The nonperturbative aspects of string theory are explored for noncritical string in two distinct formulations, loop equations and matrix models. The effects corresponding to the D-brane in these formulations are especially investigated in detail. It is shown that matrix models can universally yield a definite value of the chemical potential for an instanton while loop equations cannot. This imp...

The availability of commodity high performance components for workstations and networks made it possible to build up large, PC based compute clusters at modest costs. These clusters seem to be a realistic alternative to proprietary, massively parallel systems with respect to the price/performance ratio. However, from the administration point of view those systems are still often solely a collec...

MOTIVATION Studying combinatorial patterns in cancer genomic datasets has recently emerged as a tool for identifying novel cancer driver networks. Approaches have been devised to quantify, for example, the tendency of a set of genes to be mutated in a 'mutually exclusive' manner. The significance of the proposed metrics is usually evaluated by computing P-values under appropriate null models. T...

The aim of this paper is to use the concept of the metafrontier function to study the determination of efficiency differentials and Technological Gap Ratio (TGR) on wheat production in Khorasan Razavi province. In this study, we used the metafrontier function and group frontier based on the concept of Stochastic Nonparametric Envelopment of Data analysis (StoNED). The data used in this stud...

Data mining is the problem of inducing models from data. Models have both a descriptive and a predictive aspect. Descriptive models can be inspected and used for knowledge discovery. Models consisting of decision rules – such as those produced by methods from Pawlak’s rough set theory – are in principle descriptive, but in practice the induced models are too large to be inspected. In this thesi...

Recent deep learning models are difficult to train using a large batch size, because commodity machines may not have enough memory accommodate both the model and data size. The size is one of hyper-parameters used in training model, it dependent on limited by target machine capacity can only fit into remaining after uploaded. Moreover, item also an important factor if each larger then that beco...