• Journal of the Korean Society of Clothing and Textiles
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• v.23 no.3
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• pp.345-352
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• 1999

the purpose of this study was to consider the lower bodyshape factor of girls according to their age groups. The subject were 150 Korean Elementary School Girls and 150 Korean Junior High School Girls. The subjects were directly measured anthropometrically. In first group(Elementary School Girls) the result of factor analysis indicated that 7 factors were extracted through factor analysis and those factors comprise 83.1% of total variance and in second group (Junior High School Girls) 8 factors were extracted through factor analysis and those factors comprise 79.9% of total variance. Lower bodyshape factors were different to each groups. So these systematic information on typical bodyshape were provide to reduce the burden of stocks and increase clothing fitness.

• 한국석유지질학회:학술대회논문집
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• spring
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• pp.10-14
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• 1998

A systematic methodology is developed for the electrofacies determination from wireline log data using multivariate statistical analysis. To consider corresponding contribution of each log and reduce the computational dimension, multivariate logs are transformed into a single variable through principal components analysis. Resultant principal components logs are segmented using the statistical zonation method to enhance the efficiency and quality of the interpreted results. Hierarchical cluster analysis is then used to group the segments into electrofacies. Optimal number of groups is determined on the basis of the ratio of within-group variance to total variance and core data. This technique is applied to the wells in the Korea Continental Shelf. The results of field application demonstrate that the prediction of lithology based on the electrofacies classification matches well to the core and the cutting data with high reliability This methodology for electrofacies classification can be used to define the reservoir characteristics which are helpful to the reservoir management.

• Journal of the Korean Society of Costume
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• v.37
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• pp.181-190
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• 1998

The purpose of this study was to provide basic information for women's women's head type for mil-inary. The subjects were 141 college women aged from 19∼23. Data were collected from the real anthropometric measurements and 4 index. Correlation coefficientss, factor analysis, cluster analysis and analysis of variance in SAS package. The results were as follows : 4 factors were extracted from 20 anthrometric measurements and in index data, which explain 60.0% of variance. The subjectss were classified into 4 clusters by 11 measurement and 4 index data. Each charicteristics of cluster by the measurements was flat, big, thick, small types in women's head. Each charicteristics of cluster by the index data was mostly flat in head thickness and wide, midium, narrow, very wide type in face.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.21-26
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• 2018

As the large amount of data can be efficiently stored, the methods extracting meaningful features from big data has become important. Especially, the techniques of converting high- to low-dimensional data are crucial for the 'Data visualization'. In this study, principal component analysis (PCA; linear dimensionality reduction technique) and Isomap (non-linear dimensionality reduction technique) are introduced and applied to neural big data obtained by the functional magnetic resonance imaging (fMRI). First, we investigate how much the physical properties of stimuli are maintained after the dimensionality reduction processes. We moreover compared the amount of residual variance to quantitatively compare the amount of information that was not explained. As result, the dimensionality reduction using Isomap contains more information than the principal component analysis. Our results demonstrate that it is necessary to consider not only linear but also nonlinear characteristics in the big data analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.786-792
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• 2006

The design of experiment(DOE) with orthogonal arrays is adopted when the engineering design is needed in a discrete design space. In this research, a design process with orthogonal array is peformed to obtain the optimum design which satisfy the frequency target of the steering system. The optimum design is determined from the analysis of means(ANOM) and sensitivity information about design variables is evaluated by the analysis of variance(ANOVA). Interactions between design variables are investigated to achieve additivity which should be valid in using orthogonal array. It is shown that when strong interactions exist, the DOE process with orthogonal array considering interaction is introduced to find out optimum design.

• Journal of Fashion Business
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• v.11 no.4
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• pp.29-41
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• 2007

This study is to research how women aging from 20 through 40 Apperance -Mnagement Bhavior and care of their outer looks from a beauty treatment perspective. This research should help satisfy the wants of women who are the main clients of the beauty products and help the beauty industry to produce new products and also to help out on their marketing strategy. In order to search the general characteristics of our target women, Frequency Analysis was used, to find out the sub-factor of interest in beauty Factor Analysis and Reliability Analysis was used. In order to divide the group according to Degree of Apperance Concern 'sub-factor, cluster analysis, analysis of variance, Scheffe'-test, $X^2-test$ was used, and to find out the difference on how they care of beauty analysis of variance was used, and further more to summarize the result of analysis of variance Scheffe'-test was used. As a result, in all different ways of beauty caring, weight resisting, skin care and plastic surgery summed up similarly among the self-care group, hair care ended up with similar results among all three groups: self-caring group, no interest in beauty at all group, and the too conscious of other eyes group, and results on the interest rate of clothing ended up similarly among the other-eye conscious group, beauty care interest group, and the self-care group.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.567-578
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• 2017

Grouped multivariate data can be tested for differences between two or more groups using multivariate analysis of variance (MANOVA). However, this method cannot be used if several assumptions of MANOVA are violated. In this case, multidimensional scaling (MDS) and analysis of distance (AOD) can be applied to grouped dissimilarities based on the various distances. A permutation test is a non-parametric method that can also be used to test differences between groups. MDS is used to calculate the coordinates of observations from dissimilarities and AOD is useful for finding group structure using the coordinates. In particular, AOD is mathematically associated with MANOVA if using the Euclidean distance when computing dissimilarities. In this paper, we study the between and within group structure by applying MDS and AOD to the grouped dissimilarities. In addition, we propose a new test statistic using the group structure for the permutation test. Finally, we investigate the relationship between AOD and MANOVA from dissimilarities based on the Euclidean distance.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.253-258
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• 1998

Staggered nested designs are the most popular class of unbalanced nested designs in practical fields. The most important features of the staggered nested design are that it has a very simple open-ended structure and each sum of squares in the analysis of variance has almost the same degrees of freedom. Based on the features, a class of unbalanced nested designs which is generalized of the staggered nested design is proposed. Some of the generalized staggered nested designs are shown to be more efficient than the staggered nested design in estimating some of variance components and their linear combinations.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.1
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• pp.47-47
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• 1988

Rapid globalization of production and marketing functions makes choice of international transportation mode of great importance. In this paper, transportation mode is characterized by two factors, mean and variability of transportation lead time. We developed a simple mathematical model to estimate the relative impact of mean lead time, lead time variance and demand variance on the required average inventory level under specified service rates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.5
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• pp.428-438
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• 1987

This paper describesl the point-detector arrays system to processes the field of signal and noise of the turbulent atmosphere or variance and covariance circuit. By using the aboves, the maximum output of direct-detection shows a little differences between experimental datas. As a whole the experimental data datas are agreed with the joint Gaussian theoretical curves.