Load Balancing and Job Migration Algorithms for Autonomic Grid Environment

Resource management and load balancing are the main areas of concern in a distributed, heterogeneous and dynamic environment like Grid. Load balancing may further cause Job migration or in some cases resubmission of Job. In this paper a number of job migration algorithms have been surveyed and studied which have resulted because of the Load balancing problem. A comparative analysis of these algorithms has also been presented which summarizes the utility and applicability of different algorithms in different environment and circumstances

A Modeling, Optimization, and Analysis Framework for Designing Multi-Product Lignocellulosic Biorefineries

The objective of this research is to propose a methodology to develop modular decision analysis frameworks to design value chains for enterprises in the renewable fuels and chemicals sector. The decision support framework focuses on providing strategic decision support to startup and new product ventures. The tasks that are embedded in the framework include process and systems design, technology and product selection, forecasting cost and market variables, designing network capacities, and analysis of risks. The Decision support system (DSS) proposed is based on optimization modeling; systems design are carried out using integer programming with multiple sets of process and network configurations utilized as inputs. Uncertainty is incorporated using real options, which are utilized to design network processing capacity for the conversion of biomass resources. Risk analysis is carried out using Monte Carlo methods. The DSS framework is exemplified using a lignocellulosic biorefinery case study that is assumed to be located in Louisiana. The biorefinery utilizes energy crops as feedstocks and processes them into cellulosic biofuels and biobased chemicals. Optimization modeling is utilized to select an optimal network, a fractionation technology, a fermentation configuration, and optimal product recovery and purification unit operations. A decision tree is then used to design incremental capacity under uncertain market parameters. The valuation methodology proposed stresses flexibility in decision making in the face of market uncertainties as is the case with renewable fuels and chemicals. The value of flexibility, termed as “Option Value” is shown to significantly improve the net present value of the proposed biorefinery. Monte Carlo simulations are utilized to develop risk curves for alternate capacity design plans. Risk curves show a favorable risk reward ratio for the case of incremental capacity design with embedded decision options. The framework proposed here can be used by enterprises, government entities and decision makers in general to test, validate, and design technological superstructures and network processing capacities, conduct scenario analyses, and quantify the financial impacts and risks of their representative designs. We plan to further add functionality to the DSS framework and make available the tools developed to wide audience through an “open-source” software distribution model

Programmable optical waveform reshaping on a picosecond timescale

We experimentally demonstrate temporal reshaping of optical waveforms in the telecom wavelength band using the principle of quantum frequency conversion. The reshaped optical pulses do not undergo any wavelength translation. The interaction takes place in a nonlinear $\chi^{(2)}$ waveguide using an appropriately designed pump pulse programmed via an optical waveform generator. We show reshaping of a single-peak pulse into a double-peak pulse and vice versa. We also show that exponentially decaying pulses can be reshaped into near Gaussian shape, and vice versa, which is a useful functionality for quantum communications.Comment: Manuscript updated after comments from reviewers. Journal reference and DOI also adde

Failure Characterization of FRP by Scanning Electron Microscope Technique

Fiber-reinforced composite materials are used extensively in stiffness critical, weight sensitive structures such as those found in aerospace and motor racing. They are characterized by high inplane strength, stiffness and toughness and low density. The environmental effect on the FRP (fiber reinforced polymer) and the subsequent failure has lead to emphasize on the study of different fracture surfaces and their different modes of propagation. Delamination between layers is an important problem in applications of fiber reinforced composite laminates. This paper describes an experimental study to characterize the crack surface, crack origination and their propagation using scanning electron microscope (SEM). By observing carefully the fracture surface of the composite the factors affecting their respective failure and the type of environment they were subjected to could be determined. SEM micrographs of the fractured surfaces of carbon/epoxy and glass/epoxy composites revealed the failure modes (delamination sites, debonding, fiber pullout regions, crack propagation front, shear cups, hackles, striations, bubble bursting in the matrix)

ICT Based Agricultural Knowledge Transfer of Women Farmers: A Case of Gender Responsiveness from a Developing Country Perspective

Women are increasingly becoming an integral part of the rural economy. Feminization and empowerment in agriculture is taking place while outmigration of males in the rural Bangladesh is visible due to higher off farm income. The objective of this study is to determine the current state of the ICT-based agricultural knowledge transfer of female farmers in Bangladesh involved in agricultural operations. Data were collected through survey method using structured questionnaire from 140 female farmers involved in public ICT service centers of Bangladesh. The questionnaire was administrated face-to-face and collected data were analysed with SPSS version 23.0. The result from the data showed that the variables such as assets, inputs, land, education, extension and financial services, and technology affect farmers’ production and farm income. The gaps like gender parity and small farm holding were found in the study. The research suggests that effective agricultural information dissemination services through ICT tools in farming are essential. Special emphasis should be given to address gender disparity and resolve farm holding problems for ensuring women’s participation in agriculture

Correlation of maternal age and combined assessments on risk of chromosomal anomaly during prenatal screening

Background: Prenatal detection of genetic abnormalities is one of the biggest challenges of current fetal medicine. Prenatal screening for chromosomal abnormalities can be done using biochemical tests. The screening is a risk estimation test and not a diagnostic test. Methods: Statistical data treatment had been performed on a sample of 362 pregnant women for prenatal screening. This was a retrospective data analysis study undertaken at the National Reference Laboratory, Redcliffe Labs. Results: Nine (2.48%) women out of 362 were screen positive for chromosomopathy. The point biserial correlation between variables (Free β-hCG - Free Beta Human Chorionic Gonadotrophin, PAPP-A- pregnancy associated plasma protein-A and NT-(nuchal translucency) amongst patients with positive and negative screen test was statistically significant. There was a positive correlation between positive screen for chromosomopathy and hCG, MoM, NT MoM whereas a negative correlation between them and PAPP-A. This study indicates that higher values of hCG and lower values of PAPP-A MoM as seen in the positive screen patients is associated with a significant risk of chromosomopathy. A positive correlation between age and screen positive cases was seen. The McNemar’s test indicated a significant reduction in screen positive cases when biomarkers were added to screen for Trisomy 21 in women aged >35 years (n=86). 81 women eventually screened negative. Conclusions: The analyses stresses on the importance of using state-of-the-art, prenatal noninvasive screening software to help provide a predictive outcome, individualized for that pregnant woman.

Sigma metrics as quality indicators in guiding and tracking laboratory process improvement

Background: To demonstrate the utility of sigma metrics towards assessing the quality of processes, and optimization of statistical quality control rules in a high-volume clinical laboratory, in a two-phase quality improvement project. Methods: In the “pre” period, the sigma score was assessed across 25 routine high-volume assay parameters in our laboratory, comprising of 20 clinical chemistry and 5 immunoassay methods. Measures were taken to improve the analytical quality of low sigma score parameters within a 6-month period. Another sigma metric analysis was then performed in the “post” period to examine any measurable improvement. Results: The average sigma metric increased from 6.4σ to 9.2σ. Out of 25 analytes, 17 showed a significant improvement, defined as an increase in the sigma metric by greater than 1.0. Conclusions: The changes in sigma metric had a significant positive impact on the DPMO and reinforced the reliability of our test results. It showed that our quality control processes can be streamlined and simplified further, to optimize the frequency of internal quality control, while still maintaining the same level of error detection and analytical quality assurance. The analysis also provided additional benefits of achieving lesser errors, fewer sample reruns and troubleshooting, and improved turnaround time, for better clinician and patient satisfaction.

In-group and out-group behavior in Indian multinational corporations: An analysis of its implications on organizational performance

The purpose of this study is to investigate in-group and out-group dynamics within multinational corporations in India and their influence on organizational performance. The paper uses concurrent triangulation. Primary data were gathered via a purposive sample of 500 employees across various demographic backgrounds, ensuring diversity. Respondents participated in an online survey and a few in-depth interviews, administered in-person or online, capturing their experiences of group dynamics. Survey data were analyzed using R, SPSS, and SAS, while thematic analysis was applied to in-depth interview transcripts using NVivo software. The study also employed descriptive statistics, ANOVA, MANOVA for the survey and thematic analysis for interviews, revealing the depth and complexity of in-group favoritism. In-group members have reported significantly higher levels of communication, trust, cooperation, conflict management, and innovation, indicating the impact of group dynamics on organizational performance. The outcome of the multivariate analysis of variance (MANOVA) demonstrates a substantial impact of in-group/out-group categorization on the amalgamated dependent variables (evidenced by a Wilks’ Lambda value of 0.68, F (5,94) = 4.17, p < .001). This suggests a noteworthy influence of in-group/out-group affinities on overall team efficacy. The insights offer concrete strategies to enhance inclusivity amid diversity within multinational corporations, thereby mitigating group bias and promoting organizational performance. This study not only expands the understanding of group dynamics in Indian multinational corporations but also offers valuable guidance for managerial practices