• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• International journal of advanced smart convergence
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• v.1 no.1
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• pp.14-18
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• 2012

This paper presents a fair MAC protocol based on the CSMA/CA algorithm in visible light communication (VLC) networks. The problem of bandwidth sharing among differentiated priority in VLC networks can be solved by using number of backoff time and backoff exponent parameters with AIFS. The proposed algorithm can achieve fair allocation of the bandwidth resource among differentiated priority. The two dimension Markov chain is assisted for analyzing the proposed mechanism about throughput and delay metrics. Numerical results show that our proposed algorithm improves the fairness among different traffic flows.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.236-240
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• 2004

Stroke-based composite HMMs with articulation states are proposed to deal with 3D spatio-temporal trajectory gestures. The direct use of 3D data provides more naturalness in generating gestures, thereby avoiding some of the constraints usually imposed to prevent performance degradation when trajectory data are projected into a specific 2D plane. Also, the decomposition of gestures into more primitive strokes is quite attractive, since reversely concatenating stroke-based HMMs makes it possible to construct a new set of gesture HMMs without retraining their parameters. Any deterioration in performance arising from decomposition can be remedied by a partial tuning process for such composite HMMs.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.413-418
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• 2004

The bounded adjustment is known to be more efficient than repeated adjustment when the cost is incurred for engineering process control. The procedure of the bounded adjustment is to adjust the process when the one-step predicted deviation exceeds the adjustment limit by the amount of the prediction. In this paper, two run rules are proposed and studied in order to improve the efficiency of the traditional bounded adjustment procedure. The efficiency is studied in terms of the standardized cost through Monte Carlo simulation when the procedure is operated with and without the run rules. The adjustment procedure operated with run rules turns out to be more robust for changes in the process and cost parameters. The Markov chain approach for calculating the properties of the run rules is also studied.

• Journal of Korean Society for Quality Management
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• v.30 no.2
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• pp.99-117
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• 2002

Variable sampling interval(VSI) and variable sample size(VSS) control charts vary the sampling rate for the next sample depending on the current chart statistic. This paper develops EWMA charts with the VSI and VSS features, and investigates the effectiveness of these charts in context of an economic model. The economic properties of these charts are evaluated by using Markov chain methods. The model contains cost parameters which allow the specification of the costs associated with sampling, false alarms, and operating off target. This economic model can be used to quantify the cost saving that can be obtained by using control charts with the VSI and VSS features instead of with the fixed sampling rate(FSR) feature, and can also be used to gain insight into the way that control charts with the VSI and VSS features should be designed to achieve optimal economic performance. The economic performance of X charts with the VSI and VSS features is also considered.

• Journal of the Korean Statistical Society
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• v.35 no.3
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• pp.239-250
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• 2006

A $2{\times}2$ crossover design including carryover effect is considered for assessment of population bioequivalence of two drug formulations in a Bayesian framework. In classical analysis, it is complex to deal with the carryover effect since the estimate of the drug effect is biased in the presence of a carryover effect. The proposed method in this article uses uninformative priors and vague proper priors for objectiveness of priors and the posterior probability distribution of the parameters of interest is derived with given priors. The posterior probabilities of the hypotheses for assessing population bioequivalence are evaluated based on a Markov chain Monte Carlo simulation method. An example with real data set is given for illustration.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.773-788
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• 2000

Statistical process control (SPC) and engineering process control (EPC) are based on different strategies for processes quality improvement. SPC reduces process variability by detecting and eliminating special causes of process variation. while EPC reduces process variability by adjusting compensatory variables to keep the quality variable close to target. Recently there has been needs for a process control proceduce which combines the tow strategies. This paper considers a combined scheme which simultaneously applies SPC and EPC techniques to reduce the variation of a process. The process model under consideration is an integrated moving average(IMA) process with a step shift. The EPC part of the scheme adjusts the process back to target at every fixed monitoring intervals, which is referred to a repeated adjustment scheme. The SPC part of the scheme uses an exponentially weighted moving average(EWMA) of observed deviation from target to detect special causes. A Markov chain model is developed to relate the scheme's expected cost per unit time to the design parameters of he combined control scheme. The expected cost per unit time is composed of off-target cost, adjustment cost, monitoring cost, and false alarm cost.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.19 no.4
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• pp.429-441
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• 2015

We study optimal consumption/investment and life insurance purchase rules for a wage earner with mortality risk under regime-switching financial market conditions, in a continuous time-horizon. We apply the Markov chain approximation method and suggest an efficient algorithm using parallel computing to solve the simultaneous Hamilton-Jaccobi-Bellman equations arising from the optimization problem. We provide numerical results under the utility functions of the constant relative risk aversion type, with which we illustrate the effects of regime switching on the optimal policies by comparing them with those in the absence of regime switching.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.345-348
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• 2011

구조요소의 설계에서 유한요소해석은 매우 효과적인 방법이다. 이 방법은 시험 수행에 드는 시간과 비용을 줄여준다. 그러나 공정 과정과 환경에 의하여 생기는 입력 물성치들의 변화 때문에 우리는 유한요소해석의 결과를 전적으로 믿어서는 안 된다. 따라서 유한요소해석의 신뢰성을 증명하는 것은 매우 중요하다. 본 연구에서는 현장에 축적된 피로 수명 시험 데이터를 바탕으로 유한요소해석을 이용하여 피로수명 파라미터를 역 추정 하는 연구를 수행하였다. 베이지안 접근법을 이용하여 불확실성 피로 수명 파라미터의 사후분포를 구하였고, 마코프체인몬테카를로(Markov Chain Monte Carlo) 기법을 이용하여 역 추정된 파라미터의 샘플 데이터를 생성하였다. 얻어진 샘플 데이터를 기반으로 새로운 형상의 스프링에 대한 피로 수명을 예측한다. 신뢰성 기반 형상 최적화(RBDO)는 서스펜션 코일 스프링의 요구수명을 만족시키기 위하여 수행된다. 또한 크리깅 근사 모델은 유한요소해석의 연산 량 감소를 위해 이용한다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.9
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• pp.97-106
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• 1996

In this paper, we propose a face recognition algorithm using the hidden markov model and neural networks (HMM-NN). In the preprocessing stage, we find edges of a face using the locally adaptive threshold (LAT) scheme and extract features based on generic knowledge of a face, then construct a database with extracted features. In the training stage, we generate HMM parameters for each person by using the forward-backward algorithm. In the recognition stage, we apply probability vlaues calculated by the HMM to subsequent neural networks (NN) as input data. Computer simulation shows that the proposed HMM-NN algorithm gives higher recognition rate compared with conventional face recognition algorithms.