• Journal of the Korean earth science society
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• v.40 no.3
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• pp.259-271
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• 2019

A statistical downscaling method was adopted in order to establish the high-resolution wave prediction system in the East Sea coastal area. This system used forecast data from the Global Wave Watch (GWW) model, and the East Sea and Busan Coastal Wave Watch (CWW) model operated by the Korea Meteorological Administration (KMA). We used the CWW forecast data until three days and the GWW forecast data from three to seven days to implement the statistical downscaling method (inverse distance weight interpolation and conditional merge). The two-dimensional and station wave heights as well as sea surface wind speed from the high-resolution coastal prediction system were verified with statistical analysis, using an initial analysis field and oceanic observation with buoys carried out by the KMA and the Korea Hydrographic and Oceanographic Agency (KHOA). Similar to the predictive performance of the GWW and the CWW data, the system has a high predictive performance at the initial stages that decreased gradually with forecast time. As a result, during the entire prediction period, the correlation coefficient and root mean square error of the predicted wave heights improved from 0.46 and 0.34 m to 0.6 and 0.28 m before and after applying the statistical downscaling method.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.270-270
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• 2011

본 연구는 유역강우량을 산출을 위한 공간보간기법이 격자형 강우자료 생성에 미치는 영향에 대하여 분석하고자 하였다. 본 연구의 대상지역은 우리나라에서 규모가 가장 큰 유역인 한강유역(26,018km2)을 선정하였다. 유역강우량 산출에 이용한 강우자료는 기상청에서 제공하는 2000~2010 년까지 11년간 AWS(Automatic Weather Station) 108개소의 관측자료를 제공받아 사용하였으며, 강우이벤트로 2004년~2009년까지 재산피해를 입힌 총 11개의 호우, 태풍 사상을 선정하였다. 공간 보간기법으로는 Thiessen법과 IDW(Inverse Distance Weight)법의 2가지 기법을 선정하였다. 대상 지역에 대하여 AWS의 자료를 기반으로 보간을 실시하여 미관측지역에 대한 격자분포자료를 구축하였다. 이때, 격자분포자료는 국토해양부에서 분류한 19개 중권역을 기준으로 각 권역별 평균 강우량을 산출하였다. 2가지 공간보간기법을 이용한 한강유역전체 강우량 산출 결과 고도를 고려한 공간보간의 경우 그렇지 않은 경우에 비해 한강유역의 유역평균강우량은 IDW법은 -1.81~8.1%, Thiessen법은 6.6~9.6%의 차이를 나타내었으며, 연도별 편차가 증가하고 있었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.135-135
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• 2020

우리나라의 기후 자료는 일반적으로 기상청에서 발표하는 종관기상관측(ASOS)과 방재기상관측(AWS), 그리고 북한이 세계기상기구(WMO, World Meteorogical Organization)의 기상통신망(GTS)을 통해 보낸 북한기상관측(NKO)을 사용 할 수 있다. 그러나 이 중 40년 이상의 완전한 관측 자료를 얻을 수 있는 건 ASOS가 유일하지만 공간적인 표현에 한계를 갖고 있다. AWS는 관측소가 많다는 장점이 있지만 관측 기간이 길지 않고 이용 가능한 기간에도 관측이 연속적이지 못한 경우가 많다. NKO는 비록 27개의 관측소가 있지만 많은 데이터가 누락되어 일별 기후자료의 사용에 한계를 갖고 있다. 이러한 미관측 기간이나 관측 자료의 누락은 연속적인 시계열 자료분석을 기반으로 하는 수자원 모델링에 있어서 문제를 야기한다. 본 연구는 1973년부터 2019년까지 47년의 신뢰도 높은 한반도 일일 기후 자료를 구축하기 위해 다양한 방법론을 비교하였다. 추정에 사용한 방법은 총 7개로 EM algorithm for probabilistic principal components (PPCA-EM), Inverse distance weight method (IDWM), Nearest neighbor method (NNM), Multivariate normal copulas (Copula), Elastic net model (Elastic), Ordinary kriging (OK), Regularized principal components with EM algorithm (RPCA-EM)를 살펴보았다. 다양한 형태의 결측치를 가정하여 그 결과값을 비교하였고 이는 Root mean squared error(RMSE), Kling-Gupta efficiency(KGE), Nash-Sutcliffe efficiency(NSE)를 통해 평가하였다. 최종 선택된 방법론을 통하여 한반도 전역을 그리드 기반의 강수 및 최저온도/최고온도의 일별자료로 생성하였다.

• Spatial Information Research
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• v.15 no.3
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• pp.267-278
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• 2007

Internationally many models are developed and applied to predict the impact of the climate change, as occurring a lot of symptoms by climate change. Also, in Korea, according to increasing the application of the climate effect model in many research fields, it is required to study the method for preparing climate data and the characteristics of the climate. In this study IDSW (Inverse Distance Squared Weighting), one of the spatial statistic methods, is applied to interpolate. This method estimates a point of interest by assigning more weight to closer points, which are limited to be select by 3 in 100 km radius. As a result, annual average temperature and precipitation had increased by $0.4^{\circ}C$ and 412 mm during 1977 to 2006. They are also predicted to increase by $3.96^{\circ}C$, 319 mm in the 2100 compared to 2007. High variability of temperature and precipitation for last 30 years shows in some part of the Gangwon-do and in the southern part of Korea. Besides in the study of the variable trend, the variability of temperature and precipitation is inclined to increase in Gangwon-do and southern east part, respectively. However, during 2071 to 2100 variability of temperature is predicted to be high in midwest of Korea and variability of precipitation in the east. In the trend of variability, variability of temperature is apt to increase into west south, and variability of precipitation increase in midwest and a part of south.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.601-608
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• 2007

2 Dimensional Gel Electrophoresis(2DGE) is an essentialmethodology for analysis on the expression of various proteins. For example, information for the location, mass, expression, size and shape of the proteins obtained by 2DGE can be used for diagnosis, prognosis and biological progress by comparison of patients with the normal persons. Protein spot matching for this purpose is comparative analysis of protein expression pattern for the 2DGE images generated under different conditions. However, visual analysis of protein spots which are more than several hundreds included in a 2DGE image requires long time and heavy effort. Furthermore, geometrical distortion makes the spot matching for the same protein harder. In this paper, an iterative algorithm is introduced for more efficient spot matching. Proposed method is first performing global matching step, which reduces the geometrical difference between the landmarks and the spot to be matched. Thus, movement for a spot is defined by a weighted sum of the movement of the landmark spots. Weight for the summation is defined by the inverse of the distance from the spots to the landmarks. This movement is iteratively performed until the total sum of the difference between the corresponding landmarks is larger than a pre-selected value. Due to local distortion generally occurred in 2DGE images, there are many regions in whichmany spot pairs are miss-matched. In the second stage, the same spot matching algorithm is applied to such local regions with the additional landmarks for those regions. In other words, the same method is applied with the expanded landmark set to which additional landmarks are added. Our proposed algorithm for spot matching empirically proved reliable analysis of protein separation image by producing higher accuracy.

• Parasites, Hosts and Diseases
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• v.54 no.4
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• pp.439-446
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• 2016

Toxoplasmosis is a protozoan disease that is caused by Toxoplasma gondii in livestock and humans. Due to its medical and veterinary importance, it is essential to study the seroprevalence of T. gondii infection among humans and animals in various parts of the world. The major objective of this study was to determine the seroprevalence and spatial distribution of toxoplasmosis in small ruminants (sheep and goats) of north-eastern region, Pakistan. A total of 1,000 animals comprising of sheep (n=470) and goats (n=530) were examined for T. gondii infection by using ELISA. An epidemiological data was collected in the form of questionnaire. A surface has been generated by using method of interpolation in Arc GIS with the help of IDW (inverse distance weight). The results showed higher seroprevalence of T. gondii in goats (42.8%) as compared to sheep (26.2%). The seroprevalence was higher in females as compared to males in all examined ruminants. Similarly, there is a wide variation in the seroprevalence of T. gondii in different breeds of sheep and goats showing higher seroprevalence in Teddy (52.8%) and Damani breed (34.5%) of goat and sheep's, respectively. The geographical and spatial distribution of T. gondii shows that it is widely distributed in different parts of the north-eastern region of Pakistan. Our results suggest widespread environmental contamination with T. gondii oocysts and that small ruminants could be a potentially important source of T. gondii infection if their infected meat is consumed undercooked.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.29-38
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• 2013

This study is to construe the spatio-temporal characteristics of temperature in cities and the changes of climatical regions by analyzing a climate change in Korea peninsular. We used daily mean air temperature data which were collected in South and North climate stations for the past 34 years from 1974 to 2007. We created temperature maps of 500m resolution with Inverse Distance Weight in application with adiabatic lapse rate per month in linear relation with height and temperature. In the urbanization area, the data analyzed population in comparison with temperature changes by the year. The south climate region in Korea by the Warmth index was expanded to the middle climate region by the latitude after 1990s. A rise of mean temperature was $0.5{\sim}1.2^{\circ}C$ in urban areas such as Seoul, metropolitan and cities which had a rapid urbanization and industrialization with the population increase between 1980s and 1990s. In case of North Korea, cities such as Pyeongyang, Anju, Gaecheon, and Hesan had the same pattern.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.407-415
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• 2008

This study presents the methodology to link with aerial photos for advancing the accuracy of topographic survey data that is used to calculate water volume in urban stream. First, GIS spatial interpolation technique as Inverse Distance Weight (IDW) and Kriging was applied to construct the terrain morphology to the sand-bar and grass area using cross-sectional survey data, and also validation point data was used to estimate the accuracy of created topographic data. As the result of comparison, IDW ($d^{-2}_{ij}$, 2nd square number) in Sand-bar area and Kriging Spherical model in grass area showed more efficient results in the construction of topographic data of river boundary. But the differences among interpolation methods are very slight. Image classification method, Minimum Distance Method (MDM) was applied to extract sand-bar and grass area that are located to river boundary efficiently and the elevation value of extracted layers was allocated to the water level point value. Water volume with topographic data from aerial photos shows the advanced accuracy of 13% (in sand-bar) and 12% (in grass) compared to the water volume of original terrain data. Therefore, terrain analysis method in river linking with aerial photos is efficient to the monitoring about sand-bar and grass area that are located in the downstream of Dam in flooding season, and also it can be applied to calculate water volume efficiently.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.234-244
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• 2013

This study was conducted to determine the factors affecting to seed characteristics and seedling growth of Zelkova serrata. The seeds were collected from sixteen populations of Z. serrata and the seed characteristics (i.e., seed length, width, weight and full seed rate) were measured. We also measured the 1-year-old seedling growth of each population at nursery. All seed characteristics showed significant differences in population level. Seed length and seed width were positively correlated with latitude, longitude, altitude and distance from coast line of sampling site. Seed length and seed width also negatively correlated with annual mean temperature, mean temperature of growing season (Mar.~Oct.). The ratio of seed length/seed width showed inverse trend in case of seed length and seed width. Seed weight/1,000 grains had no correlation with geographic factors but showed negative correlation with annual mean dryness index. Seed weight/L showed negative correlation with latitude and longitude and positive correlation with mean temperature of growing season of sampling site. Full seed rate showed negative correlation with latitude, longitude and annual mean dryness index of sampling site. There were significant differences among populations, among family within population and among individuals within family in seedling growth. Height and diameter of root collar of seedling showed negative correlation with longitude and mean humidity of growing season of sampling site. Height growth of seedlings was not correlated with any seed characteristics but, diameter at root collar showed low negative correlation with seed weight/1,000 grains and seed weight/L. We discussed the implications of the results in view of tree improvement of Z. serrata.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.27-39
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• 2004

In the first part of this study, five homogeneous regions in view of topographical and geographically homogeneous aspects except Jeju and Ulreung islands in Korea were accomplished by K-means clustering method. A total of 57 rain gauges were used for the regional frequency analysis with minimum rainfall series for the consecutive durations. Generalized Extreme Value distribution was confirmed as an optimal one among applied distributions. Drought rainfalls following the return periods were estimated by at-site and regional frequency analysis using L-moments method. It was confirmed that the design drought rainfalls estimated by the regional frequency analysis were shown to be more appropriate than those by the at-site frequency analysis. In the second part of this study, LH-moment ratio diagram and the Kolmogorov-Smirnov test on the Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distributions were accomplished to get optimal probability distribution. Design drought rainfalls were estimated by both at-site and regional frequency analysis using LH-moments and GEV distribution, which was confirmed as an optimal one among applied distributions. Design rainfalls were estimated by at-site and regional frequency analysis using LH-moments, the observed and simulated data resulted from Monte Carlotechniques. Design drought rainfalls derived by regional frequency analysis using L1, L2, L3 and L4-moments (LH-moments) method have shown higher reliability than those of at-site frequency analysis in view of RRMSE (Relative Root-Mean-Square Error), RBIAS (Relative Bias) and RR (Relative Reduction) for the estimated design drought rainfalls. Relative efficiency were calculated for the judgment of relative merits and demerits for the design drought rainfalls derived by regional frequency analysis using L-moments and L1, L2, L3 and L4-moments applied in the first report and second report of this study, respectively. Consequently, design drought rainfalls derived by regional frequency analysis using L-moments were shown as more reliable than those using LH-moments. Finally, design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were derived by regional frequency analysis using L-moments, which was confirmed as a more reliable method through this study. Maps for the design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were accomplished by the method of inverse distance weight and Arc-View, which is one of GIS techniques.