• Journal of Multimedia Information System
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• v.8 no.1
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• pp.31-34
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• 2021

The classical HMM is defined by a parameter triple �� = (��, A, B), where each parameter represents a collection of probability distributions: initial state, state transition and output distributions in order. This paper proposes a new stationary parameter e = (e1, e2, …, eN) where N is the number of states and et = P(|xt = i, y) for describing how an input pattern y ends in state xt = i at time t followed by nothing. It is often said that all is well that ends well. We argue here that all should end well. The paper sets the framework for the theory and presents an efficient inference and training algorithms based on dynamic programming and expectation-maximization. The proposed model is applicable to analyzing any sequential data with two or more finite segmental patterns are concatenated, each forming a context to its neighbors. Experiments on online Hangul handwriting characters have proven the effect of the proposed augmentation in terms of highly intuitive segmentation as well as recognition performance and 13.2% error rate reduction.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.1
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• pp.83-95
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• 2010

This paper considers a firm that operates make-to-stock and make-to-order facilities in successive stages. The make-to-stock facility produces components which are consumed by the external market demand as well as the internal make-to-order operation. The make-to-order facility processes customer orders with the option of acceptance or rejection. In this paper, we address the problem of coordinating how to allocate the capacity of the make-to-stock facility to internal and external demands and how to control incoming customer orders at the make-to-order facility so as to maximize the firm's profit subject to the system costs. To deal with this issue, we formulate the problem as a Markov decision process and characterize the structure of the optimal inventory allocation and customer order control. In a numerical experiment, we compare the performance of the optimal policy to the heuristic with static inventory allocation and admission control under different operating conditions of the system.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.187-194
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• 2014

We consider a Bayesian nonignorable selection model to accommodate the selection bias. Markov chain Monte Carlo methods is known to be very useful to fit the nonignorable selection model. However, sensitivity to prior assumptions on parameters for selection mechanism is a potential problem. To quantify the sensitivity to prior assumption, the deviance information criterion and the conditional predictive ordinate are used to compare the goodness-of-fit under two different prior specifications. It turns out that the 'MLE' prior gives better fit than the 'uniform' prior in viewpoints of goodness-of-fit measures.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.245-254
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• 2014

The traditional methods of simulating daily precipitation have paid little attention to the inherent dependence structure between the total precipitation amount and the precipitation frequency for a fixed period of time. To address this issue, we propose a new simulation algorithm using copula in order to incorporate the dependence into the traditional methods. The algorithm consists of two parts: First, while reflecting the observed dependence, we generate the total precipitation amount (S) and the frequency (N) during the period of interest; then we simulate the daily precipitation whose aggregation matches the pair of (N; S) generated in the first part. Our result shows that the proposed method substantially improves the traditional methods.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.1
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• pp.30-37
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• 2016

A multi-server queueing system with an infinite buffer and impatient customers is analyzed. The system operates in the finite state Markovian random environment. The number of available servers, the parameters of the batch Markovian arrival process, the rate of customers' service, and the impatience intensity depend on the current state of the random environment and immediately change their values at the moments of jumps of the random environment. Dynamics of the system is described by the multi-dimensional asymptotically quasi-Toeplitz Markov chain. The ergodicity condition is derived. The main performance measures of the system are calculated. Numerical results are presented.

• International Journal of Quality Innovation
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• v.5 no.1
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• pp.1-9
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• 2004

The nonhomogeneous poisson process (NHPP) is often used to model repairable systems that are subject to a minimal repair strategy, with negligible repair times. In this situation, the system can be characterized by its intensity function. There have been many NHPP models according to intensity functions. However, the intensity function of system in use can be changed because of repair or its aging. We consider the single change point model as the modification of the power law process. The shape parameter of its intensity function is changed before and after the change point. We detect the presence of the change point using Bayesian methodology. Some numerical results are also presented.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.1
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• pp.1-8
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• 1994

In this paper, we have analyzed the performance of a BRAM (The Broadcasting Recognizing Access Method) protocol, as a CSMA/CA (Carrier Sense Multiple Access/Collision Avoidance) scheme, which is widely used in wireles LAN systems. We have selected a Fair BRAM protocol among CSMA/CA schemes, considering the fairness of channel usage and the simplicity of the protocol. We have compared the performance of BRAM protocol to that of CSMA/CD. to research the characteristics of BRAM in wireless LAN system. In order to analyze the performance of this system, we have set up an imbedded Markov chain and calculated state transition probabilities. Then we have calculated steady state probabilities and finally derived the throughput of a Fair BRAM moder. To verify our analysis, we have simulated practical models. Then, we have found that analytic results are very close to simulation ones. Our analysis of the BRAM protocol will be expected to be very helpful to design and evaluate a MAC (Media Access Control) protocol in wireless LAN systems.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.73.2-73.2
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• 2010

암흑에너지는 우주상수만으로 여러 우주론 관측 자료들을 잘 설명하고 있지만, 최근 SN Ia 자료가 축적됨에 따라 암흑에너지의 상태방정식 파라미터 $\omega$가 우주상수에서와 같이 -1인 상수인지, 시간에 따라 변하는지를 알아내기 위한 연구가 진행되고 있다. 본 연구에서는 $\omega$가 시간에 따라 갑자기 변하는(sudden jump) transition-$\omega$CDM 모형을 이용하여 SN Ia 자료를 Markov Chain Monte Carlo(MCMC) 방법을 통해 분석했다. Transition-$\omega$CDM 모형에서는 상수인 $\omega$의 값이 임의의 적색이동에서 변한다고 가정하였다. 분석에 사용된 SN Ia 데이터는 307개의 Union 자료와 90개의 CfA3 SN Ia가 추가된 Constitution 자료이며 개별적으로 분석됐다. 그 결과 transition 시기 전후 $\omega$ 값들의 확률밀도분포를 얻어내었고, 이를 통해 SN Ia의 특성을 조사하였다.

• Journal of Ship and Ocean Technology
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• v.2 no.1
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• pp.42-57
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• 1998

Genetic Algorithm (GA) is applied to obtain optimal Inspection plan for fatigue deteriorating structures. The optimization problem is defined so as to minimize inspection cost in the 1ifs-time of the structure under the constraint that the increment of failure probability in each inspection interval is maintained below a target value. Optimization parameters are the inspection timing and the inspection quality. The inspection timing is selected from the discrete intervals such as one year, two years, three years, etc. The inspection quality is selected from the followings; no inspection, normal inspection, sampling inspection or precise inspection. The applicability of the proposed GA approach is demonstrated through the numerical calculations assuming a structure consisting of four member sets. Influences of the level of target failure probability, initial defect condition and stress increase due to plate thickness reduction caused by corrosion on inspection planning are discussed.

• Journal of Korean Society for Quality Management
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• v.29 no.1
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• pp.113-127
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• 2001

Skip-lot sampling plans for lot-by-lot inspection are more desirable than the continuous sampling plans for units in modern mass production system under the condition of the submitted product is good. Perry(1973a, 1973b) extended the Dodge(1955)′s skip-lot sampling plans to single and two-level skip-lot sampling plans and Parker & Kessler (1981) modified Perry(1973a)′s plans so that a sample of size one is taken from every lot skipped during the skipping mode. In this paper, Perry(1973b)′s two-level skip-lot sampling plans are modified by applying Parker & Kessler′s plan, designated as MTSkSP1, MTSkSP2, MTSkSP3. Operating characteristic(OC) functions, average sample numbers(ASN) and average outgoing qualities(AOQ) for the proposed plans are derived using Markov chain properties and compared each other and Perry′s plans. The proposed plans not only reduce the ASN but also avoid the danger skipping lots entirely when the lots are produced during sudden "out-of-control".