• Journal of the Korean Society of Radiology
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• v.14 no.3
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• pp.253-259
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• 2020

Mammography has the advantage of being economical, simple and effective in detecting microcalcification, but breast is a highly sensitive organ and is accompanied by the risk of an over-exposure. While accurate dose assessments are important to prevent this, current breast dose assessments are limited to breast implant patients. This purpose of this study was to identify dose variations due to tube voltages by forming a mock-up with breast implants for an accurate dosimetric assessment on breast implant patients. As a result, doses from the presence of breast implants were smaller than those from the absence of the mammal. As the result of the change of the voltage to 26, 28, 30, and 32 kV, the imcreased tube voltage included larger dose regardless of the presence of Breast implant. Therefore, it is believed that diagnosis recommendations for breast implants will be possible if further studies on internal and external bioretical imaging and quality assessment are carried out as the basis for this study.

• Journal of the Korean Society of Radiology
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• v.11 no.3
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• pp.161-169
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• 2017

The cone beam computed tomography(CBCT) which can acquire 3-dimensions images is widely used for confirmation of patient position before radiation therapy. In this study, through the simulation using the Monte Carlo technique, we will analyze the exposure dose by cone beam computed tomography and present the standardized data. For the experiment, MCNPX(ver. 2.5.0) was used and the photon beam spectrum was analyzed after Cone beam was simulated. As a result of analyzing the photon beam spectrum, the average energy ranged from 25.7 to 37.6 keV at the tube voltage of 80 ~ 120 kVp and the characteristic X-ray energy was 9, 60, 68 and 70 keV. As a result of using the water phantom, the percentage depth dose was measured, and the maximum dose appeared on the surface and decreased with depth. The absorbed dose also decreased as the depth increased. The absorbed dose of the whole phantom was 9.7 ~ 18.7 mGy. This is a dose which accounts for 0.2% of about 10 Gy, which is generally used for radiation therapy per week, which is not expected to have a significant effect on the treatment effect. However, it should not be overlooked even if it is small compared with prescription dose.

• 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.

• 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.

• Journal of radiological science and technology
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• v.39 no.1
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• pp.89-97
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• 2016

As previous studies to proceed with the evaluation of the radioactive at linear accelerator's shielding concrete wall. And the shielding wall was evaluated the characteristics for the incoming neutron. As a result, the shielding wall is the average amount of incoming neutrons 10 MV 4.63E-7%, 15 MV 9.69E-6%, showed the occurrence of 20 MV 2.18E-5%. The proportion of thermal neutrons of which are found to be approximately 18-33%. The neutron generation rate can be seen as a slight numerical order. However, in consideration of the linear accelerator operating time we can not ignore the effects of neutrons. Accordingly radioactive problem of the radiation shield wall of the treatment room will be this should be considered.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.253-260
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• 2019

Radiation dose enhancement is a method of increasing the cross section of interaction, thus increasing the deposited dose. This can contribute to linear energy transfer, LET and relative biological effectiveness, RBE. Previous studies on dose enhancement have been mainly focused on X, ${\gamma}-rays$, but in this study, the dose enhancement was analyzed for proton using Monte Carlo simulation using MCNP6. Based on the mathematical modeling method, energy spectrum and relative intensity of spread out Bragg-peak were calculated, and evaluated dose enhancement factor and dose distribution of dose enhancement material, such as aurum and gadolinium. Dose enhancement factor of 1.085-1.120 folds in aurum, 1.047-1.091 folds in gadolinium was shown. In addition, it showed a decrease of 95% modulation range and practical range. This may lead to an uncertain dose in the tumor tissue as well as dose enhancement. Therefore, it is necessary to make appropriate corrections for spread out Bragg-peak and practical range from mass stopping power. It is expected that Monte Carlo simulation for dose enhancement will be used as basic data for in-vivo and in-vitro experiments.

• Communications for Statistical Applications and Methods
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• v.15 no.3
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• pp.451-464
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• 2008

Six sigma is the rating that signifies "best in clas", with only 3.4 defects per million units or operations. Higher sigma quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. The process capability indices and the sigma level $Z_{st}$ have been widely used in six sigma industries to assess process performance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. In this paper, we consider statistical inference for process capability indices $C_p$, $C_{pk}$ and $C_{pm}$. Also, we study better testing procedure on assessing sigma level $Z_{st}$ and capability index $C_{pm}$, for practitioners to use in determining whether a given process is capable. The proposed method is easy to use and the decision making is more reliable. Whether a process is clearly normal or nonnormal, our bootstrap testing procedure could be applied effectively without the complexity of calculation. A numerical result based on our proposed method is illustrated.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.459-471
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• 2010

Higher quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. Usually, the quality level is measured by process capability indices. The index is used to determine whether a production process is capable of producing items within a specified tolerance. The third generation index $C_{pmk}$ is more powerful than two useful indices $C_p$ and $C_{pk}$. which have been widely used in six sigma industries to assess process performance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. In this paper, we consider better testing procedure on assessing process capability index $C_{pmk}$ for practitioners to use in determining whether a given process is capable. It is easy to use the proposed method for assessing process capability index $C_{pmk}$. Whether a process is clearly normal or nonnormal, our bootstrap testing procedure could be applied effectively without the complexity of calculation. A numerical result based on our proposed method is illustrated.

• Convergence Security Journal
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• v.6 no.3
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• pp.117-126
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• 2006

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.25-46
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• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.