• 성인간호학회지
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• 제18권1호
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• pp.146-156
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• 2006

Purpose: 1) to construct cohorts according to risk scores calculated with the Gail Breast Cancer Risk Assessment Tool (Gail et al., 1989) (Gail) and the Breast Cancer Risk Appraisal (Lee et al,. 2003) (Lee) 2) to identify the distribution of risk factors and preventive behavior stages between the cohorts 3) to identify abnormal breast conditions in risk cohort. Method: Using convenience sampling, 775 rural women were selected. Risk appraisal was scored using Gail and Lee. Preventive behavior stages for BSE (Breast self examination) and mammography were measured using 4 stages of the Transtheoretical Model (Prochaska & DiClemente, 1983). Results: 1) The risk cohort according to Gail was 12.3% (n=95), and Lee, 3.1% (n=24). 2) There were significant differences in the distribution of risk factors (age, family history, age at 1st live birth, age at menarche, number of breast biopsy, history of breast disease, and breast-feeding) between cohorts. 3) There was a significant difference in the distribution of the stage of BSE according to Lee. 4) Six women in the risk group detected masses or nodules and physician consultation and ultrasonography were recommended. Conclusion: On the basis of the constructed cohorts, further longitudinal studies of cohorts are recommended with interventions according to characteristics of cohorts.

• 한국건설관리학회논문집
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• 제2권2호
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• pp.98-108
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• 2001

본 연구에서는 프로젝트의 성공적 이행을 보장하기 위하여 리스크분석모델을 제안하였다. 리스크분석 모델은 CRAS라 칭하였으며, 시공자가 RBS를 통해서 리스크를 체계적으로 확인하고 분석하고 관리하는데 도움을 줄 수 있도록 설계되었다. 제안된 CRAS모델은 크게 3단계의 분석과정으로 이루어진다. 첫 단계는 시공자가 프로젝트와 관련된 리스크를 확인하고 분석해서 입찰여부를 판단하는 것이다. 두 번째 단계는 영향도, 의사결정나무, Monte Carlo 시뮬레이션을 이용하여 리스크를 정량적으로 평가하여 예비비를 산정하는 것이며, 세 번째 단계는 확률 노드, 확률 칼렌다 등의 일정관리기법과 시뮬레이션을 통해 공사일정상의 리스크를 파악하여 프로젝트의 성공여부를 판단하는 것이다. 결과적으로 본 모델은 시공자로 하여금 프로젝트에 내재된 리스크가 프로젝트의 공기와 공사비에 미치는 영향을 정량적으로 평가할 수 있도록 함으로서 시공자가 이들 리스크를 제거하는데 필요한 여러 대안을 고려할 수 있도록 하였다.

• 한국건설관리학회논문집
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• 제10권4호
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• pp.67-75
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• 2009

최근 활발히 진행되고 있는 도시재생사업과 같은 대규모 복합개발사업은 사업기간이 길고 다양한 사업주체들이 참여한다. 이러한 특성 때문에 사업추진 과정상 많은 위험요인들을 내포하게 되고 이를 관리하는 것은 사업의 성패에 큰 영향을 미친다. 그러므로 도시재생사업에서 위험을 인지하고 대응하는 일련의 위험관리 과정은 정확하고 체계적으로 수행되어야 한다. 위험관리과정에서 위험인지단계는 다양한 위험요인을 인지하고 그 위험의 성격을 규정하는 첫 단계이며, 위험을 인지하는 기법 체크리스트는 가장 보편적이고 실용적인 방법이라고 할 수 있다. 따라서 본 연구에서는 도시재생사업의 개발단계에서 사업주체들의 업무를 분석하고, 위험요인을 도출하여 사업주체별로 위험을 분류하는 체크리스트를 제안하였다. 이러한 주체별 위험인지 체크리스트는 실무자가 쉽게 위험을 파악할 수 있는 도구로써, 도시재생사업과 같이 다양한 사업주체들이 자신은 물론 다른 사업 참여자들의 위험을 인지하는데도 효과적일 것이라고 기대된다.

• 성인간호학회지
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• 제25권2호
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• pp.183-193
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• 2013

Purpose: The purpose of this study was to identify the prevalence and risk factors of sleep disturbance among community dwelling adults in Korea. Methods: Data were collected from nine hundred fifty nine adults dwelling in a metropolitan city in Korea. Subjects were older than 45 years, did not take medication for sleep problems on a regular basis, and did not work at night. The Pittsburgh Sleep Quality Index was used to collect data about sleep disturbance. Sociodemographic, life style, and health related factors were included as risk factors. Chi square test and logistic stepwise regression were used to identify the risk factors. Results: The prevalence of sleep disturbance was 13.1%. The significant risk factors were being female, age, number of toilet use at night, perceived health, and pain. Risk factors were somewhat different by gender. Emotional and job status were the risk factors only for men and menopausal status were for women. Conclusion: Prevalence of sleep disturbance in community dwelling adults in Korea was not greater than those dwelling in other countries. Females, older adults, the number of toilet use at night, perceived health, and pain were the most important risk factors for sleep disturbances. Gender was a factor in reported sleep disturbances. It might be useful to investigate the factors that contribute to the number of toilet use at night as this might have some underlying factors that could be corrected.

• 대한통합의학회지
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• 제12권2호
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• pp.155-166
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• 2024

Purpose : This study aims to identify key factors for predicting dropout risk at the university level and to provide a foundation for policy development aimed at dropout prevention. This study explores the optimal machine learning algorithm by comparing the performance of various algorithms using data on college students' dropout risks. Methods : We collected data on factors influencing dropout risk and propensity were collected from N University. The collected data were applied to several machine learning algorithms, including random forest, decision tree, artificial neural network, logistic regression, support vector machine (SVM), k-nearest neighbor (k-NN) classification, and Naive Bayes. The performance of these models was compared and evaluated, with a focus on predictive validity and the identification of significant dropout factors through the information gain index of machine learning. Results : The binary logistic regression analysis showed that the year of the program, department, grades, and year of entry had a statistically significant effect on the dropout risk. The performance of each machine learning algorithm showed that random forest performed the best. The results showed that the relative importance of the predictor variables was highest for department, age, grade, and residence, in the order of whether or not they matched the school location. Conclusion : Machine learning-based prediction of dropout risk focuses on the early identification of students at risk. The types and causes of dropout crises vary significantly among students. It is important to identify the types and causes of dropout crises so that appropriate actions and support can be taken to remove risk factors and increase protective factors. The relative importance of the factors affecting dropout risk found in this study will help guide educational prescriptions for preventing college student dropout.

• International Journal of Computer Science & Network Security
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• 제21권5호
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2008년도 공동추계학술대회
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• pp.251-253
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• 2008

Erosion and landslide cause serious damage to forest areas. As a consequence, partial or complete destruction of vegetation occurs, which leads to many cascading problems. In this study, an attempt has been made to identify the forest areas, which are under different risk categories of erosion and landslide, in part of Eastern Ghats of Tamil Nadu. Relevantthematic maps were generated from satellite data, topographical maps, primary and secondary data and weights to each map were assigned appropriately. Weighted overlay analysis was carried out to identify the erosionprone forest areas. The result of erosion and landslide prone model reveals that 4712 ha(17%) of forest area is under high risk category and 15879 ha(58.65%) isunder medium risk category. The results of spatial modeling would be very much useful to the forest officials and conservationist to plan for effective conservation.

• 한국직업건강간호학회지
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• 제31권2호
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• pp.95-103
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• 2022

Purpose: This study aims to identify general, workplace, and health-related characteristics of outdoor workers exposed to high temperatures, and to compare the risk of disease according to outdoor high temperature exposure. Methods: This secondary analysis study used the 5th Korean Working Conditions Survey (2017) to identify 4,915 outdoor workers exposed to high temperatures. Results: Outdoor workers exposed to high temperatures were mostly male, elderly, less educated, and daily contract workers. Most of them were engaged in agriculture, forestry and fishing, and construction industries. About 40~50% of them complained of musculoskeletal pain and overall fatigue. The results showed that high temperature exposure increased the risk of illness (hearing problem, skin problem, backache, muscular pains in upper and lower limbs, headache/eyestrain, injuries, depression, and overall fatigue) among workers. Conclusion: High temperature exposure might increase the risk of illness among workers. The results of this study demonstrated that the outdoor workers should be protected from high temperatures.

• 디자인학연구
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• 제16권4호
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• pp.69-78
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• 2003

웹 디자인 프로젝트에서 리스크 매니지먼트는 매우 중요한 프로젝트 매니지먼트 항목 중 하나이다. 리스크 매니지먼트란 웹 디자인 프로젝트 위기사항을 피하기 위하여 시간을 가지고 리스크의 원인을 찾아내어 적절한 대응책을 강구하여 프로젝트의 최종 목표를 성공적으로 수행하는데 있다. 즉 프로젝트 3대 요소인 일정, 비용, 품질을 만족하기 위한 프로세스이다. 본 논문은 첫째, 웹 디자인 프로젝트 매니지먼트의 개념 및 목적, 프로세스와 지식 영역을 살펴보고 둘째, 웹 디자인 프로젝트 기 계획 단계에서 리스크 매니지먼트 계획에 대한 체계적인 리스크 매니지먼트 프로세스와 리스크 관리 모델을 제안하고 있다. 세 째는 제시한 리스크 매니지먼트 모델의 표준화 및 모델 화의 타당성을 실제 사례인 E사 프로젝트를 통해 검증하고 있다.

• 한국의류학회지
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• 제19권3호
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• pp.434-447
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• 1995

This research was intended to identify variables influencing on risk perception and risk reduction behavior in clothing purchase situations. Responses from 631 female adults living in Seoul area were collected and analyzed. Towner for social occasions or working in office was used as clothing stimulus. The analysis included three product variables(price, style, type of clothing), 4 personality variables(generalized self-confidence, specific self-confidence, generalized informativeness, fashion informativeness), 2 clothing attitude variables(clothing importance, clothing interest), 4 demographic variables(age, educational level, occupation, income), and 3 situational variables(purchase planning, time pressure, effects of shopping company). Multiple regression revealed the fact that each type of clothing risk and each type of risk reduction behavior was influenced by the set of different variables. Generalized self- confidence and age and time pressure had more effects on clothing risk perception, while clothing risk reduction behavior was more influenced by clothing risk type, clothing interest, price of clothing and fashion informativeness. Implications for marketing strategies planning were also provided.