• Proceedings of the KSR Conference
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• 2003.10b
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• pp.483-488
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• 2003

Calibration and gauge factor readjustment process made for the health monitoring system installed in the railway bridges is reviewed and some findings are explained in this study: specifically, the calibrators made for this purpose are illustrated and the regression processes of the calibration on long-term displacement using water level sensor, longitudinal displacement using LVDT sensor, instantaneous displacement using LVDT sensors and accelerometer are described in details. Based on the regression results, new gauge factors are obtained from regression equation and another verification is made by performing another calibration again with new factors. From the second calibration, it was found that the suggested regression curves and their factors are appropriate and much better results are expected. Future work will be concentrated on the long-term analysis of the measurement data and on the database structures so that the assessment of the structure such as damage detection and remaining life estimation is possible.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.601-604
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• 2000

In this paper, we compare the classification performance of both data fusion and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. Since the relationship between input & output is not typically known, we use Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: Clustering based logistic regression turns out to provide the highest classification accuracy when input variables are weakly correlated and the variance of data is high. When there is high correlation among input variables, variable bagging performs better than logistic regression. When there is strong correlation among input variables and high variance between observations, bagging appears to be marginally better than logistic regression but was not significant.

• Journal of Fashion Business
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• v.10 no.4
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• pp.140-150
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• 2006

The purpose of this study was to examine affecting the addictive buying behavior toward fashion luxury products. 227 female college students were who purchased fashion luxury products surveyed for this study. For data analysis, descriptive statistics, factor analysis, and multiple regression were used. As the results, addictive buying toward luxury products was classified into three factors: impulse addictive, money addictive, and psychological addictive. Also, consumers' individuality pursuit was classified into four factors: unique choice, non-similarity choice, individual choice and non-social interest. Multiple regression results revealed that impulse buying, stress, and unique choice accounted for 38% of the explained variance in addictive buying toward luxury products. Also, regression results indicated that impulse buying, stress, unique choice and reference group accounted for 38% of the explained variance in impulse addictive buying. Finally, regression results pointed out that unique choice and impulse accounted 24% of the explained variance in psychological addictive buying. Based on these results, fashion social responsibility marketing strategies would be suggested.

• Journal of the East Asian Society of Dietary Life
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• v.17 no.6
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• pp.963-971
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• 2007

This research aimed to determine the relationship between hotel restaurants' SCM activities and their results. The samples are included exclusive high-end hotels located in the seoul area. To analyze the data, frequency analysis, reliability analysis, factor analysis, and regression analysis were applied. Multiple regression analysis showed that SCM activities (${\beta}$=.342, p<.000), information sharing (${\beta}$=.136, p<.006), and cooperative activities (${\beta}$=.120, p<.015) had a significant impact on financial performance. The explanatory power of this model was 14%, and there was statistical significance in the regression model. SCM activities(${\beta}$=.221, p<.000), information sharing (${\beta}$=.475, p<.000), and cooperative activities (${\beta}$=.172, p<.000) also had a significant impact on non-financial performance, and the explanatory power of this model was 29%, with statistical significance in the regression model.

• Journal of Environmental Science International
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• v.16 no.11
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• pp.1301-1312
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• 2007

The objective of this study is to propose a critical storm duration forecasting model on storm runoff in small river basin. The critical storm duration data of 582 sub-basin which introduced disaster impact assessment report on the National Emergency Management Agency during the period from 2004 to 2007 were collected, analyzed and studied. The stepwise multiple regression method are used to establish critical storm duration forecasting models(Linear and exponential type). The results of multiple regression analysis discriminated the linear type more than exponential type. The results of multiple linear regression analysis between the critical storm duration and 5 basin characteristics parameters such as basin area, main stream length, average slope of main stream, shape factor and CN showed more than 0.75 of correlation in terms of the multi correlation coefficient.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.77-78
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• 2002

A regression formula including the inlet film thickness as the parameter for the starvation factor in EHL condition is obtained by numerical analysis with Elord‘s cavitation algorithm. In addition, an apparatus for starved film thickness measurement by use of the white light interferometry is developed in order to verify the proposed regression formula. From observation results by this apparatus, the proposed regression formula can predict the reduction of central film thickness caused by starvation in a ball-plate contact with an uncertainty up to 10%

• Journal of Technology Innovation
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• v.12 no.1
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• pp.115-134
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• 2004

In this paper, we tried to find the bottleneck factors of firms' innovative activities using the KIS (Korea Innovation Survey) 2002 data. Employing the method of factor analysis, we identified five bottleneck factors of innovative activities: organizational bottleneck factor, innovative bottleneck factor, economic bottleneck factor, supply-chain bottleneck factor, and market-environment bottleneck factor. Using regression analysis which includes the five bottleneck factors, industry characteristics variables (market concentration, technological opportunity, appropriability), and other control variables, we found (1) that all the five bottleneck factors are negatively related with innovative activities, (2) that technological opportunity and appropriability conditions are positively related with innovative activities, (3) that there is an inverted-U relationship between market concentration and innovative activities, and (4) that firm size has no significant influence on firms' innovative activities.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.35.1-35.1
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• 2012

Determining the virial factor of the broad-line region (BLR) gas is crucial in calibrating AGN black hole mass estimators, since the measured line-of-sight velocity needs to be converted into the representative velocity of the BLR gas. The unknown virial factor has been empirically calibrated based on the $M_{BH}-{\sigma}_*$ relation of non-AGN galaxies, but the claimed values are different by a factor of 2 in recent studies. We investigate the origin of the difference by measuring the $M_{BH}-{\sigma}_*$ relation using the most updated nearby galaxy sample, and explore the dependence of the virial factor on the various fitting methods. We find that the discrepancy is mostly caused by the sample bias while the difference stemming from various regression methods is marginal. Based on the best-determined virial factor, we present the updated $M_{BH}-{\sigma}_*$ relation of local active galaxies.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.3_4
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• pp.387-395
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• 2004

This research was designed to investigate the effect of hand and sensibility image on the preference to textiles for jacket. 85 subjects majored in fashion design were surveyed and 10 kinds of fabrics used as specimen at each season. Factor analysis, t-test, Pearson correlation, regression were used for statistical analysis by SPSS WIN 11.0. The results of this study were as follows; 1. In Spring\ulcornerFall season, 6 factors were extracted as hand factor and 2 factors as sensibility factor of textiles for jacket. 2. 6 factors were extracted as hand factor and 2 factors as sensibility image in Summer. 3. 6 factors were extracted as hand factor and 2 factors as sensibility image in Winter season. 4. There were significant differences according to sex between hand factor and sensibility image at each season. 5. There were significant correlations between hand and sensibility image in Spring\ulcornerFall and Summer. 6. Hand and sensibility image were related to the preference to textiles for jacket in Spring and Winter.

• 한국ITS학회:학술대회논문집
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• v.2007 no.10
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• pp.92-99
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• 2007