• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.395-404
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• 2018

This research evaluated the change in rainfall quantile during S1, S2, and S3 by using Representative Concentration Pathways (RCP) 4.5 climate scenario HadGEM3-RA Regional Climate Model (RCM) produced by downscaling and bias correlation compared to the past standard observation data S0. Also, the maximum flood peak volume and flood area were calculated by using the urban runoff model and the impact of climate change was analyzed in each period. For this purpose, Gumbel distribution was used as an appropriate model based on the method of maximum likelihood. As a result, in the case of the 10 year-frequency which is the design of most urban drainage facilities, the rainfall quantile is in increased about 10% if we assume 50 years from now with the $3^{rd}$ quarter value and about 20% if we assume 70 years from now. This result implies that the installed urban drainage facility based on the currently set design flood volume cannot be met the design criteria in the future. Therefore, it is necessary to reflect future climate conditions to current urban drainage facilities.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.111-116
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• 2004

It is essential to know the information about the prior model for wavelet coefficients, the probability distribution of noise, and the variance of wavelet coefficients for noise reduction using Bayesian estimation in wavelet domain. In general denoising methods, the signal variance is estimated from the proper prior model for wavelet coefficients. In this paper, we propose a variable window size decision algorithm to estimate signal variance according to image region. Simulation results shows the proposed method have better PSNRs than those of the state of art denoising methods.

• Water for future
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• v.27 no.2
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• pp.129-137
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• 1994

The surface hydrology of large land areas is susceptible to several preferred stable states with transitions between stable states induced y stochastic fluctuation. This comes about due to the close coupling of land surface and atmospheric interaction. An interesting and important issue is the duration of residence in each mode. Mean transtion times between the stable modes are analyzed for different model parameters or climatic types. In an example situation of this differential equation exhibits a bimodal probability distribution of soil moisture states. Uncertainty analysis regarding the model parameters is performed using a Monte-Carlo simulation method. The method developed in this research may reveal some important characteristics of soil moisture or precipitation over a large area, in particular, those relating to abrupt changes in soil moisture or precipitation having extremely variable duration.

• Journal of Ocean Engineering and Technology
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• v.28 no.3
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• pp.185-192
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• 2014

The riser systems for floating offshore structures are known to experience tri-modal dynamic responses. These are owing to the combined loadings from the low-frequency response due to riser tension behavior, middle-range frequency response coming from winds and waves, and high-frequency response due to vortex induced-vibration. In this study, fatigue damage models were applied to predict the fatigue damages in a well-separated tri-modal spectrum, and the resultant fatigue damages of each model were compared with the most reasonable fatigue damage calculated by the inverse Fourier transform of the spectrum, rain-flow counting method, and Palmgren-Miner rule as a reference. The results show that the fatigue damage models developed for a wide-band spectrum are applicable to the tri-modal spectrum, and both the Benasciutti-Tovo and JB models could most accurately predict the fatigue damages of the tri-modal spectrum responses.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1506-1517
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• 1999

In this paper, we propose two fast block matching algorithm using the distribution of mean absolute difference (MAD) at the search region overlapped with neighbor blocks and pixel subsapmling. The proposed methods use the lower and upper bound of MAD at the overlapped search region which is calculated from the MAD of neighbor block at that search position and MAD between the current block and neighbor block. In the first algorithm, we can reduce the computational complexity by executing the block matching operation at the only necessary search points. That points are selected using the lower bound of MAD. In the second algorithm, we use the statictical distribution of actual MAD which exists between the lower bound and upper bound of MAD. By using the statistical distribution of actual MAD, we can significantly reduce the computational complexity for motion estimation. after striking space key 2 times.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.672-679
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• 2018

This study was conducted to predict the potential distribution and risk of invasive alien plant, Amaranthus patulus, in an agricultural area of South Korea. We collected 254 presence localities of A. patulus using field survey and literature search and stimulated the potential distribution area of A. patulus using maximum entropy modeling (MaxEnt) with six climatic variables. Two different kinds of agricultural risk index, raster risk index and regional risk index, were estimated. The 'raster risk index' was calculated by multiplying the potential distribution by the field area in $1{\times}1km$ and 'regional risk index' was calculated by multiplying the potential distribution by field area proportion in the total field of South Korea. The predicted potential distribution of A. patulus was almost matched with actual presence data. The annual mean temperature had the highest contribution for distribution modeling of A. patulus. Area under curve (AUC) value of the model was 0.711. The highest regions were Gwangju for potential distribution, Jeju for 'raster risk index' and Gyeongbuk for 'regional risk index'. This different ranks among the index showed the importance about the development of various risk index for evaluating invasive plant risk.

• Journal of KIISE
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• v.41 no.9
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• pp.652-665
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• 2014

Many important terminologies in biomedical text are expressed as abbreviations or acronyms. We newly suggest a semantic link topic model based on the concepts of topic and dependency link to disambiguate biomedical abbreviations and cluster long form variants of abbreviations which refer to the same senses. This model is a generative model inspired by the latent Dirichlet allocation (LDA) topic model, in which each document is viewed as a mixture of topics, with each topic characterized by a distribution over words. Thus, words of a document are generated from a hidden topic structure of a document and the topic structure is inferred from observable word sequences of document collections. In this study, we allow two distinct word generation to incorporate semantic dependencies between words, particularly between expansions (long forms) of abbreviations and their sentential co-occurring words. Besides topic information, the semantic dependency between words is defined as a link and a new random parameter for the link presence is assigned to each word. As a result, the most probable expansions with respect to abbreviations of a given abstract are decided by word-topic distribution, document-topic distribution, and word-link distribution estimated from document collection though the semantic dependency link topic model. The abstracts retrieved from the MEDLINE Entrez interface by the query relating 22 abbreviations and their 186 expansions were used as a data set. The link topic model correctly predicted expansions of abbreviations with the accuracy of 98.30%.

• Korean Journal of Environment and Ecology
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• v.25 no.1
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• pp.47-56
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• 2011

The research was conducted to find optimal habitats of warm-temperate evergreen broad-leaved trees, and to investigate climate factors to determine their distribution using classification tree (CT) analysis. The warm-temperate evergreen broad-leaved trees model (EG-model) constructed by CT analysis showed that Mean minimum temperature of the coldest month (TMC) is a major climate factor in determining distribution of warm-temperate evergreen broad-leaved trees. The areas above the $-5.95^{\circ}C$ of TMC revealed the optimal habitats of the trees. The coldest month mean temperature (CMT) equitable to $-5.95^{\circ}C$ of TMC is $-1.7^{\circ}C$, which is lower than $-1^{\circ}C$ of CMT of warm-temperate evergreen broad-leaved trees. Suitable habitats were defined for warm-temperate evergreen broad-leaved trees in Korea. These habitats were classified into two areas according to the value of TMC. One area with more than$-5.95^{\circ}C$ of TMC was favorable to trees if the summer precipitation (PRS) is above 826.5mm; the other one with less than $-5.95^{\circ}C$ of TMC was favorable if PRS is above 1219mm. These favorable conditions of habitats were similar to those of warm-temperate evergreen broad-leaved trees in Japan. We figured out from these results that distribution of warm-temperate evergreen broad-leaved trees were expanded to inland areas of southern parts of Korean peninsula, and ares with the higher latitude. Finally, the northern limits of warm-temperate evergreen broad-leaved trees might be adjusted accordingly.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.109-116
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• 2014

This study proposed new instance selection using neural network with weighted fuzzy membership functions(NEWFM) based on Takagi-Sugeno(T-S) fuzzy model to improve the classification performance. The proposed instance selection adopted weighted average defuzzification of the T-S fuzzy model and an interval selection, same as the confidence interval in a normal distribution used in statistics. In order to evaluate the classification performance of the proposed instance selection, the results were compared with depending on whether to use instance selection from the case study. The classification performances of depending on whether to use instance selection show 77.33% and 78.19%, respectively. Also, to show the difference between the classification performance of depending on whether to use instance selection, a statistics methodology, McNemar test, was used. The test results showed that the instance selection was superior to no instance selection as the significance level was lower than 0.05.

• Journal of Korean Society of Steel Construction
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• v.22 no.6
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• pp.573-580
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• 2010

In this study, an assessment method that considers the effects of directional wind speeds on buildings or structures that are sensitive to wind is proposed. Also, the basic characteristics of directional wind speeds were assessed by means of local annual maximum wind speeds. From the method of assessment of the characteristics of directional wind speeds, their goodness-of-fit was verified by applying extreme value distribution to the data on annual maximum wind speeds from the Korea Meteorological Administration. To consider the characteristics of directional winds, an assessment method is suggested that divides the directional wind pattern of each directional wind speed into four groups. From the study results, all the data on directional wind speeds based on the Gumbel distribution were examined using data on annual maximum wind speeds from Seoul, Tongyung, and Incheon. Since the Gumbel model of all directional wind speeds has independent probability characteristics that govern the 4 directional wind pattern groups, the application ratio proposed was based on the assessment of these four groups. According to the goodness-of-fit of the data on the annual maximum wind speeds based on the Gumbel distribution, new application ratios were proposed that consider the directional wind speeds in Seoul, Tongyung, and Incheon.