• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.743-752
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• 2007

Proteins combine with other materials to achieve their function and have similar function if their active sites are similar. Thus we can infer the function of protein by identifying the binding area of proteins. This paper suggests the novel method to select binding area of protein using MCL (Markov Cluster) algorithm. We construct the distance matrix from surface residues distance on protein. Then this distance matrix is transformed to connectivity matrix for applying MCL process. We adopted Catalytic Site Atlas (CSA) data to evaluate the proposed method. In the experimental result using CSA data (94 selected single chain proteins), our algorithm detects the 91 (97%) binding area near by active site of each protein. We introduced a new geometrical features and this mainly contributes to reduce the time to analyze the protein by selecting the residues near by active site.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.4
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• pp.421-431
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• 2023

Sewer deterioration models can offer important information on prediction of future condition of the asset to decision makers in their implementing sewer pipe networks management program. In this study, Markov chain model was used to estimate sewer deterioration trend based on the historical structural condition assessment data obtained by CCTV inspection. The data used in this study were limited to Hume pipe with diameter of 450 mm and 600 mm in three sub-catchment areas in city A, which were collected by CCTV inspection projects performed in 1998-1999 and 2010-2011. As a result, it was found that sewers in sub-catchment area EM have deteriorated faster than those in other two sub-catchments. Various main defects were to generate in 29% of 450 mm sewers and 38% of 600 mm in 35 years after the installation, while serious failure in 62% of 450 mm sewers and 74% of 600 mm in 100 years after the installation in sub-catchment area EM. In sub-catchment area SN, main defects were to generate in 26% of 450 mm sewers and 35% of 600 mm in 35 years after the installation, while in sub-catchment area HK main defects were to generate in 27% of 450 mm sewers and 37% of 600 mm in 35 years after the installation. Larger sewer pipes of 600 mm were found to deteriorate faster than smaller sewer pipes of 450 mm by about 12 years. Assuming that the percentage of main defects generation could be set as 40% to estimate the life expectancy of the sewers, it was estimated as 60 years in sub-catchment area SN, 42 years in sub-catchment area EM, 59 years in sub-catchment area HK for 450 mm sewer pipes, respectively. For 600 mm sewer pipes, on the other hand, it was estimated as 43 years, 34 years, 39 years in sub-catchment areas SN, EM, and HK, respectively.

• Journal of Korea Water Resources Association
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• v.50 no.4
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• pp.277-288
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• 2017

A probabilistic risk analysis of levee system estimates the overall level of flood risk associated with the levee system, according to a series of possible flood scenarios. It requires the uncertainty analysis of all the risk components, including hydrological, hydraulic and geotechnical parts computed by employing MCMC (Markov Chain Monte Carlo), MCS (Monte Carlo Simulation) and FOSM (First-Order Second Moment), presents a joint probability combined each probability. The methodology was applied to a 12.5 km reach from upstream to downstream of the Gangjeong-Goryeong weir, including 6 levee reaches, in Nakdong river. Overtopping risks were estimated by computing flood stage corresponding to 100/200 year high quantile (97.5%) design flood causing levee overflow. Geotechnical risks were evaluated by considering seepage, slope stability, and rapid drawdown along the levee reach without overflow. A probability-based compound risk will contribute to rising effect of safety and economic aspects for levee design, then expect to use the index for riverside structure design in the future.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.9
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• pp.25-37
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• 2007

The existing route re-establishment methods which intend to extend the lifetime of the network attempt to find new routes in order not to overly consume energy of certain nodes. These methods outperform other routing algorithms in the network lifetime extension aspect because they try to consume energy evenly for the entire network. However, these algorithms involve heavy signaling overheads because they find new routes based on the flooding method and route re-acquisition occurs often. Because of the overhead they often can not achieve the level of performance they intend to. In this paper, we propose a new route re-acquisition algorithm ARROW which takes into account the cost involved in the packet transmission and the route re-acquisition. Since the proposed algorithm considers future route re-acquisition costs when it first finds the route, it spends less energy to transmit given amount of data while evenly consuming the energy as much as possible. Using 2-dimensional Markov Chain model, we compare the performance of the proposed algorithm and that of other algorithms. Analysis results show that the proposed algorithm outperforms the existing route re-acquisition methods in the signaling overhead and network lifetime aspects.

• Journal of Korean Society of Forest Science
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• v.81 no.4
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• pp.325-336
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• 1992

The successional status and potential natural vegetation were examined in a mixed broadleaved-Abies forest located at Mt, Odae National Park. The examination was based on the subsequent process of generation replacement by understory saplings for the dominant canopy trees within 88 $5m{\times}50m$ belt transects. The transition matrix model, which was modified from mathematical theory of Markov chain, was employed to analyze the successional status of the study forest. The model suggests that the study forest is still seral, and it is considered to be more than 700 years away from the steady state or climax in terms of species composition. The simulations predict a remarkable decrease in the proportion of species composition of the present dominant Quercus mongolica and Tilia amurensi.s from current 28% and 13% to less than 3% and 5%, respectively, at the steady state. On the contrary, the proportions of Abies holophylla, Acer pseudo-sieboldianum, Carpinus cordata, and Pinus koraiensis will increase at the steady state. The ratio of mixture between deciduous and coniferous trees will be gradually changed from current 6.5 : 3.5 to 5.0 : 5.0 at equilibrium. Discussion for the problems of Quercus mongolica in successional status noted that the species behaved as a mid-successional dominant, not a climax species in the study forest. The hypothesis and sensitivity of the transition matrix model were also discussed to evaluate the applicability to the real situation. The overall results indicated that the present dynamics of the forest must reflect the seral state due to previous disturbance mainly by hyman related interference.

• Journal of Korea Water Resources Association
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• v.41 no.1
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• pp.35-47
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• 2008

The low flow analysis is an important part in water resources engineering. Also, the results of low flow frequency analysis can be used for design of reservoir storage, water supply planning and design, waste-load allocation, and maintenance of quantity and quality of water for irrigation and wild life conservation. Especially, for identification of the uncertainty in frequency analysis, the Bayesian approach is applied and compared with conventional methodologies in at-site low flow frequency analysis. In the first manuscript, the theoretical background for the Bayesian MCMC (Bayesian Markov Chain Monte Carlo) method and Metropolis-Hasting algorithm are studied. Two types of the prior distribution, a non-data- based and a data-based prior distributions are developed and compared to perform the Bayesian MCMC method. It can be suggested that the results of a data-based prior distribution is more effective than those of a non-data-based prior distribution. The acceptance rate of the algorithm is computed to assess the effectiveness of the developed algorithm. In the second manuscript, the Bayesian MCMC method using a data-based prior distribution and MLE(Maximum Likelihood Estimation) using a quadratic approximation are performed for the at-site low flow frequency analysis.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.833-845
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• 2011

This paper conducts a statistical analysis of extreme values for both daily log-returns and daily negative log-returns, which are computed using a collection of KOSPI data from January 3, 1998 to August 31, 2011. The Poisson-GPD model is used as a statistical analysis model for extreme values and the maximum likelihood method is applied for the estimation of parameters and extreme quantiles. To the Poisson-GPD model is also added the Bayesian method that assumes the usual noninformative prior distribution for the parameters, where the Markov chain Monte Carlo method is applied for the estimation of parameters and extreme quantiles. According to this analysis, both the maximum likelihood method and the Bayesian method form the same conclusion that the distribution of the log-returns has a shorter right tail than the normal distribution, but that the distribution of the negative log-returns has a heavier right tail than the normal distribution. An advantage of using the Bayesian method in extreme value analysis is that there is nothing to worry about the classical asymptotic properties of the maximum likelihood estimators even when the regularity conditions are not satisfied, and that in prediction it is effective to reflect the uncertainties from both the parameters and a future observation.

• Journal of Korea Water Resources Association
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• v.42 no.9
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• pp.747-758
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• 2009

In this study, long-term variabilities of rainfall-occurrence characteristics are analyzed using rainfall data at Seoul, which is the longest data record existing in world. first, the accuracy of Chukwooki data set (CWK) are evaluated in view of rainfall-occurrence probability by analyzing the transition probabilities and occurrence characteristics based on Markov chain. And long-term inter-monthly variabilities of transition probabilities are analyzed using two dimensional LOWESS regression. From the results of analyzed transition probabilities and occurrence characteristics, it is different that rainfall-occurrence characteristics between CWK and modern rain gage data set (MRG) for original rainfall data sets (M00). For characteristics of rainfall series, occurrences probabilities of rainfall are increased and durations of each rainfall are shorter than past. And from the results of analyzing the long-term inter-monthly variabilities of transition probabilities, in case of M20, lengths of dry spells between CWK and MRG are not different significantly and lengths of wet spells are decreased persistently after A.D. 1830. Especially, decreasing trend for lengths of wet spells at recent september are appeared significantly. These results are considered with increasing trend of recent rainfall, it is concluded that recent frequencies and intensities of rainfall are increasing.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.917-929
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• 2017

Korean income data obtained from Korea Labor Panel Survey shows excessive zeros, which may not be properly explained by the Tobit model. In this paper, we analyze the data using a zero-inflated Tobit model to incorporate excessive zeros. A zero-inflated Tobit model consists of two stages. In the first stage, individuals with 0 income are divided into two groups: genuine zero group and random zero group. Individuals in the genuine zero group did not participate labor market since they have no intention to do so. Individuals in the random zero group participated labor market but their incomes are very low and truncated at 0. In the second stage, the Tobit model is assumed to a subset of data combining random zeros and positive observations. Regression models are employed in both stages to obtain the effect of explanatory variables on the participation of labor market and the income amount. Markov chain Monte Carlo methods are applied for the Bayesian analysis of the data. The proposed zero-inflated Tobit model outperforms the Tobit model in model fit and prediction of zero frequency. The analysis results show strong evidence that the probability of participating in the labor market increases with age, decreases with education, and women tend to have stronger intentions on participating in the labor market than men. There also exists moderate evidence that the probability of participating in the labor market decreases with socio-economic status and reserved wage. However, the amount of monthly wage increases with age and education, and it is larger for married than unmarried and for men than women.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.6
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• pp.394-404
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• 2013

In the present study, the characteristics of spectral peakedness parameter $Q_p$, bandwidth parameter ${\varepsilon}$, and spectral width parameter ${\nu}$ were analyzed as a first step to define the swell waves quantitatively. For the analysis, the joint probability density function of significant wave heights and peak periods were newly developed. The MCMC(Markov Chain Monte Carlo) simulations have been performed to generate the significant wave heights and peak periods from the developed probability density functions. Applying the simulated significant wave heights and peak periods to the theoretical wave spectrum models, the spectral shapes parameters were obtained and analyzed. Among the spectral shape parameters, only the spectral peakedness parameter $Q_p$, is shown to be independent with the significant wave height and peak wave period. It also best represents the peakedness of the spectral shape, and henceforth $Q_p$ should be used to define the swell waves with a wave period. For the field verification of the results, wave data obtained from Hupo port and Ulleungdo were analyzed and results showed the same trend with the MCMC simulation results.