• 대한원격탐사학회지
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• 제35권2호
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• pp.337-342
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• 2019

본 연구에서는 GDAPS(Global Data Assimilation and Prediction System) 예보모델자료와 위성기반 식생건조지수를 결합시킨 산불위험지수 WRI(Wildfire Risk Index)를 개발하였고, 이를 2019년 4월 4일의 고성-속초 산불과 강릉-동해 산불 사례에 적용해 보았다. 제시한 산불위험지수 WRI는 강수 이벤트 후에 건조 경향이 지속되었던 3월 19일 전후와 4월 4일 전후의 산불위험도 변화를 잘 나타냄으로써, 그 적합성이 확인되었다. WRI는 우리나라 산불취약성의 상시 감시를 위한 하나의 방법이 될 수 있을 것이며, 이를 더욱 발전시키기 위해서는 향후 GK-2A 위성자료의 활용과 함께, 산림청의 산불위험예보시스템과의 연계 방안에 대한 모색이 반드시 필요할 것이다.

• 한국해양공학회지
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• 제23권1호
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• pp.24-30
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• 2009

The purpose of this study was to establish an assessment method for the estimation of the pollution risk by oil spill accidents. Various oil spill patterns were calculated based on past accidents in the study area and these results were analyzed statistically. Then the risk probability, the oil arrival time, risk range, and so on were calculated. These calculations were performed for sub area sectors, fisheries and aquaculture farms, based on information about environmentally sensitive resources. Finally, the risk to each sub area sector was assessed by comparing the calculated results. These consequences indicated the objective and general risks of oil spill accidents and the result of this method will be made more appropriate by integrating real time risk predictions.

• 임상간호연구
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• 제19권2호
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• pp.265-274
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• 2013

Purpose: The aim of this study was to determine the risk factors contributed to unplanned readmission to intensive care unit (ICU) and to investigate the prediction model of unplanned readmission. Methods: We retrospectively reviewed the electronic medical records which included the data of 3,903 patients who had discharged from ICUs in a university hospital in Seoul from January 2011 to April 2012. Results: The unplanned readmission rate was 4.8% (n=186). The nine variables were significantly different between the unplanned readmission and no readmission groups: age, clinical department, length of stay at 1st ICU, operation, use of ventilator during 24 hours a day, APACHE II score at ICU admission and discharge, direct nursing care hours and Glasgow coma scale total score at 1st ICU discharge. The clinical department, length of stay at 1st ICU, operation and APACHE II score at ICU admission were the significant predictors of unplanned ICU readmission. The predictive model's area under the curve was .802 (p<.001). Conclusion: We identified the risk factors and the prediction model associated with unplanned ICU readmission. Better patient assessment tools and knowledge about risk factors could contribute to reduce unplanned ICU readmission rate and mortality.

• 생물정신의학
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• 제30권1호
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• pp.24-30
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• 2023

Objectives Alzheimer's disease (AD) is the most common form of dementia in older adults, damaging the brain and resulting in impaired memory, thinking, and behavior. The identification of differentially expressed genes and related pathways among affected brain regions can provide more information on the mechanisms of AD. The aim of our study was to identify differentially expressed genes associated with AD and combined biomarkers among them to improve AD risk prediction accuracy. Methods Machine learning methods were used to compare the performance of the identified combined biomarkers. In this study, three publicly available gene expression datasets from the hippocampal brain region were used. Results We detected 31 significant common genes from two different microarray datasets using the limma package. Some of them belonged to 11 biological pathways. Combined biomarkers were identified in two microarray datasets and were evaluated in a different dataset. The performance of the predictive models using the combined biomarkers was superior to those of models using a single gene. When two genes were combined, the most predictive gene set in the evaluation dataset was ATR and PRKCB when linear discriminant analysis was applied. Conclusions Combined biomarkers showed good performance in predicting the risk of AD. The constructed predictive nomogram using combined biomarkers could easily be used by clinicians to identify high-risk individuals so that more efficient trials could be designed to reduce the incidence of AD.

• Earthquakes and Structures
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• 제25권6호
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• pp.469-479
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• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.

• 한국건설관리학회논문집
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• 제14권1호
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• pp.63-70
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• 2013

주택재개발사업에서 수익성 예측은 성공적인 사업의 수행을 위한 중요한 요소이기 때문에 수익성 예측을 소홀히 할 경우 많은 그에 따른 리스크가 커지게 된다. 그러나 현행 주택재개발사업은 사업이 많이 진행된 시점에서 수익성을 분석하기 때문에, 수익성이 없는 것으로 판단될 경우 그에 따른 큰 손실을 감수해야 한다. 이로 인해 현재 사업이 중단되거나 지연됨에 따라 경제적인 손실을 보는 사업장이 늘어나고 있으며, 그에 따른 이해관계자간 갈등이 심화되고 있다. 주택재개발사업 시 이러한 사회적 갈등과 경제적 손실을 줄이기 위해서는 사업추진여부를 결정하기 위한 적절한 수익성 예측 방법의 개발이 필요하며, 더불어 적절한 시기에 적용할 수 있는 프로세스의 제시가 요구된다. 본 연구는 사업 초기단계인 기획단계에서 수익성을 예측할 수 있는 방법을 제시하여, 합리적이고 타당한 의사결정의 지원을 위한 것으로 본 연구모델의 적용 시 사업 초기단계에 사업 수행 여부의 결정이 가능하도록 하여, 부적절한 사업의 무리한 진행으로 인한 경제적인 손실과 그에 따른 이해관계자간의 갈등을 줄일 수 있을 것으로 판단된다.

• 한국구조물진단유지관리공학회 논문집
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• 제16권5호
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• pp.29-39
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• 2012

상관관계가 높은 복합열화의 완벽한 개별예측모델의 개발은 매우 어려운 문제로, 본 논문에서는 현수교 시스템의 미래열화와 유지 예산을 예측하기 위하여, 10년간의 유지 데이터가 주어진 매개변수(파손지표와 사용성)의 사후 확률 밀도함수를 찾기 위해 베이지언 추론을 적용하였다. 마르코프 연쇄 몬테카를로법을 이용하여 매개변수의 사후 분포를 조사하였다. 감소한 사용성의 모의위험예측은 사전분포와 연간유지 업무에서 업데이트한 데이터의 가능성에 따라 작성한 사후 분포이다. 기존의 선형 예측 모델과 비교하면, 제안된 2차 모델은 교량부품의 사용성, 위험요소, 그리고 유지 예산의 측정 데이터에 대하여 매우 개선된 수렴성과 근접성을 제공한다. 따라서 제안된 2차 추계학적 회귀 모델을 기반으로 복잡한 사회간접설비의 미래 성능과 유지관리예산을 예측하고 제어할 수 있는 기회를 제공할 것으로 기대한다.

• 건설안전기술
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• 통권46호
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• pp.74-81
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• 2008

• Journal of Preventive Medicine and Public Health
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• 제53권5호
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• pp.313-322
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• 2020

Objectives: This study was conducted to determine the incidence and risk factors of myocardial infarction (MI) and stroke in farmers compared to the general population and to establish 5-year prediction models. Methods: The farmer cohort and the control cohort were generated using the customized database of the National Health Insurance Service of Korea database and the National Sample Cohort, respectively. The participants were followed from the day of the index general health examination until the events of MI, stroke, or death (up to 5 years). Results: In total, 734 744 participants from the farmer cohort and 238 311 from the control cohort aged between 40 and 70 were included. The age-adjusted incidence of MI was 0.766 and 0.585 per 1000 person-years in the farmer and control cohorts, respectively. That of stroke was 0.559 and 0.321 per 1000 person-years in both cohorts, respectively. In farmers, the risk factors for MI included male sex, age, personal history of hypertension, diabetes, current smoking, creatinine, metabolic syndrome components (blood pressure, triglycerides, and high-density lipoprotein cholesterol). Those for stroke included male sex, age, personal history of hypertension, diabetes, current smoking, high γ-glutamyl transferase, and metabolic syndrome components (blood pressure, triglycerides, and high-density lipoprotein cholesterol). The prediction model showed an area under the receiver operating characteristic curve of 0.735 and 0.760 for MI and stroke, respectively, in the farmer cohort. Conclusions: Farmers had a higher age-adjusted incidence of MI and stroke. They also showed distinct patterns in cardiovascular risk factors compared to the general population.

• 한국지반공학회논문집
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• 제21권10호
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• pp.99-112
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• 2005

도심지에서의 지반굴착은 배면지반의 변위와 그에 따르는 건물의 손상을 유발시킨다. 굴착에 의한 지반변위의 예측과 굴착면 주변에 위치한 건물의 손상 위험도 평가는 설계단계에서 필수적인 요소이다. 본 논문에서는 기존의 굴착에 의한 지반변위 예측기법인 Peck의 방법과 Bowles의 방법을 조합하여 지보굴착에 따르는 배면지반 변위예측방법을 제안하였다. 또한, 배면지반의 Green-field 뒤틈각과 수평변형률을 이용한 인접건물 손상위험도 평가기법을 제안하였다. 이 기법은 싱가폴에서 시공중인 대규모 지반굴착공사의 설계에 성공적으로 적용되었다.