• International Journal of Highway Engineering
• /
• v.17 no.6
• /
• pp.75-83
• /
• 2015

PURPOSES : This study deals with the traffic accidents classified by the traffic analysis zone. The purpose is to develop the accident density models by using zonal traffic and socioeconomic data. METHODS : The traffic accident density models are developed through multiple linear regression analysis. In this study, three multiple linear models were developed. The dependent variable was traffic accident density, which is a measure of the relative distribution of traffic accidents. The independent variables were various traffic and socioeconomic variables. CONCLUSIONS : Three traffic accident density models were developed, and all models were statistically significant. Road length, trip production volume, intersections, van ratio, and number of vehicles per person in the transportation-based model were analyzed to be positive to the accident. Residential and commercial area ratio and transportation vulnerability ratio obtained using the socioeconomic-based model were found to affect the accident. The major arterial road ratio, trip production volume, intersection, van ratio, commercial ratio, and number of companies in the integrated model were also found to be related to the accident.

• Journal of Korean Society for Atmospheric Environment
• /
• v.14 no.1
• /
• pp.11-23
• /
• 1998

The purpose of this study was to survey chemical distribution of inorganic elements and ions in the submicron particles, to characterize qualitatively emitting sources by factor analysis, and finally to reveal existing patterns in terms of chemical compounds by a stepwise multiple regression analysis. Total of 141 samples were collected by a cascade impactor from 1989 to1996. Fifteen chemical species (Al, Ba, Cd, K, Pb, Cu, Fe, Ni, $Cl^-, NO_3^-, SO_4^{2-}, K^+, Mg^{2+}, Ca^{2+}, and Na^+$) were characterized by AAS and IC. The study showed that average seasonal levels of submicron particulate matters $(d_p<0.43 \mum)$ were 18.7 $\mug/m^3$ in spring, 15.5 $\mug/m^3$ in summer, 15.7 $\mug/m^3$ in fall, and 24.5 $\mug/m^3$ in winter, respectively. All of the anion concentrations in the particle were highest in the winter season. By applying a factor analysis, 5 source patterns were qualitatively obtained, such as sulfate related source, nitrate related source, oil burning source, calcium related source, and coal combustion source. Finally, when applying a stepwise multiple regression analysis, the results clearly showed that $Na^+ and Ca^{2+}, K^+ and Ca^{2+}, NO_3^-$ and relative humidity, $Cl^-$ and ambient temperature, $Ca^{2+} and Cl^-, Mg^{2+} and SO_4^{2-}, Na^+ and NO_3^-, and Ca^{2+} and NO_3^-$, respectively, are negatively contributed to each other. As a result of those statistical analysis, we could suggest that some chemical compounds in the submicron particles such as$NaNO_3, MgSO_4, Ca(NO_3)_2, and CaCl_2$ may not exist on the filter as final composing products; however, other compounds may possibly exist in the form of $Mg(NO_3)_2, CaSO_4, Na_2SO_4, K_2SO_4, MgCl_2, NaCl, and KCl$. Thus, it must be necessary to identify differences between the results of above statistical analysis and of the real world by laboratory experiments.

• Proceedings of the Korean Society of Agricultural Engineers Conference
• /
• 1999.10c
• /
• pp.387-392
• /
• 1999

In this paper, we attempted to eatablish questionnaire items for evaluation of residential satisfaction level by factor analysis, and the model was developed as a function of primary component of questionnaire items. For development of residential satisfaction model, items are selected by factor analysis adn regression coefficient is estimated by the multiple linear regression analysis.

• The Journal of Korean Association of Computer Education
• /
• v.18 no.5
• /
• pp.15-24
• /
• 2015

The purpose of this study is to analyze variables affecting parents' and elementary school students' value of computer science after creative computer science education, through multiple regression. Many researches on Informatics subject have focused on the effect of the subject contents on students but hardly dealt with parents' recognition. Thereupon, this study pays attention to the value of computer science recognized by parents and analyzes variables substantially affecting value variables of computer science related to parents' support for learning Informatics subjects. This paper did not verify the difference in recognition of parents and students but calculated more concrete influence by conducing multiple regression on the variables affecting the value recognized by each group. This is one of the reasons why this study is meaningful. According to the result of the analysis, variables affecting the value of parents on computer science the most are interest and satisfaction, and in students' case, self-efficacy is the variable affecting the value of computer science the most.

• Steel and Composite Structures
• /
• v.49 no.4
• /
• pp.419-430
• /
• 2023

This paper is aimed at investigating the effect of multiple longitudinal stiffeners on the patch loading resistance of slender steel plate girders. Firstly, a numerical study is conducted through geometrically and materially nonlinear analysis with imperfections included (GMNIA), the model is validated with experimental results taken from the literature. The structural responses of girders with multiple longitudinal stiffeners are compared to the one of girders with a single longitudinal stiffener. Thereafter, a patch loading resistance model is developed through machine learning (ML) using symbolic regression (SR). An extensive numerical dataset covering a wide range of bridge girder geometries is employed to fit the resistance model using SR. Finally, the performance of the SR prediction model is evaluated by comparison of the resistances predicted using available formulae from the literature.

• Journal of applied mathematics & informatics
• /
• v.13 no.1_2
• /
• pp.501-508
• /
• 2003

Although the estimate of regression function is important, some have focused the variance estimation of error term in regression model. Different variance estimators perform well under different conditions. In many practical situations, it is rather hard to assess which conditions are approximately satisfied so as to identify the best variance estimator for the given data. In this article, we suggest SHM estimator compared to LS estimator, which is common estimator using in parametric multiple regression analysis. Moreover, a combined estimator of variance, VEM, is suggested. In the simulation study it is shown that VEM performs well in practice.

• Journal of the East Asian Society of Dietary Life
• /
• v.17 no.6
• /
• pp.963-971
• /
• 2007

This research aimed to determine the relationship between hotel restaurants' SCM activities and their results. The samples are included exclusive high-end hotels located in the seoul area. To analyze the data, frequency analysis, reliability analysis, factor analysis, and regression analysis were applied. Multiple regression analysis showed that SCM activities (${\beta}$=.342, p<.000), information sharing (${\beta}$=.136, p<.006), and cooperative activities (${\beta}$=.120, p<.015) had a significant impact on financial performance. The explanatory power of this model was 14%, and there was statistical significance in the regression model. SCM activities(${\beta}$=.221, p<.000), information sharing (${\beta}$=.475, p<.000), and cooperative activities (${\beta}$=.172, p<.000) also had a significant impact on non-financial performance, and the explanatory power of this model was 29%, with statistical significance in the regression model.

• The Journal of the Korea Contents Association
• /
• v.14 no.2
• /
• pp.319-329
• /
• 2014

Purpose: The purpose of this study was to investigate the effect of adolescent's family function, impulsive behavior, stress on the bullying types. Method: Data were collected from 627 adolescents and analyzed using descriptive statistics, t-test, Pearson correlation coefficients and stepwise multiple regression with the SPSS 18.0. Results: The bullying types (injurer and victim) correlates with family function, impulsive behavior and stress. Stepwise multiple regression analysis showed emotional reactivity, non-planning impulsiveness, friends related stress, experience of drinking (yes), experience of parent depression problem (yes), explained 34.1% of the total variance in bully injurer. Stepwise multiple regression analysis showed communication, motor impulsiveness, friends related stress, gender (male), grade (junior high school), explained 30.9% of the total variance in bully victim. Conclusion: The results of this study are expected to be used as basic data in providing a better understanding of adolescents' bullying, in preventing bullying and in developing an intervention program.

• Journal of Digital Convergence
• /
• v.16 no.3
• /
• pp.497-504
• /
• 2018

The purpose of this study was to investigate the relationship between college students' work hope, career attitude maturity and career decision-making self-efficacy. For this, correlation analysis, variance analysis and multiple regression analysis were conducted using 299 data collected from 8 universities in the metropolitan area, Yeongnam, Honam, Gangwon and Chungcheong provinces. As a result of correlation analysis between work hope and career variables, there was a positive correlation between r=.64 and .73 in each sub-factor. After performing a variance analysis to explore the differences in work hope between gender, grades and major fields, there were no gender and grade differences found, but there were significant differences between major fields. Also, as a result of multiple regression analysis, it was found that work hope affecting career attitude maturity was pathways, and in career decision-making self-efficacy, agency, pathways thinking, and goal were influenced. On the analysis result, the limitations and implications of this study were discussed using college students' work hope scale.

• Journal of Distribution Science
• /
• v.13 no.8
• /
• pp.91-96
• /
• 2015

Purpose - This study reviews the delivery of child welfare service quality and examines how the dimensions of the variables of customer satisfaction impact the results from a service distribution perspective. This study differs from existing research since it proposes that a recognized level of child welfare service quality is necessary to achieve customer satisfaction from the perspective of service distribution. Research design, data, and methodology - This study explores child welfare service quality factors that affect customer satisfaction. The study examines and analyzes demographic variables, service quality dimensions, and the causal relationships between child welfare service quality and customer satisfaction. Data from 300 child welfare cases were collected from organizations in Korea in the areas of Busan and Gyeongsangnamdo. The methods of analysis are as follow. First, using descriptive analysis frequency, the percentages were evaluated to assess the demographic variables. Second, Cronbach's α was used to test reliability and to evaluate the internal consistency of the measuring of items. Third, multiple regression analysis was conducted to find out how much the independent variable can affect customer satisfaction. Results - Five factors of child welfare service quality were identified in three categories: process quality (assurance, empathy), results quality (reliability, caring), and physical environment quality (tangibles). There were significant differences among the effects of the child welfare service quality factors on customer satisfaction. A multiple regression analysis was done with process quality (assurance, empathy), results quality (reliability, caring) and physical environment quality (tangibles) to test the hypothesis: assurance (t=2.434, p<0.05), empathy (t=3.677, p<0.001), reliability (t=3.271, p<0.05), caring (t=4.380, p<0.000), and tangibles (t=3.654, p<0.01) had a positive influence on child welfare service quality from a service distribution perspective. Therefore, hypotheses 1, 2, 3, 4, and 5 were supported. In addition, multiple regression analysis on the effects of the variables showed that caring (β=0.273), empathy (β=0.246), tangibles (β=0.265), reliability (β=0.152), and assurance (β=0.131) all had a positive and strong influence on child welfare service quality from a service distribution perspective. Therefore, all child welfare service quality categories (process, results and physical environment quality) were positively statistically significant. Conclusion - In this study, the main findings can be summarized as follows. First, the quality of service of child welfare consists of three dimensions of quality: process quality, results quality, and physical environment quality. The results of the multiple regression analysis also showed that caring and reliability were confirmed as more meaningful variables by the increasing loading factors. Second, the family members involved in child welfare proposed caring as the most important variable among the dimensions of service quality. Third, the results of the hypothesis testing using regression showed that all child welfare service quality factors had a positive impact on customer satisfaction. The results of the study could provide useful information to help increase the effectiveness of delivery strategies for child welfare service quality from a service distribution perspective.