• Journal of the Korean Society of Safety
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• v.28 no.3
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• pp.95-99
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• 2013

The goal of this study was to investigate some significant factors to influence level of safety at plant construction field and analyze degree of risk by work classification. Currently, there are lots of construction fields for the nuclear power plant for electricity generation, and our government also planned constructing more nuclear power plant in near future. However, much of the safety literature neglected the degree of risk factors on the plant construction field. Safety managers participated in the brainstorming session for drawing decision criteria of the degree of risk (i.e., significant factors). Then, they were asked to answer a structured questionnaire which was developed for drawing most important factors. Finally, the analytic hierarchy process (AHP) was used to analyze level of risk by work classification. The following results were obtained. First, total twelve factors judging degree of risk were found in the brainstorming session. Second, the questionnaire showed four significant factors, including number of workers, working environments, skill of craft and accident experience. Third, the results of AHP showed Architecture work is the most dangerous work among 6 work types. The results could be used to reduce degree of risk in construction field of the nuclear power plant.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.8
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• pp.89-97
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• 2022

The e-commerce market faces significant credit risks due to the complexity of the industry and information asymmetries. Therefore, credit risk has started to stymie the growth of e-commerce. However, there is no reliable system for evaluating the creditworthiness of e-commerce companies. Therefore, this paper constructs a credit risk evaluation index system that comprehensively considers the online and offline behavior of online retail enterprises, including 15 indicators that reflect online credit risk and 15 indicators that reflect offline credit risk. This paper establishes an integration method based on a fuzzy integral support vector machine, which takes the factor analysis results of the credit risk evaluation index system of online retail enterprises as the input and the credit risk evaluation results of online retail enterprises as the output. The classification results of each sub-classifier and the importance of each sub-classifier decision to the final decision have been taken into account in this method. Select the sample data of 1500 online retail loan customers from a bank to test the model. The empirical results demonstrate that the proposed method outperforms a single SVM and traditional SVMs aggregation technique via majority voting in terms of classification accuracy, which provides a basis for banks to establish a reliable evaluation system.

• Journal of Integrative Natural Science
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• v.4 no.1
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• pp.31-37
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• 2011

Various algorithms and system development are being required to support the advanced decision making of navigation information support system because of a serious loss of lives and property accidents by officer's error like as carelessness and decision faults. Much of researchers have introduced the techniques about the systems, but they hardly consider environmental factors. In this paper, We collect the context information in order to assess the risk, which is considered the various factor of the sailing ship, then extract the features of knowledge context, which is to apply the weight of correlation coefficients among data in context information. We decide the risk after the extract features through the classification and prediction of context information, and compare the value accuracy of proposed method in order to compare efficiency of the weighted value with the non-weighted value. As a result of experience, we know that the method of weight properties effectively reflect the marine environment because the weight accurate better than the non-weighted.

• The Journal of the Korea Contents Association
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• v.19 no.6
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• pp.461-470
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• 2019

In diabetes mellitus, renal disease is a common complication, characterized by increased urinary albumin excretion and reduced eGFR. According to KDIGO CKD stage classification, Korean characteristics were analyzed according to urinary albumin and eGFR using the National Health and Nutrition Examination Survey VI raw data. According to KDIGO classification, diabetic patients were classified as Low risk 72.0%, Moderate risk 19.3%, High risk 5.6% and Very high risk 3.0%. Low risk decreased from 74.7% to 52.2%, and moderate to very high risk increased from 25.4% to 47.8% as the duration of diabetes mellitus was prolonged. The risk factors were CKD stage 1 (HR 2.064) to stage 4 (HR 11.049), the highest risk of hypertension. The incidence of renal disease was elevated according to duration of hypertension and HR 0.42 of kidney disease was decreased in the group maintaining proper blood pressure. In the hypertensive patients, the group administered with target blood pressure had a reduction of the kidney disease by 42% than the group with the hypertension. Therefore, controlling and managing hypertension to target blood pressure is important for the prevention of kidney disease.

• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.86-94
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• 2019

This study investigated the differences of perceived parenting attitude and academic stress on smartphone addiction according to the classification of addiction-risk group among middle school students. A descriptive research design was used. The subjects were 358 middle school students from five middle school in Daegu. Data were analyzed by descriptive statistics, ${\chi}^2$ test, t-test, and stepwise multiple regression using SPSS 18.0. Smartphone addiction-risk group was 97(27.0%) and general group was 261(72.9%). Smartphone addiction-risk group was more negatively perceived parenting attitude and higher academic stress than the general group. The most influential factors on addiction-risk group was using time in a day(${\beta}=.29.4$, p=.003) and general group was academic stress(${\beta}=.298$, p=.000). It is important to develop an intervention program to prevention the smartphone addiction according to the classification of addiction-risk group.

• Korean Journal of Construction Engineering and Management
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• v.12 no.5
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• pp.117-126
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• 2011

With Public-private partnership PF (project financing) deals saw explosive increase in quantity since its introduction to Korea in 2001, but, met with severe recession in the fallouts of the financial crisis that hit the global economy in 2008. This study intends to identify the risk factors corresponding to issues of public-private partnership projects financing structure and classify and analyze them by project phase. Outcomes of this research are expected to help recognize risk factors in each project phase during project planning and develop risk control and mitigation strategy during project implementation.

• Physical Therapy Korea
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• v.27 no.2
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• pp.140-148
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• 2020

Background: Scapular winging (SW) could be caused by tightness or weakness of the periscapular muscles. Although data mining techniques are useful in classifying or predicting risk of musculoskeletal disorder, predictive models for risk of musculoskeletal disorder using the results of clinical test or quantitative data are scarce. Objects: This study aimed to (1) investigate the difference between young women with and without SW, (2) establish a predictive model for presence of SW, and (3) determine the cutoff value of each variable for predicting the risk of SW using the decision tree method. Methods: Fifty young female subjects participated in this study. To classify the presence of SW as the outcome variable, scapular protractor strength, elbow flexor strength, shoulder internal rotation, and whether the scapula is in the dominant or nondominant side were determined. Results: The classification tree selected scapular protractor strength, shoulder internal rotation range of motion, and whether the scapula is in the dominant or nondominant side as predictor variables. The classification tree model correctly classified 78.79% (p = 0.02) of the training data set. The accuracy obtained by the classification tree on the test data set was 82.35% (p = 0.04). Conclusion: The classification tree showed acceptable accuracy (82.35%) and high specificity (95.65%) but low sensitivity (54.55%). Based on the predictive model in this study, we suggested that 20% of body weight in scapular protractor strength is a meaningful cutoff value for presence of SW.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.341-346
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• 2022

Due to global warming and abnormal climate, the frequency and damage of floods are increasing, and the number of people exposed to flood-prone areas has increased by 25% compared to 2000. Floods cause huge financial and human losses, and in order to reduce the losses caused by floods, it is necessary to predict the flood in advance and decide to evacuate quickly. This paper proposes a flood risk determination model using a CNN-based classification model so that timely evacuation decisions can be made using rainfall and water level data, which are key data for flood prediction. By comparing the results of the CNN-based classification model proposed in this paper and the DNN-based classification model, it was confirmed that it showed better performance. Through this, it is considered that it can be used as an initial study to determine the risk of flooding, determine whether to evacuate, and make an evacuation decision at the optimal time.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.395-404
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• 2022

Purpose: Small-scale construction sites have insufficient systematic safety management activities, and due to the characteristics of the construction site, the production structure is complex due to external environmental factors, and the risk of construction equipment is very high. We would like to propose a checklist method among practical risk assessment techniques that can derive risk factors for disaster prevention at small construction sites and reduce disasters. Method: Risk factors were derived by analyzing literature research and disaster cases, and detailed work for a checklist of risk assessment suitable for small-scale construction sites was classified based on risk factor items. Result: Hazard factors were divided into 6 major categories, and 29 detailed types of work were classified based on actual work types, and 80 detailed works were classified accordingly. Conclusion: By arranging risk factors suitable for small-scale construction sites according to the classification system, the lack of expertise in the construction site can be supplemented, and risk factors can be derived more easily and disaster reduction can be expected through establishment of safety measures.

• The Journal of KAIRB
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• v.4 no.2
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• pp.36-41
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• 2022

Purpose: The purpose of this study is to evaluate how university hospital Institutional Review Boards (IRBs) in Korea classify risk when reviewing clinical trial protocols. Methods: IRB experts (IRB chairman, vice chairman, IRB administrator) in the university hospitals obtaining a Human research protection program (HRPP) or IRB accreditation in Korea were asked to fill out the Google Survey from September 1, 2020 to October 10, 2020. Result: Among the 23 responder hospitals, 8 were accredited by the American Association for Human Research Protection Program (AAHRPP) and 8 were accredited by the HRPP of Ministry of Food and Drug Safety (MFDS). Seven were accredited by Forum for Ethical Review Committees in Asia and the Western Pacific or Korea National Institution for Bioethics Policy. Thirteen of 23 hospitals (56.5%) had 4 levels (less than minimal, low, moderate, high risk), 4 hospitals had 3 levels (less than, slightly over, over than minimal risk), 1 hospital had 5 levels (4 levels plus required data safety monitoring board), and 1 hospital had 2 levels (less than, over than minimal risk) risk classification system. Thirteen of 23 hospitals (56.5%) had difficulty classifying the risk levels of research protocols. Fourteen hospitals (60.9%) responded that different standards among hospitals for risk level determination associated with clinical trials will affect the subject protection. Six hospitals (26.1%) responded that it will not. Three hospitals (13.0%) responded that it will affect the beginning of the clinical trial. To resolve differences in standards between hospitals, 14 hospitals (60.9%) responded that either the Korean Association of IRB or MFDS needs to provide a guideline for risk level determination in clinical trials: 5 hospitals (21.7%) responded education for IRB members and researchers is needed; 3 hospitals (13.0%) responded that difference among institutions needs to be acknowledged; and 1 hospital (4.3%) responded that there needs to be communication among IRB, investigator, and sponsor. Conclusion: After conducting a nationwide survey on how IRB in university hospital determines risk during review of clinical trials, it is reasonable to use 4-level risk classification (less than minimal, low, moderate, high risk); the most utilized method among hospitals. Moreover, personal information and conflict of interest associated with clinical trials have to be considered when reviewing clinical trial protocols.