• Journal of Radiation Protection and Research
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• v.29 no.2
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• pp.105-115
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• 2004

The Monte Carlo simulation requires very much time to obtain a result of acceptable accuracy. Therefore we should know the optimum number of history not to sacrifice time as well as the accuracy. In this study, we have investigated the effects of statistical uncertainties of the photon dose calculation. BEAMnrc and DOSXYZnrc systems were used for the Monte Carlo dose calculation and the case of mediastinum was simulated. The several dose calculation result from various number of histories had been obtained and analyzed using the criteria of isodose curve comparison, dose volume histogram comparison(DVH) and root mean-square differences(RMSD). Statistical uncertainties were observed most evidently in isodose curve comparison and RMSD while DVHs were less sensitive. The acceptable uncertainties $(\bar{{\Delta}D})$ of the Monte Carlo photon dose calculation for the radiation therapy were estimated within total 9% error or 1% error for over than $D_{max}/2$ voxels or voxels at maximum dose.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.298-306
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• 2015

This study is the material of the additional filter(Cu, Ni, CaWO4, Gd+Ba) being used when the diagnosis X-ray was varied to evaluate the spatial dose distribution accordingly. And it suggest to find a suitable material. Experiments using MCNPX program based on the Monte Carlo simulation method was carried out by selecting the chest and abdomen taken. As a result, each material per dose, the average scatter dose is approximately 62%, 100 cm radius of the point of the simulated body surface exposure dose and 50 cm radius centered on the point average about 47%. It is determined that an Al material is currently available in accordance with the result to be replaced by Cu, Ni material is sufficient. With just the thickness due to the difference in the atomic number and density adjusted to be about one-tenth of the Al it will be suitable.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.1-7
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• 1994

Using a Monte-Carlo simulation technique we evaluate the empiricla distribution of a pseudo-chi-square statistic based on symmetrically Winsorized sum of squares when the population is normally distributed, and search for a chi-square distribution with appropriate degrees of freedom which can be referred to an approximate distribution for Winsorized chi-square.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.977-991
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• 2008

This study is about the k-nearest neighbor-based approach for the estimation of mutual information when the type of target variable is categorical and continuous. The results of Monte-Carlo simulation and experiments with real-world data show that k=1 is preferable. In practical application with real world data, our study shows that jittering and bootstrapping is needed.

• Journal of the Korean Society of Radiology
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• v.14 no.3
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• pp.303-311
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• 2020

Scattering-ray generated during plain radiography can cause secondary exposure to organs and tissues other than the target area. Currently, Shielding devices used to reduce radiation exposure are mostly used for radiation protection of workers, and radiation protection of patients is rarely performed. Therefore, this study intends to evaluate the organ dose by scattered-rays and the effectiveness 3D printing materials as a radiation shielding device during plain radiography through simulation. As a result, the absorbed dose for each organ at the time of examination showed a high effect due to the secondary scattering-ray as the distance from the source was close and the organ closer to the skin surface. The dose reduction effect due to the use of 3D printing shielding devices to protect this showed a higher shielding effect in the case of mixed printing materials compared to plastics.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.143-152
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• 1997

In this paper, we obtain maximum likelihood estimators for $P(X_{1}\;<\;X_{2})$ in the Marshall and Olkin's bivariate exponential model with bivariate censored data. The asymptotic normality of the estimator is derived. Also we propose approximate testing for $P(X_{1}\;<\;X_{2})$ based on the M.L.E. We compare the test powers under vsrious conditions through Monte Carlo simulation.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.163-175
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• 1998

The change of hazard rates at some unknown time point has been the interest of many statisticians. But it was restricted to the constant hazard rates which correspond to the exponential distribution. In this paper we generalize the change-point model in which any specific functional forms of hazard rates are net assumed. The assumed model includes various types of changes before and after the unknown time point. The Nelson estimator of cumulative hazard function is introduced. We estimate the change-point maximizing slope changes of Nelson estimator. Consistency and asymptotic distribution of bootstrap estimator are obtained using the martingale theory. Through a Monte Carlo study we check the performance of the proposed method. We also explain the proposed method using the Stanford Heart Transplant Data set.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.311-320
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• 2013

The purpose of this paper is to suggest the methods of forecasting the numbers of students. The generalized weighted proportion estimation models are suggested and used for forecasting the numbers of student until 2029. The results of the Monte Carlo simulation show that the suggested method is powerful for the forecasting. In conclusion, the numbers of the third grade high-school students will be less than the numbers of college admission quota from 2019.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.115-122
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• 2014

A test for randomness of the binary random sequence is proposed in this paper. The proposed test statistic is based on the mean length of runs distributed with truncated geometric distribution and asymptotically ${\chi}^2_2$-distributed when the size of the sequences is large. A small Monte Carlo simulation compared the size of the test with a significant level as well as evaluated the test power. We applied the proposed method to the sequence of yes or no numbers in Lotto 6/45 and concluded that the randomness of Lotto is retained.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.119-133
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• 1999

A Markov Chain Monte Carlo method is developed to compute the software reliability model. We consider computation problem for determining of posterior distibution in Bayseian inference. Metropolis algorithms along with Gibbs sampling are proposed to preform the Bayesian inference of the Mixed model with record value statistics. For model determiniation, we explored the prequential conditional predictive ordinate criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. To relax the monotonic intensity function assumptions. A numerical example with simulated data set is given.