• Journal of the Korean Society of Radiology
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• v.10 no.1
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• pp.39-44
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• 2016

This study is fulfilled to evaluate the exposure dose nearby a patient during the brachytherapy of the prostate cancer treatment and to minimize the radiation exposure by evaluating the exposure dose of the person near the relevant implanted patient, technicians and gardians. The experiment method is used on the study is MCNPX that is stood on the basis monte-carlo method and implant the source to MIRD-type phantom in $^{192}Ir$, $^{125}I$, and $^{103}Pd$ in virtual space. For dose evaluations according to distance, the radiation dose on the patient near the corresponding implanted patient is evaluated by each distance of 30, 50, 100, 200 cm to anterior from the implanted patient. As a result, $^{192}Ir$ showed a higher dose than $^{125}I$ and $^{103}Pd$ in every distance.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.57-69
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• 2011

Researchers are continuously trying to find innovative diagnostic tests and published articles are accumulating at an enormous rate in many medical fields. Meta-analysis enables previously published study results to be reviewed and summarized; therefore, an objective assessment of diagnostic tests can be done with a meta-analysis of sensitivities and specificities. Data obtained by applying two diagnostic tests to a well-defined group of diseased patients produce a pair of sensitivity and by applying the same medical tests to a group of non-diseased subjects produce a pair of specificity. The statistical tests in the meta-analysis need to consider the correlatedness of the results from two diagnostic tests applied to the same diseased and non-diseased subjects. The associations between two diagnostic test results are often found to be unequal for the diseased and non-diseased subjects. In this paper, multivariate meta-analytic methods are studied by taking into account the different associations between correlated variables. On the basis of Monte Carlo simulations, we evaluate the performance of the multivariate meta-analysis methods proposed in this paper.

• Journal of Aerospace System Engineering
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• v.13 no.5
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• pp.72-78
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• 2019

Inlet hammershock is the critical loads condition for designing the inlet duct structure of a fighter. The sudden flow reduction in engine compressor causes inlet hammershock with high pressure. The traditional method was used to combine extreme conditions (maximum speed, sea level altitude, and cold day) to analyze this compression wave inlet hammershock pressure. However, after the 90s there have been papers that presented the probabilistic approach for the inlet hammershock to achieve the appropriate design pressure. This study shows how to analyze the inlet hammershock pressure by making practical use of the Republic of Korea Air Force real flight usage data under probabilistic approach and then analyze approximately 30% decreased inlet hammershock pressure compared with the traditional valve.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.611-617
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• 2010

A complex system involves a large number of design variables, and its operation is non-linear. To explore the characteristics in its design space, a Kriging meta-model can be utilized; this model has replaced expensive computational analysis that was performed in traditional parametric design optimization. In this study, a Kriging meta-model with a computational orthogonal array for the design of experiments was developed to optimize the fatigue life of a turbine blade whose behavior under cyclic rotational loads is significantly non-linear. The results not only show that the maximum fatigue life is improved but also indicate that the accuracy of computational analysis is achieved. In addition, the robustness of the results obtained by six-sigma optimization can be verified by comparison with the results obtained by performing Monte Carlo simulations.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.57-68
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• 2017

Clustering algorithms attempt to find a partition of a finite set of objects in to a potentially predetermined number of nonempty subsets. Gibbs sampling of a normal mixture of linear mixed regressions with a Dirichlet prior distribution calculates posterior probabilities when the number of clusters was known. Our approach provides simultaneous partitioning and parameter estimation with the computation of classification probabilities. A Monte Carlo study of curve estimation results showed that the model was useful for function estimation. Examples are given to show how these models perform on real data.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.108-116
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• 2008

In this paper, we propose an algorithm that can estimate the distance using disparity based on stereo vision system, even though the obstacle is located in long ranges as well as short ranges. We use sub-pixel interpolation to minimize quantization errors which deteriorate the distance accuracy when calculating the distance with integer disparity, and also we use enhanced adaptive fuzzy strong tracking Kalman filter(EAFSTKF) to improve the distance accuracy and track the path optimally. The proposed method can solve the divergence problem caused by nonlinear dynamics such as various vehicle movements in the conventional Kalman filter(CKF), and also enhance the distance accuracy and reliability. Our simulation results show that the performance of our method improves by about 13.5% compared to other methods in point of root mean square error rate(RMSER).

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.758-765
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• 2016

This study analyzed for the radioactive shielding wall, which shields the medical linear accelerator. This allows to evaluate the level of waste with respect to the shield wall, which accounts for more than half of the cost of dismantling later linac facility. In addition, by analyzing the waste processing method according we discuss the way to obtain the benefits in terms of dismantling cost. Results of the simulate, the amount sufficient to screen the amount of neutron radiation occurring in the shielding wall linac was measured. And neutron activation analysis results were analyzed nuclides more than about 20. This analysis was in excess of that, $^{24}Na$, $^{45}Ca$, $^{59}Fe$ nucleus paper deregulation concentration. The value is reduced is greater the deeper the depth of the shielding wall concentration. Based on this, three specific areas (E, F, G) was estimated to be impossible to landfill or recycling. The rest area was estimated to be buried or recycled if possible more than a predetermined depth.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1355-1364
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• 2009

This work propose a robust test for location parameters in multivariate data based on MVE and MCD with the affine equivariance and the high-breakdown properties. We consider the hypothesis testing satisfying high efficiency and high test power simultaneously to bring in the one-step reweighting procedure upon high-breakdown estimators, which generally suffer from the low efficiency and, as a result, usually used only in the exploratory analysis. Monte Carlo study shows that the suggested method retains nominal significance levels and higher testing power without regard to various population distributions than a Hotelling's $T^2$ test. In an example, a data set containing known outliers does not make an influence toward our proposal, while it renders a Hotelling's $T^2$ useless.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.933-945
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• 2008

The genetic association test on age of onset trait aims to detect the putative gene by means of linear rank tests for a significant trend of onset distributions with genotypes. However, due to the selective sampling of recruiting subjects with ages less than a pre-specified limit, the genotype groups are subject to substantially different censored distributions and thus this is one reason for the low efficiencies in the linear rank tests. In testing the equality of two survival distributions, log-rank statistic is preferred to the Wilcoxon statistic, when censored observations are nonignorable. Therefore, for more then two groups, we propose a generalized log-rank test for trend as a genetic association test. Monte Carlo studies are conducted to investigate the performances of the test statistics examined in this paper.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.531-539
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• 2009

Logistic regression is widely used as a datamining technique for the customer relationship management. The maximum likelihood estimator has highly inflated variance when multicollinearity exists among the regressors, and it is not robust against outliers. Thus we propose the robust principal components logistic regression to deal with both multicollinearity and outlier problem. A procedure is suggested for the selection of principal components, which is based on the condition index. When a condition index is larger than the cutoff value obtained from the model constructed on the basis of the conjoint analysis, the corresponding principal component is removed from the logistic model. In addition, we employ an algorithm for the robust estimation, which strives to dampen the effect of outliers by applying the appropriate weights and factors to the leverage points and vertical outliers identified by the V-mask type criterion. The Monte Carlo simulation results indicate that the proposed procedure yields higher rate of correct classification than the existing method.