• 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 Navigation and Port Research
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• v.47 no.2
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• pp.93-99
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• 2023

This study aimed to determine relationships among risk factors influencing container port operation using Bayesian network. Risk factors identified from prior studies were classified into five groups: human error, machinery error, environmental risk, security risk, and natural disasters. P anel experts discussed identified risk factors to fulfil conditional probability tables of the interdependence model. The interdependence model was also validated by sensitivity analysis and provided an interrelation of factors influencing the direction of each other. Results of the interdependence model were partially in line with results from prior studies while practices in the global port industry confirmed interrelationships of risk factors. In addition, the relationship between top-ranked risk factors can provide a schematic drawing of the model. Accordingly, results of this study can expand the prior research in the Korean port industry, which may help port authorities improve risk management and reduce losses from the risk.

• Journal of the Korean Society of School Health
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• v.29 no.3
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• pp.256-266
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• 2016

Purpose: This study was to compare and to examine the factors related to risk behaviors of adolescents living in small and medium-sized cities and in rural areas. Methods: The subjects were 545 adolescents (295 from small and medium-sized cities and 250 from rural areas). The data was analyzed by descriptive statistics, Pearson corelation coefficients, and multiple regression with IBM SPSS 19.0 program. Results: The factors influencing the risk behaviors of adolescents in small- medium cities were school, peer risk factors and community risk factors, self- control among protective factors, positive communication with parents, positive peer associations, these variables explained 42.0%. The most important variable explaining the risk behaviors of adolescents in small- medium cities was positive communication with parents, followed by community risk factors, peer risk factors, positive peer relationships, school and self-control. The factors affecting the risk behaviors of rural adolescents were school, personal risk factor, peer risk factor, self- control factor, which explained 38.5% of the risk behaviors of adolescents in rural areas. Among them, the most important variable explaining risk behaviors was personal risk factors, followed by peer risk factors, school, and self-control. Conclusion: These finding suggest a need to develop a strategy to improve positive communication with parents for adolescents living in small- medium cities and a strategy to reduce personal risk factors and peer risk factors for rural adolescents.

• Journal of Korean Academy of Nursing
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• v.25 no.2
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• pp.351-361
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• 1995

The main purpose of the study is to identify critical risk factors for development of a family assessment tool to screen high risk family. This study used a conceptual framework of family diagnosis developed by Eui-sook Kim's (1993) and analyzed risk factors to identify the high risk family. As employing a explorative and methodological study design, this study has four stages. 1. In the first stage, 34 family risk factors were identified by doing intensive literature review on conceptual framework of family diagnoses. 2. In the second stage, above risk factors were tested for content validity by consultation with 29 persons in community health nursing, nursing education, family theory, and social work. 3. In the third stage, existing survey data was used for actual application of the identified risk factors. The survey data used for this purpose was previously collected for the community diagnosis in a region of Seoul. At the final stage, through the comparison between high risk and low risk families, initially identified 34 risk factors decreased to 25 risk factors. Among 34 risk factors, six factors did not agree with content of questionnaries sand two factors were not significant in differentiating the high risk family Also, two risk factors showed high correlation between themselves, so only one of those two factors was chosen. As a result, twenty-five risk factors chosen to identify the high risk family are following ; 1. A single parent family due to divorce or death of a partner, or unweded single mother 2. A family with an unrelated household members 3. A family with a working mother with a young child 4. A family with no regular income 5. A family with no rule in family or too strict rules 6. A family with little or no support from other lam-ily members 7. A family with little or no support from friends or relatives 8. A family with little or no time to share with each other 9. A family with family history of hypertension, diabetus, cancer 10. A family with a sick person 11. A family with a mentally ill person 12. A family with a disabled person 13. A family with an alcoholic person 14. A family with a excessive smoker who smokes more than 1 pack / day 15. A family with too much salt intake in their diet. 16. A family with inappropriate management skills for family health 17. A family with high utilization of drug store than hospital to solve the health problems of the family 18. A family with disharmony between husband and wife 19. A family with conflicts among the family members 20. A family with unequal division of labor among family members 21. An authoritative family structure 22. A socially isolated family 23. The location of house is not residential area 24. A family with high risk of accidents 25. The drinking water and sewage systems are not hygienic. The main implication of the results of this study is clinical use. The high risk factors can be used to identify the high risk family effectively and efficiently. The use of high risk factors woule contribute to develop a conceptual framework of family diagnosis in Korea and the list of risk factors need to be revised continuously. Further researches are needed to develop an index of weight of each risk factor and to validate the risk factors.

• Korean Journal of Child Studies
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• v.26 no.6
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• pp.127-144
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• 2005

This study is to analyze the effects of child's inner risk factors and outer risk factors intermediated by self concept on his or her resiliency at-risk. For this study, the total of 500 students in their fifth and sixth grade of elementary schools in Busan and their parents were sampled, and a measurement tool is question district court. The questionnaire for the parents measured risk factors, and the questionnaire for the students measured self-concept and about the resiliency at-risk. The SPSS for Win 12.0 and AMOS 5.0 were used to analyze the collected data. The result of this study is as follows; First, there is a significant correlation between the sub-factors of inner risk factors, which shows that the risks of students are caused not just by one of the parents but by both of them. Second, all three variables, that is, inner risk factors, self-concepts, and the resiliency at-risk, closely interact one another. The less inner risk factors of the students, the more positive their self-concept and the more the resiliency to the risk. Third, the higher the socioeconomic status (outer risk factors) and the lower the degree of risk of the family, the more positive the self-concept of the students. Fourth, the higher the socioeconomic status(outer risk factors) and the lower the degree of risk of the family, the more the resiliency to the risk.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.328-331
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• 2017

The purpose of this study is to derive construction-phase risk factors in SMEs' advance into overseas plant construction projects. For this, construction-phase risk factors were investigated on the basis of the analysis of Korean construction companies, overseas plant industry-related research institutes, and overseas data. In addition, major risk factors were derived from the investigated construction-phase risk factors, and quantitative risk factors and qualitative risk factors were analyzed and derived from these major risk factors, by the use of three rounds of the Delphi analysis.

• Preventive Nutrition and Food Science
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• v.6 no.1
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• pp.73-78
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• 2001

The elevation of total plasmahomocysteine is now an established risk factor for cardiovascular disease. Plasma folate and vitamin {TEX}$B_{12}${/TEX} influence Hcy metabolism as cofactors. In this study, we studied the relationship of major risk factors for cardovascular disease, including advanced age, male gender, obesity, hypertension, hyperglycemia, and dislipidemia and plasma homocyteine, folate and vitamin {TEX}$B_{12}${/TEX} levels in Koreans. A total of 195 adult Koreans participated. The subjects were divided into three groups according to how many major conventional risk factors of cardiovascular disease they had: no risk, low risk (1~3 risk factors) and high risk (>3 risk factors) groups. As the number of risk factors increased, the plasma homocysteine levels significantly increase, while the plasma folate levels significantly decreased. The plasma homocysteine levels re higher in males than in females. The subjects with hyperglycemia had higher plasma homocysteine levels than the subjects without the risk factor. Also the subjects with dislipidemia had higher plasma homocysteine levels than the subjects without the risk factor. The plasma folate and vitamin {TEX}$B_{12}${/TEX} levels were significantly lower in males tan females. However, there were no significant differences in plasma folate and vitamin {TEX}$B_{12}${/TEX} levels between the subjects with or without other risk factors. These results indicate that plasma homocysteine levels were positively related with risk factors for cardiovascular disease and plasma folate levels were negatively related with the risk factors for cardiovascular disease. Also, we conclude that plasmahomocysteine levels might be related to the combination of risk factors, rather than an individual risk factor.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.5
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• pp.431-438
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• 2012

The representative risk evaluation techniques of the marine traffic environment are the FSA, PAWSA, & IWRAP. For the development of these techniques, the risk factors suitable to the marine traffic environment should be selected & the assessment criterion of the risk factors should be provided. The risk factors were selected as the factors that relate both to the frequency of casualty & to the consequence of casualty because the risk was defined as the frequency of casualty times the consequence of that casualty on the existing techniques. But, the risk factors relate to the consequence of casualty are excluded because the risk is defined as the sum of the risk factors including the frequency and the consequence by factors on this study. The 20 kinds of risk factors to compose the risk are selected and classified into 5 categories according to similar nature through the analysis of preceding study on the classification of the risk factors. Finally, as the foundation of risk assessment model's development for domestic marine traffic environment, the practical assessment criterion of the risk factors are suggested.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.174-184
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• 2023

In this study, the structural relationship among risk factors, safety motivation, and safety behavior perceived by telecommunications workers was empirically verified. A survey was conducted on field workers at S telecommunications companies in Korea, and the following major results were obtained. First, among the risk factors perceived by telecommunications workers, personal, cultural, and institutional factors were found to have significant positive effects on workers' safety motivation. Second, workers' safety motivation had a significant positive effect on safety behavior. Third, among the risk factors of telecommunications companies, personal, cultural, and institutional factors did not significantly affect workers' safety behavior. Fourth, all risk-causing factors perceived by workers, such as personal, cultural, and institutional factors, indirectly affected safety behavior through safety motivation. This study presents the importance of perceiving risk factors in the workplace to prevent and alleviate industrial accidents by examining the effects of riskcausing factors perceived by carrier workers on safety motivation and behavior.

• Korean Management Science Review
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• v.33 no.3
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• pp.105-117
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• 2016

In this paper, we present empirical testing result to examine the validity of inbound supply and outbound demand risk factors in the sense of early predicting the firm's bankruptcy risk level. The risk factors are drawn from industry uncertainty attributes categorized as uncertainties of input market (inbound supply), and product market (outbound demand). On the basis of input-output table, industry level inbound and outbound sectors are identified to formalize supply chain structures, relevant inbound and outbound uncertainty attributes and corresponding risk factors. Subsequently, publicly available macro-economic indicators are used to appropriately quantify these risk factors. Total 68 industry level bankruptcy risk forecasting results are presented with the average R-square scores of between 53.4% and 37.1% with varying time lag. The findings offers useful insights to incorporate supply chain risk to the body of firm's bankruptcy risk level prediction literature.