-reversed (FR) sequences of rotations are proposed in this paper. An FR sequence of rotations is a series of finite rotations that consists of initial rotations about the axes of a body-fixed coordinate frame and subsequent rotations that undo these initial rotations. Unlike the Jacobian of conventional systems such as a robot manipulator, the Jacobian of the system manipulated through FR rotations is a null matrix at the identity, which leads to a total breakdown of the traditional Jacobian formulation. Therefore, the Jacobian algorithm is reformulated and implemented so as to synthesize an FR sequence for a desired rotational displacement. The Jacobian-based algorithm presented in this paper identifies particular six-rotation FR sequences that synthesize desired orientations. We developed the single-step and the multiple-step Jacobian methods to accomplish a given task using six-rotation FR sequences. The single-step Jacobian method identifies a specific FR sequence for a given desired orientation and the multiple-step Jacobian algorithm synthesizes physically feasible FR rotations on an optimal path. A comparison with existing algorithms verifies the fast convergence ability of the Jacobian-based algorithm. Unlike closed-form solutions to the inverse kinematics problem, the Jacobian-based algorithm determines the most efficient FR sequence that yields a desired rotational displacement through a simple and inexpensive numerical calculation. The procedure presented here is useful for those motion planning problems wherein the Jacobian is singular or null.

Energy-momentum conserving algorithm for nonlinear transient analysis within the framework of hybrid elements

This work deals with the formulation and implementation of an energy-momentum conserving algorithm for conducting the nonlinear transient analysis of structures, within the framework of stress-based hybrid elements. Hybrid elements, which are based on a two-field variational formulation, are much less susceptible to locking than conventional displacement-based elements within the static framework. We show that this advantage carries over to the transient case, so that not only are the solutions obtained more accurate, but they are obtained in fewer iterations. We demonstrate the efficacy of the algorithm on a wide range of problems such as ones involving dynamic buckling, complicated three-dimensional motions, et cetera.

A pattern adaptive thinning algorithm

A simple sequential thinning algorithm for peeling off pixels along contours is described. An adaptive algorithm obtained by incorporating shape adaptivity into this sequential process is also given. The distortions in the skeleton at the right-angle and acute-angle corners are minimized in the adaptive algorithm. The asymmetry of the skeleton, which is a characteristic of sequential algorithm, and is due to the presence of T-corners in some of the even-thickness pattern is eliminated. The performance (in terms of time requirements and shape preservation) is compared with that of a modern thinning algorithm.

An Algorithm to Decide Feasibility of Linear Integer Constraints Occurrng in Decision Tables

Abstract-To detect errors in decision tables one needs to decide whether a given set of constraints is feasible or not. This paper describes an algorithm to do so when the constraints are linear in variables that take only integer values. Decision tables with such constraints occur frequently in business data processing and in nonnumeric applications. The aim of the algorithm is to exploit. the abundance of very simple constraints that occur in typical decision table contexts. Essentially, the algorithm is a backtrack procedure where the the solution space is pruned by using the set of simple constrains. After some simplications, the simple constraints are captured in an acyclic directed graph with weighted edges. Further, only those partial vectors are considered from extension which can be extended to assignments that will at least satisfy the simple constraints. This is how pruning of the solution space is achieved. For every partial assignment considered, the graph representation of the simple constraints provides a lower bound for each variable which is not yet assigned a value. These lower bounds play a vital role in the algorithm and they are obtained in an efficient manner by updating older lower bounds. Our present algorithm also incorporates an idea by which it can be checked whether or not an (m - 2)-ary vector can be extended to a solution vector of m components, thereby backtracking is reduced by one component.

An Algorithm for Tracking a Maneuvering Target in Clutter

We consider the problem of tracking a maneuvering target in clutter. In such an environment, missed detections and false alarms make it impossible to decide, with certainty, the origin of received echoes. Processing radar returns in cluttered environments consists of three functions: 1) target detection and plot formation, 2) plot-to-track association, and 3) track updating. Two inadequacies of the present approaches are 1) Optimization of detection characteristics have not been considered and 2) features that can be used in the plot-to-track correlation process are restricted to a specific class. This paper presents a new approach to overcome these limitations. This approach facilitates tracking of a maneuvering target in clutter and improves tracking performance for weak targets.

Non-stationary signal analysis by least mean fourth (LMF) adaptive algorithm

A modified least mean fourth (LMF) adaptive algorithm applicable to non-stationary signals is presented. The performance of the proposed algorithm is studied by simulation for non-stationarities in bandwidth, centre frequency and gain of a stochastic signal. These non-stationarities are in the form of linear, sinusoidal and jump variations of the parameters. The proposed LMF adaptation is found to have better parameter tracking capability than the LMS adaptation for the same speed of convergence.

X-ray and ultraviolet photoelectron spectroscopy studies of the interaction of carbon monoxide with oxygen adsorbed on silver covered with potassium, caesium or barium

X-ray and He(II) ultraviolet photoelectron spectroscopy studies of the interaction of CO with oxygen on potassium-, caesium- and barium-covered Ag surfaces have shown the formation of carbonate at 300 K. While on a caesium-covered surface only carbonate formation takes place, on the potassium- and barium-covered surfaces molecularly chemisorbed CO is also formed. The variation of the surface concentrations of carbon and oxygen with temperature has been examined and a reaction sequence for the interaction of CO with adsorbed oxygen on potassium-, caesium- and barium-covered Ag surfaces is suggested.

An on-line algorithm for the location of cross point faults in programmable logic arrays

An on-line algorithm is developed for the location of single cross point faults in a PLA (FPLA). The main feature of the algorithm is the determination of a fault set corresponding to the response obtained for a failed test. For the apparently small number of faults in this set, all other tests are generated and a fault table is formed. Subsequently, an adaptive procedure is used to diagnose the fault. Functional equivalence test is carried out to determine the actual fault class if the adaptive testing results in a set of faults with identical tests. The large amount of computation time and storage required in the determination, a priori, of all the fault equivalence classes or in the construction of a fault dictionary are not needed here. A brief study of functional equivalence among the cross point faults is also made.