• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.65-77
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• 1993

Often in a production process, the quality of items is serially dependent. We assume that the quality of items is an attribute which can be classified as good or bad with a Markovian dependence structure. In order to determine sampling inspection plan characteristics such as total inspection cost and average outgoing quality, we design an economic model and illustrate an efficient procedure for design of best inspection plan using graphs based on numerical calculations.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.477-491
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• 2021

The Markov modulated Brownian motion is a substantial generalization of the classical Brownian Motion. On the other hand, the Markovian arrival process (MAP) is a point process whose family is dense for any stochastic point process and is used to approximate complex stochastic counting processes. In this paper, we consider a superposition of the Markov modulated Brownian motion (MMBM) and the Markovian arrival process of jumps which are distributed as the bilateral ph-type distribution, the class of which is also dense in the space of distribution functions defined on the whole real line. In the model, we assume that the inter-arrival times of the MAP depend on the underlying Markov process of the MMBM. One of the subjects of this paper is introducing how to obtain the first passage probabilities of the superposed process using a stochastic doubling algorithm designed for getting the minimal solution of a nonsymmetric algebraic Riccatti equation. The other is to provide eigenvalue and eigenvector results on the superposed process to make it possible to apply the GTH-like algorithm, which improves the accuracy of the doubling algorithm.

• Journal of Biomedical Engineering Research
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• v.9 no.2
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• pp.159-164
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• 1988

This thesis investigates the Quantitative aspect of epidemic phenomena utilizing the analytical method of discrete time systeMs based on the theory of Markov processes. In particular, the pattern on the epidemic character of turberculosis controlled by prophylaxis and BCG vaccinatioll was analyzed by the markovian model of tuberculosis system which is derived according to the ecologic relationship between nine epidemiologic states of individuals. The quantitative aspects of the model were characterized by digital computer simulations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.231-240
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• 1999

A major concern in Concurrent Engineering is the control and management of workload in a period of process. As a general rule, leveling the peak of workload in certain period is difficult because concurrent processing is comprised of various processes, including overlapping, paralleling looping and so on. Therefore, the workload management with resource constraints is so beneficial that effective methods to analyze design process are momentous. This study presents the Timed Petri Nets approach of precedence logic networks, and provides an alternative for users to analyze constraint processes to resolve conflicts of resources. Another approach to Continuous Time Markov Chain using Stochastic Petri Nets is also proposed. These approaches are expected to facilitate resolving resource constrained scheduling problems more systematically in Concurrent Engineering environment.

• Proceedings of the Korea Society for Simulation Conference
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• 1998.10a
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• pp.7-11
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• 1998

ATM 망을 효율적으로 구축하고 여러 가지 형태의 제어를 통하여 망 자원을 안정적으로 관리하기 위해서는 망의 성능에 대한 다양한 관점에서의 분석이 필수적이며, 그 기본이 되는 것이 ATM 다중화기에 대한 성능 분석이다. ATM 다중화기에 입력되는 트래픽을 분석하는데 있어서 MRP(Markov Renewal Processes) 또는 SMP(Semi-Markov Processes)는 자동 상관계수를 계산하기가 비교적 용이해서 높은 양의 상관관계를 가지는 버스티한 트래픽을 표현하기에 적절한 구조를 가지고 있으며, 입력 트래픽의 머무는 시간이 어떠한 분포이든 표현 가능한 장점이 있다. 본 연구에서는 ATM 트래픽을 분석하는데 있어서 입력되는 on/off 소스를 MRP로 모형화하고, 이를 도착과정으로 하는 이산시간 MR/D/1B 대기시스템으로 구성하여 ATM 다중화기의 셀 손실확률 등의 성능분석을 제시한다. 또한 본 연구에서 제시한 방법에 대한 타당성 검증을 위하여 시뮬레이션과 비교 검토한다.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.417-423
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• 2005

A fuzzy approach using an EM algorithm for image classification is presented. In this study, a double compound stochastic image process is assumed to combine a discrete-valued field for region-class processes and a continuous random field for observed intensity processes. The Markov random field is employed to characterize the geophysical connectedness of a digital image structure. The fuzzy classification is an EM iterative approach based on mixture probability distribution. Under the assumption of the double compound process, given an initial class map, this approach iteratively computes the fuzzy membership vectors in the E-step and the estimates of class-related parameters in the M-step. In the experiments with remotely sensed data, the MRF-based method yielded a spatially smooth class-map with more distinctive configuration of the classes than the non-MRF approach.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.26.2-26
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• 2001

• Journal of KIISE
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• v.42 no.6
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• pp.748-754
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• 2015

This paper proposes a sequential state estimation model consisting of continuous and discrete variables, as a way of generalizing all discrete-state factorial HMM, and gives a design of gait motion model based on the idea. The discrete state variable implements a Markov chain that models the gait dynamics, and for each state of the Markov chain, we created a Gaussian process over the space of the continuous variable. The Markov chain controls the switching among Gaussian processes, each of which models the rotation or various views of a gait state. Then a particle filter-based algorithm is presented to give an approximate filtering solution. Given an input vector sequence presented over time, this finds a trajectory that follows a Gaussian process and occasionally switches to another dynamically. Experimental results show that the proposed model can provide a very intuitive interpretation of video-based gait into a sequence of poses and a sequence of posture states.

• Nuclear Engineering and Technology
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• v.19 no.4
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• pp.279-291
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• 1987

The event tree/fault tree techniques used in the current probabilistic risk assessment (PRA) of nuclear power plants are based on the binary and static description of the components and the system. While these techniques Bay be adequate in most of the safety studies, more advanced techniques, e.g., the Markov reliability analysis, are required to accurately study such problems as the plant availability assessments and technical specifications evaluations that are becoming increasingly important. This paper describes a Markov model for the Reactor Protection System of a pressurized water reactor and presents results of model evaluations for two testing policies in technical specifications.

• International Journal of Quality Innovation
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• v.2 no.2
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• pp.136-144
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• 2001

The Markov Chain approach is used to develop an economic adjustment model of a process whose quality can be affected by a single special cause, resulting in changes of the process mean by incorrect adjustment of the process when it is operating according to its capability. The $\bar{X}$ control chart is thus used to signal the special cause. It is demonstrated that the expressions for the expected cycle time and the expected cycle cost are easier to obtain by the proposed approach than by adopting that in Collani, Saniga and Weigang (1994). Furthermore, this approach would be easily extended to derive the expected cycle cost and the expected cycle time for the case of multiple special causes or multiple control charts. A numerical example illustrates the proposed method and its application.