• 시스템엔지니어링학술지
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• 제14권1호
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• pp.36-43
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• 2018

The availability of the weapon system can be analyzed through state modeling and simulation using the Markov process. In this paper, show how to analyze the availability of the weapon system and can use the Markov process to analyze the system's steady state as well as the RAM at a transient state in time. As a result of the availability analysis of tracked vehicles, the inherent availability was 2.6% and the operational availability was 1.2% The validity criterion was defined as the case where the difference was within 3%, and thus it was judged to be valid. We have identified the faulty items through graphs of the number of visits per state among the results obtained through the MPS and can use them to provide design alternatives.

• Asian Pacific Journal of Cancer Prevention
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• 제15권1호
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• pp.441-447
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• 2014

Background: Multi-state models are appropriate for cancer studies such as gastrectomy which have high mortality statistics. These models can be used to better describe the natural disease process. But reaching that goal requires making assumptions like Markov and homogeneity with time. The present study aims to investigate these hypotheses. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. To assess Markov assumption and time homogeneity in modeling transition rates among states of multi-state model, Cox-Snell residuals, Akaikie information criteria and Schoenfeld residuals were used, respectively. Results: The assessment of Markov assumption based on Cox-Snell residuals and Akaikie information criterion showed that Markov assumption was not held just for transition rate of relapse (state 1 ${\rightarrow}$ state 2) and for other transition rates - death hazard without relapse (state 1 ${\rightarrow}$ state 3) and death hazard with relapse (state 2 ${\rightarrow}$ state 3) - this assumption could also be made. Moreover, the assessment of time homogeneity assumption based on Schoenfeld residuals revealed that this assumption - regarding the general test and each of the variables in the model- was held just for relapse (state 1 ${\rightarrow}$ state 2) and death hazard with a relapse (state 2 ${\rightarrow}$ state 3). Conclusions: Most researchers take account of assumptions such as Markov and time homogeneity in modeling transition rates. These assumptions can make the multi-state model simpler but if these assumptions are not made, they will lead to incorrect inferences and improper fitting.

• 한국위성정보통신학회논문지
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• 제6권1호
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• pp.12-18
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• 2011

고주파수 대역을 사용하는 위성통신 시스템의 링크 성능 저하의 가장 큰 요인 중의 하나가 강우 감쇠라고 할 수 있으며, 이러한 강우 감쇠를 보상하기 위한 가장 효율적인 방법으로써, 적응형 전송방식을 사용하고 있다. 강우 감쇠에 대처하기 위한 적응형 전송 방식을 개발하고 설계하는데 있어서 중요한 요소 중의 하나가 실제 발생하는 강우 감쇠에 대한 동적 시뮬레이션 모델이다. 본 논문에서는 초 단위 강우 감쇠 실측 데이터에 대한 통계치를 바탕으로 Markov 프로세스 모델을 이용하여 모델링하는 절차를 기술한다. 먼저 실측된 데이터의 통계적 특성을 추출하여 4가지 상태를 가지는 Markov 프로세스를 정의하고, 이를 이용하여 모델링된 데이터와 실측 데이터를 비교 분석한 결과를 제시한다.

• 한국경영과학회지
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• 제24권3호
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• pp.83-91
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• 1999

In order to build and manage an ATM network effectively under several types of control methods, it is necessary to estimate the performance of the equipments in various viewpoints, especially of ATM multiplexer. As for the method to model the input stream into the ATM multiplexer, many researches have been done to characterize it by, such as, fluid flow, MMPP(Markov Modulated Poisson Process), or MMDP (Markov Modulated Deterministic Process). We introduce an MRP(Markov Renewal Process) to model the input stream which has proper structure to represent the burst traffic with high correlation. In this paper, we build a model for aggregated heterogeneous ON-OFF sources of ATM traffic by MRP. We make discrete time MR/D/1/B queueing system, whose input process is the superposed MRP and present a performance analysis by finding CLP(Cell Loss Probability). A simulation is done to validate our algorithm.

• 한국소음진동공학회논문집
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• 제13권1호
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• pp.48-55
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• 2003

Hidden Markov Model(HMM) has a doubly embedded stochastic process with an underlying stochastic process that can be observed through another set of stochastic processes. This structure of HMM is useful for modeling vector sequence that doesn't look like a stochastic process but has a hidden stochastic process. So, HMM approach has become popular in various areas in last decade. The increasing popularity of HMM is based on two facts : rich mathematical structure and proven accuracy on critical application. In this paper, we applied continuous HMM (CHMM) approach with AR coefficient to detect and predict the chatter of lathe bite and to diagnose the wear of oil Journal bearing using rotor shaft displacement. Our examples show that CHMM approach is very efficient method for machine health monitoring and prediction.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2004년도 추계학술대회 논문집
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• pp.539-544
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• 2004

In this paper, we present reliability modeling and analysis method of the Automated Guideway Transit(AGT) vehicle system using analytical models, based on Markov Chains. The Markov model can express state transition of the AGT vehicle sys. that is considered to be in one of four states, such as basic operating (0), minor delay(1), major delay(2) and non-operating(3) state. The proposed Markov model is illustrated with a numerical example and cases to find a steady state availability, MTBF(mean time between failures), and MTTR(mean time to repair) under specified failure and repair rate arc demonstrated.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.521-523
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• 2021

관광 분야에서 온라인 리뷰의 중요성이 커지고 있다. 온라인 리뷰의 텍스트 데이터는 파악이 어렵다. 이에 본 연구에서는 특정 관광지에 대한 온라인 리뷰 텍스트 데이터가 나타내는 전반적인 의견을 직관적으로 도출하는 방법에 대해 알아보고자, 토픽 모델링과 Markov Chain을 시행했다. '해운대'에 대한 온라인 리뷰를 수집한 후, LDA와 BTM을 활용하여 주제를 도출하고, Markov Chain을 시각화하여 키워드 간의 관계와 전체적인 평가 내용을 확인했다. 사용된 기법은 각자 특징적인 결과를 제시했기 때문에 다양한 기법을 상보적으로 이용하기를 제안하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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• pp.126-128
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• 2006

현재 배전부분도 사업부체제로 진행됨에 따라 구역 및 지역별로 배전계통을 운영하는 경쟁체제에 돌입하게 되었다. 또한 각 사업부별로 예산을 추진하여 배전계통을 운영하게 되며 배분된 예산으로 배전계통의 신뢰도 및 경제적 운영을 일정 수준으로 유지하여 타 사업부와 사업성을 경쟁해야 한다. 특히, 각 배전 사업부별로 경쟁해야 하므로 최소의 비용으로 최대의 유지보수 효과를 얻을 수 있는 방법을 개발해야 하며, 비용을 최소로 하여 최적의 점검 주기를 찾는 문제는 중요하다고 할 수 있다. 본 논문에서는 최적 유지보수 기기 선정과 최적 유지보수 주기를 결정하는데 있어서 적합한 기법인 배전 계통 유지보수 기법(Reliability Centered Maintenance, RCM)을 이용하였다. 이의 구현을 위하여 Markov chain 기법을 배전 계통 기기의 유지보수 모델에 적합하도록 수정하여 유지보수에 필요한 비용과 기기의 고장으로 인하여 발생할 수 있는 정전비용 등을 고려하여 최적의 점검 주기를 결정하고자 한다. 제안된 RCM의 알고리즘은 Dynamic Programming을 이용하여 점검 및 유지보수에 필요한 기기를 결정하는 부분과 유지보수의 실행 여부를 결정하는 decision 부분으로 되어있다. 사례연구를 통하여 본 논문에서 제안된 알고리즘의 적용가능성을 살펴보았다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4825-4847
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• 2016

In this paper, we focus on the per-flow throughput analysis of IEEE 802.11 multi-hop ad hoc networks. The importance of an accurate saturation throughput model lies in establishing the theoretical foundation for effective protocol performance improvements. We argue that the challenge in modeling the per-flow throughput in IEEE 802.11 multi-hop ad hoc networks lies in the analysis of the freezing process and probability of collisions. We first classify collisions occurring in the whole transmission process into instantaneous collisions and persistent collisions. Then we present a four-dimensional Markov chain model based on the notion of the fixed length channel slot to model the Binary Exponential Backoff (BEB) algorithm performed by a tagged node. We further adopt a continuous time Markov model to analyze the freezing process. Through an iterative way, we derive the per-flow throughput of the network. Finally, we validate the accuracy of our model by comparing the analytical results with that obtained by simulations.

• 대한음성학회지:말소리
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• 제59호
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• pp.53-68
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• 2006

We report the evaluation results of the Korean speech recognition platform called ECHOS. The platform has an object-oriented and reusable architecture so that researchers can easily evaluate their own algorithms. The platform has all intrinsic modules to build a large vocabulary speech recognizer: Noise reduction, end-point detection, feature extraction, hidden Markov model (HMM)-based acoustic modeling, cross-word modeling, n-gram language modeling, n-best search, word graph generation, and Korean-specific language processing. The platform supports both lexical search trees and finite-state networks. It performs word-dependent n-best search with bigram in the forward search stage, and rescores the lattice with trigram in the backward stage. In an 8000-word continuous speech recognition task, the platform with a lexical tree increases 40% of word errors but decreases 50% of recognition time compared to the HTK platform with flat lexicon. ECHOS reduces 40% of recognition errors through incorporation of cross-word modeling. With the number of Gaussian mixtures increasing to 16, it yields word accuracy comparable to the previous lexical tree-based platform, Julius.