• Journal of Fashion Business
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• v.23 no.1
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• pp.49-63
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• 2019

The purpose of this study is to examine the characteristics of modular design observed in Korean traditional clothing. Modular design, which is one of the noticeable characteristics of modern fashion design emerged in the 20th century. This study analyzed the Korean traditional culture to investigate the characteristics that show similarities to the modular system in design. A traditional Korean house is composed of small structures called 'chae'. A traditional Korean building is composed of a basic unit space called 'kan', and the rooms are divided and recombined. Korean traditional interior design shows furniture, bedding and art works that could be used, folded then stored. Korean cuisine is served in combination with small dishes. Korean letters are combined in square shaped form to make writing and printing easy. Korean traditional clothing has a way of washing where clothing are disassembled, washed and then re-stitched. The pattern pieces are made to be rectangular shaped so that the fabric pieces can be kept in shape during washing. The rectangular shaped pattern pieces can be replaced and reused after washing. Tops and bottoms could be interchanged for color-coordination, because the shapes of the clothing were standardized. These features exhibit modular system in Korean traditional clothing design. Modular system design has common characteristics which have basic modules, pursue practical purpose, have interchangeability adapted to circumstances, and could be disassembled and re-combined. Korean traditional clothing illustrates different ways of practicing modular system, but has some common features to contemporary modular fashion design.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.101-107
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• 2023

The purpose of this study is to research and develop the concepts and functions of the Metabus dog fashion show. Currently, as the pet-related industry grows rapidly, the pet fashion industry is also naturally growing. However, unlike the fast-growing fashion industry, it was not enough to meet the needs of dog owners. Therefore, this study attempted to develop a metaverse dog fashion show by supplementing the problems that arise when purchasing existing pet clothes through metaverse. As a research method, first, a survey was conducted on the rise in the actual pet-related industry and the social trends of metaverse and virtual fashion shows. Second, the existing dog clothing purchase characteristics were examined through user demand analysis, and user needs were derived. Third, the appropriate form of content was established, and a new content consumption environment called metaverse was analyzed and derived. Finally, functions were derived and developed to give users satisfaction. In the future, it is necessary to study a clear payment system in connection with the actual dog clothing business based on this.

• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.100-107
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• 2008

The aim of this paper is to design an intelligent character manipulation system suitable for the wireless broadband network environment named as Wibro and for the recent social networking service (SNS). The main feature of our proposed system is an automatic synthesis of a character utilizing the meta data which is attached to each component stored in a character database. It is the second advantageous feature that a user can make or modify his or her own character by modifying the component animation clip of its character. Once the character database is created, it can be represented and utilized in several ways by utilizing the meta data which is related to personal properties including emotion, life style, favorite things, and so on. The system can be evolved to a more powerful one by adopting the more user-related information and the more intelligent synthesis module.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.3
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• pp.55-64
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• 1997

In this paper, a fuzzy set based decision support system is designed for the color planning, that uses the linguistic image words of the space to be colored and progressively recommend the harmoneous colors for each objects in the space. The linguistic image words denotes various emotional effects of the colored space represented as the adjectives like 'romantic', 'beautiful', and so on. The search for object color should not destroy the overall image of the colored space and should be harmoneous with the previously determined object colors. The developed color planning system is composed of five subsystems; two dimentional graphic tools to draw the color space, the input system to receive the linguistic image words, the system to determine and recommend the main colcrs, the system to determine the harmonious colors and the system to adjust the determined wlor objects. We expect that the system can help designers and the persons who are not good at color design, and it can be applied to various color design such as interior, fashions, and product design.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.375-381
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• 2019

Recently, the recommendation system has attracted the attention of users as customized recommendation services have been provided focusing on fashion, video and music. But these services are difficult to provide users with proper service according to many different contexts because they do not use contextual information emerging in real time. When applied contextual information expands dimensions, it also increases data sparsity and makes it impossible to recommend proper music for users. Trying to solve these problems, our study proposed a music recommendation system to recommend proper music in real time by applying association rules and using relationships and rules about the current location and time information of users. The accuracy of the recommendation system was measured according to location and time information through 5-fold cross validation. As a result, it was found that the accuracy of the recommendation system was improved as contextual information accumulated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.313-315
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• 2019

Although Korea's fashion market has negative growth, it has been growing again since 2018. This phenomenon means that people are becoming more interested in fashion. As interest in fashion grows, people visit various community sites for reference to find a suitable coordination for themselves. Most community sites, however, are manually categorizing each garment. Not only do these tasks take a lot of time, but they also make it difficult to search for multiple clothing at the same time. In other words, I can't choose what I want at the same time, and if I choose what I want, I have to look at what the model is wearing and refer to it. The problem with this may not help because the coordination in which the model provided is worn is more likely to be the one that the user does not want. In this paper, when the image is uploaded to improve the problem, the clothing is analyzed with AI analysis model and automatically classified and stored. Therefore, not only can you search for one clothes in the existing way, but you can also search for multiple clothes at the same time. The service is expected to allow more people to easily find and refer to the code for themselves.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.112-123
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• 2005

The latest E-commerce sites provide personalized services to maximize user satisfaction for Internet user The collaborative filtering is an algorithm for personalized item real-time recommendation. Various supplementary methods are provided for improving the accuracy of prediction and performance. It is important to consider these two things simultaneously to implement a useful recommendation system. However, established studies on collaborative filtering technique deal only with the matter of accuracy improvement and overlook the matter of performance. This study considers representative attribute-neighborhood, recommendation textile set, and similarity grouping that are expected to improve performance to the recommendation agent system. Ultimately, this paper suggests empirical applications to verify the adequacy and the validity on this system with the development of Fashion Design Recommendation Agent System (FDRAS ).

• Journal of the Korean Society of Costume
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• v.64 no.7
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• pp.156-171
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• 2014

This study attempted to comprehend the usage of the modular system in fields through literature review and objective research, as well as analysis of its expression characteristics in fashion. It tried to provide inspiring visual data for the fashion design of the modular system. After analyzing architecture and product-related books, Internet data and advanced research, the four expression characteristics of the modular system were obtained. Firstly, the formative expression characteristics of the modular system in fashion were simplicity, extensibility, variability and diversity. Secondly, of the formative expression characteristics expressed in modern fashion, simplicity (30%) was the highest, followed by extensibility (27%), diversity (22%) and variability (21%). Thirdly, simple silhouette and structure were used to express simplicity, usually simple geometric figures. In contrast, extensibility was expressed through the expansion and exaggeration of the area, length and volume of the clothes. In terms of variability, the typical characteristics of modules were reflected. For diversity, heterogeneous materials were used, and informality was expressed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.66-78
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• 2012

This paper proposes a computation model of the quantity supplied to optimize inventory costs for the fast fashion. The model is based on a forecasting, a store and production capacity, an assortment planning and quick response model for fast fashion retailers, respectively. It is critical to develop a standardized business process and mathematical model to respond market trends and customer requirements in the fast fashion industry. Thus, we define a product supply model that consists of forecasting, assortment plan, store capacity plan based on the visual merchandising, and production capacity plan considering quick response of the fast fashion retailers. For the forecasting, the decomposition method and multiple regression model are applied. In order to optimize inventory costs. A heuristic algorithm for the quantity supplied is designed based on the assortment plan, store capacity plan and production capacity plan. It is shown that the heuristic algorithm produces a feasible solution which outperforms the average inventory cost of a global fast fashion company.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.859-862
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• 2015

Recent fashion business, is to promote and make a business strategy to realize a high added value to the first goal. Completion of the best men's clothing is only by making the pattern through a person's body size, making it as the best dressed. In this paper, we propose a system to automate production processes a significant impact on menswear production process, time and cost reduction in order to satisfy the needs of manufacturers and customers. Consequently, it is possible to provide optimal men's clothing by saving a time and expense of customers by, increases the customer's needs and men's clothing demand, it is possible to more easily perform to franchising custom men's clothing manufacturer.