• Journal of the Korean Chemical Society
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• v.58 no.6
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• pp.543-552
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• 2014

A quantitative structure activity relationship (QSAR) study is performed for modeling and prediction of oral bioavailabilities of 216 diverse set of drugs. After calculation and screening of molecular descriptors, linear and nonlinear models were developed by using multiple linear regression (MLR), artificial neural network (ANN), support vector machine (SVM) and random forest (RF) techniques. Comparison between statistical parameters of these models indicates the suitability of SVM over other models. The root mean square errors of SVM model were 5.933 and 4.934 for training and test sets, respectively. Robustness and reliability of the developed SVM model was evaluated by performing of leave many out cross validation test, which produces the statistic of $Q^2_{SVM}=0.603$ and SPRESS = 7.902. Moreover, the chemical applicability domains of model were determined via leverage approach. The results of this study revealed the applicability of QSAR approach by using SVM in prediction of oral bioavailability of drugs.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.393-400
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• 2021

Body weight of livestock is a crucial indicator for assessing feed requirements and nutritional status. This study was performed to estimate the body weight of Korean cattle (Hanwoo) using body volume determined from three-dimensional (3-D) image. A TOF camera with a resolution of 640×480 pixels, a frame rate of 44 fps and a field of view of 47°(H)×37°(V) was used to capture the 3-D images for Hanwoo. A grid image of the body was obtained through preprocessing such as separating the body from background and removing outliers from the obtained 3-D image. The body volume was determined by numerical integration using depth information to individual grid. The coefficient of determination for a linear regression model of body weight and body volume for calibration dataset was 0.8725. On the other hand, the coefficient of determination was 0.9083 in a multiple regression model for estimating body weight, in which the age of Hanwoo was added to the body volume as an explanatory variable. Mean absolute percentage error and root mean square error in the multiple regression model to estimate the body weight for validation dataset were 8.2% and 24.5kg, respectively. The performance of the regression model for weight estimation was improved and the effort required for estimating body weight could be reduced as the body volume of Hanwoo was used. From these results obtained, it was concluded that the body volume determined from 3-D of Hanwoo could be used as an effective variable for estimating body weight.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.957-970
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• 2015

The purpose of this study was to analyze records of Korean pro-basketball using general linear model (two-way ANOVA and hierarchical multiple regression analysis). Korea Basketball League (KBL) informed the records (2014-2015 season) of this study. The eight variables (TA, 2PA, 3PA, 2P, 3P, Ast, TFB, CH) were selected in content validity. SPSS program was used to analyze general linear model. All alpha level was set at 0.05. Major results were as follow. 3PA had significant interaction effect between victory & defeat variable and home & away variable. Victory teams showed that 3PA was higher in home games than away games, and defeat teams was the other. 2PA, AS, TFB, and CH were selected significant variables affecting victory and defeat. In result of hierarchical regression, Ast had significant moderation effect between 3PA and TS. TFB also had significant moderation effect between AS between 2P. The other construct (Ast between 2PA and TS; TFB between AS between 3P) had no significant moderation effect. In the effect of 2PA, 3PA and Ast to TS, CH also had no significant moderation effect.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.637-644
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• 2010

The purpose of this study is to analyze characteristics of water quality factor scientifically and develop the multiple regression model predicting dissolved oxygen to save periodic replacement costs for dissolved oxygen sensor. Correlation analysis using the environmental data obtained from 2 different land-based fish farms of the Geogeum-do, Geheung-gun coastal area during the periods from November 2008 to January 2009 shows that water temperature was negatively correlated with dissolved oxygen and pH butpH was positively correlated with salinity and dissolved oxygen. The information of Keumho fish farm in 2009 is presented by the tables which are monthly statistics of water quality factors and seasonable difference by the Duncan's post-test. Also we developed multiple regression model predicting dissolved oxygen, the usefulness of which was verified by the comparison graph between estimates and actual observations. The developed regression model shows that seawater temperature and salinity give negative affect to dissolved oxygen while pH gives positive affect to it. Lastly the seawater temperature has much higher explanatory power than pH factor.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2D
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• pp.181-189
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• 2008

The purpose of this study is to comparatively analyze the characteristics and models of traffic accidents by day and nighttime. In pursuing the above, this study gives particular attentions to testing the differences and developing the models (multiple linear and non-linear and Poisson and negative binomial regression) using the data of Cheongju 4-legged signalized intersections. The main results analyzed are as follows. First, the differences between day and nighttime accidents were defined. Second, 12 accident models which are all statistically significant were developed. Finally, the differences between day and nighttime models were comparatively analyzed using the common and specific variables.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.87-95
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• 2016

This study examined the characteristics of the hourly demand of city gas in Korea and proposed multiple regression models to obtain precise estimates of the hourly demand of city gas. Forecasting the hourly demand of city gas with accuracy is essential in terms of safety and cost. If underestimated, the pipeline pressure needs to be increased sharply to meet the demand, when safety matters. In the opposite case, unnecessary inventory and operation costs are incurred. Data analysis showed that the hourly demand of city gas has a very high autocorrelation and that the 24-hour demand pattern of a day follows the previous 24-hour demand pattern of the same day. That is, there is a weekly cycle pattern. In addition, some conditions that temperature affects the hourly demand level were found. That is, the absolute value of the correlation coefficient between the hourly demand and temperature is about 0.853 on average, while the absolute value of the correlation coefficient on a specific day improves to 0.861 at worst and 0.965 at best. Based on this analysis, this paper proposes a multiple regression model incorporating the hourly demand ahead of 24 hours and the hourly demand ahead of 168 hours, and another multiple regression model with temperature as an additional independent variable. To show the performance of the proposed models, computational experiments were carried out using real data of the domestic city gas demand from 2009 to 2013. The test results showed that the first regression model exhibits a forecasting accuracy of MAPE (Mean Absolute Percentage Error) around 4.5% over the past five years from 2009 to 2013, while the second regression model exhibits 5.13% of MAPE for the same period.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.387-397
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• 2015

In this paper, the determinants of the number of job changes in the SMEs (small and medium enterprises) youth-intern project is analysed, utilizing SMEs youth-intern DB and employment insurance DB. Since the number of job changes are count data which take integer values other than negative values, general linear regression analysis becomes inappropriate. Therefore, four models such as Poisson regression model, zero inflated Poisson regression model, negative binomial regression model and zero inflated negative binomial regression model are tried to fit count data. A zero inflated negative binomial regression model is selected to be the best model. Major results are the followings. First, the number of job changes is shown to be significantly smaller in the treatment group than in the control group. Second, the number of job changes turns out to be significantly smaller in the young-age group than in the old-age group. Third, it is also shown that the number of job changes of man is significantly greater than that of woman. Lastly, the number of job changes in the bigger firm is shown to be significantly less than that of the smaller firm.

• Journal of Distribution Science
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• v.17 no.10
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• pp.27-39
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• 2019

Purpose - This study explores the relationships between e-Marketing and perceived service quality with brand trust and loyalty towards the brand of mobile telephone operators in Kosovo. Research design, data, and methodology - The conceptual model of four constructs was developed, while each construct consisted of the set of variables measured by using five-point Likert scale. The primary data was collected via an online survey through SurveyMonkey, distributed via Facebook and email. The collected data were cleaned, validated and tested for its consistency through Cronbach's Alpha; ensured that five assumptions of multiple linear regression are met. To assess the relationships between outcome variable and dependent variables of the model, performed the bivariate correlation, simple, multiple linear and hierarchical regression. Results - Perceived service quality has a positive significant effect on brand trust and loyalty. e-Marketing presents moderating direct effect on brand loyalty, and slightly higher effect through brand trust of the mobile telephone operators in Kosovo. Conclusions - The perceived service quality and brand trust are key determinants in achieving brand loyalty in telecommunication industry, followed by e-Marketing as means to creating expectations, delivering on promise to meet customers' perceptions for service quality with a purpose of building trust, that leads to loyalty towards the brands of mobile operators in Kosovo.

• The Research Journal of the Costume Culture
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• v.14 no.5
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• pp.850-863
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• 2006

The purpose of this study was to investigate if star marketing of on-line shopping malls affects consumers' WOM effect, and to compare the differences of consumption behavior between female teenagers and college students. Two hundred five female teenagers and college students who had purchased fashion goods through internet shopping mall participated in this study. For data analysis, descriptive statistics, factor analysis, t-test, and multiple regression were used. As the results, first, recognition of celebrity advertising models was classified into three factors such as 'trust of product', 'attractiveness of product' and 'leading interest of product' factors. Second, the greater exposure to celebrity models, the greater the good feelings about them, showing respondents' positive consumption behavior. Third, results of multiple regression revealed that behavior of pursuing celebrities' style accounted for 37% of the explained variance WOM behavior. Finally, t-test revealed that female college students were affected more by celebrity style and bought fashion items than female teenagers. However, female teenagers conducted more WOM behavior than college students. Based on these results, on-line fashion marketers would use these data for more their efficient fashion marketing strategies.

• The Korean Journal of Community Living Science
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• v.17 no.3
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• pp.29-41
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• 2006

The purpose of this research is to study the causal model among mother related variables, child abuse, and children's emotional maladjustment behaviors. The sample subjects were 542 pairs of fifth and sixth grade elementary school students and first as well as eighth grade middle school students, and their mothers. The major findings of the research are as follows: First, the result of multiple regression analysis on the effects of the maternal parenting stress and marital satisfaction to the children's abuse indicates that stress related to learning expectation and stress related to relationship with child are the significant contributing factor to physical abuse and verbal abuse. Second, the result of multiple regression analysis on the effects of the maternal parenting stress and child abuse to the children's emotional maladjustment behaviors indicate that verbal abuse is the significant contributing factor. Third, looking at causal relations of the maternal variables (maternal parenting stress, marital satisfaction) and child abuse (physical abuse, verbal abuse, neglect) to the children's emotional maladjustment behaviors, maternal variables impact indirectly through the child abuse factor.