• Fashion & Textile Research Journal
• /
• v.15 no.6
• /
• pp.1000-1009
• /
• 2013

Well-fitting riding breeches provide a comfortable ride. Horse-riding breeches should fit the lower body with patches located on the inside of hip and knees to prevent tears and slips. This study provides information about the fit of women's breeches using 3D human body scan data wearing commercially available two breeches according to posture. To get information about breeches fit, we measured the angle of waist line, the length, and the area of the breeches fit on four 20's women. This research showed the problem which was down for waist back line in the case of the horseback riding pose. The back waistline of the riding breeches should be raised compared to the front waistline; subsequently, an increased waistline angle results in less back waistline decrease. The breeches have plenty of length from back waist to crotch so the breech fit can be improved. The thigh circumference increased when riding in the front; therefore, good elasticity of the weft direction of the fabric is recommended. The length increase and the peripheral increase of the front knee significantly increased the surface area of the knee; consequently, knee patch material should be a two-way elastic fabric in all directions to enhance comfort according to riding motion.

• Journal of Appropriate Technology
• /
• v.5 no.2
• /
• pp.70-81
• /
• 2019

The garment industry is one of the most labor-intensive manufacturing industries, with its sewing process relying almost entirely on manual labor. Its costs highly depend on the efficiency of this production line and thus is crucial to determine the production rate in real-time for line balancing. However, current production tracking methods are costly and make it difficult for many Small and Medium-sized Enterprises (SMEs) to implement them. As a result, their reliance on manual counting of finished products is both time consuming and prone to error, leading to high manufacturing costs and inefficiencies. In this paper, a production tracking system that uses the sewing machines' energy consumption data to track and count the total number of sewing tasks completed through Convolutional Neural Network (CNN) classifiers is proposed. This system was tested on two target sewing tasks, with a resulting maximum classification accuracy of 98.6%; all sewing tasks were detected. In the developing countries, the garment sewing industry is a very important industry, but the use of a lot of capital is very limited, such as applying expensive high technology to solve the above problem. Applied with the appropriate technology, this system is expected to be of great help to the garment industry in developing countries.

• Fashion & Textile Research Journal
• /
• v.22 no.4
• /
• pp.481-494
• /
• 2020

This study examined consumer perceptions and consumer responses of Halal cosmetics and compared them with vegan cosmetics, which is a term similarly used. Twitter API of Python 3.7 was used to collect the keywords '#halalcosmetics' and '#vegancosmetics'. First, the main perception of consumers on Halal cosmetics focused on the original concept, image, expected efficacy, and factors to consider before purchase, religious keywords, labels and packaging for Halal cosmetics. Second, the main consumer perception of vegan cosmetics was the product concept, expected efficacy, factors to consider before purchase, related vegan industry, image, and vegan cosmetic components. Third, the consumer perceptions of Halal cosmetics and vegan cosmetics were similar in multiple ways, and both concepts included the Cruelty-free concept. Fourth, consumer satisfaction factors included cosmetics color, brand's consumer service, efficacy, smell, packaging design, reasonable price, effects, and formulation of cosmetics as well as satisfaction with Halal certification, and satisfaction of Vegan consumers. Consumer dissatisfaction factors included smell, flavor, delay in shipping, dissatisfaction with formulation, discrepancy between actual color and computer screen, concern and distrust about the use of prohibited ingredients for Halal products. This study examined consumer perceptions and reactions to Halal and vegan cosmetics to create basic knowledge for niche markets that are emerging as an ethical beauty consumption trend.

• Journal of Korea Society of Industrial Information Systems
• /
• v.29 no.5
• /
• pp.139-155
• /
• 2024

The purpose of this study is to understand the effect of product characteristics, purchase transactions and logistics characteristics on purchase behavior and satisfaction in the omnichannel, focusing on clothing products. A survey was conducted on consumers with experience in purchasing clothing products, and research problems were analyzed through structural equations, focusing on the hypotheses established in this study. As a result of the study, in the case of consumers with experience in internet shopping, product factors such as aesthetic, diversity, price and purchase transaction factors had a positive (+) effect on customer satisfaction, and customer satisfaction had a positive (+) effect on consumer purchasing behavior. In the case of consumers with omnichannel experience, price among product factors had a positive (+) effect on customer satisfaction. Based on this, it is expected that factors that can activate omni-channels that were not previously discussed can be derived and implications can be provided.

• Fashion & Textile Research Journal
• /
• v.20 no.5
• /
• pp.533-547
• /
• 2018

The objective of this study is to examine the perception of golfwear and related trends based on major keywords and associated words related to golfwear utilizing big data. For this study, the data was collected from blogs, Jisikin and Tips, news articles, and web $caf{\acute{e}}$ from two of the most commonly used search engines (Naver & Daum) containing the keywords, 'Golfwear' and 'Golf clothes'. For data collection, frequency and matrix data were extracted through Textom, from January 1, 2016 to December 31, 2017. From the matrix created by Textom, Degree centrality, Closeness centrality, Betweenness centrality, and Eigenvector centrality were calculated and analyzed by utilizing Netminer 4.0. As a result of analysis, it was found that the keyword 'brand' showed the highest rank in web visibility followed by 'woman', 'size', 'man', 'fashion', 'sports', 'price', 'store', 'discount', 'equipment' in the top 10 frequency rankings. For centrality calculations, only the top 30 keywords were included because the density was extremely high due to high frequency of the co-occurring keywords. The results of centrality calculations showed that the keywords on top of the rankings were similar to the frequency of the raw data. When the frequency was adjusted by subtracting 100 and 500 words, it showed different results as the low-ranking keywords such as J. Lindberg in the frequency analysis ranked high along with changes in the rankings of all centrality calculations. Such findings of this study will provide basis for marketing strategies and ways to increase awareness and web visibility for Golfwear brands.

• Fashion & Textile Research Journal
• /
• v.23 no.6
• /
• pp.799-809
• /
• 2021

This study aimed to grasp the perceptions and trends in fashion platforms and fashion smart factories using big data analysis. As a research method, big data analysis, fashion platform, and smart factory were identified through literature and prior studies, and text mining analysis and network analysis were performed after collecting text from the web environment between April 2019 and April 2021. After data purification with Textom, the words of fashion platform (1,0591 pieces) and fashion smart factory (9750 pieces) were used for analysis. Key words were derived, the frequency of appearance was calculated, and the results were visualized in word cloud and N-gram. The top 70 words by frequency of appearance were used to generate a matrix, structural equivalence analysis was performed, and the results were displayed using network visualization and dendrograms. The collected data revealed that smart factory had high social issues, but consumer interest and academic research were insufficient, and the amount and frequency of related words on the fashion platform were both high. As a result of structural equalization analysis, it was found that fashion platforms with strong connectivity between clusters are creating new competitiveness with service platforms that add sharing, manufacturing, and curation functions, and fashion smart factories can expect future value to grow together, according to digital technology innovation and platforms. This study can serve as a foundation for future research topics related to fashion platforms and smart factories.

• Fashion & Textile Research Journal
• /
• v.24 no.5
• /
• pp.593-604
• /
• 2022

The purpose of this study is to analyze the flow of change in perception of metaverse before and after COVID-19 through big data analysis. This research method used Textom to collect all data, including metaverse for two years before COVID-19 (2018.1.1~2019.11.30) and after COVID-19 outbreak (2020.1.11~2021.12.31), and the collection channels were selected by Naver and Google. The collected data were text mining, and word frequency, TF-IDF, word cloud, network analysis, and emotional analysis were conducted. As a result of the analysis, first, hotels, weddings, and glades were commonly extracted as social issues related to metaverse before and after COVID-19, and keywords such as robots and launches were derived, so the frequency of keywords related to hotels and weddings was high. Second, the association of the pre-COVID-19 metaverse keywords was platform-oriented, content-oriented, economic-oriented, and online promotion-oriented, and post-COVID-19 clusters were event-oriented, ontact sales-oriented, stock-oriented, and new businesses. Third, positive keywords such as likes, interest, and joy before COVID-19 were high, and positive keywords such as likes, joy, and interest after COVID-19. In conclusion, through this study, it was found that metaverse has firmly established itself as a new platform business model that can be used in various fields such as tourism, travel, festivals, and education using smart technology and metaverse.

• Fashion & Textile Research Journal
• /
• v.25 no.5
• /
• pp.549-559
• /
• 2023

Along with the transition to the fourth industrial revolution, the possibility of metaverse-based innovation in the fashion field has been confirmed, and various applications are being sought. Therefore, this study performs meaning structure analysis and discusses the prospects of meta fashion using big data. From 2020 to 2022, data including the keyword "metaverse + fashion design" were collected from portal sites (Naver, Daum, and Google), and the results of keyword frequency, N-gram, and TF-IDF analyses were derived using text mining. Furthermore, network visualization and CONCOR analysis were performed using Ucinet 6 to understand the interconnected structure between keywords and their essential meanings. The results were as follows: The main keywords appeared in the following order: fashion, metaverse, design, 3D, platform, apparel, and virtual. In the N-gram analysis, the density between fashion and metaverse words was high, and in the TF-IDF analysis results, the importance of content- and technology-related words such as 3D, apparel, platform, NFT, education, AI, avatar, MCM, and meta-fashion was confirmed. Through network visualization and CONCOR analysis using Ucinet 6, three cluster results were derived from the top emerging words: "metaverse fashion design and industry," "metaverse fashion design and education," and "metaverse fashion design platform." CONCOR analysis was also used to derive differentiated analysis results for middle and lower words. The results of this study provide useful information to strengthen competitiveness in the field of metaverse fashion design.

• Fashion & Textile Research Journal
• /
• v.24 no.5
• /
• pp.545-556
• /
• 2022

To overcome the pandemic, a new strategy for innovation is in demand throughout the value chains of the fashion industry that emphasize the importance of fashion technology. Accordingly, as various viewpoints and fields of debate are unfolding to consider the direction of change led by fashion technology, it is necessary to make an active value judgment precedent by understanding the differences between various opinions. This study aims to derive keywords from fashion technology used during the pandemic, to infer the characteristics of each type of perspective and to understand their characteristics. For the research, this study combines text mining analysis and content analysis. Text mining analysis is used to find statistical patterns by collecting keywords from big data from online media, and content analysis is used to interpret the data qualitatively. After analyzing the results of this study, the following observations are made. First, the perspective of positive acceptance seeks to maximize the perception and sensory action of fashion through technology; this amplifies experience, an opportunity for innovation and efficiency. Second, critical vigilance highlights the side effects of radical changes in fashion technology, characterized by concerns about capital-centered polarization, threats to human rights, and infringement of creative thinking. Lastly, the perspective of gradual adoption is the gradual convergence of technologies, characterized by the pursuit of an appropriate balance.

• Fashion & Textile Research Journal
• /
• v.22 no.5
• /
• pp.650-659
• /
• 2020

The present study provides reference data required for the design of clothing for the elderly by analyzing the body surface area during fitness motion based on 3D scan data of Korean elderly women. This study was conducted with the procedures of (1) survey of motions and main muscles for fitness, (2) acquisition of 3D scan data, and (3) analysis of rate of change for body surface area during fitness motion. Acquisition of 3D body scan data was obtained from seven elderly females (age: 64-77). We selected 66 anatomical landmarks (40 upper body and 22 lower body) by referring to previous studies. Body surface was segmented by connecting the landmarks marked on the 3D scan data acquired. Analysis of body surface area was conducted in terms of the change rate of surface area in 9 postures of elbow 0°, 90° and 180° for flexion, shoulder 90°, 180° for flexion, shoulder 0°, 180° for abduction, hip 90° for flexion, and knee 90° for flexion compared to the those in the standing posture. The amount of changes in body surface area were 12%-62% in the upper body, 15%-77% in the arm, and 10%-51% in the lower body. A future study on the rate of change of body surface length is needed; in addition, a study on how to apply the results of body surface area and body surface length analysis to clothing pattern design is also necessary.