Background: The aim of this study was to investigate organ absorbed dose for the patients undergoing routine x-ray imaging procedures in hospitals under the control of Yasuj University of Medical Sciences, Iran, in year 2014 using experimental measurement and Monte Carlo calculations.Methods: Entrance surface dose for three common radiology examinations in five radiology centers was measured. The entrance surface dose was measured in 12 randomly selected patients (male and female) for each x-ray examination. Patients were not exposed to any additional radiation and the radiographs were used for diagnostic purposes.Findings: The entrance surface dose for the chest x-ray examinations were found to be in the range of 0.29 to 1.284 mGy. The ESD values for the skull examinations were in the range of 1.96 to 3.8 mGy. For both chest and skull examinations, females received the maximum imposed radiation dose.Conclusion: The results of the present study indicate a need for quality control (QC) and quality assurance (QA) programs to be undertaken to avert high cost and high patient doses. The recommendations to avoid unnecessary radiation exposure are also needed to decrease the patient’s absorbed dose.

This paper presents two different Monte Carlo algorithms for obtaining the solution of vector x in linear system x=Ax+f, where A is a given non singular matrix and f is a known vector with the same size as A. In this paper, we consider two individual transition probabilities for our Monte Carlo computations. Considering different statistical nature for generating the random walk to select the nonzero entries of the coefficient matrix A, are caused different accuracy and computational times for our employed algorithms.We first make Monte Carlo estimator for the elements of the solution vector x, then we determine the Monte Carlo estimation of the solution vector x based on its unbiased estimator. Finally, we present the computational results obtained by two different transition probabilities.

Time pricing is a tool for traffic management. Traffic management looks after increasing trip quality by reducing direct and indirect cost (wasting time, air pollution, noise pollution, accident cost and…). So, in this paper, at first, it is implemented financial derivatives for defining travel time derivatives. At the second stage, it is used Monte Carlo method for pricing traffic congestion.Since, derivative pricing fluctuated is an index for predicting deriver behavior in that time or at least their expectation about future traffic volume: low (high) price is likely to be light (heavy) congestion at that time and in the specific route. So, it is an intelligent method that indirectly dependent to drivers’ decision. In addition, in the usual method, the price is fixed, however, in the new method it is used market mechanism, so it is changed. Furthermore, in travel time derivative, two factors, traffic volume and diversion is implied in this forecasting. At the end, the introduced method is run for Karaj-Chalos route at 10 first of 31 July 2017. The derivative determined that the travel time will be 72 minutes. The result shows that, buying opportunity price is more than celling, so the travel time will be less than threshold time 72 minutes.

Testing the capability of a productive process on the basis of the exible fuzzy quality using Yongting's index is proposed in this paper by the Monte Carlo simulation. The theoretical approach and detailed steps of an algorithm are given to simulate the critical-value-based and also p-value-based approaches to statistical testing fuzzy quality. Also, the probability of type II error of the quality test simulated by Monte Carlo approach. Moreover, a real-world case study is provided to show the performance of the proposed algorithm for triangular and trapezoidal fuzzy qualities.