• Environmental Analysis Health and Toxicology
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• v.14 no.3
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• pp.103-111
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• 1999

To effectively predict the lipophilicity, the aryl hydrocarbon receptor (AhR) affinity, and TEF (Toxic equivalency factor) of dioxins by geometrical descriptors, the multiple linear regression methods with the forward selection and backward elimination were employed with statistical validity. The lipophilicity, the Ah receptor binding affinity, and the toxic equivalency factor of dioxins could be predicted using some geometrical descriptors.

• Korean Journal of Psychosomatic Medicine
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• v.3 no.1
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• pp.28-38
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• 1995

The purpose of this study is to investigate the relationship between irrational belief and psychopathology. The Korean version of Symptom Check List-90-R and Irrational Belief Test were administered to 621 high school students in group. The author used Pearson correlation coefficiency and multiple regression analysis to seek the regression patterns of the irrational belief. The results were as follows. 1) Most of the subscales of the SCL-90-R and Irrational Belief Test were correlated significantly. 2) In multiple regression analysis, the irrational belief associated with anxious overconcern was the most predictable variable for psychopathology.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.4
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• pp.23-29
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• 2004

In this study, four kinds of $Si_3N_4$-based ceramic cutting tools with different sintering time were fabricated to investigate the relation among mechanical properties, grain size and tool life. They were used to turn gray cast iron at a cutting speed of 330m/min and depth of cut of 0.5mm and 1mm in dry, continuos cutting conditions. Multiple linear regression model was used to determine the relations among the mechanical property, grain size and the density. It was found that the combination of hardness and fracture toughness showed a good relation with tool life. It was also shown that hardness was the most important single element for the tool life.

• Science of Emotion and Sensibility
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• v.5 no.3
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• pp.11-20
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• 2002

There are Two new models developed for objective evaluation of fabric color patterns by applying a multiple regression analysis and an adaptive foray-rule-based system. The physical features of fabric color patterns are extracted through digital image processing and the emotional features are collected based on the psychological experiments of Soen[3, 4]. The principle physical features are hue, saturation, intensity and the texture of color patterns. The emotional features arc represented thirteen pairs of adverse adjectives. The multiple regression analyses and the adaptive fuzzy system are used as a tool to analyze the relations between physical and emotional features. As a result, both of the proposed models show competent performance for the approximation and the similar linguistic interpretation to the Soen's psychological experiments.

• Journal of Environmental Science International
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• v.10 no.3
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• pp.173-178
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• 2001

The aim of this paper is to evaluate users benefit values of theme park using Travel Cost Method with special reference to Woobang Tower Land in Taegu for the estimation of economic values. This research is mainly based on questionnaire survey of 100 users of the theme park. Socio-economic factors such as income, year of education, annual income, age and money(travel cost) are analysed from 5 residential areas of the respondents. Multiple regression analysis was used for the evaluation of annual number of park visitings based on the analysis. The regression model shows NV = $\alpha$+$\beta_1$TC+$\beta_2$INC+$\beta_3$EDU+$\beta_4$AGE (NV : Annual Number of Visitings, TC : Travel Cost, INC : Annual Income, EDU : Years of Education, AGE : Age). Regarding to visitors demand curve based on the equation showed that annual economic values of Woobang Tower Land was estimated as 50billion Korean Won.

• 중국학논총
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• no.67
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• pp.157-177
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• 2020

The rapid change in the university environment due to the decrease in the school-age population calls for enhancing the competitiveness of China-related departments. In this paper, the university's competitiveness and dropout rate were studied in combination with various factors such as geographical location of Chinese-related departments set up at national universities, convergence with other departments, competition rate for entrance exams, scholarships, and employment rate that have a comprehensive impact on student satisfaction. In particular, the dropout rate presented research results that could help universities strengthen their competitiveness in China-related departments, such as by differentiating customized academic strategies according to the atmosphere of elimination through multiple regression analysis and quantile analysis. We hope this thesis will be the basis for policymaking and judgment in China-related departments.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.149-160
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• 2009

The purpose of this study is to comparatively analyse the behavior patterns of the first and the repeated offenders in DWI, and to develope the models of BAC(Blood Alcohol Concentration) by using multiple regression analysis method and a model of repeated DWI conviction by using logistic regression analysis method. The main results are as follows. First, the repeated offenders are more in criminal and traffic accidents records than that of the first offenders. The unlicenced drivers are in higher BAC than licenced drivers. Second, multiple regression model of BAC was developed, and the model revealed that criminal records and driving distance were important factors. Third, a model of repeated DWI conviction was developed, and the model revealed that traffic accidents records, whether or not having licence, and criminal records were most important factors.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.5
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• pp.312-315
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• 2012

In this study, the model which can predict the quality of effluent has been implemented through multiple regression analysis to use operation data of a sewage treatment plant, to which a media process is applied. Multiple regression analysis were carried out by cases according to variable selection method, removal of outliers and log transformation of variables, with using data of one year of 2011. By reviewing the results of predictable models, the accuracy of prediction for $COD_{Mn}$ of treated water of secondary clarifiers was over 0.87 and for T-N was over 0.81. Using this model, it is expected to set the range of operating conditions that do not exceed the standards of effluent quality. In conclusion, the proper guidance on the effluent quality and energy costs within the operating range is expected to be provided to operators.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.65-76
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• 2017

The purpose of this study was to present a prediction model that reflects crime risk area analysis, including factors and spatial characteristics, as a precursor to preparing an alternative plan for crime prevention and design. This analysis of criminal cases in high-risk areas revealed clusters in which approximately 25% of the cases within the study area occurred, distributed evenly throughout the region. This means that using a multiple linear regression model might overestimate the crime rate in some regions and underestimate in others. It also suggests that the number of deserted houses in an analyzed region has a negative relationship with the dependent variable, based on the multiple linear regression model results, and can also have different influences depending on the region. These results reveal that closure signs in a study area affect the dependent variable differently, depending on the region, rather than a simple or direct relationship with the dependent variable, as indicated by the results of the multiple linear regression model.

• Fire Science and Engineering
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• v.30 no.6
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• pp.31-36
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• 2016

The flash point is one of the most important properties for characterizing the fire and explosion hazard of liquid solutions. In this study, the flash points of two flammable binary mixtures, n-pentanol + n-propanol and n-pentanol + n-heptanol systems were measured using a Seta flash closed cup tester. The flash point was estimated using the methods based on Raoult's law and multiple regression analysis. The measured flash points were also compared with the predicted flash points. The absolute average errors (AAE) of the results calculated by Raout's law were $1.3^{\circ}C$ and $1.3^{\circ}C$ for the n-pentanol + n-propanol and n-pentanol + n-heptanol mixtures, respectively. The absolute average errors of the results calculated by multiple regression analysis were $0.4^{\circ}C$ and $0.3^{\circ}C$ for the n-pentanol + n-propanol and n-pentanol + n-heptanol mixtures, respectively. According to the AAE, the calculated values based on multiple regression analysis were better than those based on Raoult's law.