• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.1
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• pp.28-34
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• 2004

In this study, new way of evaluating manufacturing cost Is organized and applied. In real manufacturing circumstances, tolerances of parts and assemblies are closely related to the cost. Several researches have been tried to identify the relations and set models. Moreover tolerances have influences on the maintenance of the manufacturing facilities. However Past researches have not considered the processing cost for the failed products. Therefore maintenance costs are represented as stochastic expressions, which include reliability of assembly and facilities. The stochastic nature of the maintenance cost is modeled and solved using Markov chain approach. Results show that this approach gives reliable estimations with remarkable computing time reduction.

• Journal of the Korean Statistical Society
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• v.31 no.1
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• pp.63-75
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• 2002

Most attempts at Bayesian analysis of neural networks involve hierarchical modeling. We believe that similar results can be obtained with simpler models that require less computational effort, as long as appropriate restrictions are placed on parameters in order to ensure propriety of posterior distributions. In particular, we adopt a model first introduced by Lee (1999) that utilizes an improper prior for all parameters. Straightforward Gibbs sampling is possible, with the exception of the bias parameters, which are embedded in nonlinear sigmoidal functions. In addition to the problems posed by nonlinearity, direct sampling from the posterior distributions of the bias parameters is compounded due to the duplication of hidden nodes, which is a source of multimodality. In this regard, we focus on sampling from the marginal posterior distribution of the bias parameters with Markov chain Monte Carlo methods that combine traditional Metropolis sampling with a slice sampler described by Neal (1997, 2001). The methods are illustrated with data examples that are largely confined to the analysis of nonparametric regression models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.2
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• pp.1-8
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• 2011

This paper proposes a variable sampling interval multivariate $T^2$ control chart with sampling at fixed times, where samples are taken at specified equally spaced fixed time points and additional samples are allowed between these fixed times when indicated by the preceding $T^2$ statistics. At fixed sampling points, the $T^2$ statistics are composed of all quality characteristics and a part of quality characteristics are selected to obtain $T^2$ statistics at additional sampling points. A Markov chain approach is used to evaluate the performance of the proposed chart. Numerical studies for the performance of the proposed chart show that the proposed chart reduces the observations obtained from a process and detects the assignable cause of a process with low correlated quality characteristics quickly.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.428-432
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• 2012

SWAT모형을 이용하여 악근천, 호근천, 동흥천을 대표 3개 유역으로 구분하여 1990년 토지이용상태에 1980년부터 1999년까지의 기상자료를 사용하였고 2000년 토지이용상태에 2000년부터 2010년까지의 기상자료를 적용하여 분석한 결과, 적용 기간 평균 지하수 함양률은 30%로 분석되었다. 이러한 연구결과는 기존의 제주지역 지하수 함양량 분석연구에서 나타난 40-50%보다 훨씬 적은 값으로 나타나고 있음을 알 수 있었다. 이 결과는 투수성 다공질 지층이 제주지역의 지질특성을 고려하더라도 개발형태가 비투수성 포장형태이고, 개발된다면 육지지역과 같은 지하수함양특성과 비슷할 수 밖에 없음을 알 수 있었다. 또한 Markov-chain을 이용하여 장래토지이용상태를 분석한 결과 장래의 토지이용은 2000년 현재에 비해 산림 3.4%감소, 농경지 0.2% 증가, 수계 1.0% 증가, 도심지 0.5%증가 하는 것으로 나타났다. 토지이용상태에 따른 SWAT모형 분석을 비교한 결과 현재에 비해 유출량은 평균 22mm 증가하였으며, 증발산량은 평균 5mm감소, 함양량은 평균15mm감소하여 0.7% 정도 감소하는 것으로 토지이용상태가 함양량에 영향을 미치는 것으로 분석되었다.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.51.3-52
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• 2020

We present the status of the development of a Markov Chain Monte Carlo (MCMC) parameter estimation (PE) pipeline for compact binary coalescences (CBCs) with the Japanese KAGRA gravitational-wave (GW) detector. The pipeline is included in the KAGRA Algorithm Library (KAGALI). Basic functionalities are benchmarked from the LIGO Algorithm Library (LALSuite) but the KAGRA MCMC PE pipeline will provide a simpler, memory-efficient pipeline to estimate physical parameters from gravitational waves emitted from compact binaries consisting of black holes or neutron stars. Applying inspiral-merge-ringdown and inspiral waveforms, we performed simulations of various black hole binaries, we performed the code sanity check and performance test. In this talk, we present the situation of GW observation with the Covid-19 pandemic. In addition to preliminary PE results with the KAGALI MCMC PE pipeline, we discuss how we can optimize a CBC PE pipeline toward the next observation run.

• 한국해양학회지
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• v.22 no.2
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• pp.57-62
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• 1987

The Markov chain properties of the sea surface temperature (SST) anomalies, namely, the dependency of the monthly SST anomaly on that of the previous month, are studied based on the SST data for 28years(1957-1984) at 5 stations in the southeastern coast of Korea. Wi classified the monthly SST anomalies at each station into the low, the normal and the high state, and computed transition probabilities between SST anomalies of two successive months The standard deviation of SST anomalies at each station is used as a reference for the classification of SST anomalies into 3states. The transition probability of the normal state to remain in the same state is about 0.8. The transition probability of the high or the low states to remain in the same state is about one half. The SST anomalies have almost no probability to transit from the high (the low) state to the low (the high) state. Statistical tests show that the Markov chain properties of SST anomalies are stationary in tine and homogeneous in space. The multi-step Markov chain analysis shows that the 'memory' of the SST anomalies at the coastal stations remains about 3 months.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.71-78
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• 2020

Recently, as the issue of gentrification emerges, it becomes important to understand the dynamics of local commercial district, which plays the important role for facilitating the local economy and building the community in a city. This paper attempts to provide the framework for systemically analyzing and understanding the local commercial district. Then, this paper empirically analyzes the patterns of sales and flow of floating population by focusing on two representative local commercial districts in Seoul. In addition, the floating population data from telecommunication bases is further modeled with Markov chain for systemically understanding the local commercial districts. Finally, the transition patterns and consumption amounts of floating population are comprehensively analyzed for providing the implications on the evolutions of local commercial districts in a city. We expect that findings of our study could contribute to the economic growth of local commercial district, which could lead to the continuous development of city economy.

• Journal of Korea Water Resources Association
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• v.37 no.4
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• pp.305-314
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• 2004

Climate change mainly due to the increase of green house gases cause different patterns of water cycle within the basin. However, it is common that current planning and management practices do not consider the effect of the climate change. So, this study evaluated the effect of climate change on the water circulation within the watershed. This study used several GCM simulations for the double $CO_2$condition for the generation of temperature and rainfall series using the Markov chain. Daily runoff series for 100 years were generated using a rainfall-runoff model. As results. annual temperature increase by ＋3.2 ∼＋4.6$^{\circ}C$, annual precipitation change －7 ∼ ＋8 %, annual runoff change －14 ∼ ＋7 %, and potential evapotranspiration amount change ＋3 ∼＋4 % for the change of 1 $^{\circ}C$ are found to be expected depending on GCM simulations. Even though the simulation results are very dependent on the GCM predictions considered, overall variability of runoff is expected to become higher than the current state.

• Journal of Korea Water Resources Association
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• v.48 no.12
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• pp.969-979
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• 2015

This study applied a probabilistic-based hidden Markov model (HMM) to better characterize drought patterns. In addition, a copula-based bivariate drought frequency analysis was employed to further investigate return periods of the current drought condition in year 2015. The obtained results revealed that western Kangwon area was generally more vulnerable to drought risk than eastern Kangwon area using the 40-year data. Imjin-river watershed including Cheorwon area was the most vulnerable area in terms of severe drought events. Four stations in Han-river watershed showed a joint return period exceeding 1,000 years associated with the drought duration and severity in 2014-2015. Especially, current drought status in Northern Han-river and Imjin-river watershed is most severe drought exceeding 100-year return period.

• Journal of the Korean Geographical Society
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• v.52 no.1
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• pp.123-141
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• 2017

This study predicted urban green spaces for 2020 based on two scenarios keeping or freeing the green-belt in the Daegu metropolitan city using a hybrid Cellular Automata(CA)-Markov model and analyzed the spatial dynamics of urban green spaces between 2009 and 2020 using a land cover change detection technique and spatial metrics. Markov chain analysis was employed to derive the transition probability for projecting land cover change into the future for 2020 based on two land cover maps in 1998 and 2009 provided by the Ministry of Environment. Multi-criteria evaluation(MCE) was adopted to develop seven suitability maps which were empirically derived in relation to the six restriction factors underlying the land cover change between the years 1998 and 2009. A hybrid CA-Markov model was then implemented to predict the land cover change over an 11 year period to 2020 based on two scenarios keeping or freeing the green-belt. The projected land cover for 2009 was cross-validated with the actual land cover in 2009 using Kappa statistics. Results show that urban green spaces will be remarkably fragmented in the suburban areas such as Dalseong-gun, Seongseo, Ansim and Chilgok in the year 2020 if the Daegu metropolitan city keeps its urbanization at current pace and in case of keeping the green-belt. In case of freeing the green-belt, urban green spaces will be fragmented on the fringes of the green-belt. It is thus required to monitor urban green spaces systematically considering the spatial change patterns identified by this study for sustainably managing them in the Daegu metropolitan city in the near future.