• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1722-1725
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• 1997

This paper presents image analysis method using a Markov random field(MRF) model. Particulary, image esgmentation is to partition the given image into regions. This scheme is first segmented into regions, and the obtained domain knowledge is used to obtain the improved segmented image by a Markov random field model. The method is a maximum a posteriori(MAP) estimation with the MRF model and its associated Gibbs distribution. MAP estimation method is applied to capture the natural image by TMS320C80(MVP) and to realize the segmented image by a MRF model.

• 한국안전학회지
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• 제32권3호
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• pp.54-59
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• 2017

This paper presents an efficient finite analysis model and a simulation-based reliability analysis method for stowage device system failure of a container crane with respect to lateral load. A quasi-static analysis model is introduced to simulate the nonlinear resistance characteristics and failure of tie-down and stowage pin, which are the main structural stowage devices of a crane. As a reliability analysis method, a subset simulation method is applied considering the uncertainties of later load and mechanical characteristic parameters of stowage devices. An efficient Markov chain Monte Carlo (MCMC) method is applied to sample random variables. Analysis result shows that the proposed model is able to estimate the probability of failure of crane system effectively which cannot be calculated practically by crude Monte Carlo simulation method.

• 한국정보통신학회논문지
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• 제12권12호
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• pp.2253-2258
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• 2008

산화물 반도체 감지막이 동작온도에 따라 감응특성을 가지는 마이크로 흐름센서를 설계하기 위해서 통계적 수법에 기초한 Markov 체인 MCM을 이용하여 기초방정식을 정식화하고 마이크로 소자의 열 전달특성을 해석하였다. 계산 결과를 통하여 기존 유한차분법이 가지는 계산 정밀도와 차이가 없음을 확인하였다. 본 논문에서 제안한 Markov 체인 MCM을 활용하면 다양한 마이크로 소자의 열전달 특성과 같은 물리적 특성을 해석하고 설계하는데 유용할 것으로 판단된다.

• 대한조선학회논문집
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• 제28권2호
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• pp.228-240
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• 1991

균열진전에 관한 많은 실험결과는 피로 균열진전 과정이 확률과정(stochastic process)임을 보여주고 있다. 따라서, 피로 균열진전에 관한 연구는 확률론적 기반에서 다루어져야 한다. 본 연구에서는 균열의 진전과정을 discrete Markov process로 가정하여, Bogdanoff가 제안한 Markov chain model(MCM)을 이용하여 구조물의 신뢰도를 평가할 수 있는 방법을 제시한다. 본 연구에서는 구조부재의 파괴형태로 누출, 소성붕괴 그리고 취성파괴를 취하였으며, 초기 균열크기의 변동성, 검사의 효과 등이 고려되었다. 또한, 불규칙 하중은 등가음력의 개념을 도입하여 처리하였다. 그리고, 구조물에의 계산례를 통하여 본 연구의 유용성을 보였다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2007년도 한국컴퓨터종합학술대회논문집 Vol.34 No.1 (C)
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• pp.263-266
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• 2007

본 논문은 베이지안 통계 추론에 대하여 논의한다. 논문은 베이지안 추론, Markov Chain과 Monte Carlo 적분, MCMC(Markov Chain Monte Carlo) 기법, Metropolis-Hastings 알고리즘, Gibbs 샘플링, Maximum Likelihood Estimation, EM 알고리즘, 상실된 데이터 보완 기법, BMA(Bayesian Model Averaging) 순서로 논의를 진행한다. 이러한 통계적 기법들은 대용량의 데이터를 처리하는 생물학, 의학, 생명 공학, 과학과 공학, 그리고 일반 데이터 조사와 처리 등에 사용되고 있으며, 최적의 추론 결과를 이끌어 내는데 중요한 방법을 제공하고 있다. 그리고 마지막으로 PC(Principal Component) 분석 기법에 대하여 논의한다. PC 분석 기법도 데이터 분석과 연구에 많이 활용된다.

• Journal of the Korean Statistical Society
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• 제25권3호
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• pp.445-456
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• 1996

In this paper, we derive unbiased estimators for the sensitivities of expected performance measures in a Markov renewal process. We restrict our derivation to the performance measures during a busy cycle and apply smoothed perturbation analysis method to find those esti-mators. The results show all the terms in the derived estimators can be obtained from a single sample path.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2006년도 학술대회 1부
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• pp.772-779
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• 2006

The new model proposed in this paper is the hidden Markov mesh model or the 2D HMM with the causality of top-down and left-right direction. With the addition of the causality constraint, two algorithms for the evaluation of a model and the maximum likelihood estimation of model parameters have been developed theoretically which are based on the forward-backward algorithm. It is a more natural extension of the 1D HMM than other 2D models. The proposed method will provide a useful way of modeling highly variable image patterns such as offline cursive characters.

• Journal of Electrical Engineering and information Science
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• 제2권6호
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• pp.7-13
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• 1997

Morphological Analysis of Korean has known to be a very complicated problem. Especially, the degree of part-of-speech(POS) ambiguity is much higher than English. Many researchers have tried to use a hidden Markov model(HMM) to solve the POS tagging problem and showed arround 95% correctness ratio. However, the lack of lexical information involves a hidden Markov model for POS tagging in lots of difficulties in improving the performance. To alleviate the burden, this paper proposes a method for combining multiword units, which are types of lexical information, into a hidden Markov model for POS tagging. This paper also proposes a method for extracting multiword units from POS tagged corpus. In this paper, a multiword unit is defined as a unit which consists of more than one word. We found that these multiword units are the major source of POS tagging errors. Our experiment shows that the error reduction rate of the proposed method is about 13%.

• International Journal of Naval Architecture and Ocean Engineering
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• 제6권4호
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• pp.775-787
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• 2014

Availabilities of subsea Blowout Preventers (BOP) in the Gulf of Mexico Outer Continental Shelf (GoM OCS) is investigated using a Markov method. An updated ${\beta}$ factor model by SINTEF is used for common-cause failures in multiple redundant systems. Coefficient values of failure rates for the Markov model are derived using the ${\beta}$ factor model of the PDS (reliability of computer-based safety systems, Norwegian acronym) method. The blind shear ram preventer system of the subsea BOP components considers a demand rate to reflect reality more. Markov models considering the demand rate for one or two components are introduced. Two data sets are compared at the GoM OCS. The results show that three or four pipe ram preventers give similar availabilities, but redundant blind shear ram preventers or annular preventers enhance the availability of the subsea BOP. Also control systems (PODs) and connectors are contributable components to improve the availability of the subsea BOPs based on sensitivity analysis.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 추계학술대회 논문집 전력기술부문
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• pp.230-233
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• 2005

This paper proposes power qualify assessment using Markov Chain applied to Ergodic theorem. The Ergodic theorem introduces the state of aperiodic, recurrent, and non-null. The proposed method using Markov Chain presents very well generated harmonic characteristics according to the traction's operation of electric railway system. In case of infinite iteration, the characteristic of Markov Chain that converges on limiting probability Is able to expected harmonic currents posterior transient state. TDD(Total Demand Distortion) is also analyzed in expected current of each harmonic. The TDD for power quality assesment is calculated using Markov Chain theory in the Inceon international airport IAT power system.