• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.129-141
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• 2019

In recent years, fast growing cities in Korea are showing signs of being vulnerable to more disasters as their population and facilities increase and intensify. In particular, fire is one of the most common disasters in Korea's cities, along with traffic accidents. Therefore, in this study, we analyze what type of factors affect the fire that threatens urban people. Fire data were acquired for 10 years, from 2007 to 2017, in Jinju, Korea. Spatial distribution pattern of fire occurrence in Jinju was assessed through the spatial autocorrelation analysis. First, spatial autocorrelation analysis was carried out to grasp the spatial distribution pattern of fire occurrence in Jinju city. In addition, correlation and multiple regression analysis were used to confirm spatial dependency and abnormality among factors. Based on this, OLS (Ordinary Least Square) regression analysis was performed using space weighting considering fire location and spatial location of each facility. As a result, First, LISA (Local Indicator of Spatial Association) analysis of the occurrence of fire in Jinju shows that the most central commercial area are fire department, industrial area, and residential area. Second, the OLS regression model was analyzed by applying spatial weighting, focusing on the most derived factors of multiple regression analysis, by integrating population and social variables and physical variables. As a result, the second kind of neighborhood living facility showed the highest correlation with the fire occurrence, followed by the following in the order of single house, sales facility, first type of neighborhood living facility, and number of households. The results of this study are expected to be useful for analyzing the fire occurrence factors of each facility in urban areas and establishing fire safety measures.

• Journal of Families and Better Life
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• v.21 no.2
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• pp.87-101
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• 2003

The purposes of this study were to analyze causes of wife abuse through married couples as the research subject. The study employed ecological perspective to the study of wife abuse as an multiple dimensional and integrated paradigm combined with isolated theories of other research. The subjects were 369 married couples who live in Gwangju area. Data were analyzed with Cronbach'α, factor analysis, basic statistics, paired-t test, 1-test, ANOVA, Duncan's test, correlation analysis, stepwise multiple regression analysis. and hierarchical regression analysis using the SPSS 10.0 for windows. The major findings were as follows; 1. The psychological abuse score, physical abuse score, and sexual abuse score were lower than median without exception. Hut prevalence rates of wife abuse were considerably serious; 91.9% psychological abuse, 44.4% physical abuse, and 53.7% sexual abuse. 2. The results of the hierarchical regression analysis indicated that the marital conflict had the strongest impact on wife abuse. And the attitude toward wife abuse of husband, hostility of husband, exposure experience of domestic violence during a growth period of husband, perception toward social violence of husband, exposure experience of domestic violence during a growth period of wife, drinking problem of husband, and interpersonal relationships stress of husband had influenced on wife abuse. These variables accounted for 49.5% of variance of wife abuse behaviors. As the result of the study, it concludes that the ecological systemic approach on the cause of wife abuse is useful as a theoretical instrument. Suggestions and implications are made for further research and practical application.

• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.73-87
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• 2016

The purpose of this study is to investigate the empirical results of Analytic Hierarchy Process/Data Envelopment Analysis-Assurance Region(AHP/DEA-AR) by using multiple regression analysis during the period of 2009-2012 with 5 inputs (number of gantry cranes, number of berth, berth length, terminal yard, and mean depth) and 2 outputs (container TEU, and number of direct calling shipping companies). Assurance Region(AR) is the most important tool to measure the efficiency of seaports, because individual seaports are characterized in terms of inputs and outputs. Traditional AHP and multiple regression analysis techniques have been used for measuring the AR. However, few previous studies exist in the field of seaport efficiency measurement. The main empirical results of this study are as follows. First, the efficiency ranking comparison between the two models (AHP/DEA-AR and multiple regression) using the Wilcoxon signed-rank test and Mann-Whitney signed-rank sum test were matched with the average level of 84.5 % and 96.3% respectively. When data for four years are used, the ratios of the significant probability are decreased to 61.4% and 92.5%. The policy implication of this study is that the policy planners of Korean port should introduce AHP/DEA-AR and multiple regression analysis when they measure the seaport efficiency and consider the port investment for enhancing the efficiency of inputs and outputs. The next study will deal with the subjects introducing the Fuzzy method, non-radial DEA, and the mixed analysis between AHP/DEA-AR and multiple regression analysis.

• Journal of Korean Society for Quality Management
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• v.12 no.2
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• pp.25-32
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• 1984

The purpose of this paper is to compare several forecasting methods for the case of the cement product by the analysis of the forecasting data and by the study of major forecasting methods, which are the Trend Projection, Exponential Smoothing, and Multiple Regression Analysis. As a result, it is thought that the Multiple Regression Analysis is the optimal model for the case of the cement product. In addition, it is important to consider the future circumstances for forecasting, and to improve the level of the forecasting results through the precise analysis of the collected data.

• Journal of the Korean Home Economics Association
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• v.36 no.10
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• pp.131-144
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• 1998

The purpose of this study was to examine the differences of symbolic consumption of adolescents, and the effects of demographic factors on the symbokic consumption in clothing. Data were administered to 957 adolescents in middle, high school, and college students living in Seoul, Chonju, Sunchon, Yousu, and Kwangyang from May to June 1997. For analysis of the data, factor analysis, t-test, one-way ANOCA, duncan's multiple range test, and multiple regression analysis were employed. The results of this study were summarized as follows. 1) Symbolic consumption in colthing were shown to have the significant differences accoding to age, gender, the level of urbanization, parent's education, father's occupation, social stratification groups. The higher the age, the level of urbanization, and parent's education, father's occupation, social stratification is, or the female, the higher is symbolic consumption in clothing. 2) According to the results of the regression analysis examining the rerlative influences of variables affecting symbolic consumption in clothing, the relative importance of the variables are in order of; income, gender, age, mother's education, residence, and their explanatory powere totalled 11.5%.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.8 s.101
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• pp.939-944
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• 2005

In this paper, a sound quality index for the evaluation of the vehicle intake noise was developed through a correlation analysis of the objective measurement and the subjective evaluation. First, intake orifice noise was measured at the wide-open throttle sweep condition. And then, the acoustic transfer function between intake orifice noise and interior noise was measured. Simultaneously, subjective evaluation was carried out with a 10-scale score by 8 special engineers. The correlation analysis between the psychoacoustic parameters derived from the measurement and the subjective evaluation was performed. The most critical factor was determined and the corresponding sound quality index for intake noise was obtained from the multiple factor regression analysis method. Finally, the effectiveness of the proposed index was validated.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.45-50
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• 2012

This paper on analysis of roundness error after boring turning of Al-6061 materials with CNC lathe. Experiment applying turning parameters is based on experimental design method. A design and analysis of experiments is conducted to study the effects of these parameters on the roundness error using the S/N ratio and analysis of ANOVA. Multiple linear regression analysis is applied to compare experimental with predicted data in consideration of roundness error. To fixation pressure and the opening which are a turning parameter, the cutting depth and feed speed respected the objective attainment of dissertation and to be applied the result they investigated.

• Journal of the Korean Home Economics Association
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• v.40 no.2
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• pp.175-186
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• 2002

The purpose of this study was to examine the influences of goal-oriented value to the financial management and financial satisfaction of female college students. The samples were selected from 541 female collegians. Data analysed were carried out using SAS package. Statistics used for data analysis was Cronbach'$\alpha$ coefficient, multiple regression, Pearson correlation analysis, and path analysis. The results were summarized as follows : First, resulting from the multiple regression analysis, the goal-oriented value had positive effects to the financial management - planning, implementing, evaluating, and saving - of female collegians. And the goal-oriented value had not indirectly but directly positive effects to the financial satisfaction. Second, the variables that have significant influence on the financial satisfaction were the level of household income, goal-oriented value, implementing, and monthly personal allowance.

• Journal of Nutrition and Health
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• v.26 no.3
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• pp.357-366
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• 1993

The purposes of this study were to investigate the operational affecting productivity in hospital foodservice, and to examine the relationships between operational factors affecting productivity. The 28 hospitals over 400 beds in Seoul were mailed questionnaires assessing the factors that affect productivity in hospital foodservice(23 hospitals responded). Data analyses included descriptive statistics. Pearson product moment correlation analysis, and stepwise multiple regression analysis. The result of Pearson product moment correlation analysis indicated that the percentage of patient meals was significantly correlated to the productivity (r=.5560, p<.01). Stepwise multiple regression analysis indicated that the percentage of patient meals and the average work hours of employees were significant predictors of the operational factors at productivity.

• Journal of Korean Society for Quality Management
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• v.43 no.2
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• pp.151-168
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• 2015

Purpose: The purpose of this study was to investigate the effect of the innovation performance through business innovation activities by small and medium size company as well as to test the moderating effects on the innovation techniques'understanding and conformance. Methods: The data for the empirical analysis was collected from 132 companies mainly located in Jeolla and Gyeonggi Province. Cronbach's alpha factor analysis, multiple regression analysis and hierarchical multiple regression were used for statistical methods. Results: The Statistical analysis results show that innovation performance through business innovation techniques and activities was effected by CEO leadership, company capability and training for employees. Conclusion: Through this study we tried to give some suggestions for improving innovation performance through business innovation activities for the small and medium size company.