The use of Monte Carlo simulations in diagnostic medical imaging research is widespread due to its flexibility and ability to estimate quantities that are challenging to measure empirically. However, any new Monte Carlo simulation code needs to be validated before it can be used reliably. The type and degree of validation required depends on the goals of the research project, but, typically, su...

Introduction: The purpose of this study is to build homogeneous equivalent phantom chest in order to provide the necessary ability for checking the image quality in radiographic tests in four age groups of children in terms of the most recent age group categorization ICRP103. This phantom provides the features of weakness and discrepancies similar to body and can be consi...

Kinetic Monte Carlo simulation was applied to investigation of kinetics and mechanism of oxalic acid degradation by direct and heterogeneous catalytic ozonation. La-containing perovskites including LaFeO3, LaNiO3, LaCoO3 and LaMnO3 was studied as catalyst for oxalic acid ozonation. The reaction kinetic mechanisms of each abovementioned catalytic systems has been achieved. The rate constants val...

Recently, Monte-Carlo Tree Search (MCTS) has advanced the field of computer Go substantially. In this article we investigate the application of MCTS for the game Lines of Action (LOA). A new MCTS variant, called MCTS-Solver, has been designed to play narrow tactical lines better in sudden-death games such as LOA. The variant differs from the traditional MCTS in respect to backpropagation and se...

This paper investigates a class of algorithms for numerical integration of a function in d dimensions over a compact domain by Monte Carlo methods. We construct a histogram approximation to the function using a partition of the integration domain into a set of bins specified by some parameters. We then consider two adaptations; the first is to subtract the histogram approximation, whose integra...

Sequential Monte Carlo (SMC) samplers are an alternative to MCMC for Bayesian computation. However, their performance depends strongly on the Markov kernels used rejuvenate particles. We discuss how calibrate automatically (using current particles) Hamiltonian within SMC. To do so, we build upon adaptive SMC approach of Fearnhead and Taylor (2013), also suggest methods. illustrate advantages us...

introduction: in recent decades, several monte carlo codes have been introduced for research and medical applications. these methods provide both accurate and detailed calculation of particle transport from linear accelerators. the main drawback of monte carlo techniques is the extremely long computing time that is required in order to obtain a dose distribution with good statistical accuracy. ...

medical linear accelerators are one of the most widespread methods for cancer treatment. despite their advantages, unwanted photoneutrons are produced by high energy linacs. this photoneutrons are as undesired doses to patients and a significant problem for radiation protection of the staffs and patients. photoneutrons radiological risk must be evaluated because of their high let and range.in o...

this paper proposes a hybrid method to find cumulative distribution function (cdf) of completion time of gert-type networks (gtn) which have no loop and have only exclusive-or nodes. proposed method is cre-ated by combining an analytical transformation with gaussian quadrature formula. also the combined crude monte carlo simulation and combined conditional monte carlo simulation are developed a...