• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.235-251
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• 1999

In this paper we examine extremal behavior of a $textsc{k}$th-order stationary Markov chain {X\ulcorner} by considering excesses over a high level which typically appear in clusters. Excesses over a high level within a cluster define a cluster damage, i.e., a normalized sum of all excesses within a cluster, and all excesses define a damage point process. Under some distributional assumptions for {X\ulcorner}, we prove convergence in distribution of the cluster damage and obtain a representation for the limiting cluster damage distribution which is well suited for simulation. We also derive formulas for the mean and the variance of the limiting cluster damage distribution. These results guarantee a compound Poisson limit for the damage point process, provided that it is strongly mixing.

• Journal of Welding and Joining
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• v.20 no.6
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• pp.45-45
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• 2002

This study is a middle report on the development of intelligent spot welding monitoring technology applicable to the production line. An intelligent algorithm has been developed to predict the quality of welding in real time. We examined whether it is effective or not through the In-Line and the Off-Line tests. The purpose of the present study is to provide a reliable solution which can prevent welding defects in production site. In this study, the process variables, which were monitored in the primary circuit of the welding, are used to estimate the weld quality by Hidden Markov Model(HMM). The primary dynamic resistance patterns are recognized and the quality is estimated in probability method during the welding. We expect that the algorithm proposed in the present study is feasible to the applied in the production sites for the purpose of in-process real time quality monitoring of spot welding.

• Journal of Welding and Joining
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• v.20 no.6
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• pp.769-775
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• 2002

This study is a middle report on the development of intelligent spot welding monitoring technology applicable to the production line. An intelligent algorithm has been developed to predict the quality of welding in real time. We examined whether it is effective or not through the In-Line and the Off-Line tests. The purpose of the present study is to provide a reliable solution which can prevent welding defects in production site. In this study, the process variables, which were monitored in the primary circuit of the welding, are used to estimate the weld quality by Hidden Markov Model(HMM). The primary dynamic resistance patterns are recognized and the quality is estimated in probability method during the welding. We expect that the algorithm proposed in the present study is feasible to the applied in the production sites for the purpose of in-process real time quality monitoring of spot welding.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.6
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• pp.1-8
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• 2019

Modern weapon systems are multifunctional, with capabilities for executing complex missions. However, they are required to be highly reliable, which increases their total cost of ownership. Because it is necessary to produce the best results within a limited budget, there is an increasing interest in development, acquisition, and maintenance costs. Consequently, there is a need for tools that calculate the lifecycle costs of weapons systems development to facilitate decision making. In this study, we propose a cost calculation function based on the Markov process simulator-a reliability, availability, and maintainability analysis tool developed by applying the Markov-Monte Carlo method-as an alternative to these requirements to facilitate decision-making in systems development.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.217-226
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• 2014

In this research, we study the problem of opportunistic spectrum access (OSA) in a time-varying environment with fading channels, where the channel state is characterized by both channel quality and the occupancy of primary users (PUs). First, a finite-state Markov channel model is introduced to represent a fading channel. Second, by probing channel quality and exploring the activities of PUs jointly, a two-dimensional partially observable Markov decision process framework is proposed for OSA. In addition, a greedy strategy is designed, where a secondary user selects a channel that has the best-expected data transmission rate to maximize the instantaneous reward in the current slot. Compared with the optimal strategy that considers future reward, the greedy strategy brings low complexity and relatively ideal performance. Meanwhile, the spectrum sensing error that causes the collision between a PU and a secondary user (SU) is also discussed. Furthermore, we analyze the multiuser situation in which the proposed single-user strategy is adopted by every SU compared with the previous one. By observing the simulation results, the proposed strategy attains a larger throughput than the previous works under various parameter configurations.

• International Journal of Contents
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• v.13 no.4
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• pp.80-87
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• 2017

Since the advent of the Internet, and the development of smart devices, people have begun to spend more time in online platforms; this phenomenon has created a large number of online Words of Mouth (WOM) daily. Under these changes, one of the important aspects to consider is the conformity effect in online WOM; that is, whether an individual's own opinion would be influenced by the majority opinion of other people. This study, therefore, investigates whether there is the conformity effect in online product ratings for Amazon.com using the method called Markov Chain analysis. Markov Chain analysis considers the stochastic process that satisfies the Markov property, and we assume that the generation of online product ratings follows the process. Under the assumption that people are usually independent when they express their opinion in online platforms, we analyze the interdependency among rating sequences, and we find weak evidence that there exists the conformity effect in online product rating. This suggests that people who leave online product ratings consider others' opinions.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.549-556
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• 2020

This paper proposes several suboptimal methods of designing a controller for a networked control system with state feedback where delay due to transmission error and transmission delay is modeled as a Markov process. A stability condition for a control system with Markov delay is found through an equivalent relationship that corresponding delay-dependent Lyapunov-Krasovskii functional has the same form of the Lyapunov function of an augmented control system. Several suboptimal methods of designing a controller from the stability condition are proposed to reduce complexity. A simple numerical experiment shows that a restricted subspace method which limits the search space of a matrix variable to a block diagonal form provides the best tradeoff between the complexity and performance.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.61-69
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• 2008

In order to evaluate the performance of priority queues for future event list in discrete-event simulations, models representing patterns of enqueue and dequeue processes are required. The time complexities of diverse priority queue implementations can be compared using the performance models. This study aims at developing such performance models especially under the environment that a developed simulation model is used repeatedly for a long period. The developed performance model is based on multi-stage Markov process models; probabilistic patterns of enqueue and dequeue are considered by incorporating non-homogeneous transition probability. All necessary parameters in this performance model would be estimated by analyzing a results obtained by executing the simulation model. A case study with a war game simulation model shows how the parameters defined in muti-stage Markov process models are estimated.

• Journal of Korea Water Resources Association
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• v.42 no.3
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• pp.213-225
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• 2009

A stationary Markov chain model is a stochastic process with the Markov property. Having the Markov property means that, given the present state, future states are independent of the past states. The Markov chain model has been widely used for water resources design as a main tool. A main assumption of the stationary Markov model is that statistical properties remain the same for all times. Hence, the stationary Markov chain model basically can not consider the changes of mean or variance. In this regard, a primary objective of this study is to develop a model which is able to make use of exogenous variables. The regression based link functions are employed to dynamically update model parameters given the exogenous variables, and the model parameters are estimated by canonical correlation analysis. The proposed model is applied to daily rainfall series at Seoul station having 46 years data from 1961 to 2006. The model shows a capability to reproduce daily and seasonal characteristics simultaneously. Therefore, the proposed model can be used as a short or mid-term prediction tool if elaborate GCM forecasts are used as a predictor. Also, the nonstationary Markov chain model can be applied to climate change studies if GCM based climate change scenarios are provided as inputs.

• Journal of Integrative Natural Science
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• v.7 no.3
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• pp.200-207
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• 2014

Average number of samples to signal (ANSS) and average time to signal (ATS) are the most widely used criterion for comparing the efficiencies of the quality control charts. In this study the method of evaluating ANSS and ATS values of the multivariate exponentially weighted moving average (EWMA) control charts with Markov chain approach was presented when the production process is in control state or out of control state. Through numerical results, it is found that when the number of transient state r is less than 50, the calculated ANSS and ATS values are unstable; and ATS(r) tends to be stabilized when r is greater than 100; in addition, when the properties of multivariate EWMA control chart is evaluated using Markov chain method, the number of transient state r requires bigger values when the smoothing constatnt ${\lambda}$ becomes smaller.