• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.1-13
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• 2005

Latent Class model has been considered recently by many researchers and practitioners as a tool for identifying heterogeneous segments or groups in a population, and grouping objects into the segments. In this paper we consider data on prostate cancer patients from Korean National Cancer Institute and propose a method for grouping prostate cancer patients by using latent class Poisson model. A Bayesian approach equipped with a Markov chain Monte Carlo method is used to overcome the limit of classical likelihood approaches. Advantages of the proposed Bayesian method are easy estimation of parameters with their standard errors, segmentation of objects into groups, and provision of uncertainty measures for the segmentation. In addition, we provide a method to determine an appropriate number of segments for the given data so that the method automatically chooses the number of segments and partitions objects into heterogeneous segments.

• 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.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.279-289
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• 2022

Since the frequency of heavy rainfall is increasing due to climate change, water levels in the river exceed past historical records. The rating-curve is to convert water level into flow dicscharge from the regression analysis of the water level and corresponding flow discharges. However, the rating-curve involves many uncertainties because of the limited data especially when observed water level exceed past historical water levels. In order to compensate for insufficient data and increase the accuracy of flow discharge data, this study estimates the flow discharge in the river computed mathematically using Monte Carlo simulation based on a 1D hydrodynamic numerical model. Based on the existing rating curve, a random combination of coefficients constituting the rating-curve creates a number of virtual rating curve. From the computed results of the hydrodynamic model, it is possible to estimate flow discharge which reproduces best fit to the observed water level. Based on the statistical evaluation of these samples, a method for mathematically estimating the water level and flow discharge of all cross sections is porposed. The proposed methodology is applied to the junction of Yochoen Stream in the Seomjin River. As a result, it is confirmed that the water level reproducibility was greatly improved. Also, the water level and flow discharge can be calculated mathematically when the proposed method is applied.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.12
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• pp.31-36
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• 2007

This paper presents a novel statistical characterization for accurate timing analysis in Partially-Depleted Silicon-On-Insulator (PD-SOI) circuits in BSIMSOI3.2 100nm technology. The proposed timing estimate algorithm is implemented in Matlab, Hspice, and C, and it is applied to ISCAS85 benchmarks. The results show that the error is within 5% compared with Monte Carlo simulation results.

• 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.

• Proceeding of EDISON Challenge
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• 2017.03a
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• pp.64-74
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• 2017

본 연구에서는 동역학 격자기반 대정준 Monte Carlo (Kinetic Lattice Grand Canonical Monte Carlo, KLGCMC) 모의실험 방법과 Poisson-Nernst-Planck (PNP) 계산 방법을 이용하여 이온채널의 전하분포, 채널 반지름, 그리고 이온의 농도와 이온의 크기가 이온전류와 이온전도도에 미치는 영향과, 이온 간 상관관계 (correlation)가 이온전류와 이온전도도에 미치는 영향을 조사하였다. 이로부터 이온 간 상호작용에 의해 이온 이동에 제약이 가해지는 이온 간 상관관계 효과는 채널 내 이온 수가 증가할수록 커지는 것을 알 수 있었다. 또한, 평균장 이론에 기반한 PNP 이론은 이온 간 상관관계 효과를 적절하게 기술하지 못하며, 이온 간 상관관계 효과가 중요해지는 이온 채널 관련 결맞음 공명 (coherence resonance) 등 특이 현상을 연구하기 위해서는 이온 간 상관관계를 기술할 수 있는 KLGCMC 모의실험 방법이 필요함을 알 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2015-2021
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• 2017

Recently, a lot of attention is fallen to IoT(Internet of Things) for hyper-connected society and the number of unlicensed wireless device has been increasing. Thus, this paper analyzed the impact of unlicensed wireless device on the basis of 802.11ah on licensed LTE user equipment in 900 MHz frequency band for efficient frequency use. As the interference analysis method, Minimum Coupling Loss (MCL) method and Monte Carlo (MC) method were used. In case of one interferer, minimum separation distance between interferer and victim was calculated as about 22 m through the MCL method under the assumption of the worst case. The maximum number of interferer to meet the interference probability of 5% below within a cell radius of the victim was computed as about 3000 by using MC method based on statistical technique. The analysis method and results in this paper are expected to be used for the coexistence between unlicensed wireless device and licensed wireless device.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.288-295
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• 2011

The paper proposes a localization method of an underwater robot using Monte Carlo Localization(MCL) approach. Localization is one of the fundamental basics for autonomous navigation of an underwater robot. The proposed method resolves the problem of accumulation of position error which is fatal to dead reckoning method. It deals with uncertainty of the robot motion and uncertainty of sensor data in probabilistic approach. Especially, it can model the nonlinear motion transition and non Gaussian probabilistic sensor characteristics. In the paper, motion model is described using Euler angles to utilize the MCL algorithm for position estimation of an underwater robot. Motion model and sensor model are implemented and the performance of the proposed method is verified through simulation.

• Korean Journal of Optics and Photonics
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• v.31 no.2
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• pp.59-70
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• 2020

We discuss a modified numerical model based on the Monte Carlo radiative transfer (MCRT) method, i.e., the MCRT matrix method, for the analysis of atmospheric scattering effects in three-dimensional flash LIDAR systems. Based on the MCRT method, the radiative transfer function for a LIDAR signal is constructed in a form of a matrix, which corresponds to the characteristic response. Exploiting the superposition and convolution of the characteristic response matrices under the paraxial approximation, an extended computer simulation model of an overall flash LIDAR system is developed. The MCRT matrix method substantially reduces the number of tracking signals, which may grow excessively in the case of conventional Monte Carlo methods. Consequently, it can readily yield fast acquisition of the signal response under various scattering conditions and LIDAR-system configurations. Using the computational model based on the MCRT matrix method, we carry out numerical simulations of a three-dimensional flash LIDAR system operating under different atmospheric conditions, varying the scattering coefficient in terms of visible distance. We numerically analyze various phenomena caused by scattering effects in this system, such as degradation of the signal-to-noise ratio, glitches, and spatiotemporal spread and time delay of the LIDAR signals. The MCRT matrix method is expected to be very effective in analyzing a variety of LIDAR systems, including flash LIDAR systems for autonomous driving.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.9
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• pp.634-640
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• 1999

Resonance radiation trapping has a great influence on the characteristics of vacuum ultraviolet(VUV) photon emissions in AC PDP cell. We calculate the spatial andspectral distributions of VUV photons, which are radiated by excited Xe in AC PDP cell by Monte Carlo method. Especially a dip in the spectrum at center frequency is discovered both in simulation and in experiment. We give a physical explanation of this phenomenon by the concept of frequency-dependent mean free path of VUV photons.