• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.744-748
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• 2008

In this paper, we propose a novel technique that generate a new song with given example songs. Our system use k-th order Markov chain of which each state represents notes in a measure. Because we have to consider very high-dimensional space if we use notes in a measure as a state of Markov chain directly, we exploit a hierarchical clustering technique for given example songs to use each cluster as a state. Each given examples can be represented as sequences of cluster ID, and we use them for training data of the Markov chain. The resulting Markov chain effectively gives new song similar to given examples.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2253-2258
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• 2008

To design micro flow sensor varying depending on temperature of driving heater in the detector of Oxide semiconductor, Markov chain MCM(MCMCM), which is a kind of stochastic and microscopic method, was introduced. The formulation for the thermal transfer equation based on the FDM to obtain the MCMCM solution was performed and investigated, in steady state case. MCMCM simulation was successfully applied, so that its application can be expanded to a three-dimensional model with inhomogeneous material and complicated boundary.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.266-266
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• 2019

Marine accidents are increasing year by year, and various accidents occur such as engine failure, collision, stranding, and fire. These marine accidents present a risk of large casualties. It is important to prevent accidents beforehand. In this study, we propose a modeling to predict the occurrence of marine accidents by applying the Markov Chain Process that can predict the future based on past data. Applying the proposed modeling, the probability of future marine accidents was calculated and compared with the actual frequency. Through this, a probabilistic model was proposed to prepare a prediction system for marine accidents, and it is expected to contribute to predicting various marine accidents.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.147-157
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• 2017

The test of transition probabilities in panel Markov chains are introduced. We deal with the hypotheses whether panel Markov chains have the same transition probabilities or not for all times. We suggest a LR test statistic for the test and its limit distribution is derived. We perform a simulation study to examine the limit distribution of test statistics when the number of the individuals are large.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.263-275
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• 2014

The present study used a hierarchical Bayesian approach was used to develop a mixed effect model to describe the transitional behavior of subjects in time nonhomogeneous Markov chains. The posterior distributions of model parameters were not in analytically tractable forms; subsequently, a Gibbs sampling method was used to draw samples from full conditional posterior distributions. The proposed model was implemented with real data.

• Convergence Security Journal
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• v.14 no.4
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• pp.19-26
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• 2014

Mobile malicious code is typically spread by the worm, and although modeling techniques to analyze the dispersion characteristics of the worms have been proposed, only macroscopic analysis was possible while there are limitations in predicting on certain viruses and malicious code. In this paper, prediction methods have been proposed which was based on Markov chain and is able to predict the occurrence of future malicious code by utilizing the past malicious code data. The average value of the malicious code to be applied to the prediction model of Markov chain model was applied by classifying into three categories of the total average, the last year average, and the recent average (6 months), and it was verified that malicious code prediction possibility could be increased by comparing the predicted values obtained through applying, and applying the recent average (6 months).

• Journal of Information Management
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• v.20 no.1
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• pp.66-85
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• 1989

The purpose of this study is to verify the following two hypotheses by using a test collection of 3.815 documents on the subject of chemistry. First hypothesis is that a Markov chain model can be used t9 describe and predict authors' movements among subareas of a discipline. Second hypothesis is that a transition matrix of the Markov chain can be applied to describ the intellectual structure of a discipline en the multidimensional space. The results of this study have shown that the Markov chain is a good model to be used to study the movement of korean chemists in 7 subtopics in chemistry and understand the intellectual structure of chemistry.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.79-94
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• 2018

The purpose of this study is to specify a probabilistic tracking mechanism for customer luxury purchase implemented by hidden Markov model, Bayesian inference, customer satisfaction and net promoter score. In this paper, we have designed a probabilistic model based on customer's actual data containing purchase or non-purchase states by tracking the SPC chain : customer satisfaction -> customer referral -> purchase/non-purchase. By applying hidden Markov model and Viterbi algorithm to marketing theory, we have developed the statistical model related to probability theories and have found the best purchase pattern scenario from customer's purchase records.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.1013-1019
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• 2016

This paper describes a novel Context-awareness Markov Chain Prediction (CMCP) algorithm based on movement prediction using Markov chain in Delay Tolerant Network (DTN). The existing prediction models require additional information such as a node's schedule and delivery predictability. However, network reliability is lowered when additional information is unknown. To solve this problem, we propose a CMCP model based on node behaviour movement that can predict the mobility without requiring additional information such as a node's schedule or connectivity between nodes in periodic interval node behavior. The main contribution of this paper is the definition of approximate speed and direction for prediction scheme. The prediction of node movement forwarding path is made by manipulating the transition probability matrix based on Markov chain models including buffer availability and given interval time. We present simulation results indicating that such a scheme can be beneficial effects that increased the delivery ratio and decreased the transmission delay time of predicting movement path of the node in DTN.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.3
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• pp.36-41
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• 2005

페트리 네트(Petri Nets)는 이산 사건 시스템을 모델링할 수 있는 그래픽하고, 수학적인 도구이다. 본 연구는 유연제조 시스템을 확률적인 페트리 네트(Stochastic Petri Nets)중의 하나인 임베디드 마코프 체인(Embeded Markov Chain)에 도입하고, 임베디드 마코프 체인의 방법 중에 하나인 일반화된 확률적 페트리 네트(Generalized Stochastic Perti Nets)에 적용시켰다. 그리고 결과치의 정확성을 알아내기 위하여, 페트리 네트 시뮬레이션과 아레나를 사용하여 실행하였다.