• 패션비즈니스
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• 제10권1호
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• pp.79-93
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• 2006

The purpose of this study is to analyze designs of exhibition clothing in terms of the use of Korean image, to review objectively contents about the use of traditional image, understand external elements of works, and give directions and basic data for future works. This study selected the total 250 works as the subject of this study among the collected data. This study classified and examined the use of Korean image found in exhibition clothing according to period, item, line and form, material, technique of expression and accessary between 1996 and 2004. The results of analysis are as follows (1) The most artworks were comprised in adaptation were Choson costume. (2) Most of them were clothing works for female. The item of chima were the most preferred in use. (3) The straight lines are used more frequently than curved lines. Forms of skirts were applied to those of silhouettes, H and A form were common. (4) In terms of materials, traditional materials such as silk, linen and cotton were commonly used. (5) Geometric patterns and plant pattern were found more often than others. (6) In terms of techniques of expression, patchwork was most frequent, quilting, embroidery and pleating were ranked second, third and fourth. (7) In accessaries and other item, gorom were most common and norigae were ranked second. (8) As Korean image has been expressed by fine parts of traditional costumes, the traditional living item, and local symbols, the range of works are becoming wider.

• 한국전자거래학회지
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• 제12권1호
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• pp.25-40
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• 2007

최근에 메모리 용량이 확대된 태그가 개발되면서 다양한 제품식별코드체계를 사용할 수 있게 되었다. 여기서는 새로 개발된 ISO태그 용량을 수용하면서 ISO의 식별표준을 수용하는 국가물품식별코드 체계를 새롭게 제안하였다. 우선, 물품관리에 필요한 식별코드체계로서 ISO/IEC 15459와 EPC 코드체계를 비교 분석한다. 그리고 ISO/IEC 18000-6C와 EPC 태그 메모리 구조를 비교 분석한다. 이러한 분석을 기반으로 기존에 개발된 RFID기반의 국가물품식별코드를 분석하며 표준화 관점에서 문제점을 제시한다. 그리고 지적된 문제점을 극복하기 위해 ISO/IEC 15459 표준에 적합한 새로운 식별코드체계를 제시한다. 마지막으로 태그 인코딩을 위하여 식별코드체계 관련 데이터를 설계한다.

• 패션비즈니스
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• 제24권2호
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• pp.1-16
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• 2020

Hijab as a symbol of women's oppression due to the opening and reform of Islamic State group, is becoming more diverse as younger generation begins to dress more freely than ever before, spreading the perception that it is a fashion item. In response, this research conducted a theoretical review about the history of hijab, various forms of hijab, and characteristics of hijab using relevant literature, media reports, and fashion media articles. As an empirical study, image-oriented photo data shared by Tehran Street Fashion from 2015 to November 2019 were analyzed separately by fashion majors into color, pattern, and hijab-making forms. According to the analysis, six different fashion images were categorized as romantic feminine, modern chic, natural elegant, classic formal, sporty casual and gorgeous ethnic. For Muslim women in the past, hijab was worn as a repressive and closed sense by the religious system. However, in modern times, it is a way to express one's style and ideas as a fashion item. It is also and a means to express one's thoughts and beliefs. Through aesthetic consideration of Hijab as a fashion item, it was found that it was a medium for freedom of expression and a medium for beauty and individuality.

• Management Science and Financial Engineering
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• 제11권3호
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• pp.137-153
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• 2005

Collaborative filtering-based recommendation systems make personalized recommendations based on users' ratings on products. Recommender systems must collect sufficient rating information from users to provide relevant recommendations because less user rating information results in poorer performance of recommender systems. To learn about new users, recommendation systems must first present users with an initial item list. In this study, we designed and analyzed seven selection strategies including the popularity, favorite, clustering, genre, and entropy methods. We investigated how these strategies performed using MovieLens, a public dataset. While the favorite and popularity methods tended to produce the highest average score and greatest average number of ratings, respectively, a hybrid of both favorite and popularity methods or a hybrid of demographic, favorite, and popularity methods also performed within acceptable ranges for both rating scores and numbers of ratings.

• 대한영양사협회학술지
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• 제16권1호
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• pp.1-12
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• 2010

This study was conducted to characterize well-being menus and to examine the service frequency and profitability of those served in the contract-managed workplace foodservice. In-depth interviews were conducted with six persons who were in charge of menu management in the headquarters of six different foodservice management companies during March, 2007. In addition, 122 set menus consisting of 777 menu items, which were on one month menus served during January to April, 2007, were collected from three workplace operations managed by three different foodservice management companies. As a result of the in-depth interviews, four categories of well-being menu items were extracted: 'medicinal functional menu item', 'environmentally-friendly menu item', 'natural food menu item', and 'harmful components-limiting menu item'. Accordingly, a well-being menu item was defined as 'a menu item with increased nutrition value or decreased health risk by changing food material or cooking method'. When the menu items (n=777) were analyzed by applying the definition and categories, approximately 14% of the items were identified as well-being menu items and most of them were either medicinal functional (65%) or natural food menu items (33%). Approximately 59% of the 122 set menus included at least one well-being menu item, and therefore they were named the well-being set menus. These well-being set menus, however, were not significantly different from the rest set menus in terms of profitability as measured by the contribution margin. The results of this study could be useful for foodservice management companies to develop and plan well-being menus targeting workplace foodservice operations.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 추계학술발표대회
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• pp.1295-1298
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• 2015

Many firms have used e-business systems to efficiently perform their business in an e-business management environment. Firms have applied their e-business capabilities to management activities in order to raise the performance of business execution in a global market environment. In this business environment, the analysis and management for the performance of a firm's e-business execution need to efficiently build and improve its e-business capability and competitiveness. This research presents an analysis tool for a firm e-business performance to efficiently manage and improve the e-business performance in this environment. The analysis items for a firm e-business performance are developed and extracted from the major components of a general firm performance in previous studies. The generated analysis items were verified by factor analysis and reliability analysis through a pilot test. The developed twelve items were extracted from twenty items by these analyses. This study developed a 12-item tool that can totally analyze a firm e-business performance in an e-business management environment. The developed tool consists of four analysis factors and twelve items.

• 지능정보연구
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• 제29권1호
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• pp.203-214
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• 2023

우리나라 관세청은 효과적인 원스톱(One-stop) 업무 처리가 가능한 전자통관 시스템으로 효율적으로 업무처리를 하고 있지만 기술의 발달과 비대면 서비스의 증가로 매년 수출입건수가 증가하고 있으며 그에 따른 업무량도 폭증하고 있는 실정으로 이에 따른 보다 효과적인 방법이 매우 필요하다. 수입과 수출은 모든 물품에 대한 분류 및 세율 적용을 위한 HS Code(Harmonized system code)가 필요하고 해당 HS Code를 분류하는 품목 분류는 전문지식과 경험이 필요한 업무 난이도가 높고 관세 통관절차에서 중요한 부분이다. 이에 본 연구는 품목 분류 의뢰서의 물품명, 물품상세설명, 물품 이미지 등의 다양한 유형의 데이터 정보를 활용하여 멀티모달 표현 학습(Multimodal representation learning) 기반으로 정보를 잘 반영할 수 있도록 딥러닝 모델을 학습 및 구축하여 HS Code를 분류 및 추천해 줌으로써 관세 업무 부담을 줄이고 신속한 품목 분류를 하여 통관절차에 도움을 줄 것으로 기대한다.

• 유통과학연구
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• 제13권10호
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• pp.93-99
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• 2015

Purpose - It has been argued that the regulations restricting entry and opening hours of General Super Markets and Super Super Markets have not been as effective as expected. In contrast, the win-win item scheme that appeared recently has the advantage that it could raise the effectiveness of the system in that win-win items are in principle resigned on the basis of bilateral agreements. This study analyzes the win-win item agreement made between Homeplus at Hap-jung and small traditional markets to examine the practical effectiveness of the win-win item scheme. While existing literature studying the regulatory effects have concentrated on the restrictions around store entry or opening hours of large retailers, it can be said that there have been few empirical studies on the effect of win-win items agreement with large retailers. Research design, data, and methodology - Homeplus at Hap-jung made a win-win items agreement with nearby small traditional market traders in 2013. In accordance with this voluntary agreement, Homeplus started by limiting its sales to 15 win-win items. The survey was conducted through one-on-one interviews, April 14 to May 2, 2014, by a professional public opinion research agency. The interviews were targeted at small business retailers in the nearby traditional market. We divided the traditional markets near Homeplus at Hap-jung where the win-win item agreement was achieved into two groups, win-win item agreement markets and non win-win item agreement markets, to compare the performance difference between the two groups. Results - To determine the change in sales of the 15 win-win items, we examined the performance difference between the two groups using two criteria (compared with similar items, and compared to sales volume a year ago). The results show that the individual sales of win-win items in the win-win item agreement markets are more likely to increase than in the non win-win item agreement markets. Total sales volume of individual stores in the agreement markets also showed a more significant increase compared to a year ago than those in non win-win item agreement markets. Conclusions - Contrary to the existing retail regulations that have one-sided and uniform characteristics, it can be pointed out that the win-win item scheme has the effect of increasing the success of the system itself because it is done on the basis of mutual agreement between General Super Markets and traditional markets. The empirical results of this study can be said to support this conjecture. For the successful settlement of a win-win items agreement, the following points should be reviewed. First, it requires a great effort from the selection process of win-win items in order to improve the effectiveness of the agreement. Second, the existing General Super Markets customers should be introduced to the traditional markets or small shops to increase the sales of win-win items. Therefore, voluntary effort is essentially required from the traditional markets to engage customers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

• International Journal of Advanced Culture Technology
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• 제8권1호
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• pp.165-172
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• 2020

Industrial Revolution means the improvement of productivity through technological innovation and has been a driving force of the whole change of economic system and social structure as the characteristic of technology as the tool of this productivity has changed. Since the first industrial revolution of the 18th century, productivity efficiency has been advanced through three industrial revolutions so far, and this fourth industrial revolution is expected to bring about another revolution of production. In this study, the demand for the introduction of artificial intelligence(AI) technology has been increasing in various business fields due to the rapid development of ICT technology, and the classification of HS(harmonized commodity description and coding system) items has been decided using artificial intelligence technology, which is the core of the fourth industrial revolution. And it is enough to construct HS classification system based on AI technology using inference and deep learning. Performing the HS item classification is not an easy task. Implementation of item classification system using artificial intelligence technology to analyze information of HS item classification which is performed manually by the current person more accurately and without any mistake, And the customs administrations, customs offices, and customs agencies, it is expected to be highly utilized in the innovation of trade practice and the customs administration innovation FTA origin agent.