• International Journal of Reliability and Applications
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• 제9권2호
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• pp.167-182
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• 2008

The objective of this paper is to discuss the stochastic analysis and the statistical inference of a three-states semi-Markov reliability model. Using the maximum likelihood procedure, the parameters included in this model are estimated. Based on the assumption that the lifetime and repair time of the system are gener-alized Weibull random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is derived. Many important special cases are discussed. Finally, the obtained results are compared with those available in the literature.

• International Journal of Reliability and Applications
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• 제6권1호
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• pp.13-29
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• 2005

This paper deals with the stochastic analysis of a three-states semi-Markov reliability model. Using both the maximum likelihood and Bayes procedures, the parameters included in this model are estimated. Next, assuming that the lifetime and repair time are generalized exponential random variables, the reliability function of this system is obtained. Then, the distribution of the first passage time of this system is discussed. Finally, some of the obtained results are compared with those available in the literature.

• 한국경영과학회지
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• 제14권1호
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• pp.1-15
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• 1989

Multistate survival data with censoring often arise in biomedical experiments. In particular, a four-state space is used for cancer clinical trials. In a four-state space, each patient may either respond to a given treatment and then relapse or may progress without responding. In this four-state space, a model which combines the Markov and semi-Markov models is proposed. In this combined model, the generalized maximum likelihood estimators of the Markov and semi-Markov hazard functions are derived. These estimators are illustrated for the data collected in a study of treatments for advanced breast cancer.

• 한국물환경학회지
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• 제36권5호
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• pp.373-384
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• 2020

Hydrological models are based on a combination of parameters that describe the hydrological characteristics and processes within a watershed. For this reason, the model performance and accuracy are highly dependent on the parameters. However, model uncertainties caused by parameters with stochastic characteristics need to be considered. As a follow-up to the study conducted by Choi et al (2020), who developed a relatively simple semi-distributed hydrological model, we propose a tool to estimate the posterior distribution of model parameters using the Metropolis-Hastings algorithm, a type of Markov-Chain Monte Carlo technique, and analyze the uncertainty of model parameters and simulated stream flow. In addition, the uncertainty caused by the parameters of each version is investigated using the lumped and semi-distributed versions of the applied model to the Hapcheon Dam watershed. The results suggest that the uncertainty of the semi-distributed model parameters was relatively higher than that of the lumped model parameters because the spatial variability of input data such as geomorphological and hydrometeorological parameters was inherent to the posterior distribution of the semi-distributed model parameters. Meanwhile, no significant difference existed between the two models in terms of uncertainty of the simulation outputs. The statistical goodness of fit of the simulated stream flows against the observed stream flows showed satisfactory reliability in both the semi-distributed and the lumped models, but the seasonality of the stream flow was reproduced relatively better by the distributed model.

• International Journal of Reliability and Applications
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• 제12권1호
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• pp.1-14
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• 2011

This paper discusses the stochastic analysis and the statistical inference of a quadratic failure rate semi-Markov reliability model. Maximum likelihood procedure will be used to obtain the estimators of the parameters included in this reliability model. Based on the assumption that the lifetime and repair time of the system units are random variables with quadratic failure rate, the reliability function of this system is obtained. Also, the distribution of the first passage time of this system is derived. Many important special cases are discussed.

• International Journal of Reliability and Applications
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• 제11권1호
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• pp.1-16
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• 2010

In this paper we will discuss the stochastic analysis of a three state semi-Markov reliability model. Maximum likelihood procedure will be used to obtain the estimators of the parameters included in this reliability model. Based on the assumption that the lifetime and repair time of the system units are generalized linear failure rate random variables, the reliability function of this system is obtained. Also, the distribution of the first passage time of this system will be derived. Some important special cases are discussed.

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권12호
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• pp.1034-1037
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• 2009

수화 적출이란 연속된 영상에서 수화의 시작과 끝점을 찾고, 이를 사전에 정의된 수화 단어로 인식하는 방법을 말한다. 수화는 매우 다양한 손의 움직임과 모양으로 구성되어 있고, 그 변화가 다양하여 적출에 많은 어려움이 있다. 특히, 다양한 길이의 궤적 정보로 구성된 수화는 길이가 긴 수화에 대해 짧은 길이를 갖는 수화가 인식에 필요한 정보를 추출하기 어려운 문제점 있다. 본 논문에서는 다양한 길이를 갖는 입력 데이터의 특징을 반영할 수 있는 Semi-Markov Conditional Random Field에 기반하여 다양한 수화의 길이에 강인하게 수화를 적출하는 방법을 제안한다. 성능 평가를 위해 미국 수화와 한국 수화 데이터베이스를 사용하여 연속된 수화 영상에서의 수화 적출 성능을 평가하였고, 실험 결과 기존의 Hidden Markov Model과 Conditional Random Field보다 뛰어난 성능을 보였다.

• 한국경영과학회지
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• 제19권3호
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• pp.93-109
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• 1994

Even though sojourn time distributions are essential information in analyzing queueing networks, there are few methods to compute them accurately in non-product form queueing networks. In this study, we model the location process of a typical customer as a GMPH semi-Markov chain and develop computationally useful formula for the transition function and the first-passage time distribution in the GMPH semi-Markov chain. We use the formula to develop an effcient method for approximating sojourn time distributions in the non-product form queueing networks under quite general situation. We demonstrate its validity through numerical examples.

• 한국통신학회논문지
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• 제34권9B호
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• pp.867-875
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• 2009

무선 신체망 (WBAN: Wireless Body Area Network)은 생체 신호를 검출하고 전송하기 때문에 인간의 생명과 직결되어 있다 그러므로 무선 신체망은 다른 망과 비교해 망의 신뢰성이 극도로 높아야 하기 때문에 이 신뢰성과 관련된 연구가 매우 중요한 분야로 부각되고 있다. 본 논문에서는 다중 오류 (multi-type failures) 가 발생한 무선 신체 망에서 노드의 오동작들에 대해 분석하고 오동작 분석에 대한 새로운 모델을 제시한다. 오동작 모델링을 위해, 각 노드들을 라우팅 기능의 유무에 따라 분류하고, 노드의 에너지가 완전 소비되었거나 노드가 악의적인 공격에 의해 오류가 발생되었을 경우 각 노드들의 동작을 세미 마르코프 프로세스 (Semi-Markov Process)를 이용하여 모델링하였다. 본 논문에서 제시된 모델은 다중 오류 (multi-type failures) 환경에서 무선신체망의 신뢰성 분석에 매우 유용하다.

• Journal of Electrical Engineering and Technology
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• 제6권1호
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• pp.25-31
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• 2011

The purpose of power system maintenance is to prevent equipment failure. The maintenance strategy should be designed to balance costs and benefits because frequent maintenance increases cost while infrequent maintenance can also be costly due to electricity outages. This paper proposes maintenance modeling of a power distribution system using reliability centered maintenance (RCM). The proposed method includes comprehensive equipment modeling and impact analysis to evaluate the effect of equipment faults. The problem of finding the optimum maintenance strategy is formulated in terms of dynamic programming. The applied power system is based on the RBTS Bus 2 model, and the results demonstrate the potential for designing a maintenance strategy using the proposed model.