An improved load-balancing mechanism based on deadline failure recovery on GridSim

Grid computing has emerged a new field, distinguished from conventional distributed computing. It focuses on large-scale resource sharing, innovative applications and in some cases, high performance orientation. The Grid serves as a comprehensive and complete system for organizations by which the maximum utilization of resources is achieved. The load balancing is a process which involves the resource management and an effective load distribution among the resources. Therefore, it is considered to be very important in Grid systems. For a Grid, a dynamic, distributed load balancing scheme provides deadline control for tasks. Due to the condition of deadline failure, developing, deploying, and executing long running applications over the grid remains a challenge. So, deadline failure recovery is an essential factor for Grid computing. In this paper, we propose a dynamic distributed load-balancing technique called “Enhanced GridSim with Load balancing based on Deadline Failure Recovery” (EGDFR) for computational Grids with heterogeneous resources. The proposed algorithm EGDFR is an improved version of the existing EGDC in which we perform load balancing by providing a scheduling system which includes the mechanism of recovery from deadline failure of the Gridlets. Extensive simulation experiments are conducted to quantify the performance of the proposed load-balancing strategy on the GridSim platform. Experiments have shown that the proposed system can considerably improve Grid performance in terms of total execution time, percentage gain in execution time, average response time, resubmitted time and throughput. The proposed load-balancing technique gives 7 % better performance than EGDC in case of constant number of resources, whereas in case of constant number of Gridlets, it gives 11 % better performance than EGDC.     

Analyzing the efficacy of using digital ink devices in a learning environment

There has been increased interest on the impact of mobile devices such as PDAs and Tablet PCs in introducing new pedagogical approaches and active learning experiences. We propose an intelligent system that efficiently addresses the inherent subjectivity in student perception of note taking and information retrieval. We employ the idea of cross indexing the digital ink notes with matching electronic documents in the repository. Latent Semantic Indexing is used to perform document and page level indexing. Thus for each retrieved document, the user can go over to the relevant pages that match the query. Techniques to handle problems such as polysemy (multiple meanings of a word) in large databases, document folding and no match for query are discussed. We tested our system for its performance, usability and effectiveness in the learning process. The results from the exploratory studies reveal that the proposed system provides a highly enhanced student learning experience, thereby facilitating high test scores.

Fold-recognition and comparative modeling of human beta3GalT I, II, IV, V and VI and beta3GalNAcT I: prediction of residues conferring acceptor substrate specificity

beta3GalTs are type II transmembrane proteins that transfer galactose from UDP-Gal donor substrate to acceptor GlcNAc, GalNAc or Gal in beta1-->3-linkage. beta1-->3-linked galactose have been found to be a part of many glycans like glycosphingolipids, core tetrasaccharide of proteoglycans, type 1 chains. The 3-D structure of none of the beta3GalTs is known to date. In this study, the 3-D structures of human beta3GalT I, II, IV, V, VI and beta3GalNAcT I have been modeled using fold-recognition and comparative modeling methods. Residues that constitute the UDP-Gal binding site have been predicted. The models are able to qualitatively rationalize data from the site-directed mutagenesis experiments reported in the literature. Residues likely to be involved in conferring differential acceptor substrate specificity have been predicted by a combination of specificity determining positions prediction (SDPs) and subsequent mapping on the generated 3-D models.     

Beta-hairpins with native-like and non-native hydrogen bonding patterns could form during the refolding of staphylococcal nuclease

Refolding of staphylococcal nuclease has been studied recently by hydrogen-deuterium exchange and NMR spectroscopy. These studies infer that beta-hairpin formed by strand 2 and strand 3 connected by reverse turn forms early during the refolding of nuclease. Typically, hydrogen-deuterium exchange NMR techniques are usually carried out on a time scale of milliseconds whereas beta-hairpins are known to fold on a much shorter time scale. It follows that in the experiments, the hydrogen-deuterium exchange protection patterns could be arising from a significant population of fully formed hairpins. In order to demonstrate it is the fully formed hairpins which gives rise to the hydrogen-deuterium exchange protection patterns, we have considered molecular dynamics simulation of the peptide (21)DTVKLMYKGQPMTFR(35) from staphylococcal nuclease corresponding to the beta-hairpin region, using GROMOS96 force field under NVT conditions. Starting from unfolded conformational states, the peptide folds into hairpin conformations with native-like and non-native hydrogen bonding patterns. Subsequent to folding, equilibrium conditions prevail. The computed protection factors and atom depth values, at equilibrium, of the various amide protons agree qualitatively with experimental observations. A collection of molecules following the trajectories observed in the simulations can account for experimental observations. These simulations provide a molecular picture of the formed hairpins and their conformational features during the refolding experiments on nuclease, monitored by hydrogen-deuterium exchange.     

A robust algorithm for reduction of truncation artifact in chemical shift images

A new iterative technique to reduce the ringing artifacts in chemical shift images due to the truncation of the high spatial frequency is presented. In this approach the authors extrapolate the high spatial frequency data guided by the edge information obtained from a high resolution anatomic image of the region of interest. The fact that the edge information obtained from the anatomic image can be off by a few pixels (due to factors such as chemical shift artifact, error in edge detection or misregistration) is taken into account by assuming a confidence interval of several pixels around the anatomic edges. The algorithm is validated on simulated and in vivo data, and excellent results were obtained.     

Systems programming for data communications on minicomputers

This paper examines some of the special considerations which apply to the development of such software for minicomputers. These are treated under the following general categories:

• loading and throughput
• the external interfaces of the system software
• the internal structure of the system software
• developing the software

.     

Nanoclays for polymer nanocomposites, paints, inks, greases and cosmetics formulations, drug delivery vehicle and waste water treatment

An overview of nanoclays or organically modified layered silicates (organoclays) is presented with emphasis placed on the use of nanoclays as the reinforcement phase in polymer matrices for preparation of polymer/layered silicates nanocomposites, rheological modifier for paints, inks and greases, drug delivery vehicle for controlled release of therapeutic agents, and nanoclays for industrial waste water as well as potable water treatment to make further step into green environment. A little amount of nanoclay can alter the entire properties of polymers, paints, inks and greases to a great extent by dispersing 1nm thick layered silicate throughout the matrices. The flexibility of interlayer spacing of layered silicates accommodates therapeutic agents which can later on be released to damaged cell. Because the release of drugs in drug-intercalated layered materials is controllable, these new materials have a great potential as a delivery host in the pharmaceutical field. The problem of clean water can be solved by treating industrial and municipal waste water with organoclays in combination with other sorbents like activated carbon and alum. Organoclays have proven to be superior to any other water treatment technology in applications where the water to be treated contains substantial amounts of oil and grease or humic acid.     

Research and Improvement on structure stability and corrosion resistance of nickel-base superalloy INCONEL alloy 740

INCONEL alloy 740 is a newly developed Ni–Cr–Co–Mo–Nb–Ti–Al superalloy in the application to ultra-supercritical boilers with steam temperatures up to 700 °C. By means of scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), micro-chemical phase analyses, and corrosion-resisting test, this paper investigates the structure stability of the alloy at elevated temperature and concentrates on coal ash corrosion performance of the alloy under the simulated coal ash/flue gas condition. Experimental results show that the most important structure instabilities of the alloy during prolonged aging are γ′ coarsening, γ′ to η transformation and G phase formation at grain boundary. The performance of corrosion resistance of the alloy would meet the requirement of ultra-supercritical boiler tubes. The phase computation by means of Thermo-Calc has been adopted in chemical composition modification for structure stability improvement. Two suggested new modified alloys in adjustment of the Al and Ti contents and in control of Si level, and also in maintenance of Cr content of the alloy were designed and melted for experimental investigation. These two modified alloys exhibit more stable microstructure during 760 °C long time aging.     

Stable identification of nonlinear systems using neural networks: theory and experiments

This paper presents an approach for stable identification of multivariable nonlinear system dynamics using a multilayer feedforward neural network. Unlike most of the previous neural network identifiers, the proposed identifier is based on a nonlinear-in-parameters neural network (NLPNN). Therefore, it is applicable to systems with higher degrees of nonlinearities. Both parallel and series-parallel models are used with no a priori knowledge about the system dynamics. The method can be considered both as an online identifier that can be used as a basis for designing a neural network controller as well as an offline learning scheme for monitoring the system states. A novel approach is proposed for the weight updating mechanism based on the modification of the backpropagation (BP) algorithm. The stability of the overall system is shown using Lyapunov's direct method. To demonstrate the performance of the proposed algorithm, an experimental setup consisting of a three-link macro-micro manipulator (M/sup 3/) is considered. The proposed approach is applied to identify the dynamics of the experimental robot. Experimental and simulation results are given to show the effectiveness of the proposed learning scheme.     

Synchronized transform-limited operation of 10-GHz colliding pulse mode-locked laser

We report a 10-GHz colliding pulse mode-locked laser fabricated with integrated active-passive waveguides. The laser fabrication adopted a deep reactive ion etching and single-step metal-organic vapor phase epitaxy regrowth process for forming the buried heterostructure waveguide. Clean output pulses resulted from laterally tilting the active-passive interface and effectively suppressing residual back-reflections at the interface. Hybrid mode-locking resulted in a synchronized transform-limited sech/sup 2/optical waveform. Pulsewidth, chirp, timing jitter, and frequency-locking range were investigated through systematic device biasing condition optimization.