Background: Monte Carlo and experimental relative dose determination in a water phantom, due to a high dose rate (HDR) 192Ir source is presented for real energy spectrum and monochromatic at 356 keV. Materials and Methods: The dose distribution has been calculated around the 192Ir located in the center of 30 cm ×30 cm ×30 cm water phantom using MCNP4C code by Monte Carlo method. Relati...

Background: Iodine brachytherapy sources with low photon energies have been widely used in treating cancerous tumors. Dosimetric parameters of brachytherapy sources should be determined according to AAPM TG-43U1 recommendations before clinical use. Monte Carlo codes are reliable tools in calculation of these parameters for brachytherapy sources. Materials and Methods: Dosimetric param...

For the small-angle Bhabha-scattering process, we consider the error budget for the calculation of the LEP/SLC luminosity in the Monte Carlo event generator BHLUMI 4.04, from the standpoint of new calculations of exact results for the respective O(α 2) photonic corrections in the context of the Yennie-Frautchi-Suura exponentiation. We find that an overall precision tag for the currently availab...

Nested Monte-Carlo search is a general algorithm that gives good results in single player games. Genetic Programming evaluates and combines trees to discover expressions that maximize a given evaluation function. In this paper Nested Monte-Carlo Search is used to generate expressions that are evaluated in the same way as in Genetic Programming. Single player Nested Monte-Carlo Search is transfo...

Monte Carlo simulation methods are frequently used to determine light propagation in tissue and x-ray propagation as well as for solving other non-medically related problems. Such techniques are computationally slow, with the signal to noise ratio improving only as the square root of computation time. We present a method for the design of a Monte Carlo program that is capable of running on up t...

A novel method to improve the yield gradient estimation in parametric yield optimization is proposed. By introducing some deterministic information into the conventional Monte Carlo method and fully utilizing the samples, it is possible to obtain yield gradient estimation with significantly smaller variance. The additional computation is almost negligible. Examples are presented to indicate the...

We propose a semiparametrically efficient estimator for α-risk-minimizing portfolio weights. Based on the work of Bassett et al. 2004 , an α-risk-minimizing portfolio optimization is formulated as a linear quantile regression problem. The quantile regression method uses a pseudolikelihood based on an asymmetric Laplace reference density, and asymptotic properties such as consistency and asympto...