• Geomechanics and Engineering
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• v.23 no.2
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• pp.115-125
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• 2020

This study aims to explore practical and useful equations for rapid evaluation of uniaxial compressive strength of concrete (UCS-C) during the preliminary design stage of aggregate selection. For this purpose, aggregates which were produced from eight different intact rocks were used in the production of concretes. Laboratory experiments involved the tests for uniaxial compressive strength (UCS-R), point load index (PLI-R), P wave velocity (UPV-R), apparent porosity (n-R), unit weight (UW-R) and aggregate impact value (AIV-R) of the rock samples. UCS-C, point load index (PLI-C) and P wave velocity (UPV-C) of concrete samples were also determined. Relationships between UCS-R-rock parameters and UCS-C-concrete parameters were developed by regression analyses. In the simple regression analyses, PLI-C, UPV-C, UCS-R, PLI-R, and UPV-R were found to be statistically significant independent variables to estimate the UCS-C. However, higher coefficients of determination (R²=0.97-1.0) were obtained by multiple regression analyses. The results of simple regression analysis were also compared to the limited number of previous studies. The strength conversion factor (k) values were found to be 14.3 and 14.7 for concrete and rock samples, respectively. It is concluded that the UCS-C can roughly be estimated from derived equations only for the specified rock types.

• Korean Journal of Human Ecology
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• v.20 no.6
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• pp.1135-1151
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• 2011

This study examined green consumption behavior according to the lifestyles of college students. The data were collected from 314 college students in Yeungnam region by a self-administered questionnaire. Frequencies, Cronbach's alpha, factor analysis, cluster analysis, chi-square tests, one-way analysis of variance, Duncan's multiple range tests, Pearson's correlation analysis, and multiple regression analyses were conducted by SPSS Windows V.18.0. According to the result of factor analysis, lifestyles were categorized into six factors: thrift-saving type, enthusiastic activity type, brand ostentation type, freedom-seeking type, material oriented type, and practice-seeking type. Cluster analysis showed respondents belonged to one of four groups: thrift practice group, indifference group, freedom-seeking group, and material ostentation group. The levels of green purchase behavior, green usage behavior and green disposal behavior of the respondents was not high. The thrift practice group showed higher levels of green purchase behavior, green usage behavior, and green disposal behavior. Finally, according to multiple regression analyses, environmental consciousness, knowledge about green consumption, lifestyle groups were the significant factors affecting green consumption behaviors. These results imply that green consumption education for college students should be activated to induce green life.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.60 no.1
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• pp.57-70
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• 2024

In order to present a predictive drift model, Jeju National University's training ship was tested for about 11 hours and 40 minutes, and 81 samples that selected one of the entire samples at ten-minute intervals were subjected to regression analysis after verifying outliers and influence points. In the outlier and influence point analysis, although there is a part where the wind direction exceeds 1 in the DFBETAS (difference in Betas) value, the CV (cumulative variable) value is 6%, close to 1. Therefore, it was judged that there would be no problem in conducting multiple regression analyses on samples. The standard regression coefficient showed how much current and wind affect the dependent variable. It showed that current speed and direction were the most important variables for drift speed and direction, with values of 47.1% and 58.1%, respectively. The analysis showed that the statistical values indicated the fit of the model at the significance level of 0.05 for multiple regression analysis. The multiple correlation coefficients indicating the degree of influence on the dependent variable were 83.2% and 89.0%, respectively. The determination of coefficients were 69.3% and 79.3%, and the adjusted determination of coefficients were 67.6% and 78.3%, respectively. In this study, a more quantitative prediction model will be presented because it is performed after identifying outliers and influence points of sample data before multiple regression analysis. Therefore, many studies will be active in the future by combining them.

• Journal of the Korean Home Economics Association
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• v.28 no.1
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• pp.57-66
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• 1990

The purpose of this study was to investigate the analytical model of the implicit price according to objective and subjective characteristics of housing. The hedonic price regression was used for estimating the implicit price. The subjectives of this study were 1,143 dwellers who live in Seoul metropolitan area. Taejeon, and Jeonju. Satistical analyses were conducted using frequencies, percentiles, mean, and multiple regression. The major findings were as follows: 1. There was a significant difference in the implict price of the apartment between owners and renters. 2. There was a sginificant difference in the implicit price of the apartment among Seoul metropolitan area, Taejeon, and Jeonju. 3. Using a stepwise multiple regression method, the order of variables as they were entered in the model were different between tenure types (owner/renter), and regions(Seoul metroplitan area/Taejeon/Jeonju). 4. The linear model was the most appropriate noe which explained the housing price. 5. Subjective characteristics of housing in Taejeon and Jeonju had an effect on the housing price more than those in Seoul metropolitan area.

• 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.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.3
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• pp.700-714
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• 2014

This study aims to identify the relations between seakeeping characteristics and hull form parameters for YTU Gulet series with cruiser stern. Seakeeping analyses are carried out by means of a computer software which is based on the strip theory and statistical short term response prediction method. Multiple regression analysis is used for numerical assessment through a computer software. RMS heave-pitch motions and absolute vertical accelerations on passenger saloon for Sea State 3 at head waves are investigated for this purpose. It is well known that while ship weight and the ratios of main dimensions are the primary factors on ship motions, other hull form parameters ($C_P$, $C_{WP}$, $C_{VP}$, etc.) are the secondary factors. In this study, to have an idea of geometric properties on ship motions of gulets three different regression models are developed. The obtained outcomes provide practical predictions of seakeeping behavior of gulets with a high level of accuracy that would be useful during the concept design stage.

• Culinary science and hospitality research
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• v.22 no.6
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• pp.151-159
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• 2016

With the targeted coffee consumers in Kwangju city, South Korea, this paper investigates a few determinants such as taste, aroma, mouth-feel, and satisfaction to influence coffee price, based upon self-evaluations by those who enjoy specialty coffee. Using both simple regression and standard multiple regression analyses, it turned out that tastes, smell, mouth-feel, and satisfaction of specialty coffee had effects on coffee price. This study implies that when coffee consumers decide coffee price, they consider multiple factors to influence their overall satisfaction in multiple aspects than a single facet like taste, aroma, and mouth-feel. Practical and theoretical discussion and implications are suggested for the following studies.

• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.1
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• pp.36-45
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• 2012

This study locates factors that affect the intention to use fashion SNS (social network service) and intention for word-of-mouth on fashion SNS. Independent variables were fashion shopping orientation, attitude toward innovative products, fashion leadership, and demographics. A questionnaire method was used to collect data on college students while factor analyses, multiple regression, $x^2$ analyses, and Pearson correlation coefficients were applied in analyzing data. Factor analyses resulted in four factors for fashion shopping orientation, three on attitude toward innovative products and two on fashion leadership. Multiple regression analyses showed that information compatibility of attitude toward innovative products had a significant impact on two models of intention to use fashion SNS and two models of intention for word-of-mouth on fashion SNS. Opinion leadership and gender were significant factors for two models of intention to use fashion SNS, which means that women are likely to have more intention to use fashion SNS. Meanwhile, fashion innovativeness was found to be a significant factor on two models of intention for word-of-mouth on fashion SNS. Shopping orientation factors were not important for any model. $x^2$ analyses showed that women rather than men wanted more information on online fashion shows, general fashion information, and user participation programs. Fashion major students wanted more information on online fashion shows and user participation programs than non-fashion major students.

• Annals of Occupational and Environmental Medicine
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• v.34
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• pp.34.1-34.13
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• 2022

Background: This study aimed to investigate the association between lead exposure and serum gamma-glutamyl transpeptidase (γGT) levels as an oxidative stress marker in male steelworkers. Methods: Data were collected during the annual health examination of workers in 2020. A total of 1,654 steelworkers were selected, and the variables for adjustment included the workers' general characteristics, lifestyle, and occupational characteristics. The association between the blood lead level (BLL) and serum γGT level was investigated by multiple linear and logistic regression analyses. The BLL and serum γGT values that were transformed into natural logarithms were used in multiple linear regression analysis, and the tertile of BLL was used in logistic regression analysis. Results: The geometric mean of the participants' BLLs and serum γGT level was 1.36 ㎍/dL and 27.72 IU/L, respectively. Their BLLs differed depending on age, body mass index (BMI), smoking status, drinking status, shift work, and working period, while their serum γGT levels differed depending on age, BMI, smoking status, drinking status, physical activity, and working period. In multiple linear regression analysis, the difference in models 1, 2, and 3 was significant, obtaining 0.326, 0.176, and 0.172 (all: p < 0.001), respectively. In the multiple linear regression analysis stratified according to drinking status, BMI, and age, BLLs were positively associated with serum γGT levels. Regarding the logistic regression analysis, the odds ratio of the third BLL tertile in models 1, 2, and 3 (for having an elevated serum γGT level within the first tertile reference) was 2.74, 1.83, and 1.81, respectively. Conclusions: BLL was positively associated with serum γGT levels in male steelworkers even at low lead concentrations (< 5 ㎍/dL).

• Water for future
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• v.6 no.2
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• pp.6-11
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• 1973

This paper include the hydrometeorological analyses of evapotranspiration which is import factor concerning the estimate of water budgest over a certain basin. Evapotranspiration model mode by the multiple regression analysis between the evapotranspiration measured on various kinds of ground cover (water, bare soil and lawn) and the other meteorological elements affecting the evapotranspiration process, and the simple regression analysis between the evapo transpiration measured on each ground cover and the evapotranspiration on water and vegetables calculated from the Penman equation. It is expected that the evapotranspiration models are a very useful formulae estimating ten days amounts or a month's amounts.