• Progress in Medical Physics
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• v.16 no.3
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• pp.138-147
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• 2005

The Monte Carlo method cannot have been used for routine treatment planning because of heavy time consumption for the acceptable accuracy. Since calculation time is proportional to particle histories, we can save time by decreasing the number of histories. However, a small number of histories can cause serious uncertainties. In this study, we proposed Monte Carlo dose computation time and uncertainty reduction method using specially designed filters and adaptive denoising process. Proposed algorithm was applied to 6 MV photon and 21 MeV electron dose calculations in homogeneous and heterogeneous phantoms. Filtering time was negligible comparing to Monte Carlo simulation time. The accuracy was improved dramatically in all situations and the simulation of 1 $\%$ to 10$\%$ number of histories of benchmark in photon and electron dose calculation showed the most beneficial result. The empirical reduction of necessary histories was about a factor of ten to fifty from the result.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.169-174
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• 2002

본 연구는 k개 지수분포 모수들의 기하평균에 대한 베이지안추정 방법을 제시하였다. 이를 위해 Tibshirani가 제안한 직교변환법으로 비정보적 사전확률분포를 도출하여 모수들의 결합사후확률분포를 유도해 내었으며, 이 분포 하에서 가중 몬테칼로 방법을 사용하여 기하평균을 추정하는 절차를 제안하였다. 모의실험과 실제자료의 예를 통해 제안된 베이지안 추정의 유효성 및 효용성을 보였으며, 본 연구에서 제안한 사전확률분포가 전통적인 포함확률을 기준으로 볼 때, Jeffrey의 사전확률분포 보다 더 유효한 추정을 함을 보였다.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.6
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• pp.25-31
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• 2004

In this paper, we introduce kinetic Monte Carlo (kMC) methods for simulating diffusion process in nano-scale device fabrication. At first, we review kMC theory and backgrounds and give a simple point defect diffusion process modeling in thermal annealing after ion (electron) implantation into Si crystalline substrate to help understand kinetic Monte Carlo methods. kMC is a kind of Monte Carlo but can simulate time evolution of diffusion process through Poisson probabilistic process. In kMC diffusion process, instead of. solving differential reaction-diffusion equations via conventional finite difference or element methods, it is based on a series of chemical reaction (between atoms and/or defects) or diffusion events according to event rates of all possible events. Every event has its own event rate and time evolution of semiconductor diffusion process is directly simulated. Those event rates can be derived either directly from molecular dynamics (MD) or first-principles (ab-initio) calculations, or from experimental data.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.45-53
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• 2000

본 논문에서는 모든 판정자(judge)들이 모든 객체(object)들에 대해 순위를 부여할 수 없는 경우에 얻어지는 불완전 순위자료에서 판정자들의 처리 효과에 대한 유의성을 검정하는데 관심이 있다. 이를 위해 불완전 순위자료를 완전자료로 바꾸는 알고리즘을 제안하고 알고리즘에 의해 얻어진 완전 순위자료에 Friedman 검정법을 적용하고자 한다. 제안된 검정법은 결측 객체에 순위를 부여하는데 있어서 완전순위를 갖는 판정자들의 정보를 이용함으로서 효율적이며 검정을 시행하는데 기존의 Friedman 통계량에 대한 분포표를 사용할 수 있어 간편하다. 그리고 몬테칼로 모의실험을 통하여 제안된 검정법과 기존의 평균 순위법, 최대/최소 Friedman 검정법과 검정력을 비교하였다.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.187-195
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• 2009

In a fault tree analysis, an uncertainty importance measure is often used to assess how much uncertainty of the top event probability (Q) is attributable to the uncertainty of a basic event probability ($q_i$), and thus, to identify those basic events whose uncertainties need to be reduced to effectively reduce the uncertainty of Q. For evaluating the measures suggested by many authors which assess a percentage change in the variance V of Q with respect to unit percentage change in the variance $\upsilon_i$ of $q_i$, V and ${\partial}V/{\partial}{\upsilon}_i$ need to be estimated analytically or by Monte Carlo simulation. However, it is very complicated to analytically compute V and ${\partial}V/{\partial}{\upsilon}_i$ for large-sized fault trees, and difficult to estimate them in a robust manner by Monte Carlo simulation. In this paper, we propose a method for experimentally evaluating the measure using a Taguchi orthogonal array. The proposed method is very computationally efficient compared to the method based on Monte Carlo simulation, and provides a stable uncertainty importance of each basic event.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.505-514
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• 2000

A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduced mixture failure model of Rayleigh and Erlang(2) pattern. This data augmentation approach facilitates specification of the transitional measure in the Markov Chain. Gibbs steps are proposed to perform the Bayesian inference of such models. For model determination, we explored sum of relative error criterion that selects the best model. A numerical example with simulated data set is given.

• Proceedings of the Korean Vacuum Society Conference
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• 1999.07a
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• pp.186-186
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• 1999

시뮬레이션 모델 및 AES, SIMS에 의한 깊이방향 분석의 유용성을 확인하기 위해 이체 충돌모델에 기초한 몬테칼로 시뮬레이션을 수행하였다. 이를 위해, 현 시뮬레이션에서는 충돌 캐스캐이드에 의한 interstitial 및 vacancy 원자의 발생과 각 원자 층이 일정한 원자농도를 유지하도록 interstitial에 의한 vacancy의 소멸을 고려하였다. 이 모델은 AES 깊이 방향 분석에서는 AsAs/GaAs 초격자에, SIMS 깊이 방향 분석에는 Ta2O5/SiO2 초격자에 적용되었고, 실험으로부터 얻어진 결과들을 잘 나타냈다. 0.5keV Ar+ 이온 스퍼터링에 의한 AES 깊이방향 분석의 경우 AlAs 층에서 Al의 선택 스퍼터링에 의해 AlAs 층에서 As(MVV-32eV)의 Auger 강도는 GaAs 층에서보다 약 1.2배 크게 나타났다. 이 시뮬레이션은 Ta2O5(18nm)/SiO2(0.5nm)에 대한 SIMS 깊이방향 분석에서 표면 쪽으로의 1-3nm 정도의 피크(SiO+) 이동 및 decay length도 또한 잘 설명할 수 있었다. 이때, 낮은 에너지에서 보다 더 깊은 이온빔 믹싱이 발생하기 때문에 높은 에너지에서 오히려 더 좋은 분해능을 얻을 수 있었다.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.557-563
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• 1997

Marshall-Olkin의 이변량 지수모형을 따르는 두개의 부품으로 이루어진 시스템에서, 두 부품의 수명들이 이변량 1종 중단된 자료로 관찰되는 경우, 모수에 대한 최우추정량을 구한다. 그리고 두 부품의 수명에 대한 근사적 독립성과 동일성 검정법을 제안하고 몬테칼로 모의실험을 통하여 검정력을 비교하였다.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.353-366
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• 1997

In this paper, we derive an approximate optimal Bayes group sequential design for a given loss function. We use the Monte-Carlo method to compare the ASN(average sample size) function and Bayes risk of approximate optimal Bayes group sequential design, Pocock design and O'Brien and Fleming design. Also introduced is the concept of Bayes efficiency and percentage loss of information due to grouping for the group sequential design and use it to measure the loss of information for different group sizes.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.423-433
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• 1998

In agricultural field experiments, the completely randomized block design is often used for the analysis of variety trials. An important assumption is that every experimental unit in each block has the some fertility. But, in most agricultural field experiments there often exists a systematic heterogeneity in fertility among the experimental units. To account for the heterogeneity, we propose to use the hierarchical generalized linear models. We compare our analysis of the data from Scottish Agricultural colleges list with that using Markov chain Monte Carlo method.