Sharif Digital Repository

Grid scheduling problems are dynamic as the jobs and resources in the system vary overtime. The Rulebased scheduling algorithms are a new trend in grid scheduling which are applicable in dynamic grid environments; The arriving jobs waiting for execution is ordered according to a certain rule and they are dispatched for processing according to that order. Grid scheduling algorithms usually involve more than one objective function. In particular, it is not enough to minimize the Maximum completion time (Makespan) objective function without taking into consideration the lateness of the jobs (Tardiness). In this paper two novel dispatching rules are proposed that aims to minimize the maximum... 

The rule based scheduling algorithms are a new trend in grid scheduling algorithms; the combination of rule based algorithms for resource selection with various dispatching rules for queuing of jobs can improve or deteriorate their performance. Thus, choosing a proper queuing strategy for each algorithm is a prominent issue in scheduling. In this paper, we introduce two new dispatching rules for resource selection and three new dispatching rules for queuing of jobs; we evaluate the performance of various combinations of these new rule based scheduling algorithms and queuing strategies. Also, we use some major combination of rule based scheduling algorithms with some important queuing... 

Disease association study is of great importance among various fields of study in bioinformatics. Computational methods happen to be advantageous specifically when experimental approaches fail to obtain accurate results. Haplotypes are believed to be the most responsible biological data for genetic diseases. In this paper, the problem of reconstructing haplotypes from error-containing SNP fragments is discussed For this purpose, two new methods have been proposed by a combination of k-means clustering and particle swarm optimization algorithm. The methods and their implementation results on real biological and simulation datasets are represented which shows that they outperform the methods... 

This paper presents a novel method to estimate the design parameters of a diaphragm thermoacoustic Stirling engine and investigate the stable limit cycle (sufficient condition) of the engine dynamic using the genetic algorithm and system energy changes. In this regard, first, the parametric equations are extracted by employing both the governing equations of the engine and energy standpoint. Next, Vc 0 (initial volume of compression space), Rq (pneumatic resistance), Vh (initial volume of expansion space), and hot gas temperature (Th) are taken as the design parameters in this study. Genetic algorithm and parametric equations were then utilized to estimate the chosen design parameters. Next,... 

Face to face meetings and physical presence are important concepts in student-professor relations. Many students require flexibility in arranging meetings or the possibility of ad-hoc meeting with their professors. However, adhoc meetings could be difficult to arrange due to busy schedule of professors. It is not unusual for students to attempt several times in a day to catch a professor, or wait an hour behind his door. To overcome this challenge, some professors have teaching assistants (TAs) or office assistant who manage their schedule or provide students with helpful information on how to reach them or handover their documents, projects, etc. Many other professors do not have any... 

Single Nucleotide Polymorphisms (SNPs), a single DNA base varying from one individual to another, are believed to be the most frequent form responsible for genetic differences. Genotype is the conflated information of a pair of haplotypes on homologous chromosomes. Although haplotypes have more information for disease associating than individual SNPs and genotype, it is substantially more difficult to determine haplotypes through experiments. Hence, computational methods which can reduce the cost of determining haplotypes become attractive alternatives. MEC, as a standard model for haplotype reconstruction, is fed by fragments as input to infer the best pair of haplotypes with minimum error... 

Recently, there has been great interest in Bio informatics among researches from various disciplines such as computer science, mathematics, statistics and artificial intelligence. Bioinformatics mainly deals with solving biological problems at molecular levels. One of the classic problems of bioinformatics which has gain a lot attention lately is Haplotyping, the goal of which is categorizing SNP-fragments into two clusters and deducing a haplotype for each. Since the problem is proved to be NP-hard, several computational and heuristic methods have addressed the problem seeking feasible answers. In this work it is shown that using PCM to solve Haplotyping problem in DALY dataset yields...