• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.69-82
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• 2023

High-tech sensibility textile and fashion, in which consumers' emotions and various textile and fashion technologies are converged, is an important industrial group. It is important to develop the ability to apply in practice by gathering the creative by understanding other fields and exchanging ideas through interdisciplinary collaboration in the field of emotional engineering. Through interdisciplinary research and collaboration, talent must be nurtured of individuals who would lead the era of the 4^th Industrial Revolution with the ability to empathize with others as well as the creative convergence-type intellectual ability necessary for the rapidly changing society. To determine content-creation methods, basic research is conducted. Additionally, this study investigates on the current status and educational process of the emotional textile-fashion industry worldwide. To nurture talents in the textile and fashion sensibility science, the basic contents are created to manage the knowledge that delivers sensibility science and the ICT related to this field, as well as in the intensive, PB-style conceptual design based on sensibility. The process from derivation of consumer emotion analysis and product development can be experienced through smart kit practice. Moreover, various methods are developed to set up intellectual property rights generated while developing ICT convergence products as start-ups. The study also covers new knowledge rights to develop emotional textile fashion.

• Fashion & Textile Research Journal
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• v.3 no.2
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• pp.162-167
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• 2001

The dyeing powder drawn out from Cinnamoum cassia by water was concentrated. Using this powder, the silk fabrics were dyed and they measured with the K/S value, surface color, dye fastness and antimicrobial properties. The colorant of Cinnamoum cassia was proved flavonoids by FT-IR spectrum. The K/S values of silk by mordants concentration were much higher than those of high-concentration, the color yield of the silk fabrics were most efficient the premordanting method. The surface colors on the dyed fabric depended heavily upon mordants used or mordanting methods. For all cases, the value of the dyed fabric was generally dark except AI-mordant. The chroma produced clear for the unmordanting, the color difference was distinct when using the Fe-mordant. The color fastness was significantly improved when mordants were added. In the case of the light fastness, Cu-mordants improved more than 1-2 level. The Cu-mordant showed the greatest antimicrobial activity on the silk fabric.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.321-326
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• 2019

As AI technology is recently introduced into various fields, it is being applied to the fashion field. This paper proposes a system for recommending cody clothes suitable for a user's selected clothes. The proposed system consists of user app, cody recommendation module, and server interworking of each module and managing database data. Cody recommendation system classifies clothing images into 80 categories composed of feature combinations, selects multiple representative reference images for each category, and selects 3 full body cordy images for each representative reference image. Cody images of the representative reference image were determined by analyzing the user's preference using Google survey app. The proposed algorithm classifies categories the clothing image selected by the user into a category, recognizes the most similar image among the classification category reference images, and transmits the linked cody images to the user's app. The proposed system uses the ResNet-50 model to categorize the input image and measures similarity using ORB and HOG features to select a reference image in the category. We test the proposed algorithm in the Android app, and the result shows that the recommended system runs well.

• Fashion & Textile Research Journal
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• v.25 no.6
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• pp.739-744
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• 2023

With the popularization of 5G networks and the development of AI (artificial intelligence) technology, Metaverse, which creates production capacity by combining virtual space and reality, is attracting attention. In this study, we searched for makeup applications with more than 100 million downloads from October 11, 2020 to November 3, 2020 through the Google Play Store. As a result of the search, four applications were found: YouCam Makeup, YouCam Perfect, Beauty Plus, and Sweet Snap. Based on the functions provided by the four applications, we attempted to suggest makeup functions applicable to Zepeto's avatar. Functions for the eyes (eyeliner, eyelashes, mascara, eye shadow, eye shape, eyebrow shape, lenses, double eyelids), functions for the nose (nose shape), functions for the mouth (lipstick, lip shape, smile function) ) Functions corresponding to the facial contour (contour, skin foundation, blusher, shading, highlighter, face painting, theme makeup) and functions corresponding to the body (body adjustment) were proposed. This study is the first in the beauty field to propose a method of applying the functions of the Metaverse platform as the importance of digital platforms is highlighted, and is the first to propose a makeup function applied to the Metaverse so that it can be used as important basic data in the future.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.329-346
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• 2022

Recently, as the market for short form videos (Instagram, TikTok, YouTube) on social media has gradually increased, research using them is actively being conducted in the artificial intelligence field. A representative research field is Video to Shop, which detects fashion products in videos and searches for product images. In such a video-based artificial intelligence model, product features are extracted using convolution operations. However, due to the limitation of computational resources, extracting features using all the frames in the video is practically impossible. For this reason, existing studies have improved the model's performance by sampling only a part of the entire frame or developing a sampling method using the subject's characteristics. In the existing Video to Shop study, when sampling frames, some frames are randomly sampled or sampled at even intervals. However, this sampling method degrades the performance of the fashion product search model while sampling noise frames where the product does not exist. Therefore, this paper proposes a sampling method MF (Missing Fashion items on frame) sampler that removes noise frames and improves the performance of the search model. MF sampler has improved the problem of resource limitations by developing a keyframe mechanism. In addition, the performance of the search model is improved through noise frame removal using the noise detection model. As a result of the experiment, it was confirmed that the proposed method improves the model's performance and helps the model training to be effective.

• Journal of Fashion Business
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• v.19 no.1
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• pp.95-105
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• 2015

This study investigated the color culture in the Japanese Medieval Age. The Japanese Medieval Age included the Kamakura period (1180-1333) and Muromachi period (1336-1573), and the leading group transitioned from the Kuge families to the Buke families. The taboos about colors from ancient times became nominal, and forbidden colors, such as purple, celadon, and red, became the colors of the samurai, leading to beautiful soldier gears that were unparalleled in history. In the Kamakura period, colors that conveyed a strong impression were created and preferred with the combination of a samurai's reasonable spirit and zen thoughts. The period was also called "the era of hari", and cross dyeing based on basic colors such as suou (red), ai (blue), and kuchinasi (yellow) was popular. In both the Kamakura and Muromachi periods, conspicuous and strong colors were sought for costumes, and embroidery was used with gold leaf, silver leaf, gold threads, silver threads, and background color. The colors of costume preferred by Buke men in the period included green, blue, and brown. In the characteristics of the kosode, the sugan and hitadare were used for men's formal dress, while kosode was used for the grooming of the working class. In these periods, additionally, the working class began to be socially engaged in actively wearing the one-layer kosode, which became popular, and the characteristics of the Japanese Medieval Age, during which functionality and practicality was valued, were also reflected in the dressing.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.712-714
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• 2022

프로젝트 테마는 'CNN 딥러닝 모델을 기반으로 한 AI 가상 옷장'이다. 딥러닝 기술을 웹페이지에 적용시켜 사용자의 옷장 속에 있는 옷들을 자동으로 저장해서 관리해준다. 의류 이미지를 수집하고 딥러닝 모델을 통해 이미지를 학습시키고 분류하여 저장함으로써 사람들이 옷을 쉽게 찾을 수 있는 방법을 고안한다.

• Journal of Korean Home Economics Education Association
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• v.34 no.4
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• pp.93-111
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• 2022

This study started with the question of 'What innovative task should elementary and secondary school clothing life education perform in accordance with the changes in the future educational environment?' It is time to prepare for a major shift in the educational paradigm that improves the quality of life for all everyone, based on social innovations such as the 4th industrial revolution and the transition to the post-corona era. This study examined the literature for the characteristics of changes in the future educational environment from an educational perspective, and examined the curriculum focusing on the clothing life with the porpose of presenting the direction for the clothing life education. In order to carry out this study, various literature including previous studies related to clothing life education and the national curriculum from the first curriculum to the 2015 revision were analyzed. In conclusion, the direction of the clothing life education curriculum according to the changes in the future educational environment is proposed as follows: First, nurturing convergence education experts that can combine human emotion, environment, and clothing life culture to artificial intelligence(AI); second, developing a clothing life education curriculum that links software competency and practical problem-solving competency; and lastly, implementing fashion maker education using artificial intelligence(AI) and value-oriented clothing life education. In the future, it is expected that the direction of teaching/learning methods and evaluation in clothing life education curriculum is proposed, and that this educational discussion process will help establish the identity of clothing life education in school education.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.497-502
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• 2022

Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.6
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• pp.969-981
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• 2010

This study explains the consumer acceptance of smart clothing using the extended Technology Acceptance Model (TAM); in addition, it compares the difference in the path hypotheses of the perceived group and nonperceived group from the aspect of the extended TAM. A total of 815 copies of questionnaire were collected from a web-based survey in March 2009. Structural equation modeling was used to examine the entire pattern of intercorrelations among the constructs and to test related propositions using an AMOS 5.0 package. The fitness of the extended TAM explains the process of the adaptation of smart clothing. Technology Innovation (TI) and Clothing Involvement (CI) were confirmed as antecedent variables to affect TAM. In the perceived group, Technology Innovation (TI) and Clothing Involvement (CI) showed significant impacts on the Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) while Technology Innovation (TI) did not influence the Perceived Ease of Use (PEOU) in the non-perceived group. Perceived Ease of Use (PEOU) influenced the Perceived Usefulness (PU) and indirectly influenced Attitude (A) through the Perceived Usefulness (PU) in both groups. In addition, Perceived Usefulness (PU) did not influence Acceptance Intention (AI) but indirectly affected Acceptance Intention (AI) through Attitude (A). Therefore, Attitude (A) was found to be an important parameter in the adaptation of smart clothing in both groups. This finding implies that consumers first perceive the usefulness of smart clothing, then take favorable attitudes towards the smart clothing, and finally have the intention to adopt it. Strategies for publishing and informing consumers of the functions of smart clothing and usefulness in life are necessary; in addition, understanding what useful values they expect from the clothing is also crucial.