• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.418-433
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• 1995

본 연구에서는 MPEG 트래픽과 같이 셀 흐름에 주기성을 갖는 비디오 트래픽 모형에 대한 쉐이핑 정책을 제시하고, 쉐이퍼에서의 셀손실율, 셀지연, 및 완만화 효과를 분석하였다. 분석 모형으로는 이산 상태 마코프 연쇄를 사용하였으며, 예제를 통해 시뮬레이션 결과와 비교하므로서 분석모형을 검증하였다. 분석 결과 셀지연 및 완만화 효과 사이에는 서비스율의 증가에 따라 trade off가 존재함이 나타났다. 본 연구는 ATM 트래픽관리에 있어서 다중화 장치에서의 성능분석과 병행하여 쉐이퍼의 설계에 있어서 정량화된 기초자료를 제공할 수 있을 것이라 여겨진다.

• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.825-838
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• 2014

The stationary Markov chain model has been widely used as a daily rainfall simulation model. A main assumption of the stationary Markov model is that statistical characteristics do not change over time and do not have any trends. In other words, the stationary Markov chain model for daily rainfall simulation essentially can not incorporate any changes in mean or variance into the model. Here we develop a Non-stationary hidden Markov chain model (NHMM) based stochastic downscaling scheme for simulating the daily rainfall sequences, using general circulation models (GCMs) as inputs. It has been acknowledged that GCMs perform well with respect to annual and seasonal variation at large spatial scale and they stand as one of the primary sources for obtaining forecasts. The proposed model is applied to daily rainfall series at three stations in Nakdong watershed. The model showed a better performance in reproducing most of the statistics associated with daily and seasonal rainfall. In particular, the proposed model provided a significant improvement in reproducing the extremes. It was confirmed that the proposed model could be used as a downscaling model for the purpose of generating plausible daily rainfall scenarios if elaborate GCM forecasts can used as a predictor. Also, the proposed NHMM model can be applied to climate change studies if GCM based climate change scenarios are used as inputs.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.537-542
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• 1996

ITU-T에서 표준 비디오 코딩 알고리즘으로 채택한 MPEG 코딩방식은 세 가지의 코딩방식 (I,B,P,방식)을 주기적으로 사용하기 때문에, 코딩된 정보량에 강한 주기성을 보인다. 본 연구에서는 이러한 MPEG 비디오 트래픽의 주기성을 반영하는 개별 비디오 원의 트래픽을 모형화하고 이를 바탕으로 다중화 장치의 성능분석을 실시하였다. 개별 비디오 원에서 발생된 트래픽은 I, B, P의 코딩순서를 반영하고, I, B, P 프레임 별로 셀 수를 모형화 하였다. 그리고 다중화 장치에 입력되는 트래픽은 프레임 시간 단위로 이산화시켜 셀 수를 모형화하였고, 이를 이산시간 마코프 연쇄를 이용해 다중화 장치에서의 셀 손실률을 구하였다. 다중화 장치에서 셀 손실은 입력되는 잘대적인 트래픽의 양 뿐만 아니라, 비디오 원 정렬 (Source Alignment)에도 많은 영향을 받는다. 이러한 비디오 원의 정렬 효과를 반영하여 다중화 장치에 연결될 수 있는 비디오 원의 수를 결정하였다.

• Journal of Korea Water Resources Association
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• v.42 no.9
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• pp.747-758
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• 2009

In this study, long-term variabilities of rainfall-occurrence characteristics are analyzed using rainfall data at Seoul, which is the longest data record existing in world. first, the accuracy of Chukwooki data set (CWK) are evaluated in view of rainfall-occurrence probability by analyzing the transition probabilities and occurrence characteristics based on Markov chain. And long-term inter-monthly variabilities of transition probabilities are analyzed using two dimensional LOWESS regression. From the results of analyzed transition probabilities and occurrence characteristics, it is different that rainfall-occurrence characteristics between CWK and modern rain gage data set (MRG) for original rainfall data sets (M00). For characteristics of rainfall series, occurrences probabilities of rainfall are increased and durations of each rainfall are shorter than past. And from the results of analyzing the long-term inter-monthly variabilities of transition probabilities, in case of M20, lengths of dry spells between CWK and MRG are not different significantly and lengths of wet spells are decreased persistently after A.D. 1830. Especially, decreasing trend for lengths of wet spells at recent september are appeared significantly. These results are considered with increasing trend of recent rainfall, it is concluded that recent frequencies and intensities of rainfall are increasing.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.375-384
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• 1997

In this paper, chain-shaped multi-level skip-lot sampling plan is designed, which is a normal inspection plan between Choi(1993)'s tightened inspection plan and Choi(1995)'s reduced inspection plan. In every skipping inspection of the proposed plan, when designed numbers of consecutively inspected lots are accepted, switch to the next skipping inspection, and when a lot is rejected, switch to the skipping inspection of two-level lower. Also, the formulae of the operating chareacteristic function, average sampling number and average outgoing quality for the proposed skip-lot sampling plan are derived using the morkov chain approach and their properties are studied and graphically compared with those of the other multi-level skip-lot sampling plans.

• The Korean Journal of Applied Statistics
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• v.8 no.2
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• pp.55-64
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• 1995

Three-level Skip-lot sampling plan split by two stages (Split2-SkSP0 is proposed by modifying multi-level skip-lot sampling plan proposed by Choi(1993), which has normal and terrace inspections on the first and the second stages, respectively. The plan is designed to work more higher level inspections when the quality of the submitted products are good, otherwise, return to the normal or the terrace inspection as fast as possible. Also, the formula of the operating characteristic function for the split skip-lot sampling plan is derived using the Markov chain approach. Also, operating characteristic properties of the proposed plans are studied and graphically compared with those of the multi-level skip-lot sampling plans.

• Journal of Wetlands Research
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• v.5 no.2
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• pp.1-13
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• 2003

In Korea, most of the rainfalls have been concentrated in the flood season and the flood study has received more attention than low flow analysis. One of the reasons that the analysis of low flows has less attention is the lacks of the required data like daily rainfall and so we have used the stochastic processes such as pulse noise, exponential distribution, and state model of Markov chain for the rainfall simulation in short term such as daily. Especially this study will pay attention to the state model of Markov chain. The previous study had performed the simulation study by the state model without considerations of the flood and non-flood periods and without consideration of the frequency of rainfall for the period of a state. Therefore this study considers afore mentioned two cases and compares the results with the known state model. As the results, the RMSEs of the suggested and known models represent the similar results. However, the PRE(relative percentage error) shows the suggested model is better results.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.45-60
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• 1997

본연구의 목적은 1994년과 1995년의 연구 결과를 토대로 고속국도 교통류의 차량 추종, 차선 변경 특성을 현장 조사 자료를 통하여 분석·규명하고, 국내 고속도로의 교통류 특성을 반영할 수 있는 한국형 고속국도 모의실험 모형을 개발하는데 있다. 본 연구의 주요 결과는 다음과 같다. ▶ 국내 고속국도 교통류의 차두시간, 속도, 차량군의 크기, 차선 변 경, 중차량의 영향 등의 특성을 조사·분석하여 관련 매개변수와 모형식을 도출하였다. ▶ 차량 생성 모형은 개별 차량의 차두시간, 속도를 이용하여 구축하였으며, 중차량의 구성 비 율에 따른 속도 변화를 연구하여 그 결과를 모형 구축에 응용하였다. ▶ 차량 추종 모형은 1995년 연구에서 검증된 PITT-KLD 모형에 기반을 두었으며, 현장 실측 자료를 분석하여 차량 추종과 관련된 매개변수들을 설정하였다. ▶ 차선 변경 모형은 기본적으로 간격 수락 모형을 이용하였으며, 차선 변경시 임계 간격을 국내 운전자들의 유형에 따라 10가지로 설 정하였다. 차선 변경 확률은 현장 조사 자료를 기초로 한 경험적 모형을 구축하여 선정하였 으며, 마코프 연쇄 기법과도 비교·검토하였다. ▶ 개발된 모의실험 모형을 비교·평가하기 위 해 고속국도 합류부의 현장 조사 자료와 모의실험 모형을 비교·평가한 결과, 합류 이전 단 계에서는 실측치와 모형의 통계량이 어느 정도 유사한 양상을 보이지만 합류 이후 단계에서 는 차이를 나타내고 잇다.

• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.11-20
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• 2011

Pictorial Structures is known as an effective method that recognizes and tracks human poses. In this paper, the upper body pose is also tracked by PS and a particle filter(PF). PF is one of dynamic programming methods. But Markov chain-based dynamic motion model which is used in dynamic programming methods such as PF, couldn't predict effectively the highly articulated upper body motions. Therefore PF often fails to track upper body pose. In this paper we propose the key pose-based proposal distribution for proper particle prediction based on the similarities between key poses and an upper body silhouette. In the experimental results we confirmed our 70.51% improved performance comparing with a conventional method.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.377-387
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• 1998

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 latent variables that indicates with component of the Superposition model. This data augmentation approach facilitates specification of the transitional measure in the Markov Chain. Metropolis algorithms along with Gibbs steps are proposed to preform the Bayesian inference of such models. for model determination, we explored the Pre-quential conditional predictive Ordinate(PCPO) criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. To relax the monotonic intensity function assumptions, we consider in this paper Superposition of Musa-Okumoto and Erlang(2) models. A numerical example with simulated dataset is given.