• Journal of Korean Institute of Industrial Engineers
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• v.15 no.1
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• pp.89-103
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• 1989

In this paper the approximate average outgoing quality and properties of a class of continuous sampling plans in a short production run are investigated when the quality of successive units follows a two-state time-homogeneous Markov chain. The results of previous studies can be obtained as special cases. It is observed that the long-run average outgoing quality limit values under the statistical control differ significantly as compared to the case of short production runs in a Markov-dependent production process.

• The Journal of the Acoustical Society of Korea
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• v.9 no.2
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• pp.61-69
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• 1990

We have investigated the digital bit synchronization problem in baseband communication receiver systems using the Gauss-Markov estimation technique which is equivalent to the weighted least square method. The realized bit synchronizer, including the data detector, processes the input signal two dimensionally into the transition phase and data level under the white Gaussian noise environment. We have confirmed the relization of the bit synchronizer via computer simulation. In addition, we have compared and evaluated the estimation error performance of the proposed method with that of the conventional DTTL method and of the minimum likelihood method.

• 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.

• Spatial Information Research
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• v.11 no.3
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• pp.227-240
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• 2003

The primary focus of this study is to provide a general methodology which can be utilized to understand and analyze environmental issues such as long term ecosystem dynamics and land use/cover change by development of 2D dynamic landscape models and model-based simulation. Change processes in land cover and ecosystem function can be understood in terms of the spatial and temporal distribution of land cover resources. In development of a system to understand major processes of change and obtain predictive information, first of all, spatial heterogeneity is to be taken into account because landscape spatial pattern affects on land cover change and interaction between different land cover types. Therefore, the relationship between pattern and processes is to be included in the research. Landscape modeling requires different approach depending on the definition, assumption, and rules employed for mechanism behind the processes such as spatial event process, land degradation, deforestration, desertification, and change in an urban environment. The rule-based models are described in the paper for land cover change by natural fires. Finally, a case study is presented as an example using spatial modeling and simulation to study and synthesize patterns and processes at different scales ranging from fine-scale to global scale.

• Communications of the Korean Mathematical Society
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• v.11 no.4
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• pp.1117-1122
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• 1996

A class of nonlinear Markov processes on the real line is considered, and a functional central limit theorem is proved for the functions of bounded variation on the real line by identifying a broad subset of the range of the generator.

• Journal of the Korean Statistical Society
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• v.35 no.1
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• pp.79-90
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• 2006

We consider the subdiagonal bilinear model and ARMA model with subdiagonal bilinear errors. Sufficient conditions for geometric ergodicity of associated Markov chains are derived by using results on generalized random coefficient autoregressive models and then strict stationarity and ,a-mixing property with exponential decay rates for given processes are obtained.

• 한국가스학회:학술대회논문집
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• 2000.09a
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• pp.174-179
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• 2000

• Journal of Applied Reliability
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• v.16 no.4
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• pp.295-304
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• 2016

Purpose: This paper presents an application of Markov Process to reliability and availability analysis. In order to do that of analysis, we set up a specific case of Tablet PC and it's usage scenario. The case has it some spares and maintenance and repair processes. Methods: Different configurations of the tablet PC and as well as their functions are defined. The system configuration and calculated failure rates of components are modeled from Windchill Quality Solution. Two models, without a spare and with spare, are created and compared using Markov Process. The Matlab numerical analysis is used to simulate and show the change of state with time. Availability of the system is computed by determining the time the system stays in different states. Results: The mission availability and steady-state condition availability in accordance with the mission are compared and the availability of the system with spares have improved availability than without spares. Simulated data shows that downtime of the system increased which results in greater availability through the consideration of spares. Conclusion: There's many techniques and methods to do reliability and availability analysis and mostly are time-independent assumptions. But Markov Process, even though its steady-state and ergodic properties, can do time analysis any given time periods.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.3
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• pp.229-239
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• 2015

In light of the significant increase in the quantities of goods transported and the development of the shipping industry, the frequency of usage of port structures has increased; yet, the government's budget for the shipping & port of SOC has been reduced. Port structures require systematically effective maintenance and management trends that address their growing frequency of usage. In order to construct a productive maintenance system, it is essential to develop deterioration models of port structures that consider various characteristics, such as location, type, use, constructed level, and state of maintenance. Processes for developing such deterioration models include examining factors that cause the structures to deteriorate, collecting data on deteriorating structures, and deciding methods of estimation. The techniques used for developing the deterioration models are multiple regression analysis and Markov chain theory. Multiple regression analysis can reflect changes over time and Markov chain theory can apply status changes based on a probabilistic method. Along with these processes, the deterioration models of open-type and gravity-type wharfs were suggested.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.3
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• pp.81-96
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• 2006

We consider a rental company that dynamically manages Its capacity level through capacity addition and return While serving customer with its own capacity, the company expands its capacity by renting items from an outside source so that it can avoid lost opportunities of rental which occur when stock is not sufficient. If stock becomes sufficiently large enough to cope with demands, the company returns expanded capacity to the outside source. Formulating the model into a Markov decision problem, we identify an optimal capacity management Policy which states when the company should expand its capacity and when it should return expanded capacity after capacity addition. Since it is intractable to analytically find the optimal capacity management policy and the optimal size of capacity expansion, we present a numerical procedure that finds these optimal values based on the value iteration method. Numerical analysis is implemented and we observe monotonic properties of the optimal performance measures by system parameters, which are meaningful in developing effective heuristic policies.