• Journal of Welding and Joining
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• v.20 no.6
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• pp.776-782
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• 2002

The experimental model of arc sensor in $CO_2$ arc welding has been individually developed according to welding condition and welding procedure. Therefore, the development of new arc sensor having the features of all conventional arc sensor is important in point of its application to various welding environment. In this study, the arc sensor experimental models comprised of a regression model and noise term were formulated using conventional arc sensing algorithm such as current area difference, current integration difference and weaving end current difference method, and their features were observed. The new regression arc sensor model was suggested using multiple linear regression analysis using current variables as independent variables of regression analysis. The artificial neural network model was also suggested where current variables and offset distance was used input/out variables of input/output node.

• Korean Journal of Child Studies
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• v.30 no.3
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• pp.145-160
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• 2009

The study explored differences in variables related to academic achievement by profiles of learning strategies. The Motivated Strategies for Learning Questionnaire (Pintrich & DeGroot, 1990), the Test of Beliefs on Intelligence (Cho et al., 2004), the School Satisfaction Scale (Son, 1993; Taft, 1979) and Scales for Rating the Behavioral Characteristics of Superior Students (Renzulli et al., 2002) were administrated to 221 subjects in grade 6 (107 girls, 114 boys). Data were analyzed by cluster analysis and ANOVA. Results identified six different clusters; significant differences of variables related to academic achievement were found among the six clusters. Frequent use of various cognitive strategies plays an important role in higher academic achievement.

• East Asian Economic Review
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• v.18 no.3
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• pp.253-276
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• 2014

We examine which traditional asset pricing variables together with bank-specific accounting variables explain the cross-sectional variation of future bank stock returns, using a firm-level data of eight Asian countries. Our empirical evidence shows that exchange rate risk, firm size, the book-to-market ratio, and the net income ratio are important in explaining future bank stock returns during normal times. However, during the Global Financial Crisis period, different variables such as local market beta, illiquidity risk, equity ratio, and off-balance sheets ratio were statistically significant. Thus, researchers and policy practitioners should monitor these variables during normal times as well as during times of crisis.

• Korean Journal of Human Ecology
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• v.2 no.1
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• pp.25-37
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• 1999

The purposes of this research were to find out general trends of employed women's stress and to investigate the differences and effects of related variables. The data were obtained through 239 employed women living in Kwangju and Chonnam. The major findings were as follows : 1) Employed women's scores of stressor, stress cognition and distress were under medium but coping scores were relatively high. 2) Significant differences in employed women's stressors were found according to age, income, job satisfaction, and family life cycle. Stress cognition differed according to job adjustment conditions and self-esteem. Also distress related with job conditions and object. Stress coping levels were different according to income, job conditions, self-esteem, and sex-role attitude. 3) In analyzing the causal effects among related variables, employed women's stressors were affected by job satisfaction and age. Also stress cognition were influenced by job satisfation and self-esteem. Job conditions showed significant effects on distress and self-esteem, sex-role attitudes showed on coping. Conclusively job satisfaction, self-esteem and gender equality were most important variables for employed women's stress. (Korean J of Human Ecology 2(1) : 25-37 1999)

• Proceedings of the Korean Society of Toxicology Conference
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• 2003.10b
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• pp.148-148
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• 2003

The cynomolgus monkey(Macaca fascicularis) is used widely in efficacy and safety assessment of new drugs. The ranges of physiological variables are important end points in the toxicological study. Both the basic physiological variables such as body weight, body temperature, blood pressure, urine pH and blood variables such as biochemical and hematological variables were determined in nineteen male and sixteen female monkey prior to treatment.(omitted)

• Journal of the Korean Society of Safety
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• v.38 no.1
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• pp.1-8
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• 2023

It is extremely important to design safety-guaranteed industrial processes because such process determine the ultimate outcomes of industrial activities, including worker safety. Application of artificial intelligence (AI) in industrial safety involves modeling industrial safety systems by using vast amounts of safety-related data, accident prediction, and accident prevention based on predictions. As a preliminary step toward realizing AI-based industrial safety in Korea, this study discusses neural network-based modeling of industrial safety systems. The input variables that are the most discriminatory relative to the output variables of industrial safety processes are selected using two information-theoretic measures, namely entropy and cross entropy. Normalized frequency and severity of industrial accidents are selected as the output variables. Our simulation results confirm the effectiveness of the proposed neural network model and, therefore, the feasibility of extending the model to include more input and output variables.

• Nonlinear Functional Analysis and Applications
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• v.28 no.3
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• pp.613-622
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• 2023

In this paper, finite element method is applied to solve boundary control problem governed by elliptic variational inequality with an infinite number of variables. First, we introduce some important features of the finite element method, boundary control problem governed by elliptic variational inequalities with an infinite number of variables in the case of the control and observation are on the boundary is introduced. We prove the existence of the solution by using the augmented Lagrangian multipliers method. A triangular type finite element method is used.

• Journal of Korea Artificial Intelligence Association
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• v.1 no.2
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• pp.21-25
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• 2023

The purpose of this study was to compare the performance using multiple regression models to predict the energy consumption of steel industry. Specific independent variables were selected in consideration of correlation among various attributes such as CO2 concentration, NSM, Week Status, Day of week, and Load Type, and preprocessing was performed to solve the multicollinearity problem. In data preprocessing, we evaluated linear and nonlinear relationships between each attribute through correlation analysis. In particular, we decided to select variables with high correlation and include appropriate variables in the final model to prevent multicollinearity problems. Among the many regression models learned, Boosted Decision Tree Regression showed the best predictive performance. Ensemble learning in this model was able to effectively learn complex patterns while preventing overfitting by combining multiple decision trees. Consequently, these predictive models are expected to provide important information for improving energy efficiency and management decision-making at steel industry. In the future, we plan to improve the performance of the model by collecting more data and extending variables, and the application of the model considering interactions with external factors will also be considered.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.176-179
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• 2003

The mean temperature prediction of strip is very important in hot strip finishing mill because of affecting on product quality and shape. Also, temperature can be used by basic information in other on-line control models with affecting control accuracy in factory. So, FE based on-line temperature model was developed for predicting strip mean temperature accurately in various process conditions and factory environments. There are many variables in affecting strip mean temperature in on-line states of factory. But some problems are occurred in considering all variables for making temperature model because of the bad efficiency of regression or fitting analysis. In this report, we have adopted dimensional analysis for solving these problems. We have many variables with dimensions affecting strip temperature but we are able to make non-dimensional variables less than dimensional variables from the combination of dimensional variables caused by PI-Theorem in fluid mechanics. The developed models are divided by two parts. The one is interstand temperature prediction model. The other is roll gap temperature model.

• Korean Journal of Adult Nursing
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• v.28 no.2
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• pp.156-168
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• 2016

Purpose: The purpose of this study was to provide basic data by surveying the literature for the past fifteen years (2001-2015). The focus of the search was death anxiety among the elderly. Methods: Sixty-two published works including graduate theses were selected for the Meta-analysis. Results: Study results showed that variables related to familial factors were the most often cited in the review of the manuscripts as relevant to death anxiety among the elderly. Specifically family support was most important. The other variables reported in the literature review were classified into four other groupings: social, physical, psychological, and demographics. The significant variable in the social grouping was religious activities, health promotion in the physical grouping and ego integrity in the psychological group. Conclusion: This study could provide effect sizes of variables based on materials, which are needed to make an intervention program that is related to death anxiety of the elderly. Since this study identified major variables as significant to death anxiety, several distinctions within these variables can be further studied as these relate to death anxiety.