• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.936-943
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• 2009

In this study, a risk assessment model based on the ETA (Event Tree Analysis) and FTA (Fault Tree Analysis) is developed according to the procedure of hazard analysis and risk assessment in order to estimate the risk quantitatively. The FTA technique is applied to estimate the branch probability (frequency) and the ETA technique is applied to estimate the consequence for each branch path on the ET (Event Tree). A risk assessment model is developed by the combination of those ETA and FTA. In addition, the reliability and the validity of the risk assessment model are verified by comparing the risk estimated through the developed model with the actual equivalent fatality.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.303-313
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• 2023

This study aimed to investigate the relevance of cardiovascular disease risk factors AI and AIP, divided into three groups, among 300 individuals who underwent health checkups at the hospital. Various variables such as Age, Sex, BMI, WC, TC, TG, HDL-C, LDL-C, FBS, HbA1C, SBP, DBP, HR, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) were analyzed using statistical methods including frequency analysis, cross-tabulation, one-way ANOVA, Pearson's correlation analysis, and multiple linear regression analysis. The cross-analysis based on cardiovascular disease risk criteria revealed that men and individuals in their 50s had higher cardiovascular disease risk based on AI and AIP. Significant differences were observed in TG, TC, HDL-C, LDL-C, SBP, DBP, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) according to AI criteria. For the AIP criteria, TG, TC, HDL-C, FBS, HbA1C, HR, AI (TC/HDL-C), and AIP (log(TG/HDL-C)) were identified as cardiovascular disease risk factors. FBS and HbA1c showed the highest positive correlation In the correlation analysis, followed by TC and LDL-C. The lowest positive correlation was observed between LDL-C and DBP. In terms of negative correlation, HDL-C and AI had the highest negative correlation, while LDL-C and TG showed the lowest negative correlation. Multiple regression analysis indicated that the AI and AIP risk criteria had explanatory powers of 73.6% and 72.5%, respectively. HDL-C had the greatest negative effect on the AI risk criterion, while TG had the most significant influence on the AIP risk criterion. In conclusion, while other serological variables are important, managing HDL-C and TG levels may help reduce the risk of cardiovascular disease.

• The Journal of Information Systems
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• v.20 no.3
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• pp.63-79
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• 2011

Deducting the risk level of infrastructure and buildings based on past human disaster risk cases and implementing prevention measures are important activities for disaster prevention. The object of this study is to measure the confidence to proceed quantitative analysis of various disaster risk cases through text mining methodology. Indeed, by examining confidence calculation process and method, this study suggests also a basic quantitative framework. The framework to measure the confidence is composed into four stages. First step describes correlation by categorizing basic elements based on human disaster ontology. Secondly, terms and cases of Term-Document Matrix will be created and the frequency of certain cases and terms will be quantified, the correlation value will be added to the missing values. In the third stage, association rules will be created according to the basic elements of human disaster risk cases. Lastly, the confidence value of disaster risk cases will be measured through association rules. This kind of confidence value will become a key element when deciding a risk level of a new disaster risk, followed up by preventive measures. Through collection of human disaster risk cases related to road infrastructure, this study will demonstrate a case where the four steps of the quantitative framework and process had been actually used for verification.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.329-341
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• 2021

This study derives the risk-Influence factors for subway structures, the basis for the transition from the current subway disaster recovery-oriented maintenance system to a preemptive disaster management system, to reduce risk factors for existing subway structures. To apply reasonable risk assessment techniques, risk influence factors for subway underground structures using statistical information(spatial information) and risk influence factors according to frequency of accidents were selected to derive the risk factors. The significant risk factors were verified through ground subsidence (SI: Subsidence Impact)-based correlation analysis. This process confirmed that the subsidence of the ground was a risk influence factor for the subway structure. The main result of this study is that derive the risk factors to improve the risk factors of subway structures due to the rapid increase in disaster risk factors. The derived risk factors that were expected to affect the depression around subway stations and track structures did not show a noticeable correlation, but the cause of this may be that there is no physical connection between them, but on the other hand, the accumulated data may not accurately record the surrounding depression. Accordingly, in order to evaluate the risk of depression around the station and track, more intensive observation and data accumulation around the structure are required.

• Journal of Biomedical Engineering Research
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• v.31 no.5
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• pp.375-384
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• 2010

The purpose of this study is to determine whether there is a correlation between the segmental bio-impedance measurement with the frequency modulations and the life-style disease of obesity. An obesity is not simply the factor for estimating the life-style disease of obesity, but also the risk factor occurring. There are many methods (BMI, WHR, Waist, CT, DEXA, BIA, etc.) for measuring a degree of obesity; the bio-impedance measurement is more economic and more effective than others. The physical examination, the blood test, the medical imaging diagnosis and the bio-impedancemeasurementswithmultiple frequencies for each body parts have been conducted for 77 people. The estimated value has been calculated through a segmental bio-impedance model based on multi-frequency that was created to reflect the highest correlation by analyzing correlation with linear regression analysis method for the measured bio-impedance and the risk factors. Then we compared with the clinical diagnosis. In case of high level cholesterol, low HDL-C and high LDL-C for life-style disease, the sensitivity is 80~100%and the specificity is 83~100%. This study has shown conclusively that bio-impedance can be a possible predictor to analyze the disease risk rate of population and individual health maintenance. And also the multi-frequency segmental bio-impedance can be used as early predictor to estimate the life-style disease of obesity.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.3
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• pp.387-393
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• 2018

Considering the effect of climate change, a quantitative analysis of extreme drought is needed to reduce the damage from extreme droughts. Therefore, in this study, a quantitative risk analysis of extreme drought was conducted. The threshold level method was applied to define a drought event using Cheugugi rainfall data in past, gauged rainfall data in present, and climate change scenario rainfall data in future. A bivariate drought frequency analysis was performed using the copula function to simultaneously consider two major drought characteristics such as duration and severity. Based on the bivariate drought frequency curves, the risks for the past, present and future were calculated and the risks for future extreme drought were analyzed comparing with the past and present. As a result, the mean drought duration of the future was shorter than that of past and present, however, the mean drought severity was much larger. Therefore short term and severe droughts were expected to occur in the future. In addition, the analysis of the maximum drought risk indicated that the future maximum drought risk was 1.39~1.94 times and 1.33~1.81 times higher than the past and present. Finally, the risk of extreme drought over past and present maximum drought in the future was very high, ranging from 0.989 to 1.0, and the occurrence probability of extreme drought was high in the future.

• Journal of Korean Public Health Nursing
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• v.33 no.1
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• pp.47-58
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• 2019

Purpose: Regarding the rapid growth of the obesity in Korea's youths, environmental factors as well as biological tendencies have been major focus of years of study. Methods: This study, as a secondary analysis research, bases its source upon the raw data from the 13th on-line survey of the Korean adolescents' health behaviors. In particular, it is a descriptive research for clarifying the relevance of the Korean youths' smart phone use with their health behaviors and obesity. Results: In logistic analysis, variables showing a significant difference are as follows: soft drinks frequency(p<.001), sweet drinks intake frequency(p<.001), fast food intake frequency(p<.001) and smoking status (p=.005). Based on the amount of time the teenagers using smart phones, there have been different results in the risk of obesity. Four to six hours a week of smart phone use (p=.002) has a 1.132 times higher risk, six to eight hours(p<.001) are 1.212 times higher, over eight hours(p=.020) are 1.132 times higher, than less than two hours'. Conclusion: This study has significance in that it has emphasized the new lifestyle, teenagers' smart phone use, as an additional important factor for the increased risk of obesity.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.3
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• pp.123-134
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• 2006

In this study ship collision risk analysis is performed to determine the design vessel for collision impact analysis of the maritime bridge. Method II which is a probability based analysis procedure is used to select the design vessel for collision impact from the risk analysis results. The analysis procedure, an iterative process in which a computed annual frequency of collapse(AF) is compared to the acceptance criterion, includes allocation method of acceptance criterion of annual frequency of bridge component collapse. The AF allocation by weights seems to be more reasonable than the pylon concentration allocation method because this AF allocation takes the design parameter characteristics quantitatively into consideration although the pylon concentration allocation method brings more economical results when the overestimated design collision strength of piers compared to the strength of pylon is moderately modified. From the assessment of ship collision risk for each bridge pier exposed to ship collision, a representative design vessel for all bridge components is selected. The design vessel size varies much from each other in the same bridge structure depending upon the vessel traffic characteristics.

• Journal of the Korean Society of School Health
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• v.32 no.1
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• pp.32-40
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• 2019

Purpose: The purpose of this study was to investigate the risk factors for addiction-related behaviors among Korean adolescents. Methods: The study's subjects were 60,040 middle and high school students who participated in the 14th (2018) Korea Youth Risk Behavior Web-based Survey. Frequency analysis, $x^2$ test, and multivariate logistic regression were conducted using SPSS 21.0. Results: The risk factors for addiction-related behaviors were sex, school type, living area, academic performance, economic status, residence type, health status, depression, perceived stress and sleep satisfaction. Conclusion: Addiction-related behaviors are associated with mental health. Therefore, in order to prevent addictive-behaviors of adolescents, it is necessary to develop strategies to prevent addictive-behaviors by improving their mental health.

• Structural Engineering and Mechanics
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• v.66 no.1
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• pp.75-84
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• 2018

This study presents the reliability-based analysis of nonlinear structures using the analytical fragility curves excited by random earthquake loads. The stochastic method of ground motion simulation is combined with the random vibration theory to compute structural failure probability. The formulation of structural failure probability using random vibration theory, based on only the frequency information of the excitation, provides an important basis for structural analysis in places where there is a lack of sufficient recorded ground motions. The importance of frequency content of ground motions on probability of structural failure is studied for different levels of the nonlinear behavior of structures. The set of simulated ground motion for this study is based on the results of probabilistic seismic hazard analysis. It is demonstrated that the scenario events identified by the seismic risk differ from those obtained by the disaggregation of seismic hazard. The validity of the presented procedure is evaluated by Monte-Carlo simulation.