b a c k g r o u n d & aim: the aim of the current study was to investigate the advantages of bayesian method in comparison to traditional methods to detect best antioxidant in freezing of human male gametes. methods  &  materials:   semen  samples  were  obtained  from  40  men  whose  sperm  had  normal criteria. a part of each sample was separated without antioxidant  as fresh and the remaini...

we propose to use a mathematical method based on stochastic comparisons of markov chains in order to derive performance indice bounds‎. ‎the main goal of this paper is to investigate various monotonicity properties of a single server retrial queue with first-come-first-served (fcfs) orbit and general retrial times using the stochastic ordering techniques‎.

We propose a new method for designing quantum search algorithms for finding a “marked” element in the state space of a classical Markov chain. The algorithm is based on a quantumwalk à la Szegedy [Sze04] that is defined in terms of the Markov chain. The main new idea is to apply quantum phase estimation to the quantum walk in order to implement an approximate reflection operator, which is used ...

We propose a new method for designing quantum search algorithms for finding a “marked” element in the state space of a classical Markov chain. The algorithm is based on a quantumwalk à la Szegedy [Sze04] that is defined in terms of the Markov chain. The main new idea is to apply quantum phase estimation to the quantum walk in order to implement an approximate reflection operator, which is used ...

Link analysis algorithms for Web search engines determine the importance and relevance of Web pages. Among the link analysis algorithms, PageRank is the state of the art ranking mechanism that is used in Google search engine today. The PageRank algorithm is modeled as the behavior of a randomized Web surfer; this model can be seen as Markov chain to predict the behavior of a system that travels...

A new Markov Chain Monte Carlo algorithm that allows parallel processing has been described in a previous paper (“Markov Chain Monte Carlo Calculations Allowing Parallel Processing Using a Variant of the Metropolis Algorithm”) that appeared in this journal in 2010. In this second follow-on paper, the problem of calculating the normalization integral of the distribution function is considered. I...

We show how some graph theoretical arguments may be used to reduce the complexity of the computation of the steady-state distribution of Markov chain. We consider the directed graph associated to a Markov chain derived from a Stochastic Automata Network (SAN). The structural properties of the automata are used to establish new various results. First, we establish the complexity of the resolutio...

Adaptive Markov Chain Monte Carlo (MCMC) algorithms attempt to ‘learn’ from the results of past iterations so the Markov chain can converge quicker. Unfortunately, adaptive MCMC algorithms are no longer Markovian, so their convergence is difficult to guarantee. In this paper, we develop new diagnostics to determine whether the adaption is still improving the convergence. We present an algorithm...

the problem we investigate deals with the optimal assignment of resources to the activities of a stochastic project network. we seek to minimize the expected cost of the project include sum of resource utilization costs and lateness costs. we assume that the work content required by the activities follows an exponential distribution. the decision variables of the model are the allocated resourc...