background: monte carlo (mc) modeling of a linear accelerator is a prerequisite for monte carlo dose calculations in external beam radiotherapy. in this study, a simple and efficient model was developed for elekta sl-25 linear accelerator using mcnp4c monte carlo code materials and methods: the head of elekta sl-25 linac was simulated for 6 and 18 mv photon beams using mcnp4c mc code. energy sp...

Introduction Radiotherapy with small fields is used widely in newly developed techniques. Additionally, dose calculation accuracy of treatment planning systems in small fields plays a crucial role in treatment outcome. In the present study, dose calculation accuracy of two commercial treatment planning systems was evaluated against Monte Carlo method. Materials and Methods Siemens Once or linea...

Monte Carlo (MC) technique is a numerical method that makes use of random numbers to solve mathematical problems for which an analytical solution is not known. The first article, “The Monte Carlo Method” by Metropolis and Ulam, has appeared for the first time in 1949 [9], even though well before that certain statistical problems were solved using random numbers. Since the simulation of random n...

Background: Various variance reduction techniques such as forced detection (FD) have been implemented in Monte Carlo (MC) simulation of nuclear medicine in an effort to decrease the simulation time while keeping accuracy. However most of these techniques still result in very long MC simulation times for being implemented into routine use. Materials and Methods: Convolution-based force...

This paper is intended to provide a numerical algorithm based on random sampling for solving the linear Volterra integral equations of the second kind. This method is a Monte Carlo (MC) method based on the simulation of a continuous Markov chain. To illustrate the usefulness of this technique we apply it to a test problem. Numerical results are performed in order to show the efficiency and accu...

background: various variance reduction techniques such as forced detection (fd) have been implemented in monte carlo (mc) simulation of nuclear medicine in an effort to decrease the simulation time while keeping accuracy. however most of these techniques still result in very long mc simulation times for being implemented into routine use. materials and methods: convolution-based forced detectio...

A Monte Carlo (MC) technique is employed to investigate stationary electron transport in lead telluride (PbTe). Results for electron mobility as a function of lattice temperature, free carrier concentration, and electric field are compared with experimental data and the few available other Monte Carlo simulation results.

Grand scale projects such as protein folding and drug design have put molecular simulation at the forefront of computational research. Even so, inherent limitations in both the models and the methods keep researchers from achieving their goals. Much effort has been expended to improve the traditional simulation methods known as molecular dynamics (MD) and Monte Carlo (MC). Duane and Kennedy[1] ...

Monte Carlo (MC) simulation is widely recognized as a gold standard in biophotonics for its high accuracy. Here we analyze several issues associated with tetrahedron-based optical Monte Carlo simulation in the context of TIM-OS, MMCM, MCML, and CUDAMCML in terms of accuracy and efficiency. Our results show that TIM-OS has significant better performance in the complex geometry cases and has comp...

one of known methods for measuring, forecasting and managing risk is value at risk, which recently has been used by financial institutions extensively. value at risk (var) is a method for recognizing and evaluating risk and uses standard statistical techniques that have daily using in other contexts. this research is seeking a career for managing investment risk in stock exchange and selection ...