• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.5
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• pp.402-409
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• 2016

Vessel traffic servies (VTS) control movements in ports and coastal areas 24 hours a day using VHF. Thus, we were able to check ship movements and the patterns followed by VTS officers in VTS areas using VHF communication analysis. This study is intended to identify control intervals for dangerous situations and provide VTS officers with basic data and guidelines to prevent these occurrences in advance. We listened to Busan port's VHF communication for seven days and obtained risk values using the Park model with reference to controlled ships. The probability of a dangerous situation arising under a controller's watch per unit of time was confirmed to follow a Poisson distribution. As a result, for each 3.50 hours that VTS directly controls an area, (and in daytime for each 2.85 hours) a ship communicates in a VTS area every 3.84 hours, and some of there communications exceed certain risk values in VTS areas.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.95-102
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• 2023

This study was to identify the factors affecting nurses' use intention of digital healthcare and the moderating effect of clinical career based on the UTAUT model. The items were composed by performance expectancy 3 items, facilitation condition 3tiems, and perceived risk 3 items. CFA was performed to verify the construct validity. As a results, average variance extracted (AVE) was .5 or higher, and construct reliability (CR) was .7 or higher. Model fit was confirmed as CMIN/df=1.797, GFI=.955, CFI=.979, TLI=.968, IFI=.979, and RMSEA=.063. The internal reliability was .93 for performance expectancy, .84 for facilitating conditions, and .64 for perceived risk. Performance expectancy, facilitating condition, and perceived risk had a significant effect on use intention, and clinical career showed a moderating effect(t=-2.159, p=.032). Therefore, in order to enhance the use intention of digital health care, performance expectancy, and facilitating conditions should be raised and perceived risk should be reduced.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.245-253
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• 2021

Purpose: This study develops a risk prediction model that predicts the risk of a fire site by using initial information such as building information and reporter acquisition information, and supports effective mobilization of fire fighting resources and the establishment of damage minimization strategies for appropriate responses in the early stages of a disaster. Method: In order to identify the variables related to the fire damage scale on the fire statistics data, a correlation analysis between variables was performed using a machine learning algorithm to examine predictability, and a learning data set was constructed through preprocessing such as data standardization and discretization. Using this, we tested a plurality of machine learning algorithms, which are evaluated as having high prediction accuracy, and developed a risk prediction model applying the algorithm with the highest accuracy. Result: As a result of the machine learning algorithm performance test, the accuracy of the random forest algorithm was the highest, and it was confirmed that the accuracy of the intermediate value was relatively high for the risk class. Conclusion: The accuracy of the prediction model was limited due to the bias of the damage scale data in the fire statistics, and data refinement by matching data and supplementing the missing values was necessary to improve the predictive model performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.603-610
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• 2018

The development of industry and the increase in the use of fossil fuels have accelerated the process of global warming and climate change, resulting in more frequent and intense natural disasters than ever before. Since electricity facilities are often installed outdoors, they are heavily influenced by natural disasters and the number of related accidents is increasing. In this paper, we analyzed the statistical status of domestic electrical fires, electric shock accidents, and electrical equipment accidents and hence analyzed the risk associated with climate change. Through the analysis of the electrical accidental data in connection with the various regional (metropolitan) climatic conditions (temperature, humidity), the risk rating and charts for each region and each equipment were produced. Based on this analysis, a basic electric risk prediction model is presented and a method of displaying an electric hazard prediction map for each region and each type of electric facilities through a website or smart phone app was developed using the proposed analysis data. In addition, efforts should be made to increase the durability of the electrical equipment and improve the resistance standards to prevent future disasters.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2010.04a
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• pp.53-58
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• 2010

발열량은 화재현상을 이해하고 화재의 위험도를 평가하는데 있어서 가장 기본이 되는 물리량으로 화재강도를 나타내는 척도로 인식되고 있다. 발열량의 신뢰성은 화재 물성이나 공간화재 특성의 이해뿐만 아니라 화재해석을 통한 위험성 평가에 있어서 중요한 요소이기 때문에 측정의 신뢰성이 매우 중요하다. 본 연구에서는 수치해석 모델을 통하여 화재 발열량계의 배기덕트 구조에 따른 내부 유동특성을 파악하고자 한다. 해석결과를 바탕으로 각 측정점의 위치에 따른 상태오차 정도를 분석하고 산소소모법에 의해 계산된 발열량을 비교한다. 화재 발열량계의 수치해석을 통하여 발열량 산정의 오차특성을 평가함으로써 발열량계 설계 과정을 최적화하고 효과적인 발열량계 운영을 위한 기초자료를 얻는데 기여하고자 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1385-1389
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• 2010

수자원 계획에 있어서 강우 또는 홍수빈도분석시 주로 사용되는 확률의 개념은 상대빈도에 대한 극한으로 확률을 정의하는 빈도학파적 확률관점에 속하며, 확률모델에서 미지의 매개변수들은 고정된 상수로 간주된다. 따라서 확률은 객관적이고 매개변수들은 고정된 값을 가지기 때문에 이러한 매개변수들에 대한 확률론적 설명은 매우 어렵다. 본 연구에서는 강우빈도해석에서 확률분포의 매개변수에 대한 불확실성을 정량화하기 위하여 베이지안 MCMC 및 Metropolis-Hastings 알고리즘을 이용한 불확실성 평가모델을 구축하였다. 그리고 베이지안 MCMC 및 Metropolis-Hastings 알고리즘의 적용을 통하여 확률강우량 산정시 확률분포의 매개변수에 대한 통계학적 특성 및 불확실성 구간을 정량화하였으며, 이를 바탕으로 홍수위험평가 및 의사결정과정에서 불확실성 및 위험도를 충분히 설명할 수 있는 프레임워크 구성을 위한 기초를 마련할 수 있었다.

• The Journal of Engineering Geology
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• v.21 no.4
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• pp.393-402
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• 2011

Asbestos is a toxic material that can lead to lung cancer and other diseases. There is no information regarding areas in Korea that contain asbestos in nature; consequently we need to manage such areas with care. The purpose of this study was to construct a local graded map of asbestos exposure risk based on the natural occurrence of asbestos in rocks. We first developed a means of evaluating the asbestos exposure risk and produced thematic maps based on a field survey. In addition, we constructed a knowledge base for asbestos through analysis, representation and processes about asbestos data and prepare for the development of an evaluation model for asbestos exposure risk. The spatial analysis of asbestos exposure risk is based on a weighted-overlay analysis using expert opinion and the literature, and a fuzzy-overlay analysis using the uncertainty in the data. The map of asbestos exposure risk, compiled according to the weighted and fuzzy operations, is expected to be used to ensure safety and to reduce the risk of exposure to asbestos.

• Economic and Environmental Geology
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• v.40 no.3 s.184
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• pp.295-306
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• 2007

In this study, we predicted areas vulnerable to ground subsidence near abandoned underground coal mine at Sam-cheok City in Korea using a probability (frequency ratio) model with Geographic Information System (GIS). To extract the factors related to ground subsidence, a spatial database was constructed from a topographical map, geo-logical map, mining tunnel map, land characteristic map, and borehole data on the study area including subsidence sites surveyed in 2000. Eight major factors were extracted from the spatial analysis and the probability analysis of the surveyed ground subsidence sites. We have calculated the decision coefficient ($R^2$) to find out the relationship between eight factors and the occurrence of ground subsidence. The frequency ratio model was applied to deter-mine each factor's relative rating, then the ratings were overlaid for ground subsidence hazard mapping. The ground subsidence hazard map was then verified and compared with the surveyed ground subsidence sites. The results of verification showed high accuracy of 96.05% between the predicted hazard map and the actual ground subsidence sites. Therefore, the quantitative analysis of ground subsidence near abandoned underground coal mine would be possible with a frequency ratio model and a GIS.

• Information Systems Review
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• v.13 no.2
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• pp.17-41
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• 2011

A review of the related literature indicates that consumers' risk perceptions are largely affected by product involvement. This study investigates the impact of product involvement on required trust level and the online merchant choice. We developed a conceptual model that depicts the nomological relationships among product involvement, required trust level, and the online merchant choice, and formulated three hypotheses based on the conceptual model. An empirical study designed to accomplish the research objectives has been conducted using a questionnaire survey with 230 students in a university in Korea. The findings indicated that high-involvement products have higher trust level as required by consumers than low-involvement products, that consumers buying high-involvement products prefer digital storefronts, and that consumers buying low-involvement products prefer B2C e-marketplaces. The paper offers implications for academics as well as practitioners, based on the research results.

• Journal of agriculture & life science
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• v.44 no.6
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• pp.69-78
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• 2010

Haines index which include the rating of atmosphere instability and dryness indicated the potential of the forest fire danger. In this study, the relationships between forest fire occurrence and Haines index were analyzed. The probability of forest fire occurrence was the highest in April and HI 5, 6 and the dryness of atmosphere was higher than the atmosphere instability. Therefore, It was proved that HI affected on the forest fire occurrence and propagation.