• Title/Summary/Keyword: the multiple regression analysis

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A Study on the Seatbelt Use and Influence Factors among Firefighters (소방공무원 안전벨트 착용률과 영향요인에 관한 연구)

  • Baek, In-hwan
    • Journal of the Korea Safety Management & Science
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    • v.23 no.1
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    • pp.49-56
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    • 2021
  • The purpose of this study is to investigate the current status of firefighting seatbelt use and factors affecting the wearing seatbelt of firefighters. The seatbelt use of citizens was also studied for comparative study. Two T-tests were conducted to confirm the characteristics of firefighters' safety belts wearing firefighters. As a result, there was a statistically significant difference, on seatbelt use in general vehicles, between firefighters and citizens. And a significant difference between fire vehicles and general vehicles, on firefighters' seatbelt use, and the average was lower in fire vehicles. Factor analysis, reliability analysis, correlation analysis and multiple regression analysis were conducted to 10 influential factors affecting seatbelt use of firefighters'. And factor analysis and reliability analysis revealed two major factors (Physical factors, Learning factors). In multiple regression analysis, it was confirmed the two independent factors had a positive effect on the dependent variable, the rate of seatbelt use of firefighters'.

A Cost Estimation Model for Highway Projects in Korea

  • Kim, Soo-Yong;Kim, Young-Mok;Luu, Truong-Van
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2008.11a
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    • pp.922-925
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    • 2008
  • Many highway projects are under way in Korea. However, owners frequently find that the project cost exceeds the budget and they are unable to identify the underlining reasons. The main purpose of this research is to develop cost models for transportation projects in Korea using the multiple linear regression (MLR). The data consist of 27 completed transportation projects, built from 1991 to 2001, The technique of multiple regression analysis is used to develop the parametric cost estimating model for total budget cost per highway square meter (TBC/$m^2$). Findings of the study indicated that MLR car be applied to highway projects in Korea. There are twf) major contributions of this research. (1) the identification of transportation parameters as a significant cost driver for transportation costs and (2) the successful development of the parametric cost estimating models for transportation projects in Korea.

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Particle size distributions and concentrations above radiators in indoor environments: Exploratory results from Xi'an, China

  • Chen, Xi;Li, Angui
    • Environmental Engineering Research
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    • v.20 no.3
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    • pp.237-245
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    • 2015
  • Particulate matter in indoor environments has caused public concerns in recent years. The objective of this research is to explore the influence of radiators on particle size distributions and concentrations. The particle size distributions as well as concentrations above radiators and in the adjacent indoor air are monitored in forty-two indoor environments in Xi'an, China. The temperatures, relative humidity and air velocities are also measured. The particle size distributions above radiators at ten locations are analyzed. The results show that the functional difference of indoor environments has little impact on the particle size distributions above radiators. Then the effects of the environmental parameters (particle concentrations in the adjacent indoor air, temperatures, relative humidities and air velocities) on particle concentrations above radiators are assessed by applying multiple linear regression analysis. Three multiple linear regression models are established to predict the concentrations of $PM_{10}$, $PM_{2.5}$ and $PM_1$ above radiators.

Optimal Process Parameters for Achieving the Desired Top-Bead Width in GMA welding Process (GMA 용접의 윗면 비드폭 선정을 위한 최적 공정변수들)

  • ;Prasad
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.11 no.4
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    • pp.89-96
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    • 2002
  • This paper aims to develop an intelligent model for predicting top-bead width for the robotic GMA(Gas Metal Arc) welding process using BP(Back-propagation) neural network and multiple regression analysis. Firstly, based on experimental data, the basic factors affecting top-bead width are identified. Then BP neural network model and multiple regression models of top-bead width are established. The modeling methods and procedure are explained. The developed models are then verified by data obtained from the additional experiment and the predictive behaviors of the two kind of models are compared and analysed. Finally the modeling methods, predictive behaviors md the advantages of each models are discussed.

Potential of near infrared spectroscopy for non-destructive estimation of soluble solids in growing melons

  • Ito, Hidekazu;Morimoto, Susumu;Yamauchi, Ryougo
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1525-1525
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    • 2001
  • Non-destructive determination of soluble solids(Brix) in harvested fruits using near infrared(hereafter, NIR) spectroscopy has been reported by many researchers. We have just reported on non-destructive estimation of Brix in harvested melons using a NIR Systems Model 6500 spectrophotometer(Ito et al., 2000). There is a melon cultivar that is difficult to judge the harvest time from the external appearance. If we can determine Brix in growing fruits non-destructively in the field, immature fruits will not be harvested. A portable m spectrophotometer for field use has been just developed by Kubota Corporation. The spectral data of growing melons were measured by the portable spectrophotometer. A commercial program was used for multiple linear regression analysis. Brix in growing melons could be estimated by a multiple regression equation calibrated with harvested melons. Absorbances of 906 and 874 nm were included as the independent variables in the multiple regression equation, and these wavelengths are key wavelengths for non-destructive Brix determination.

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Evaluation of the Relationship between the Exposure Level to Mixed Hazardous Heavy Metals and Health Effects Using Factor Analysis (요인분석을 이용한 유해 중금속 복합 노출수준과 건강영향과의 관련성 평가)

  • Kim, Eunseop;Moon, Sun-In;Yim, Dong-Hyuk;Choi, Byung-Sun;Park, Jung-Duck;Eom, Sang-Yong;Kim, Yong-Dae;Kim, Heon
    • Journal of Environmental Health Sciences
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    • v.48 no.4
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    • pp.236-243
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    • 2022
  • Background: In the case of multiple exposures to different types of heavy metals, such as the conditions faced by residents living near a smelter, it would be preferable to group hazardous substances with similar characteristics rather than individually related substances and evaluate the effects of each group on the human body. Objectives: The purpose of this study is to evaluate the utility of factor analysis in the assessment of health effects caused by exposure to two or more hazardous substances with similar characteristics, such as in the case of residents living near a smelter. Methods: Heavy metal concentration data for 572 people living in the vicinity of the Janghang smelter area were grouped based on several subfactors according to their characteristics using factor analysis. Using these factor scores as an independent variable, multiple regression analysis was performed on health effect markers. Results: Through factor analysis, three subfactors were extracted. Factor 1 contained copper and zinc in serum and revealed a common characteristic of the enzyme co-factor in the human body. Factor 2 involved urinary cadmium and arsenic, which are harmful metals related to kidney damage. Factor 3 encompassed blood mercury and lead, which are classified as related to cardiovascular disease. As a result of multiple linear regression analysis, it was found that using the factor index derived through factor analysis as an independent variable is more advantageous in assessing the relevance to health effects than when analyzing the two heavy metals by including them in a single regression model. Conclusions: The results of this study suggest that regression analysis linked with factor analysis is a good alternative in that it can simultaneously identify the effects of heavy metals with similar properties while overcoming multicollinearity that may occur in environmental epidemiologic studies on exposure to various types of heavy metals.

Development of the Parent-Satisfaction Scale (<부모의 역할만족도 척도> 의 개발)

  • 현온강
    • Journal of the Korean Home Economics Association
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    • v.32 no.1
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    • pp.103-118
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    • 1994
  • The purpose of this study was to develop the Parent Satisfaction Scale(PSS) to measure the various components of satisfaction related to parenting. The subjects were 1210 parents(249 fathers and 961 mothers) selected nation widely from 7 cities and several rural area in Korea. the statistics used for data analysis were Fisher's Exact Test, Cramer's V, factor analysis multiple regression, Cronbach's α,and Pearson's correlation. To begin with eighty of 100-item scale were selected through the item analysis and from that 48 items were abstracted through the multiple regression analysis conducted to reduce the length of the scale. Results of factor analysis indicated that the PSS comprised of five factors: general satisfaction parent-child relationship spouse support parent's role conflict support of children. Reliabilities for the domains ranged from 79 to 91. To determine the construct validity of this instrument the Marital Satisfaction Scale and the Proverb about child rearing were administered. The two creterion measures showed significant relationships with the PSS. The final 48 items scale from the current analysis were considered to be critical steps in the development of this assessment device.

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The influence analysis of admission variables on academic achievements (학업성취도에 대한 대입전형 요인들의 영향력 분석)

  • Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.4
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    • pp.729-736
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    • 2010
  • In this paper, we study the influence analysis of admission variables including their characteristics on academic achievements of freshmen at K university in Busan. First, multiple regression analysis is used to examine the main effects of admission variables including students' characteristics on the academic achievements. Also, Decision tree analysis is used to examine the interaction effects for the admission variables on the academic achievements. The results of this paper may be helpful to K university in designing effective admissions strategies for recruiting students.

A Study on the Emotional Evaluation of fabric Color Patterns

  • Koo, Hyun-Jin;Kang, Bok-Choon;Um, Jin-Sup;Lee, Joon-Whan
    • 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.

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Estimation of Biological Action of Dioxins by Some Geometric Descriptors (기하학적 변수에 의한 다이옥신의 독성 예측)

  • Hwang, Inchul
    • 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.

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