• Journal of the Korea Society for Simulation
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• v.33 no.1
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• pp.19-26
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• 2024

The phase-type, PH, distribution is defined as the time to absorption into a terminal state in a continuous-time Markov chain. As the PH distribution includes family of exponential distributions, it has been widely used in stochastic models. Since the PH distribution is represented and generated by an initial probability vector and a generator matrix which is called the Markovian representation, we need to find a vector and a matrix that are consistent with given set of moments if we want simulate a PH distribution. In this paper, we propose an approach to simulate a PH distribution based on distribution function which can be obtained directly from moments. For the simulation of PH distribution of order 2, closed-form formula and streamlined procedures are given based on the Jordan decomposition and the minimal Laplace transform which is computationally more efficient than the moment matching methods for the Markovian representation. Our approach can be used more effectively than the Markovian representation in generating higher order PH distribution in queueing network simulation.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.107-119
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• 2020

This study analyzed past drought characteristics based on the observed rainfall data and performed a long-term outlook for future extreme droughts using Representative Concentration Pathways 8.5 (RCP 8.5) climate change scenarios. Standardized Precipitation Index (SPI) used duration of 1, 3, 6, 9 and 12 months, a meteorological drought index, was applied for quantitative drought analysis. A single long-term time series was constructed by combining daily rainfall observation data and RCP scenario. The constructed data was used as SPI input factors for each different duration. For the analysis of meteorological drought observed relatively long-term since 1954 in Korea, 12 rainfall stations were selected and applied 10 general circulation models (GCM) at the same point. In order to analyze drought characteristics according to climate change, trend analysis and clustering were performed. For non-stationary frequency analysis using sampling technique, we adopted the technique DEMC that combines Bayesian-based differential evolution ("DE") and Markov chain Monte Carlo ("MCMC"). A non-stationary drought frequency analysis was used to derive Severity-Duration-Frequency (SDF) curves for the 12 locations. A quantitative outlook for future droughts was carried out by deriving SDF curves with long-term hydrologic data assuming non-stationarity, and by quantitatively identifying potential drought risks. As a result of performing cluster analysis to identify the spatial characteristics, it was analyzed that there is a high risk of drought in the future in Jeonju, Gwangju, Yeosun, Mokpo, and Chupyeongryeong except Jeju corresponding to Zone 1-2, 2, and 3-2. They could be efficiently utilized in future drought management policies.

• Journal of Korean Society of Forest Science
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• v.89 no.5
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• pp.655-665
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• 2000

Taking account of the structural variation on species composition by topography, the successional trends were comparatively analyzed for the three topographic positions (valley, mid-slope, and ridge) in the natural deciduous forest of Mt. Chumbong area. The analysis was based upon the subsequent process of generation replacement by understory saplings and seedlings over the overstory trees which will be eventually fallen down. This study adopted the plot sampling method, establishing twenty $20m{\times}20m$ quadrats and collecting vegetation and site data on each different topographic position. The transition matrix model, which was modified from the mathematical theory of Markov chain, was employed to analyze the successional trends and thereafter to predict the overstory species composition in the future for each different topographic position. In valley, the simulation indicated the remarkable decrease in the proportion of species composition of present dominants Quercus mongolica and Fraxinus mandshurica from current 23% and 21% to around 4% of each at the steady state, which is predicted to take less than 200 years. On the other hand, the proportion of such species as Abies holophylla, Acer mono, Tilia amurensis, and Ulmus laciniata will increase at the steady state. In mid-slope, the result showed the remarkable decrease in the proportion of Juglans mandshurica, Kalopanax pictus, and Tilia amurensis from current 15%, 8%, and 15% to 2%, 1%, and 5%, respectively, at steady state predicted to take more than 250 years. In ridge, the current dominant Quercus mongolica was predicted to be decreased dramatically from 58% to 8% at steady state which could be achieved about 200 years. On the contrary, the proportion of Acer mono and Tilia amurensis will be increased from current 4% and 3% to more than 20% and 40%, respectively, at the steady state. Overall results suggested that the study forest is more likely seral rather than climax community. Even though a lot of variation is inevitable due to various kinds of site and vegetation development, the study forest is considered to be more than 200 years away from the steady state or climax in terms of overstory species composition.

• Journal of Life Science
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• v.21 no.3
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• pp.385-392
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• 2011

The otter (Lutra lutra) in Korea is classified as a first grade endangered species and is managed under state control. We performed a phylogenetic analysis of the otter that inhabits the Changnyeong, Jinju, and Geoje areas in Gyeongsangnamdo, Korea using mtDNA and microsatellite (MS) markers. As a result of the analysis using the 676-bp D-loop sequence of mtDNA, six haplotypes were estimated from five single nucleotide polymorphisms. The genetic distance between the Jinju and Geoje areas was greater than distances within the areas, and the distance between Jinju and Geoje was especially clear. From the phylogenetic tree estimated using the Bayesian Markov chain Monte Carlo analysis by the MrBays program, two subgroups, one containing samples from Jinju and the other containing samples from the Changnyeong and Geoje areas were clearly identified. The result of a parsimonious median-joining network analysis also showed two clear subgroups, supporting the result of the phylogenetic analysis. On the other hand, in the consensus tree estimated using the genetic distances estimated from the genotypes of 13 MS markers, there were clear two subgroups, one containing samples from the Jinju, Geoje and Changnyeong areas and the other containing samples from only the Jinju area. The samples were not identically classified into each subgroup defined by mtDNA and MS markers. It could be inferred that the differential classification of samples by the two different marker systems was because of the different characteristics of the marker systems used, that is, the mtDNA was for detecting maternal lineage and the MS markers were for estimating autosomal genetic distances. Nonetheless, the results from the two marker systems showed that there has been a progressive genetic fixation according to the habitats of the otters. Further analyses using not only newly developed MS markers that will possess more analytical power but also the whole mtDNA are needed. Expansion of the phylogenetic analysis using otter samples collected from the major habitats in Korea should be helpful in scientifically and efficiently maintaining and preserving them.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.12
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• pp.1919-1927
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• 1993

A new MAC protocol has been proposed and analysed to relieve the unfairness problems exhibited by the basic version of the DQDB standard. DQDB MAC protocol has the unfairness problems in throughputs. message delay and so or. And when the slots are reused or the file transmissions takes long, the unfairness problems in the system become worse. The new access protocol proposed here, which of called the Balanced DQDB, guarantees a fair bandwidth distribution by using one bit of the dual bus network protocol and keeps up all characteristics of DQDB. the DQDB analysis model introduced by Wen Jing, et al, was considered to analyse a sequential balance distribution of solts. And the probabilities of the empty in operation mode were represented to determine the probabilities for busy bits to generate on each node of the bus using the Markov chain. Through the simulations. the performances of the proposed Balanced DQDB and that of the standard DQDB of the BWB mechanism were compared at the state that the values of the RQ or CD counter on each node varied dynamically. As the results, it is shown that the Balanced DQDB has the decrement of throughputs in upstream, but the numbers of the used empty slots at each node of the Balanced DQDB had more than that of the others because the Balanced DQDB has over 0.9 throughputs in the 70~80% nodes of total node and it has constant throughputs at each node. And there results were analogous to that of the analytical model.

• Journal of KIISE:Information Networking
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• v.32 no.4
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• pp.515-524
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• 2005

As the number of the mobile nodes (MNs) increases in the networks, the signaling traffic generated by mobility management for MNs will increase explosively, and such a phenomenon will probably affect overall network performance. In this paper, we propose a novel analytical approach using a continuous-time Markov chain model and hierarchical network model for the analysis on the signaling load of representative IPv6 mobility support Protocols such as Mobile IPv6 (MIPv6) and Hierarchical Mobile IPv6 (HMIPv6). According to these analytical modeling, this paper derives the various signaling costs, which are generated by an MN during its average domain residence time when MIPv6 and HMIPv6 are deployed under the same network architecture, respectively. In addition, based on these derived costs, we investigate the effects of various mobility/traffic-related parameters on the signaling costs generated by an MN under MIPv6 and HMIPv6. The analytical results show that as the average moving speed of an MN gets higher and the binding lifetime is set . to the larger value, and as its average packet arrival rate gets lower, the total signaling cost generated during its average domain residence time under HMIPv6 will get relatively lower than that under MIPv6, and that under the reverse conditions, the total signaling cost under MIPv6 will get relatively lower than that under HMIPv6.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.9
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• pp.4049-4054
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• 2014

Background: Race and ethnicity are significant factors in predicting survival time of breast cancer patients. In this study, we applied advanced statistical methods to predict the survival of White non-Hispanic female breast cancer patients, who were diagnosed between the years 1973 and 2009 in the United States (U.S.). Materials and Methods: Demographic data from the Surveillance Epidemiology and End Results (SEER) database were used for the purpose of this study. Nine states were randomly selected from 12 U.S. cancer registries. A stratified random sampling method was used to select 2,000 female breast cancer patients from these nine states. We compared four types of advanced statistical probability models to identify the best-fit model for the White non-Hispanic female breast cancer survival data. Three model building criterion were used to measure and compare goodness of fit of the models. These include Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC). In addition, we used a novel Bayesian method and the Markov Chain Monte Carlo technique to determine the posterior density function of the parameters. After evaluating the model parameters, we selected the model having the lowest DIC value. Using this Bayesian method, we derived the predictive survival density for future survival time and its related inferences. Results: The analytical sample of White non-Hispanic women included 2,000 breast cancer cases from the SEER database (1973-2009). The majority of cases were married (55.2%), the mean age of diagnosis was 63.61 years (SD = 14.24) and the mean survival time was 84 months (SD = 35.01). After comparing the four statistical models, results suggested that the exponentiated Weibull model (DIC= 19818.220) was a better fit for White non-Hispanic females' breast cancer survival data. This model predicted the survival times (in months) for White non-Hispanic women after implementation of precise estimates of the model parameters. Conclusions: By using modern model building criteria, we determined that the data best fit the exponentiated Weibull model. We incorporated precise estimates of the parameter into the predictive model and evaluated the survival inference for the White non-Hispanic female population. This method of analysis will assist researchers in making scientific and clinical conclusions when assessing survival time of breast cancer patients.

• Korean Journal of Ichthyology
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• v.21 no.4
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• pp.221-226
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• 2009

Six microsatellite DNA markers were used to investigate the genetic variability between wild populations and cultured stocks of olive flounder Paralichthys olivaceus. The average of observed (Ho) and expected heterozygosity (He) ranged from 0.722 to 0.959, and from 0.735 to 0.937, respectively. There was no distinguishable difference between the wild populations and cultured stocks in terms of the observed and expected heterozygosities. However, number of alleles per locus differed markedly between the two fish groups: 19.7 to 21.8 for the wild populations and 12.0 to 14.7 for the cultured stocks. This result gives important information concerning the production of seedling for the improvement of genetic diversity in this species.

• Journal of Korea Water Resources Association
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• v.41 no.1
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• pp.49-63
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• 2008

The Bayesian MCMC(Bayesian Markov Chain Monte Carlo) and the MLE(Maximum Likelihood Estimation) methods using a quadratic approximation are applied to perform the at-site low flow frequency analysis at the 4 stage stations (Nakdong, Waegwan, Goryeonggyo, and Jindong). Using the results of two types of the estimation method, the frequency curves including uncertainty are plotted. Eight case studies using the synthetic flow data with a sample size of 100, generated from 2-parmeter Weibull distribution are performed to compare with the results of analysis using the MLE and the Bayesian MCMC. The Bayesian MCMC and the MLE are applied to 36 years of gauged data to validate the efficiency of the developed scheme. These examples illustrate the advantages of the Bayesian MCMC and the limitations of the MLE based on a quadratic approximation. From the point of view of uncertainty analysis, the Bayesian MCMC is more effective than the MLE using a quadratic approximation when the sample size is small. In particular, the Bayesian MCMC is a more attractive method than MLE based on a quadratic approximation because the sample size of low flow at the site of interest is mostly not enough to perform the low flow frequency analysis.

• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.505-516
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• 2012

The study applies a hydrologic simulation model, HEC-1 developed by Hydrologic Engineering Center to Daecheong dam watershed for modeling hourly inflows of Daecheong dam. Although the HEC-1 model provides an automatic optimization technique for some of the parameters, the built-in optimization model is not sufficient in estimating reliable parameters. In particular, the optimization model often fails to estimate the parameters when a large number of parameters exist. In this regard, a main objective of this study is to develop Bayesian Markov Chain Monte Carlo simulation based HEC-1 model (BHEC-1). The Clark IUH method for transformation of precipitation excess to runoff and the soil conservation service runoff curve method for abstractions were used in Bayesian Monte Carlo simulation. Simulations of runoff at the Daecheong station in the HEC-1 model under Bayesian optimization scheme allow the posterior probability distributions of the hydrograph thus providing uncertainties in rainfall-runoff process. The proposed model showed a powerful performance in terms of estimating model parameters and deriving full uncertainties so that the model can be applied to various hydrologic problems such as frequency curve derivation, dam risk analysis and climate change study.