• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.2
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• pp.364-375
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• 2002

The purpose of this study is to identify the differences between married women's dissatisfaction towards imported and domestic clothing and to test the role of socioeconomic variables on dissatisfaction. Two-piece formal suit was selected as the item, and country of origin of imported suit was not controlled. Sample selection criteria included married women living in Seoul, Korea, between ages 30-59. The data were analysed using factor analysis, paired t-test, and one-way ANOVA. The results indicate, in the Korean clothing market, both international and Korean marketers should be prudent with their price policies and should implement differentiated marketing strategy based on their target market's demogrophic profile. Higher dissatisfaction towards domestic clothing in terms of most factors, under the rapidly globalizing market environment suggests the Korean marketers will be forced to face full-scale harsh competition from international marketers.

• The Research Journal of the Costume Culture
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• v.6 no.3
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• pp.34-45
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• 1998

The purposes of this study were 1) to segment the female formal suit market based on clothing benefits sought by housewives in Checheon 2) to compare the real and ideal self-image's relative power on the clothing benefits factor, and 3) to develop a profile of each segment concerning self-image (real and ideal), and demographics. The data wer collected via a questionnaire from housewives. Using factor and cluster analysis, four groups were identified and labeled as 1) Easy care oriented users 2) Aesthetics/fashion oriented users 3) Low benefit oriented users. ANOVA, Duncan's Multiple Range Test, Chi-square statistics revealed significant differences among the three groups according to clothing benefits, real and ideal self-image and demographic variables.

• Journal of the Korea Fashion and Costume Design Association
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• v.13 no.4
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• pp.69-77
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• 2011

The purpose of this study was to identify the analysis of men's wear color preference between Korean and Chinese college women. The experimental materials developed for this study were a set of stimulus and response scales. The 24 color pictures and 5-point scales were used for evaluation of preference. Data were obtained from 120 Korean college women living in Kyeongnam, Korea and 120 Chinese college women living in Shandog, China on October and November 2010. For data analysis, ANOVA and Duncan-test were used by using SPSS program. Results of this study were as follows. Korean and Chinese college women, shirts hue, tie hue, and shirts/tie tone showed an independent effect on men's wear color preference. Interaction effects of Korean and Chinese college women and shirts hue, Korean and Chinese college women and tie hue, suit hue and shirts hue, shirts hue and shirts/tie tone, and tie hue and shirts/tie tone were found. These results suggested that men's wear color preference can be affected by Korean and Chinese college women, suit hue, shirts hue, tie hue, and shirts/tie tone.

• Journal of the Korea Fashion and Costume Design Association
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• v.24 no.3
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• pp.1-15
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• 2022

The purpose of this study is to compare and analyze the perception of men's fashion before and after the COVID-19 pandemic. TEXTOM allowed the collection of Big Data based on the term 'men's fashion'. As for the data collection periods, Jan. 1, 2018 to Dec. 31, 2019 was set as the pre-COVID-19 era, while Jan. 1, 2020 to Dec. 31, 2021 was set as the post-COVID-19 era. The top 50 words in terms of appearance frequency were extracted from the data. The extracted words were processed using network centrality analysis and CONCOR analysis using Ucinet 6. Research findings were as follows. 1) In the pre-COVID-19 era, the appearance frequency of 'men' was the highest, followed by 'fashion', 'men's fashion', 'brand', 'daily look', 'suit', and 'department store'. These words came up with a high TF-IDF values. Network centrality analysis discovered that 'men', 'fashion', 'men's fashion', 'brand', and 'suit' had a high level of connectivity with other words. CONCOR analysis showed four significant groups: 'fashion item and styles', 'fashion show', 'purchase', and 'collection'. 2) In the post-COVID-19 era, the appearance frequency of 'men' was the highest, followed by 'fashion', 'brand', 'men's fashion', 'discount', 'women', and 'luxury'. These words also displayed high TF-IDF values. Network centrality analysis found that 'fashion', 'men', 'brand', 'men's fashion', and 'discount' had a high level of connectivity with other words. CONCOR analysis showed four significant groups: 'fashion item and style', 'fashion show', 'purchase', and 'situation'. 3) Before the outbreak of the pandemic, men were interested in suits to wear to the office, daily look, and fashion shows in Milan and Paris. They often purchased menswear in multi-brand and open stores. However, they were more interested in sneakers, casual styles, and online fashion shows as social distancing and working from home became common. Most purchased menswear through online platforms.

• Journal of the Korean Society of Clothing and Textiles
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• v.19 no.5
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• pp.747-764
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• 1995

The purpose of the present study were 1) to identify the dimensional structure of impression formed of a female figure, 2) to analyze effects of several elements of apparel design on impression formation of the figure in suit. The experimental materials developed for this study were a set of stimuli and a response scale. The stimuli consisted of 60 drawings made by identical manipulations of 3 indepndent variables in 3 clothing styles(suit, dress and pants with blouse). The independent variables were (1) five clothing colors (red, blue, yellow, white and black), (2) two lengths(short/long) of suit skirt, dress, and pants (3) two types of blouse and dress collars (shirt collar/ribbon collar). The 7-point semantic differential response scale to measure the dependent variables (formed impressions of the female figure) was composed of 37 bipolar adjectives. Further- more, two open-ended questions were used for interpretation of the reponses. The study proceeded in three independent experimental part was based on the 3 clothing styles using a 5(color)$\times$2(length)$\times$2(collar) factorial design. Subject were 200 female undergraduate students reandomly assigned to one of 20 combinations in each part of the experiment. The data were analyzed by factor analysis, 3-way ANOVA and Multiple Classification Analysis. Five factors emerged to account for the dimensional structure of impression of the female figure in specific attire. These factors included three basic dimensions of impression identified as potency, activity and evaluation, confirming the results of previous studies. Result from open-ended questionaire supported the theoretical perspective of Schneider, Hastorf and Ellsworth on the procedure of impression formation.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.11
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• pp.1683-1695
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• 2009

This study analyzes the production process of eight domestic companies that manufacture scuba diving suits for men with an emphasis on the level of consumer satisfaction in scuba diving suits purchases. One hundred fifty questionnaires were distributed and a total of 140 usable data were coded for further statistical analysis that includes descriptive statistics (frequency and ${\chi}^2$ test) through SPSSWIN 17.0. The results show that a majority of the domestic scuba diving suit companies were either small, manufactured products under original equipment manufacturer (OEM) brands, or were involved in the import business. Many of these companies have developed a local sizing system derived from a company database of customer sizing. As a result, different companies have different sizes that lead to confusion and complication among consumers in selecting the correct size for scuba diving suits. The results indicate that most high-priced diving suits are made of imported fabrics because they had superior quality, fitness, and thickness compared to domestic brands. The degree of consumer satisfaction with scuba diving suits was found to be low in comfort, stuffiness, and activity. Respondents indicated that they felt a little tightness in circumstances such as bust, wrist, and thigh in measurements of circumstances. On the other hand, the respondents showed a high degree of satisfaction with body fitness in scuba diving suits. Further research will clarify a standardized sizing system and develop patterns suitable for Korean men's scuba diving suit body sizes.

• Fashion & Textile Research Journal
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• v.13 no.1
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• pp.82-90
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• 2011

This study examines if men in the 20's and 30's have different preference for bag types according to their age and gender-role identity types in order to provide foundational data for the male bag market to segment its customers and establish marketing strategies. Total 288 questionnaire sheets were distributed to 186 men in the 20's and 102 men in the 30's residing in Busan. First, according to the result of analyzing their preference for bag types, adult men in the 20's and 30's preferred cross bags the most. It was also shown that men who are feminine or androgynous prefer back packs, shoulder bags, and tote bags to the other two types. Second, about cross bags, men in the 20's showed a higher rate of having two or three than those in the 30's. Men in the 20's possessed back packs more than those in the 30's. And men tend to show a lower rate of having shoulder bags compared with that of cross bags or back packs. Men in the 30's possessed briefcases more than those in the 20's. Masculine men had more briefcases than the other types of bags, and androgynous men tend to have more tote bags than the other types of bags. Third, men in the 20's and 30's all deemed that back packs go well with the casual style. Men in the 20's regarded shoulder bags are the type of bags that harmoniously matches all styles including casual or semi-suit; however, men in the 30's think they only suit casual or semi-suit. And it was also found that men in the 20's think briefcases are the type of bags that goes well with various styles of clothes while men in the 20's consider they are the type of bags only matching suits.

• Journal of the Korean Society of Clothing and Textiles
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• v.38 no.5
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• pp.733-742
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• 2014

This study investigated the degree of inconvenience in existing ready-made clothes and clothing preferences through a survey of 197 wheelchair-bound males in order to provide preliminary data for the development of a suit that considers the physical characteristics and requirements of the disabled in wheelchairs for improved quality of living and positive interpersonal relations. Among the survey respondents, the 30s to 40s age group was the largest at 71.6%. The most common type of disability was myelopathy at 72.6%. Also 59.9% of respondents had a job and ongoing external and social activities. As for the duration of wheelchair use, 10-20 years was the longest at 40.6%. It was found from the survey that respondents felt inconvenienced with existing clothes and changing pants was most inconvenient. Most experienced having their clothes altered due to the difficulty in finding well-fitting ones; consequently, the length of pants was the most altered item because pants are based on the size of a standing man and there exists a discrepancy in length due to the atrophy of the legs of the disabled. They preferred one style in general for clothing preferences as well as common design and details as well. However, they preferred a style with a short front and long back due to a discomfort in jacket length. A short length was the most complained about pants item.

• Journal of Internet of Things and Convergence
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• v.9 no.3
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• pp.13-19
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• 2023

In this paper, we investigated the implementation of a hairstyle recommendation system based on big data and deepfake technology. The proposed hairstyle recommendation system recognizes the facial shapes based on the user's photo (image). Facial shapes are classified into oval, round, and square shapes, and hairstyles that suit each facial shape are synthesized using deepfake technology and provided as videos. Hairstyles are recommended based on big data by applying the latest trends and styles that suit the facial shape. With the image segmentation map and the Motion Supervised Co-Part Segmentation algorithm, it is possible to synthesize elements between images belonging to the same category (such as hair, face, etc.). Next, the synthesized image with the hairstyle and a pre-defined video are applied to the Motion Representations for Articulated Animation algorithm to generate a video animation. The proposed system is expected to be used in various aspects of the beauty industry, including virtual fitting and other related areas. In future research, we plan to study the development of a smart mirror that recommends hairstyles and incorporates features such as Internet of Things (IoT) functionality.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.9
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• pp.251-260
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• 2021

Gait analysis is one of the research fields for obtaining various information related to gait by analyzing human ambulation. It has been studied for a long time not only in the medical field but also in various academic areas such as mechanical engineering, electronic engineering, and computer engineering. Efforts have been made to determine whether there is a problem with gait through gait analysis. In this paper, as a pre-step to find out gait abnormalities, it is investigated whether it is possible to differentiate whether experiment participants wear elderly simulation suit or not by applying gait data to machine learning models for the same person. For a total of 45 participants, each gait data was collected before and after wearing the simulation suit, and a total of six machine learning models were used to learn the collected data. As a result of using an artificial neural network model to distinguish whether or not the participants wear the suit, it showed 99% accuracy. What this study suggests is that we explored the possibility of judging the presence or absence of abnormality in gait by using machine learning.