• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.8
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• pp.1222-1233
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• 2006

The purpose of this study was to classify the modern image by clothing design elements. This research was done by survey method with 25 kinds of modern image photos selected in fashion magazines. The data was analyzed by Reliability Analysis, Factor Analysis, MANOVA, One-Way ANOVA, Duncan's test and MDS. The results of this study are as follows: 1. modern image was classified by 5 factors. Those were sexy-modern, elegant-modern, natural-modern, mannish-modern and minimal-modern images. 2. Sexy-modern image was well-expressed by chromatic and chromatic color coordinations. Elegant-modern image was well-expressed by fitted silhouette, fit and achromatic and chromatic color coordinations. Natural-modern image was well-expressed by A silhouette, loose apparel-fit, chromatic and chromatic coordinations and soft texture. Mannish-modern image was well-expressed by H silhouette, loose apparel-fit, chromatic and chromatic color coordinations and hard texture. Minimal-modern image was well-expressed by H silhouette, tight or loose apparel-fit and soft texture. 3. modern image was positioned into mostly hard or masculine on image scale.

• Science of Emotion and Sensibility
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• v.5 no.1
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• pp.9-16
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• 2002

This study was designed to cluster the preferred sensibilities of college students, and to distinguish the most preferred sensibility according to gender and their inter-subject differences. 98 of sensibility adjectives were composed into questionnaire with SD method and the data of 176 students were analyzed in ANOVA, Cluster and Correspondence analysis using SAS package. College students were divided into 10-sensibility clusters: the Casual(no-decoration casual, cool-dynamic casual and elaborate-clean casual), the Romantic Modem, the Simple Natural, the Classic(craft-romantic classic and monotonous classic), the Expressionless, the Gorgeous, and the Traditional Folklore. The adjectives and the sensibility clusters of students were visualized together into 2-D with two axis of static vs. dynamic and light vs. heavy.