• 대한한의학회지
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• 제28권1호통권69호
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• pp.35-41
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• 2007

Objectives : To gain better insights on the characteristics of stroke patients admitted to oriental medical hospitals, we analyzed the data of 363 consecutive patients with acute ischemic stroke from Hanbang Stroke Registry supported by the Ministry of Science and Technology of Korea. Methods : Subjects' enrollment was in the oriental medical hospitals of 3 universities located in the metropolitan region from October 2005 to October 2006. We assessed the subjects' general characteristics, risk factors, and etiology of stroke. Each patient's TOAST classification type was confirmed by two independent specialists. Those were small vessel occlusion (SVO), large artery atherosclerosis (LAA), cardioembolism (CE), stroke with other determined etiology (SOE), and stroke with undetermined etiology (SUE).Results 'The distribution of the subjects' general characteristics and risk factors for stroke were similar with result storm previous reports. However, in the TOAST classification, SVO was the major type occupying 78.5% in the total subjects, which is the highest share compared with other research with similar methods. These results imply that patients with more severe symptoms rarely visit oriental medical hospitals. Conclusion : Assuming that this research will continue adding patient's data continuously, this work will help us to understand the features of stroke patients at oriental medical hospitals, and contribute to expansion of the Korean Hanbang Stroke Data Bank.

• 수산해양기술연구
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• 제15권1호
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• pp.35-42
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• 1979

This paper concerns the receding of the eastern coastline of Korean peninsula at a macroscopic point of view, the result is as following. 1. Eastern coast is gradually developed from maturity stage to full maturity stage. 2. The coastline recession due to sea level rise is amounted to the receding distance, x=0.045 m per yr. 3. The author proposes another classification from the new view point, which is classified by comparing quantities between river supplying sediment loads, and the littoral drifting due to wave actions. According this, eastern coast is receding(Type Q-A), and we could find it's geomorphological characteristics. 4. The general piofile of eastern coast sand beach is erosional storm profile(Type I) which accompany offshore bar. 5. From the wave measuring data of eastern coast(Hoopo port), I can derive the linear regression line of the exceedance probability of wave height from the log-normal distribution. $z=O. 113+4.335 log_lo H, r=0.983.$ Above equation made it possible to estimate $\omega[=P(H>H_c)]for the effective wave height H_c=2. Om4, 4. Om and their corresponding values are considerable (7.8%, 0.3%) 6. Eastern coastline certainly have the tendency of erosive and receding, owing to the sea level rise, poor sediment source and effective wave actions. It's very desirable to survey coastline evolution for a long time systematically, in order to make more elaborate diagnosis.

• 대한원격탐사학회지
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• 제32권5호
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• pp.539-550
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• 2016

육상의 수체를 탐지하는 것은 홍수, 태풍, 지진해일과 같은 재해 모니터링에 있어 핵심적인 사항이며, 습지, 빙하 등 지표 수자원의 시 공간적 변화를 파악하는데 중요한 역할을 한다. 본 연구에서는 Kompsat-5 SAR 영상으로부터 육상의 수체를 탐지하기 위하여 임계값에 기반한 접근방법의 적용성을 분석하고, 다양한 임계값 설정 기법의 탐지 성능을 평가하였다. 또한 SAR 영상의 스펙클 필터링이 임계값 설정에 미치는 영향을 분석하였으며, 영상에서 수체가 차지하는 비율에 따른 탐지 성능의 변화에 대한 정량적인 평가를 수행하였다. 추가적으로 탐지 성능을 향상시키기 위해 히스토그램의 bimodality 검정과 majority filtering 처리를 활용하는 새로운 알고리즘을 제안하였다. 세종시 지역의 사례의 경우 제안된 알고리즘을 통해 최종적으로 약 96%의 탐지율과 0.3%의 오탐지율로 수체를 탐지할 수 있음을 보였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2002년도 학술발표회 논문집(I)
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• 한국안전학회지
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• 제31권2호
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• pp.119-126
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• 2016

Across the world, the industrialization has increased the frequency of climate anomaly. The size of damage due to recent natural disasters is growing large and fast, and the human damage and economic loss due to disasters are consistently increasing. Urbanization has a structure vulnerable to natural disasters. Therefore, in order to reduce damage from natural disasters, both hardware and software approaches should be utilized. Currently, however, the development of a statistical access process for 'analysis of disaster occurrence factor' and 'prediction of damage costs' for disaster prevention and overall disaster management is inadequate. In case of local governments, overall disaster management system is not established, or even if it is established, unscientific classification system and management lead to low utility of natural statistics of disaster year book. Therefore, in order to minimize disaster damage and for rational disaster management, the disaster damage survey process should be improved. This study selected gale as the focused analysis target among natural disasters recorded in disaster year book such as storm, torrential rain, gale, high seas, and heavy snow, and analyzed disaster survey process. Based on disaster year book, the gale damage size was analyzed and the issues occurring from the correlation of gale and damage amount were examined, so as to suggest an improvement plan for reliable natural disaster information collection and systematic natural disaster damage survey.

• 한국수자원학회논문집
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• 제35권4호
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• pp.411-423
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• 2002

유출에 대한 신속하고 정확한 예측은 수문 및 수자원 분야에 있어서 궁극적인 목표 중의 하나이며, 우리나라와 같이 강우에 대한 유출의 응답이 짧은 시간에 발생하는 경우에 무엇보다도 중요하다. 따라서, 토지이용변화 등에 의한 유출의 변화 및 감시를 포함하는 유역내의 수문 변수의 변화를 적절하게 고려할 수 있는 분포형 자료를 선호하게 된다. 이때 분포형 모형을 적용시키기 위해서는 강우의 공간특성을 알아야 하며, 각 격자별 강우량이 입력자료로 활용되어 각 격자별 유출특성을 파악하게 된다. Landsat TM 자료를 이용할 경우 분포형 모형을 위한 유역 내에 관련된 인자 및 식생, 토지피복 등의 자세한 정보를 제공할 수 있다. 본 연구에서는 SCS의 유출곡선번호(CN)에 의한 방법을 이용하여 유효우량도를 작성하여 신속하게 유출의 감시가 가능하도록 하는 기법에 대하여 검토하였다. 호우시에 있어서 유효우량에 대한 시계열 자료는 본 기법을 통하여 분포형태로서 계산i과 수 있으며, 이 결과는 분포형 유출모형을 이용하여 유역 출구에서의 수문곡선을 산정할 수 있다.

• 한국안전학회지
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• 제38권6호
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• pp.50-59
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• 2023

As the diversity of disasters continues to increase, the concept of "complex disasters" has gained prominence in various policies and studies related to disaster management. However, there has been a certain limitation in the availability of the systematic statistics or data in advancing policies and research initiatives related to complex disasters. This study aims to analyze the macro-level characteristics of the complex disasters that have occurred domestically utilizing a 30-year span of a news data. Initially, we categorize the complex disasters into the three types: "Natural disaster-Natural disaster", "Natural disaster-Social disaster", and "Social disaster-Social disaster". As a result, the "natural diaster-social disaster" type is the most prevalent. It is noted that "natual disaster-natural disaster" type has increased significantly in recent 10 years (2011-2020). In terms of specific disaster types, "Storm and Flood", "Collapse", "Traffic Accident", "National Infrastructure Paralysis", and "Fire⋅Explosion" occur the most in conjunction with other disasters in a complex manner. It has been observed that the types of disasters co-ocuuring with others have become more diverse over time. Parcicularly, in recent 10 years (2011-2020), in addition to the aforementioned five types, "Heat Wave", "Heavy Snowfall⋅Cold Wave", "Earthquake", "Chemical Accident", "Infectious Disease", "Forest Fire", "Air Pollution", "Drought", and "Landslide" have been notable for their frequent co-occurrence with other disasters. These findings through the statistical analysis of the complex disasters using long-term news data are expected to serve as crucial data for future policy development and research on complex disaster management.

• 한국터널지하공간학회 논문집
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• 제6권3호
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• pp.213-225
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• 2004

일반 국도의 선형개량사업 및 도로 확포장 사업의 일환으로 터널의 수가 증가하고 있는 실정이다. 최근들어 집중호우 및 이상기후로 인하여 국지적인 강우가 발생하여 갱구사면의 붕괴도 적지 않게 발생하고 있다. 따라서, 국내의 터널 갱구사면 피해 및 유지관리를 효율적으로 대처할 필요성이 대두되었다. 본 연구는 일반국도변에 기설치 운영되고 있는 터널 갱구사면의 현황 및 상태에 대한 조사를 실시하고 수집된 데이터의 효율적인 관리를 위한 데이터베이스 시스템을 개발, 향후 유지관리를 위한 상태평가 기법을 개발하는 것이다. 연구방법으로는 국도변의 터널 갱구사면의 형태를 분석하기 위하여 현장 조사를 통하여 국내의 터널을 진입형태, 갱문형식, 터널 유형 등 기하학적인 형태에 따른 분석을 실시하였다. 수집된 자료의 효율적인 관리를 위해서 그래픽 사용자 인터페이스를 사용하여 입력, 수정 및 조회가 가능한 데이터베이스 관리 시스템을 개발하였고, 조사된 갱구사면의 위험상태에 대한 등급을 분류하기 위한 상태평가 기준표를 제시하고 이에 따른 등급을 분류하였다. 본 상태평가를 이용하여 국도변의 터널 갱구사면을 분류하여 위험 등급에 따라 향후 지속적으로 유지 관리를 실시할 수 있도록 기초자료로 활용하고자 하는 것이 주 목적이다.

• 한국지반공학회논문집
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• 제28권4호
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• pp.23-33
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• 2012

최근 들어 집중호우 및 태풍과 국지성 집중호우로 인한 산사태 피해가 자주 보고되고 있다. 국내 지형특성상 산지 인근에서 도시가 발달되고 도로 철도 등의 기간시설물이 건설된 경우가 많기 때문에 산사태로 인한 인명 및 재산피해는 매우 심각하다. 이러한 피해를 효과적으로 방지하기 위해서는 건설계획 단계부터 산사태 위험이 높은 지역을 파악하고 적절한 대책을 마련하는 것이 중요하다. 본 연구에서는 산사태 발생에 영향을 미칠 수 있는 지형학적 특성, 토질의 특성, 강우 정보, 나무의 종류 정보 등의 자료를 재해대장 분석, 항공사진 분석, 현장조사를 실시하여 구축한 423 지점의 산사태 데이터에 대한 통계학적 분석을 수행하여 산사태 위험도 예측식을 제안하였다. 제안된 예측식으로 예측된 결과와 실제 산사태 발생여부를 비교해 본 결과 약 92%의 분류 정확도를 보였다. 예측식에 필요한 입력치들은 단 시간 내에 저비용으로 획득할 수 있도록 구성하였다. 또한 예측결과의 경우 재해지도 형식으로 표현하기 용이하기 때문에 제안된 산사태 위험도 예측식은 광범위한 지역의 산사태 발생 위험도를 산정하는데 효과적으로 활용될 수 있다고 판단된다.

• 대기
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• 제25권4호
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• pp.611-622
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• 2015

Heavy rainfall ($>30mm\;hr^{-1}$) over the Korean Peninsula is examined in order to understand thermo-dynamic characteristics of the atmosphere, using radiosonde observational data from seven upper-air observation stations during the last 17 years (1997~2013). A total of 82 heavy rainfall cases during the summer season (June-August) were selected for this study. The average values of thermo-dynamic indices of heavy rainfall events are Total Precipitable Water (TPW) = 60 mm, Convective Available Potential Energy (CAPE) = $850J\;kg^{-1}$, Convective Inhibition (CIN) = $15J\;kg^{-1}$, Storm Relative Helicity (SRH) = $160m^2s^{-2}$, and 0~3 km bulk wind shear = $5s^{-1}$. About 34% of the cases were associated with a Changma front; this pattern is more significant than other synoptic pressure patterns such as troughs (22%), migratory cyclones (15%), edges of high-pressure (12%), typhoons (11%), and low-pressure originating from Changma fronts (6%). The spatial distribution of thermo-dynamic conditions (CAPE and SRH) is similar to the range of thunderstorms over the United States, but extreme conditions (supercell thunderstorms and tornadoes) did not appear in the Korean Peninsula. Synoptic conditions, vertical buoyancy (CAPE, CIN), and wind parameters (SRH, shear) are shown to discriminate among the environments of the three types. The first type occurred with high CAPE and low wind shear by the edge of the high pressure pattern, but Second type is related to Changma front and typhoon, exhibiting low CAPE and high wind shear. The last type exhibited characteristics intermediate between the first and second types, such as moderate CAPE and wind shear near the migratory cyclone and trough.