Designing a scalable dynamic load -balancing algorithm for pipelined single program multiple data applications on a non-dedicated heterogeneous network of workstations

Dynamic load balancing strategies have been shown to be the most critical part of an efficient implementation of various applications on large distributed computing systems. The need for dynamic load balancing strategies increases when the underlying hardware is a non-dedicated heterogeneous network of workstations (HNOW). This research focuses on the single program multiple data (SPMD) programming model as it has been extensively used in parallel programming for its simplicity and scalability in terms of computational power and memory size.;This dissertation formally defines and addresses the problem of designing a scalable dynamic load-balancing algorithm for pipelined SPMD applications on non-dedicated HNOW. During this process, the HNOW parameters, SPMD application characteristics, and load-balancing performance parameters are identified.;The dissertation presents a taxonomy that categorizes general load balancing algorithms and a methodology that facilitates creating new algorithms that can harness the HNOW computing power and still preserve the scalability of the SPMD application.;The dissertation devises a new algorithm, DLAH (Dynamic Load-balancing Algorithm for HNOW). DLAH is based on a modified diffusion technique, which incorporates the HNOW parameters. Analytical performance bound for the worst-case scenario of the diffusion technique has been derived.;The dissertation develops and utilizes an HNOW simulation model to conduct extensive simulations. These simulations were used to validate DLAH and compare its performance to related dynamic algorithms. The simulations results show that DLAH algorithm is scalable and performs well for both homogeneous and heterogeneous networks. Detailed sensitivity analysis was conducted to study the effects of key parameters on performance

GMG Airlines in Bangladesh Decided to Fold Wings: Is It the Solution?

The prime objective of this case study is to examine the recent crisis going on in the GMG airlines in Bangladesh. The study analyzes air-business related information particularly for the case of the GMG airlines. It includes SWOT analysis and also provides the possible solution for tackling the crisis.  The findings of the study indicate that proper marketing strategies and identification of the voice of passengers through service quality dimensions can be possible to be revived in the market. Keywords: GMG Airlines, SWOT, Marketing strategies

The Potential of Establishing Technology Computer Aided Design Industry: Africa - Sudan As a Case-Study

Very-Large-Scale-Integration (VLSI) Integrated-Circuit (IC) designs have steadily grown in their capacity and complexity through the years. The need for technology simulations using technology computer-aided-design (TCAD) tools have become an essential part of design success. The TCAD simulations facilitate process optimization, highlight device performance tradeoffs, enable worst case analysis, and reveal device defects and weakness. Microelectronics higher education in African universities focuses mainly on the chip/circuit design instruction. Virtually little or no emphasis is applied to grow students TCAD simulation skills. This paper discusses the potential of African educational institutes of becoming the supplier of qualified TCAD simulation engineers for future African IC industry and/or worldwide VLSI job market. The African universities are encouraged to emphasize on establishing frameworks that would include TCAD simulation research and development into their curriculums and motivate students to venture the VLSI design and automation fields. This would enable African graduates to exploit the microelectronics job market worldwide and establish TCAD industries within Africa to industrialize African job market

Design Optimization of Composite Deployable Bridge Systems Using Hybrid Meta-heuristic Methods for Rapid Post-disaster Mobility

Recent decades have witnessed an increase in the transportation infrastructure damage caused by natural disasters such as earthquakes, high winds, floods, as well as man-made disasters. Such damages result in a disruption to the transportation infrastructure network; hence, limit the post-disaster relief operations. This led to the exigency of developing and using effective deployable bridge systems for rapid post-disaster mobility while minimizing the weight to capacity ratio. Recent researches for assessments of mobile bridging requirements concluded that current deployable metallic bridge systems are prone to their service life, unable to meet the increase in vehicle design loads, and any trials for the structures’ strengthening will sacrifice the ease of mobility. Therefore, this research focuses on developing a lightweight deployable bridge system using composite laminates for lightweight bridging in the aftermath of natural disaster. The research investigates the structural design optimization for composite laminate deployable bridge systems, as well as the design, development and testing of composite sandwich core sections that act as the compression bearing element in a deployable bridge treadway structure. The thesis is organized into two parts. The first part includes a new improved particle swarm meta-heuristic approach capable of effectively optimizing deployable bridge systems. The developed approach is extended to modify the technique for discrete design of composite laminates and maximum strength design of composite sandwich core sections. The second part focuses on developing, experimentally testing and numerically investigating the performance of different sandwich core configurations that will be used as the compression bearing element in a deployable fibre-reinforced polymer (FRP) bridge girder. The first part investigated different optimization algorithms used for structural optimization. The uncertainty in the effectiveness of the available methods to handle complex structural models emphasized the need to develop an enhanced version of Particle Swarm Optimizer (PSO) without performing multiple operations using different techniques. The new technique implements a better emulation for the attraction and repulsion behavior of the swarm. The new algorithm is called Controlled Diversity Particle Swarm Optimizer (CD-PSO). The algorithm improved the performance of the classical PSO in terms of solution stability, quality, convergence rate and computational time. The CD-PSO is then hybridized with the Response Surface Methodology (RSM) to redirect the swarm search for probing feasible solutions in hyperspace using only the design parameters of strong influence on the objective function. This is triggered when the algorithm fails to obtain good solutions using CD-PSO. The performance of CD-PSO is tested on benchmark structures and compared to others in the literature. Consequently, both techniques, CD-, and hybrid CD-PSO are examined for the minimum weight design of large-scale deployable bridge structure. Furthermore, a discrete version of the algorithm is created to handle the discrete nature of the composite laminate sandwich core design. The second part focuses on achieving an effective composite deployable bridge system, this is realized through maximizing shear strength, compression strength, and stiffness designs of light-weight composite sandwich cores of the treadway bridge’s compression deck. Different composite sandwich cores are investigated and their progressive failure is numerically evaluated. The performance of the sandwich cores is experimentally tested in terms of flatwise compressive strength, edgewise compressive strength and shear strength capacities. Further, the cores’ compression strength and shear strength capacities are numerically simulated and the results are validated with the experimental work. Based on the numerical and experimental tests findings, the sandwich cores plate properties are quantified for future implementation in optimized scaled deployable bridge treadway

Astrophysical parameters of ten poorly studied open star clusters

We present here the fundamental parameters of ten open star clusters, nominated from Kronberger et al. (2006) who presented some new discovered stellar groups on the basis of 2MASS photometry and DSS visual images. Star counts and photometric parameters (radius, membership, distances, color excess, age, luminosity function, mass function, total mass, and the dynamical relaxation time) have been determined for these ten clusters for the first time. In order to calibrate our procedures, the main parameters (distance, age, and color excesses) have been re-estimated for another five clusters, which are studied by Kronberger et al. (2006) as well.Comment: 10 pages, 5 figures, 2 tables; accepted in "Research in Astronomy and Astrophysics Journal

Serum calprotectin as a diagnostic marker of late onset sepsis in full-term neonates

Background: Calprotectin, a complex of two calcium-binding proteins that belong to the S100 protein family, is abundant in the cytosolic fraction of neutrophils. A high level of calprotectin reportedly exists in extracellular fluid during various inflammatory conditions, but its role in neonatal sepsis was investigated only in one study as a marker of sepsis in very low birth weight neonates. Objective: This study aimed to measure the serum calprotectin level by ELISA in full-term neonates with late onset neonatal sepsis, its correlations with other laboratory markers of sepsis as interleukin-6, C-reactive protein (CRP), total leucocytic count and platelet count and its relation to the outcome of cases. Methods: This study comprised 48 full-term neonates with gestational ages of 37 to 42 weeks with manifestations of late onset neonatal sepsis admitted to the neonatal intensive care unit, Minia University Hospital during the period from February, 2011 to December, 2011 and 40 healthy neonates, age and sex matched as a control group. Serum levels of calprotectin, IL6 and CRP were measured for all neonates recruited in this study. Results: Serum calprotectin levels were significantly higher in term neonates with late onset neonatal sepsis than controls (3.77±1.85 μg/ml and 0.70±0.33 μg/ml respectively, P-value = 0.000). Cases with positive blood cultures and poor outcomes had the highest levels of calprotectin (5.8±0.61 μg/ml and 6.1±0.42 μg/ml respectively). Significant positive correlations were found between calprotectin levels and IL6 (P-value =0.000, r=0.92), C-reactive protein (p=0.000,r=0.95) and total leucocytic count (P-value =0.000, r=0.72), and negative correlations were found between its level and platelet count (P-value =0.000, r=-0.87), gestational age (P-value =0.014, r=-0.35) and body weight (P-value=0.018, r=-0.34). No significant differences were observed between males and females as regards calprotectin levels (3.96±2.10 μg/ml vs 3.55±1.52 μg/ml, P-value=0.444). Conclusions: Serum calprotectin levels are significantly higher in full-term neonates with late onset neonatal sepsis. Its levels correlated well with other laboratory markers of sepsis and neonatal mortality. It is a sensitive diagnostic marker for late onset neonatal sepsis.Keywords: Calprotectin, IL6, Full-term, Late-onset sepsisEgypt J Pediatr Allergy Immunol 2012;10(1):19-2

Does obesity affect the plasma level of Plasminogen Activator Inhibitor-1? And does CO2 pneumoperitoneum affect it?

AbstractBackgroundThis prospective controlled study was designed to evaluate the effect of obesity on the plasma level of Plasminogen Activator Inhibitor-1 (PAI-1) and also to evaluate the effect of CO2 pneumoperitoneum on the plasma level of PAI-1 in patients underwent laparoscopic surgery.MethodsThe study included two groups; first group (non obese) included 30 patients with normal average BMI underwent laparoscopic cholecystectomy while the second group included 30 obese patients with BMI>30kg/m2 underwent laparoscopic band ligation or fundoplication surgery. Five ml of venous blood was collected from each patient in the non obese group once before induction of anesthesia while three venous blood samples (5ml) were collected from each patient in the obese group as follows: first sample was taken before induction of anesthesia to compare it with the non obese group, second sample was taken after 1h of CO2 insufflations (to know the effect of CO2 insufflations on PAI-1 level) and third sample was taken 1week after surgery (to know the remaining effect in the postoperative period).ResultsThe level of PAI-1 was significantly high (5.423±2.5ng/ml) in the obese patients compared to non obese patients (1.4±0.641ng/ml) (P value=0.001). The level of PAI-1 was significantly high after CO2 insufflations compared to baseline level (6.396±2.542ng/ml vs. 5.423±2.5ng/ml) in obese group (P value=0.001). And this level also showed significant increase up to 1week (6.01±2.492ng/ml vs. 5.423±2.5ng/ml) (P value=0.028) in the obese group.ConclusionThe PAI-1 level was higher in obese patients when compared to non obese patients. PAI-1 level was elevated after CO2 insufflations and this elevation did not reach base line level up to 1week after laparoscopic surgery

Multi objective genetic algorithm for training three term backpropagation network

Multi Objective Evolutionary Algorithms has been applied for learning problem in Artificial Neural Networks to improve the generalization of the training and testing unseen data.This paper proposes the simultaneous optimization method for training Three Term Back Propagation Network (TTBPN) learning using Multi Objective Genetic Algorithm.The Non-dominated Sorting Genetic Algorithm II is applied to optimize the TTBPN structure by simultaneously reducing the error and complexity in terms of number of hidden nodes of the network for better accuracy in classification problem.This methodology is applied in two kinds of multiclasses data set obtained from the University of California at Irvine repository.The results obtained for training and testing on the datasets illustrate less network error and better classification accuracy, besides having simple architecture for the TTBPN