• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.55-74
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• 2005

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper employs a relatively new machine learning technique, support vector machines (SVMs). to bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use grid search technique using 5-fold cross-validation to find out the optimal values of the parameters of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM. we compare its performance with multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.615-616
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• 2006

Many manufacturing companies manage their production-related data for quality management and production management. Nevertheless, production related-data should be closely related to each other Stored data is mainly used to monitor their process and products' error. In this paper, we provide an enterprise-wide production data model for decision support system and product automation. Process data, quality-related data, and test data are integrated to identify the process inter or intra dependency, the yield forecasting, and the trend of process status. In addition, it helps the manufacturing decision support system to decide critical manufacturing problems.

• Journal of the Korea Safety Management & Science
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• v.7 no.1
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• pp.199-210
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• 2005

Customer segmentation prediction has attracted a lot of research interests in previous literature, and recent studies have shown that artificial neural networks (ANN) method achieved better performance than traditional statistical ones. However, ANN approaches have suffered from difficulties with generalization, producing models that can overfit the data. This paper employs a relatively new machine learning technique, support vector machines (SVM), to the customer segmentation prediction problem in an attempt to provide a model with better explanatory power. To evaluate the prediction accuracy of SVM, we compare its performance with logistic regression analysis and ANN. The experiment results with real data of insurance company show that SVM superiors to them.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1319-1325
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• 2010

Quantile regression provides a more complete statistical analysis of the stochastic relationships among random variables. Sometimes quantile functions estimated at different orders can cross each other. We propose a new non-crossing quantile regression method applying support vector median regression to restricted regression quantile, restricted support vector quantile regression. The proposed method provides a satisfying solution to estimating non-crossing quantile functions when multiple quantiles for high dimensional data are needed. We also present the model selection method that employs cross validation techniques for choosing the parameters which aect the performance of the proposed method. One real example and a simulated example are provided to show the usefulness of the proposed method.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.340-345
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• 1996

Because of limited resources of time and information processing capability during abnormal situation, diagnosis is difficult tasks in nuclear power plant (NPP) operators. Moreover since minimizing of adverse consequences according to process abnormalities is vital for the safety of NPP, introducing of diagnosis support systems have particularly emphasized. However, considerable works to develop effective diagnostic support system are not sufficiently fulfilled because of the complexity of NPP is one of the major problems. To cope with this complexity, a lot of model-based diagnosis support systems have considered and implemented worldwide. In this paper, as a prior step to development of model-based diagnosis support systems, primary side of pressurized water reactor is functionally modeled by multilevel flow modeling (MFM) concept. MFM is suitable for complex system modeling and for diagnosis of abnormalities. Furthermore, knowledge-based diagnosis process, of NPP operator could be supported because this diagnosis strategy can represent operator's one.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.386-401
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• 2024

The study introduces and validates a model of post-traumatic growth among parents of children with special needs. The model incorporates cognitive processes, coping strategies, and sociocultural factors as intra-personal variables. The statistical analysis unveiled significant pathways that connect the factors, explaining 71% of the variance associated with post-traumatic growth. The study highlighted intentional reflection and robust decentralization skills as crucial factors that predict post-traumatic growth. Deliberate rumination functioned as a mediating factor, reducing the impact of trauma and facilitating post-traumatic growth, while social support played a crucial role in initiating purposeful rumination. The study findings indicate that the effect of self-disclosure on post-traumatic growth is not direct but rather indirect, as it is mediated by its influence on social support and deliberate rumination. The study underscores the significance of examining particular characteristics of social support networks and suggests integrating additional variables for future research, such as gender, types of traumatic events, and the age of children with disabilities.

• Journal of dental hygiene science
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• v.18 no.1
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• pp.32-41
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• 2018

This study investigated the relationship between the organizational culture, organizational support, organizational health, personal health, and quality of work life of dental hygienists and analyzed the factors affecting the quality of work life in order to identify ways to improve their quality of work life. A total of 320 dental hygienists completed a self-administered survey; after excluding data from 21 respondents, 299 responses were included in the analysis. Frequency analyses, t-tests, one-way analysis of variation (ANOVA), and correlation analyses were conducted. A path analysis was also conducted to confirm the causal relationships. The findings are as follows. First, there was a significant difference in several general characteristics of the organizational culture including years in the current job and the number of dental hygienists; organizational support including age and the number of dental hygienists; organizational health including years in the current job and annual salary; and personal health including annual salary. Second, the quality of work life showed a positive correlation with organizational culture, organizational support, personal health, and organizational health in that order. Third, the results of path analysis revealed that organizational culture had a positive effect on organizational support; organizational support and personal health on organizational health; organizational support on personal health; and organizational support and organizational health on quality of work life. In addition, organizational support and organizational health had a direct effect on the quality of work life, while organizational culture, organizational support, and personal health had an indirect effect. These results indicated existence of a relationship among organizational culture, organizational support, organizational health, personal health, and quality of work life. It is necessary to identify ways to improve the quality of work life of dental hygienists.

• Korean Journal of Biological Psychiatry
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• v.21 no.4
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• pp.141-150
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• 2014

Objectives The purpose of this study is to evaluate the effects of attachment security, social support and health-related burden in the prediction of psychological distress and the mediation effects of social support and health-related burden in relationship between attachment security and psychological distress. Methods Finally, 161 patients were included for the analysis. Chi-square test and independent samples t-test were used for comparing differences between depressive/anxious group and non-depressive/non-anxious group. For evaluating the relationship among attachment security, social support, psychological distress and health-related burden, structural equation modeling analysis were performed. Results 40.7% and 32.0% of the patients have significant depressive symptoms and anxiety symptoms, respectively. In the analysis for testing the differences between groups who have psychological distress and who have not, there were no significant differences of sociodemographic factors and medical characteristics between groups, except for association between depressive symptoms and type of surgery (p = 0.01). Contrary to sociodemographic and medical characteristics, there were significant differences of health-related burden and two coping resources (attachment security and social support) between groups (all p < 0.01), except for the support from medical team in between anxious group and non-anxious group (p = 0.20). In the structural equation model analysis (Model fit : chi-square/df ratio = 0.8, root mean square error of approximation = 0.000, comparative fit index = 1.000, non-normed fit index =0.991), attachment security and social support emerged as an important predictor of psychopathology. Conclusions Attachment security and social support are important factors affecting the psychological distress. We suggest that individual attachment style and the social support state must be considered to approach the newly diagnosed breast cancer patients with psychological distress.

• Health Policy and Management
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• v.8 no.1
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• pp.52-96
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• 1998

To find causal factors and improvement plans of organizational commitment of public servants in urban health centers, a hypothetical causal model, which included 2 endogenous variables(organizational commitment & organizational satisfaction) and 15 exogenous variables, was constructed. Exogenous variables consisted of individual factors (sex, age, education, job-grade, and annual salary), psychological variables(pride for organization, extrinsic motivation, intrinsic motivation and support of supervisor) ad structural variables(formalization, centralization, communication, job-conflict, job-decision, and workload). In the hypothetical causal model, organizational commitment was supposed to be effect variable, and organizational satisfaction was presumed to be intervening variable to mediate between organizational commitment and exogenous variables. For data collection, cross-sectional self-administered questionnaire survey was conducted to 1,295 public servants from 32 urban health centers nationwide. The survey responses were from 934, 72.1% of subjects. But 756 responses(58.4%) were analyzed because of excluding ones with missing values. The hypothetical causal model was fitted by covariance structural analysis with maximum likelihood method. Main results were as follows: (1) The fitted causal model accounted for 33 and 55 percent of total variance of organizational commitment and organizational satisfaction of public servants, respectively. (2) In order of effect size, pride for organization, supervisor support, communication, extrinsic motivation and centralization had an indirect effect effect on organizational commitment through organizational satisfaction. However, the effect of centralization was negative. (3) Pride for organiztion, intrinsic motivation, organizational satisfaction, job-conflict, supervisor support, communication, age, centralization, annual salar and extrinsic motivation had indirect or direct effects on organizational commitment in order of effect size. Among them, effects of job-conflict and centraldization were negative. In conclusion, these results suggested that organizational commitment of public servants in urban health centers could be enhanced by pride for organization, intrinsic and extrinsic motivations, prevention of job-conflict and excess centralization, supervisor support and active communication. Especially, pride for organization and intrinsic motivation were expected to play the most important role.

• Nuclear Engineering and Technology
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• v.51 no.8
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• pp.1905-1915
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• 2019

This paper investigated the influence of simple support girds on flow, irrespective of having mixing vanes, in a 1 × 3 array rod bundle by using CFD methodology and the most accurate turbulence model which could reflect the actual physics of the flow was determined. In this context, a CFD model was created simulating the experimental studies on a single-phase flow [1] and the results were compared with the experimental data. In the first part of the study, influence of mesh was examined. Tetra, hybrid and poly type meshes were analyzed and convergence study was carried out on each in order to determine the most appropriate type and density. k - ε Standard and RSM LPS turbulence models were used in this section. In the second part of the study, the most appropriate turbulence model that could reflect the physics of the actual flow was investigated. RANS based turbulence models were examined using the mesh that was determined in the first part. Velocity and turbulence intensity results obtained on the upstream and downstream of the spacer grid at -3d_h, +3d_h and +40d_h locations were compared with the experimental data. In the last section of the study, the behavior of flow through the spacer grid was examined and its prominent aspects were highlighted on the most appropriate turbulence model determined in the second part. Results of the study revealed the importance of mesh type. Hybrid mesh having the largest number of structured elements performed remarkably better than the other two on results. While comparisons of numerical and experimental results showed an overall agreement within all turbulence models, RSM LPS presented better results than the others. Lastly, physical appearance of the flow through spacer grids revealed that springs has more influence on flow than dimples and induces transient flow behaviors. As a result, flow through a simple support grid was examined and the most appropriate turbulence model reflecting the actual physics of the flow was determined.