• Near Infrared Analysis
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• v.1 no.1
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• pp.1-7
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• 2000

A convenient algorithm for optimizing wavelength selection in multiple linear regression (MLR) has been developed. MOP (MLP Optimization Program) has been developed to test all possible MLR calibration models in a given spectral range and finally find an optimal MLR model with external validation capability. MOP generates all calibration models from all possible combinations of wavelength, and simultaneously calculates SEC (Standard Error of Calibration) and SEV (Standard Error of Validation) by predicting samples in a validation data set. Finally, with determined SEC and SEV, it calculates another parameter called SAD (Sum of SEC, SEV, and Absolute Difference between SEC and SEV: sum(SEC+SEV+Abs(SEC-SEV)). SAD is an useful parameter to find an optimal calibration model without over-fitting by simultaneously evaluating SEC, SEV, and difference of error between calibration and validation. The calibration model corresponding to the smallest SAD value is chosen as an optimum because the errors in both calibration and validation are minimal as well as similar in scale. To evaluate the capability of MOP, the determination of benzene content in unleaded gasoline has been examined. MOP successfully found the optimal calibration model and showed the better calibration and independent prediction performance compared to conventional MLR calibration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.4764-4769
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• 2011

This study intends to investigate the organizational commitment and Its related factors among medium hospital of nurses. The collected data were analyzed descriptive statistics, t-test, ANOVA, Scheffe's test, Pearson correlation coefficient and stepwise multiple regression using SPSS 19.0 Program. The score of level of organizational commitment was statistically significant difference according to working period, marital state, monthly income, personality, night-duty. The score of organizational commitment level correlated positively with job satisfaction and burnout. Stepwise multiple regression analysis for organizational commitment level revealed that the most powerful predictor was burnout, job satisfaction and night-duty explained 49.5% of the variance. Therefore, It suggested that goal of increasing nurses' organizational commitment in hospital should be helped them raise job satisfaction and decrease nurses' burnout and night duty.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.3
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• pp.137-143
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• 2003

The degree of contamination on outdoor insulator is ons of the most importance factor to determine the pollution level of outdoor insulation, and the sea salt is known as the most dangerous pollutant. As shown through the preceding study, the generation of salt pollutant and the pollution degree of outdoor insulator have a close relation with meteorological conditions, such as wind velocity, wind direction, precipitation and so fourth. So, in this paper, we made an investigation on the prediction method, a statistical estimation technique for equivalent salt deposit density of outdoor insulator with multiple linear regression analysis. From the results of the analysis, we proved the superiority of the prediction method in which the variables had a very close(about 0.9) correlation coefficient. And the results could be applied to establish the Pollution Prediction System for power utilities, and the system could provide an invaluable information for the design and maintenance of outdoor insulation system.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.143-151
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• 2021

This study was a cross-sectional descriptive research to analyze the effects of sub-factors of cognitive emotional control on happiness levels. The participants of the study were 201 men and women in their 20s, and data were collected online from January 1 to 15 collected data were, 2001 using structured cognitive control and happiness level questionnaires. The collected data were conducted Independent t-test, Pearson correlation analysis, simple regression analysis, multiple regression Analysis, hierarchical regression analysis using SPSS 18.0 statistic program. As a result, the study appeared that the level of happiness by gender does not differ, and cognitive emotional control affected 58.5%. The average of cognitive emotional control was higher for all men, but women were higher than men in criticized others. Also, acceptance was the sub-factor of emotional control that most affected the level of happiness (β=-.587, p<0.01). Based on the results of this study, it is suggested that a systematic program on subject of acceptance, a sub-factor of cognitive emotional control, should be developed to improve the level of happiness.

• Korean Journal of Child Studies
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• v.28 no.5
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• pp.253-267
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• 2007

This study examined the relationships between multiple intelligences as cognitive factors and affective factors of learning motivation and academic self-concept. The data were collected from 276 4th grade elementary school students and analyzed by correlation, multi-variate analysis, and step-wise multiple regression. Results were that (1) multiple intelligences, learning motivation, and academic self-concept had statistically significant correlations among themselves. Multi-variate analysis showed that intra-personal intelligence explained 58.6% of the linear combination of learning motivation and academic self-concept. (2) Intra-personal intelligence explained 29% to 58% of learning motivation and its sub-factors of achievement motivation, internal locus of control, self-efficacy, and self-regulation. (3) Intra-personal intelligence, logical-mathematical intelligence, musical intelligence, and inter-personal intelligence were explanatory variables for academic self-concept and its sub-factors.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.17.1-17
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• 2001

• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.635-645
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• 2000

In tidal rivers, the river level, discharge and tide are interrelated. Therefore, the stage-discharge relation that takes no account of tidal effects is inaccurate. For the calculation of river discharge in low water level, this paper attempts to formulate a multiple regression equation of stage-discharge curve to calculate the river discharge in low water level with variables as river level and differences between sea level and river level. Numerical application were perfonned on Ulsan gaging station in Taehwa river, and the comparison with existing rating curve equation showed good applicability of this multiple regression equation.uation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.3
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• pp.111-116
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• 2021

This study aims to identify the representative factors affecting the air trade between the two countries over the past 20 years, targeting China, Korea's largest trading partner for air transport. In the analysis, the two countries' GDP, GDP per capita, and tariff rates, as well as exchange rates, international oil prices, and FTAs were used as variables. For the analysis method, OLS multiple regression analysis was performed, and each was analyzed by dividing the export amount, import amount, and trade amount. As a result of the analysis, China's GDP and Korea's GDP per capita showed a positive (+) direction, an increase in the exchange rate resulted in an increase in the amount of trade, and an increase in the tariff rate resulted in a decrease in the amount of trade. Whether the FTA was concluded or not acted as a factor in increasing the amount of trade between the two countries.

• Studies on Life and Culture
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• v.52
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• pp.225-248
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• 2019

This study examines the variables affecting the cyberbullying of adolescents. The purpose of this study is to analyze the difference of variables that personal, domestic environmental, school environment, digital media factors, and more specifically, gender differences. In order to achieve the purpose of the study, we used 811 online survey data of youths with smart phones nationwide. The results of technical statistics, T-test, correlation analysis and multiple regression analysis can be summarized as follows. First, the descriptive statistics showed that male cyberbullying scores were higher than female students, and t-test results were statistically significant. Second, multiple regression analysis including gender variables showed that male cyberbullying was higher than female students. Finally, multiple regression analysis of male and female students showed that the variables affecting the cyberbullying of boys and girls were somewhat different. The common causative variables were 'parental stress', 'peer attachment', and 'game addiction'. The direction was statistically significant (+) direction. The causes of 'depression', 'aggression', and 'SNS addiction' were different among males and females were 'academic stresses', suggesting that there are differences in cyberbullying factors according to gender.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.1017-1023
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• 2021

This research aims to determine the effect of customers' threat emotion and price on the decision to purchase a certain smartphone product. This study uses a quantitative method with a type of descriptive and causal research. It employs non-probability sampling with purposive sampling, with 385 respondents to answer the questionnaires. Data analysis techniques used descriptive analysis and multiple linear regression analysis. Based on the results of descriptive analysis of emotion, price and purchasing decisions are in sync with each other. The results of multiple linear regression analysis techniques indicate the threat emotion and brand trust are influential against the positive decision to purchase smartphone products. The magnitude of the influence of emotions and price have simultaneous effect on purchasing decisions and other decision variables, which are not included in this study, also play minor role in determining purchase intention, such as product quality, brand image and others. Partially, threat emotion and brand trust have a positive effect toward purchasing decisions. The magnitude of the highest influence was the one of price, then followed by emotional threats. The findings of this study suggest that psychological and behavioral effects also play important roles in determining customers' purchase decision.