• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.240-243
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• 2000

An apparel products retrieval system was proposed in which users can refer to products using Kansei evaluation values. The system adopts relevance feedback using history of the retrieval to learn the tendency of user evaluation. The system is based on a vector space retrieval model using products images expression as semantic scales. The system makes a query from user inputting information and retrieves closest products from the database. Revising algorithms of the difference method. linear multiple regression performed to investigate the effectiveness and criteria of the search. As a result of evaluation of the accuracy, it was found that the linear multiple regression and the neural network models are effective for the retrieval considering the individual Kansei.

• Journal of Korean Society on Water Environment
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• v.30 no.1
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• pp.8-15
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• 2014

In this study, regression equation was analyzed to estimate non-point source (NPS) pollutant loads in orchard area. Many factors affecting the runoff of NPS pollutant as precipitation, storm duration time, antecedent dry weather period, total runoff density, average storm intensity and average runoff intensity were used as independent variables, NPS pollutant was used as a dependent variable to estimate multiple regression equation. Based on the real measurement data from 2008 to 2012, we performed correlation analysis among the environmental variables related to the rainfall NPS pollutant runoff. Significance test was confirmed that T-P ($R^2=0.89$) and BOD ($R^2=0.79$) showed the highest similarity with the estimated regression equations according to the NPS pollutant followed by SS and T-N with good similarity ($R^2$ >0.5). In the case of regression equation to estimate the NPS pollutant loads, regression equations of multiplied independent variables by exponential function and the logarithmic function model represented optimum with the experimented value.

• 모자간호학회지
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• v.1
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• pp.34-44
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• 1991

The purposes of this study were to predict newborn birthweight by use of gestational period and fundal height and to identify growth curve of fundal height according to gestational period and growth curve of newborn birthweight according to fundal height. The subjects for the study were 802 women who delivered the normal newborn babies at Seoul National University Hospital from Sep. 1, 1981 to Aug.31, 1986. The data were collected bit chart review and analyzed nth SPSS program. The results of study were as follows : 1. The multiple regression equation ($R^2$=0.416) used for the prediction of newborn birthweight was y=(newborn birthweight, kg)=-4.421+0.075$x_1$(fundal height, cm)+0.053$x_2$(gestational period, weeks)+0.016$x_3$(abdominal girth, cm)+0.010$x_4$(maternal height, cm) 2. The growth curve of fundal height according to gestational period was obtained by polynomial regression. The regression equation was Y(fundal height, cm)=-36.78+18.58$log_ex$(gestational period, weeks) The growth curve of newborn birth weight according to fundal height was obtained by polynomial regression. The regression equation was Y(newborn birthweight, kg)=-8.09+3.27$log_ex$ (Fundal Height, cm) 3. In the following subgroups no significant difference was found in fundal height : engaged vs. nonengaged presentation, and nulliparous vs. multiparous women.

• Ocean and Polar Research
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• v.26 no.3
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• pp.465-473
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• 2004

Five parameters such as the entrance size of the front wall, conduit size, wave period, wave height and the width of water pool were selected to estimate the inflow rate, which is basic and essential input data to design seawater exchange breakwater with a submerged mound by conducting hydraulic model experiments. In the results of multiple regression analysis, log-log equation showed a good agreement rather than linear equation and the estimation of inflow rate was well done with only two parameters except entrance size of the front wall, wave period and the width of water pool. Finally, non-dimensional flow rate equation is derived.

• Journal of the Korean Institute of Gas
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• v.11 no.3
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• pp.13-18
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• 2007

The multivariate statistical analysis, using the multiple linear regression(MLR), have been applied to analyze and predict the flash points of binary systems. Prediction for the flash points of flammable substances is important for the examination of the fire and explosion hazards in the chemical process design. In this paper, the flash points are predicted by MLR based on the physical properties of pure substances and the experimental flash points data. The results of regression and prediction by MLR are compared with the values calculated by Raoult's law and Van Laar equation.

• Journal of the Korean Society of Tobacco Science
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• v.10 no.1
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• pp.83-91
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• 1988

The effects of tipping paper permeability and plugwrap porosity on the ventilation and the pressure drop of cigarettes have been studied and the results obtained were as follows. 1. The single and the multiple regression equation to estimate tip ventilation were establised. In the equations, the observed values of the tip ventilation with the varieties the plugwrap porosity were content with them by the single regression equation. 2. As based on the statistical consideration of the above equation, the deviation of the observed tip ventilation versus the tipping paper permeability were higher than them to the plugwrap porosity. 3. The regression equations to calculate pressure drop ratio and the total ventilation rate in filter tip from the tea ventilation were obtained. According to the equation, the observed values of the pressure drop ratio were significantly similar to them calculated. 4. It was found that the equations could be applied to the calculation of the ventilation of cigarettes using the mechanical and micro laser perforation tipping paper as well as the electrically perforated tipping paper of this Study.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.109-118
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• 2011

In this research estimated accuracies that were results in all the area of filtering of the plane equation that was used by whole data set, and regional of filtering that was driven by the plane equation for each vertual Grid. All of this estimates were based by all the area of filtering that deduced the plane equation by multiple linear regression analysis that was used by ground data set. Therefore, accuracy of all the area of filtering that used whole data set has been dropped about 2~3% when average of accuracy of all the area of filtering was based on ground data set while accuracy of Regional of filtering dropped 2~4% when based on virtual Grid. Moreover, as virtual Grid which was set 3~4 cm was difference about 2% of accuracy from standard data. Thus, it leads conclusion of set 3~4 times bigger size in virtual Grid filtering over LiDAR scan gap will be more appropriated. Hence, the result of this research allow us to conclude that there was difference in average accuracy has been noticed when we applied each different approaches, I strongly suggest that it need to research more about real topography for further filtering accuracy.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.125-130
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• 2009

Storage function method which considers the non-linearity of the relationship between rainfall and runoff has been frequently used to predict runoff in a basin and a flood pattern. However, it is time-consuming to estimate appropriate parameters of every basin and rainfall event, which requires the empirical parameter equation applicable in Korea. In this study, multiple regression analysis is used to develop empirical equations to estimate parameters of Storage Function method using basin characteristics. The basin area, maximum stream length, and stream slope are considered as the basin characteristics as the result of the regression analysis. Collinearity is removed and trial-and-error method is used to choose the most descriptive parameters to the dependent variables in Han River basin which is divided into 30 subbasins. The developed equations are validated using the rainfall events in MunMak gauging station and named as 'Han River equation'. The equation could provide the useful information about Storage Function method parameter to calculate runoff from a basin and predict river stage.

• PNF and Movement
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• v.10 no.4
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• pp.1-7
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• 2012

Purpose : The purpose of this study was to evaluate the relationship between physical performance, such as gait and postural control, and cognition on as assessed by clinical tools in individuals with chronic hemiparetic stroke. Methods : Twenty-six patients who had hemiparetic stroke participated in this study, and were evaluated four common clinical measurements, including the Berg balance scale (BBS), 10 meter walk test (10MWT), 6 minute walking test (6MWT), and Montreal cognitive assessment (MoCA). Multiple regression analysis was used BBS score, 10MWT, and 6MWT as the dependent variables; MoCA score, post-stroke duration, age, and affected side as independent variables. Results : In the regression equation of the BBS score, the correlation coefficient (r) was 0.875, the coefficient of determination (R2) was 0.786, and the MoCA score was the most important variable for determining the BBS score. In the regression equation for the 10MWT, ther was 0.888, the R2 was 0.999, and the MoCA score was the most important variable for determining 10MWT. Finally, the r was 0.777, the R2 was 0.998, and the MoCA score was the most important variable for determining 6MWT in the regression equation of the 6MWT. Conclusion : The results show that cognitive abilities affect gait proficiencies in individuals with chronic hemiparetic stroke. Therefore, these results suggest that cognitive tests are necessary for examining and evaluating the abilities of postural control and gait performance for chronic stroke patients in research and clinical environments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.26
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• pp.59-66
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• 1992

This Paper, first, tries to optimize the output specifications with uncertain characteristics. And then aims to solve the problem not only by making use of transformed multiple regression equation which can yield objective function of output characteristics but also by formulating developed multiple fuzzy goal programming using fuzzy set theory which can treat uncertainty easily, and the efficiency of these techniques, will be also demonstrated through a case study.