• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.658-663
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• 2005

This study presents the empirical results of comparing several demand forecasting methods for Supply Chain Management(SCM). Adaptive exponential smoothing using change detection statistics (Jun) is compared with Trigg and Leach's adaptive methods and SAS time series forecasting systems using weekly SCM demand data. The results show that Jun's method is superior to others in terms of one-step-ahead forecast error and eight-step-ahead forecast error. Based on the results, we conclude that the forecasting performance of SCM solution can be improved by the proposed adaptive forecasting method.

• Korean Journal of Adult Nursing
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• v.18 no.5
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• pp.798-808
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• 2006

Purpose: The purpose of this study was to investigate the effects of aquatic exercise on rehabilitation in home stroke patients. Method: A quasi-experimental pretest and posttest design was used to examine the change of balance, ADL, IADL, pain, depression and self-efficacy atthe completion of 6-weeks aquatic exercise program. The subjects consisted of 25 adults who had a stroke. Thirteen experimental and twelve control subjects completed pre and post test measures. Outcome variables were balance, ADL, IADL, pain, depression and self-efficacy. Chi-Square test(Fisher's exact method) was used to examine the equality of the subjects and Wilcoxon Rank Sum Test used to examine the group difference by using SAS. Results: There was no significant difference in balance and depression between the two groups. However, there was a significant difference in ADL, IADL, pain and self-efficacy between the two groups. Conclusion: Aquatic exercise can improve ADL, IADL, self-efficacy and reduce pain. Therefore, further research is recommended by increasing the length of aquatic exercise and number of subjects, so that its effects can be more generalizable.

• Research in Community and Public Health Nursing
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• v.18 no.1
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• pp.136-145
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• 2007

Purpose: This study was attempted to illuminate danger signals through an extensive analysis of factors influencing adolescents' illicit drug use. On this basis, it built predictive factors of adolescents' illicit drug use. Method: A questionnaire was distributed to 1,238 subjects living in Seoul, and of them 1,082 answers were analyzed using the SAS 8.2 program. Also logistic regression analysis was conducted based on the stepwise selection method for constructing the predictive factors. Results: The findings of this study are as follows. Individual-related factors were psycho-somatic symptoms, self-esteem, fortune delinquent experience, and sexual-violence delinquent experience. Home-related factors were insincerity, threatening and the assessment of the parent (rearer)-adolescent communication type. Society-related factors were affection of friends and friends' attitude toward delinquency. Conclusion: These findings of this study suggest that a broad intervention program should be provided to nurture wholesome youth culture related to illicit drug use. It is also recommended that a variety of individual, home and society-related programs should be developed for drug users.

• IE interfaces
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• v.18 no.3
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• pp.343-349
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• 2005

This study presents the empirical results of comparing several demand forecasting methods for Supply Chain Management(SCM). Adaptive exponential smoothing using change detection statistics (Jun) is compared with Trigg and Leach's adaptive methods and SAS time series forecasting systems using weekly SCM demand data. The results show that Jun's method is superior to others in terms of one-step-ahead forecast error and eight-step-ahead forecast error. Based on the results, we conclude that the forecasting performance of SCM solution can be improved by the proposed adaptive forecasting method.

• Journal of Korean Society for Quality Management
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• v.33 no.1
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• pp.73-82
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• 2005

This article proposes a practical approach, which is based on the concept of the expected squared relative error, that can consider both the prediction quality and the practitioner's subjectivity in simultaneously optimizing multiple responses. Through a case study, multiresponse optimization using the expected squared relative error approach is illustrated, and the SAS program to implement the proposed method is provided.

• Journal of the Korea Fashion and Costume Design Association
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• v.2 no.2
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• pp.155-171
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• 2000

This study is to measure and evaluate the sensibility image for textile pattern design based on the generation. Ten patterns classified by a practical survey on the market are presented. A questionnaire has 14 sensibility related words scaled by 7 point semantic differential method. The practical research is performed for 200 women screened by sensibility test for individual character analysis based on the generation. Each subject is answered by a face-to-face interview method to improve survey's accuracy, For statistical test about differences in treatment means, SAS package is used and analyzed through ANOVA, significance probability and mean, In summary, this paper has proposed the sensibility image scale for apparel pattern design to satisfy individual sensibility, The results of this study can be effectively applied to develop textile pattern design based on human sensibility.

• Journal of the Korean Society of Clothing and Textiles
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• v.21 no.4
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• pp.727-739
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• 1997

The purpose of this study was to classify and analyze the lower body of adult female and to provide it'stotal data for clothing construction. The subjects were 82 Korean adult females and their age range is from 19 to 24 years old. 42 variables (10 variables from the direct anthropometric data, 2 variables from the multiplication method and 30 variables from the indirect anthropometric data) in total were applies to analyze(means, standard deviations, factor analysis, cluster analysis) The result of factor analysis indicated that 10 factors were extract'cd through factor analysis and orthogonal rotation by the method of varimax and those factors comprise 82. 5 percent of total variance. The obesity of lower body was closely related to hip angle indicated the degree of drooping hip was extracted a independent factor, not influenced by other variance. And somatotype of lower body is classified by cluster analysis, using the FASTCLUS of SAS. To classify the lower body, two kinds of silhouette, front- back and side were applied to analize. The front- back silhouette was subdivided into five groups and the side silhouette four.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.59-60
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• 2021

To measure the effect of the stress-strain dispersion across the installed waterproofing layer on the concrete surface, a strain gauge was attached to the gap between the waterproofing layer and the concrete structure at specified points of upper, center and bottom of the load-displacement simulation specimen, and the peak stress-strain at the displacement interface were measured and compared with stress-strain at other areas to analyze each material types' stress-strain dispersion ratio properties. Based on the results of the testing, it was shown that materials with high load-displacement resistance performance accordingly had high stress-strain dispersion ratio results, and the materials from highest performance to lowest performance were; CAS, SAS, PUC and CSC.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.635-647
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• 2013

Imputation is a commonly used method to handle missing survey data. The performance of the imputation method is influenced by various factors, especially an outlier. The removal of the outlier in a data set is a simple and effective approach to reduce the effect of an outlier. In this paper in order to improve the precision of multiple imputation, we study a imputation method which reduces the effect of outlier using various weight adjustment methods that include the removal of an outlier method. The regression method in PROC/MI in SAS is used for multiple imputation and the obtained final adjusted weight is used as a weight variable to obtain the imputed values. Simulation studies compared the performance of various weight adjustment methods and Monthly Labor Statistic data is used for real data analysis.

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.1
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• pp.47-58
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• 2018

A solar array simulator (SAS) consists of an engine that generates a setpoint according to panel characteristics, a power stage that provides the actual output, and a controller. Particularly, if the control method is not suitable due to the nonlinearity of the solar panel output curve depending on the irradiation amount and the temperature, and the variation of the curve factor depending on the various panel materials, then the panel simulation function cannot be performed properly. Current and voltage mode controls are usually used for the conventional control method. However, these control methods deteriorate the control performance near the maximum power point; thus, a hybrid control method using two or more controllers has been investigated. In this study, we analyze the hybrid control method using three controllers divided into different areas. The design equation of the controller is derived based on the small signal modeling of each controller, and the simulation performance of the solar array simulator verifies its stability and response speed.