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유한중,신종환,서흥석,김기홍,이승우 한국방재학회 2012 한국방재학회논문집 Vol.12 No.4
In general, landslides of mountain areas have been occurred by typhoon and severe rain storm in Korea. The multiple landslides caused by heavy rain may lead to debris flow which is very rapid downslope movement of debris of a high water content along stream channels. Generally, a debris flow causes larger and severe damage. than a landslide. To protect and reduce the damage of debris flow, a reliable tool to predict potential damage area by drbris flow is needed. Since the water and moveable soils by landslide flow from high elevation to low elevation with additional erosion through the stream of valley, the magnitude of debris can subsequently amplified. Therefore any structures and people in the path of debris flow lies in great risk. Due to the chacteristics of debris flow which is delivered quite a long distance from the location of initiation (hundread meters - kilometers), the risk analysis of debris flow should consider larger area compared with landslide analysis and analysis unit need to be determined based a watershed. In this study, an anlysis tool for the evaluation of debris flow risk in a watershed incorperated with GIS system is proposed. The essence of system is a model to predict the risk of debris flow for any given location. The model is developed based on the statistical analysis of forty eight debris flow cases, which obtained from: field surveys, disaster reports on national roads of korea, and digital maps of the debris flow area. Each set of data in the database includes debris flow size, rainfall information,bedrock types, and run out distance of the debris. The comparison between predicted risk and actual occurrence of the debris flow hazard for forty eight site, showed accuracy of seventy seven percent based on accuracy-classification. 최근 국내 산사태는 주로 태풍 혹은 국지성 집중호우에 의해 발생하기 때문에, 강우가 내리는 지역 내에서 동시다발적으로발생하는 경향을 보이며, 토석류의 경우 다수의 산사태에서 발생된 사태물질이 계곡부를 따라 흘러 본류로 합류하기 때문에 일반적인 산사태에 비해 사태물질의 규모가 크다. 또한 피토석류 시발점으로부터 수백 미터에서 수 킬로미터까지의 떨어진 위치까지 토석류 피해가 전파될 수 있으므로 토석류에 의한 피해를 예측하기는 매우 어렵다. 따라서 토석류의 위험도를 평가하기 위해서는 임의의 피해지역까지 도달 가능한 토석류를 유역단위로 구분하여 분석하는 모델이 효과적이다. 본 연구에서는 유역별 토석류 위험도 평가모델을 개발하기 위하여 다양한 공간정보를 보유하고 있는 GIS시스템을 이용하였으며, 임의의 피해지역에 대해 도달 가능한 범위의 유역을 선정하였다. 또한 토석류 피해 발생에 영향을 미칠 수 있는 토석류 규모, 강우 정보, 표토의모암, 토석류 이동거리 등의 자료를 재해대장과, 항공사진분석, 그리고 현장조사를 실시하였으며, 48개 유역의 토석류 피해 데이터에 대한 통계적 분석을 수행하여 유역별 토석류 위험도 평가 모델을 제안하였다. 제안된 예측 모델로 예측된 결과와 실제토석류 피해발생여부를 비교해 본 결과 약 77%의 분류 정확도를 보였다.
Evaluation of Sperm Sex-Sorting Method using Flow Cytometry in Hanwoo (Korean Native Cattle)
유한중,이경진,이창우,박정준,정희태,양부근,박춘근,이영성 사단법인 한국동물생명공학회 2012 한국동물생명공학회지 Vol.27 No.1
This study evaluated a method of sorting X and Y chromosomes based on size using the forward angle light scatter related refractive index (FSC) of a flow cytometer. Hanwoo bulls sperm were separated to X and Y chromosomes by the parameters of FSC or Hoechst 33342 intensity. As a result, using monitor program linked flow cytometry during sorting processing, the purities were 97 ± 0.57 or 96 ± 0.67% for the X-fraction and 96 ± 0.33 or 97 ± 1.33% for the Y-fraction in the two sperm sorting methods. There were no differences in the X and Y ratios (X and Y %) between the sperm sorting methods based on FSC or DNA content. The proportions of female and male embryos used for in vitro fertilization and development were 66.03 ± 3.31 or 69.37 ± 1.41%, and 70.56 ± 2.42 or 56.11 ± 3.09% when sperm were processed using the sex sorting method by FSC or Hoechst 33342. In conclusion, further study is needed to determine the optimum procedure and improve the nozzle to enhancing sorting accuracy or efficiency. Also, the findings of this study do not negate the possibility that the difference method of sperm sorting cannot use a UV laser beam
유한중(Ryu, Han-Joong),홍성재(Hong, Seong-Jae),이승우(Lee, Seung-Woo),김기홍(Kim, Gi-Hong),윤차영(Yune, Chan-Young) 한국지반공학회 2012 한국지반공학회논문집 Vol.28 No.4
Recently, landslide disasters caused by severe rain storms and typhoons have been frequently reported. Due to the geomorphologic characteristics of Korea, considerable portion of urban area and infrastructures such as road and railway have been constructed near mountains. These infrastructures may encounter the risk of landslide and debris flow. It is important to evaluate the highly risky locations of landslide and to prepare measures for the protection of landslide in the process of construction planning. In this study, a landslide-risk prediction equation is proposed based on the statistical analysis of 423 landslide data set obtained from field surveys, disaster reports on national road, and digital maps of landslide area. Each dataset includes geomorphologic characteristics, soil properties, rainfall information, forest properties and hazard history. The comparison between the result of proposed equation and actual occurrence of landslide shows 92 percent in the accuracy of classification. Since the input for the equation can be provided within short period and low cost, and the results of equation can be easily incorporated with hazard map, the proposed equation can be effectively utilized in the analysis of landslide-risk for large mountainous area.