• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.177-184
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• 1992

The control policy algorithm is examined and compared in this study. This research investigates a two state partially observable Markov chain in which only deterioration can occur and for which the only actions possible are to replace or to live alone. The goal of this research is to compare the computational efficiencies of control policy algorithm. One is Sondik's algorithms and the other one is jump algorithm.

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

• ETRI Journal
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• v.34 no.6
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• pp.816-826
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• 2012

Self-healing Ethernet rings show promise for realizing the SONET/SDH-grade resilience in Carrier Ethernet infrastructures. However, when a ring is faulty, high-priority protection messages are processed in less time than low-priority data frames are processed. In this situation, any delayed data frames either being queued or traveling through long ring spans will cause the ring nodes to generate incorrect forwarding information. As a result, the data frames spread in the wrong direction, causing the ring to become unstable. To solve this problem, we propose four schemes, that is, dual flush, flush delay timer setting, purge triggering, and priority setting, and evaluate their protection performance under various traffic conditions on a ring based on the Ethernet ring protection (ERP) method. In addition, we develop an absorbing Markov chain model of the ERP protocol to observe how traffic congestion can impact the protection performance of the proposed priority setting scheme. Based on our observations, we propose a more reliable priority setting scheme, which guarantees faultless protection, even in a congested ring.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.1
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• pp.53-60
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• 2014

Redundant handovers cause degraded quality of service to passengers in vehicle. This paper proposes a handover scheme suitable for users traveling in vehicles, which enables continuous learning of the handover process using a discrete-time Markov chain (DTMC). Through AdaBoost machine learning algorithm, the proposed handover scheme avoids unnecessary handover trials when a short dwell time in a target cell is expected or when the target cell is an intermediate cell through which the vehicle quickly passes. Simulation results show that the proposed scheme reduces the number of handover occurrences and maintains adequate throughput.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.576-585
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• 2017

Dynamic thermal rating (DTR) of overhead transmission lines can provide a significant increase in transmission capacity compared to the static thermal rating. However, the DTR are usually estimated by the traditional thermal model of overhead conductor that is highly dependent on the solar, wind speed and wind direction data. Consequently, the estimated DTR would be unreliable and the safety of transmission lines would be reduced when the solar and wind sensors are out of function. To address this issue, this study proposed a novel thermal model of overhead conductor based on the thermal-electric analogy theory and Markov chain. Using this thermal model, the random variation of conductor temperature can be simulated with any specific current level and ambient temperature, even if the solar and wind sensors are out of function or uninstalled. On this basis, an estimation method was proposed to determine the DTR in the form of probability. The laboratory experiments prove that the proposed method can estimate the DTR reliably without measured solar and wind data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2450-2469
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• 2018

In this paper, we develop a spatiotemporal model to analysis of cellular user in underlay D2D communication by using stochastic geometry and queuing theory. Firstly, by exploring stochastic geometry to model the user locations, we derive the probability that the SINR of cellular user in a predefined interval, which constrains the corresponding transmission rate of cellular user. Secondly, in contrast to the previous studies with full traffic models, we employ queueing theory to evaluate the performance parameters of dynamic traffic model and formulate the cellular user transmission mechanism as a M/G/1 queuing model. In the derivation, Embedded Markov chain is introduced to depict the stationary distribution of cellular user queue status. Thirdly, the expressions of performance metrics in terms of mean queue length, mean throughput, mean delay and mean dropping probability are obtained, respectively. Simulation results show the validity and rationality of the theoretical analysis under different channel conditions.

• Journal of Korea Water Resources Association
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• v.37 no.4
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• pp.315-328
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• 2004

Recent increase of green house gases may increase the frequency of meteorological extremes. In this study, using the index and meteorological data generated by the Markov chain model under the condition of GCM predictions, the possible width of variability of flood and drought occurrences were predicted. As results, we could find that the frequency of both floods and droughts would be increased to make the water resources planning and management more difficult. Thus, it is recommended to include the effect of climate change on water resources in the related policy making.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.411-423
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• 2009

In the current paper, by extending Verall (1990)'s work, we propose a new Bayesian model for analyzing run-off triangle data. While Verall's (1990) work only account for the calendar year and evolvement time effects, our model further accounts for the "absolute time" effects. We also suggest a Markov Chain Monte Carlo method that can be used for estimating the proposed model. We apply our proposed method to analyzing three empirical examples. The results demonstrate that our method significantly reduces prediction error when compared with the existing methods.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.41-44
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• 2005

Cytokines play a crucial role in the immune and inflammatory responses. But because of the high evolutionary rate of these proteins, the similarity between different members of their family is very low, which makes the identification of novel members of cytokines very difficult. According to this point, a new bioinformatic strategy to identify novel cytokine of the short-chain and long-chain 4${\alpha}$ helix cytokine using hidden markov model (HMM) is proposed in the paper. As a result, two motifs were created on the two train data sets, which were used to search three different databases. In order to improve the result, a strict criterion is established to filter the novel cytokines in the subject proteins. Finally, according to their E-value, scores and the criterion, four subject proteins are predicted to be possible novel cytokines for each family respectively.

• Journal of Wetlands Research
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• v.10 no.2
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• pp.143-153
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• 2008

The purpose of this paper is to evaluate impacts of ENSO on frequency and spatial distribution of rainfall in South Korea. In this paper, First, rainfall data in 60 climate stations were categorized into Warm(El Nino), Cold(La Nina), Normal episodes based on the Cold & Warm Episodes by Season, then 100 years of daily rainfall data were generated for each episodic events(El Nino, La Nina, Normal) using Markov Chain model. Finally, Estimating frequency based flood and comparison for each episodes were conducted. From the results, it shows that there are significant changes in the rainfall frequency and the spatial distribution of rainfall among Warm(EL Nino), Cold(La Nina) and Normal episodes.