• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.133-141
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• 2020

Up to date cosmetic OEM/ODM (original equipment manufacturing/original development manufacturing) industry receives attention as a future growth engine due to steady growth. However, because of limited research and development capability, many companies have employed commercial management platforms specialized for large-sized companies; thus, overall system effectiveness and efficiency is low. Especially, MRP (material requirement planning) system introduced originally in 1970s is employed to calculate the requirement of the parts. However, dynamic nature of production lead time usually results in incorrect requirements. In addition, its algorithm does not consider the capability of the production resources. Also, because the commercial MRP system calculates all subcomponent for fixed period, the more goods have subcomponent, the slower calculation is. Therefore, conventional MRP system cannot respond complicated situation in time. In this study, we will suggest a new method that can respond to complicated situations resulting from short lead time and urgent production order in Korean cosmetic market. In particular, a distributed MRP system is proposed, that consists of multi-functional and operational modules, based on the characteristic of the BOM (bill of material). The distributed MRP system divides components (i.e. products and parts) into several fields and decrease the problem size; thus, we can respond to dynamically changed data any time. Through this solution, we can order components quickly, adjust schedules and planned quantity, and manage stocks reasonably. In addition, a prototype of the distributed MRP system is presented in this paper, in which ERP (enterprise resource planning) sever data is associated with an excel spreadsheet via MSsql. System user interface is implemented by a VBA (visual basic for applications) tool. According to a case study, response rate for delivery and planning achievement rate were enhanced about 20%, and inventory turnover was also decreased. Consequently, the proposed system improves overall profit.

• Journal of the Korean Society of Costume
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• v.62 no.4
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• pp.58-68
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• 2012

Personal image concerns a person's talent, expertise, as well as the internal and external image. It is a core value that differentiates one individual from another. As personal branding via personal image management has become more important, there is a fast-growing number of online systems that provide self-test programs to analyze one's style and habits and also provide expert advice for not only styles but lifestyles as well. This study develops a systematic and objective personal image consulting system and offers basic information for the research of personal image making. For that purpose, the study attempts to examine the present state of global companies that use online image consulting programs and analyze their digital content. The results are as follows: 1) two domestic companies, Colorz and Atzine, and seven foreign companies, notably Covet and Boutique, were brisk in business; 2) two types of personal image-diagnosis programs - Visual search and Virtual matching - are now in operation; and 3) mobile applications exist as an evolved personal image-diagnosis program. With an increased interest in such programs, various companies at home and abroad are establishing systematic and scientific analysis systems, which are needed for personal image-making online. Under these circumstances, domestic companies are also urged to enhance levels of image-diagnosis content and actual commercialization and utilization, to develop programs that enable objectified, systematic personal image-making. To this end, the results of this study may serve as a helpful tool to consider future directions.

• Fashion & Textile Research Journal
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• v.15 no.2
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• pp.173-181
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• 2013

This research analyzed the expression trend about the slit which composes the open space by the visual concept and then introduced the imbedded aesthetic value in it. Based on it, this work aims at showing the evidence on the slit as a utilizing tool for various design applications and providing the basic materials in order to develop the creative design production in the fashion area in the future. Specifically, for the theoretical background in this research, the concept of slit and its chronological changes were reviewed through literature. For the empirical analysis on the slit, a total of 226 designs with its application were analyzed from collection pieces in the four major collections including Paris, Milan, New York, and London from 2006S/S to 2012S/S. As a result of analysis, types of slit appeared as a slash, opening, slit, or a mix of them. These were applied to many different items of clothing, and among which, one-piece or dress was adopted most for application. In regard to space form, perpendicularity was used most frequently. But other various forms like cross and geometrical pattern were also used as well as curve, oblique line and horizontality. As to the arrangement of slit, single type was most frequently used. However, in addition to it, other types were also applied, producing both the functionality and the decorative detail such as bilateral symmetry, free irregularity, and a combination of regular and repeated layout which makes an effect of single pattern. Aesthetic values imbedded in slit were revealed as functionality, sensuality, spatiality, and decorativeness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.510-518
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• 2020

With the promotion of digitalization in the construction industry, BIM has become an indispensable technology. On the other hand, it has not been actively utilized in practice because of the difficulty of BIM modeling. The reason is that 3D modeling is less productive not only because of the difficulty of learning BIM software but also the modeling work is done manually. Therefore, this study proposes a method and system that can improve the productivity of BIM-based modeling. For this reason, in the study, a slit caisson, which is a typical structure of a port, was selected as a development target, and various parameters were derived through interviews with experts so that it could be used in practice. This study presents a UI construction plan that considers user convenience for efficient management and operation of diverse and complex parameters. Based on this, this study used visual programming and Excel VBA to develop a BIM-based design automation system for slit caissons. The developed system can use many parameters to quickly develop slit caisson models suitable for various design conditions that can contribute to BIM-based modeling and productivity improvement.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.938-943
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• 2003

In this paper, we Propose a method using the Tikhonov-Miller process to improve the robustness of watermarking under various attacks. A visually recognizable pattern watermark is embedded in the LH2, HL2 and HH2 subband of wavelet transformed domain using threshold and besides watermark is embeded by utilizing HVS(Human Visual System) feature. The pattern watermark was interlaced after random Permutation for a security and an extraction rate. To demonstrate the improvement of robustness and similarity of the proposed method, we applied some basic algorithm of image processing such as scaling, filtering, cropping, histogram equalizing and lossy compression(JPEG, gif). As a result of experiment, the proposed method was able to embed robust watermark invisibility and extract with an excellent normalized correlation of watermark under various attacks.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.2212-2216
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• 2008

본 연구는 하도특성의 불규칙으로 인해 수위와 유량이 단일 관계가 형성되지 않은 경우와 유수의 흐름이 지속되어 GZF 측정이 어려운 경우에 구간분리와 GZF를 결정하는 곡선식 개발 방법론이라 할 수 있다. 첫번째 연구과제는 저수위 구간 수위-유량관계곡선식의 GZF 추정방법의 개선에 관한 연구이다. 다음과 같은 연구를 수행하기 위해서 GZF의 변화에 따라 곡선식의 신뢰도를 분석할 수 있는 프로그램을 개발하였다. 본 연구에서 개발한 프로그램은 사용자들이 쉽게 이용할 수 있는 엑셀 VBA(Visual Basic for Applications)로 작성되었으며, 입력자료 구축 모듈, 하도단면 입력 모듈, GZF 설정 모듈, GZF 평가 등의 4개 모듈로 구성되어 있다. 두 번째 연구과제는 구간분리 유무의 기준에 관한 연구로서 수위-유량관계곡선의 신뢰도에 직접적인 영향을 미친다. 본 연구에서는 일차적으로 단면의 특성이 상이한 4개의 수위관측소를 선정하여 수위-면적 곡선과 수위-면적변화량곡선을 생성하였으며 이로부터 단면변화와 구간분리의 특성을 분석하였다. 구간분리의 기준에 영향을 미치는 변수로는 단면특성인자, 유속, 하상경사, 수면경사, 단면통제, 하도통제 등을 들 수 있으며, 또한 다음과 같은 주요변수들이 서로 복합적으로 작용되기 때문에 일정한 기준을 제시하기란 어려운 부분이라 할 수 있다. 따라서 본 연구에서는 구간분리에 영향을 미치는 주요 변수 중에서도 가장 크게 영향을 주는 변수인 하도 단면의 특성 등을 중심으로 연구를 진행하였다. 먼저 단면의 특성이 서로 상이한 수위 관측소 단면을 선정하여 수위관측소별로 저수부에서 고수위 구간까지 10cm의 등간격으로 수위별 면적을 산정하여 구간분리의 가능성을 판단하였다. 구간분리의 유무에 관한 연구는 현재 진행 중에 있으며, 향후에는 1단면, 2단면, 3단면까지 파악하여 단면 특성이 구간분리에 미치는 영향 등을 파악할 계획에 있다. 또한 하도 단면의 다양성을 고려하여 단면형상이 상이한 여러 수위관측소 지점에서 구간분리의 기준을 연구할 계획이며, 단면의 특성을 파악한 후에는 유량, 유속, 하상경사, 하도통제 등을 고려할 계획이다.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.285-297
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• 2000

One of the research objectives in the area of multimedia human-computer interaction is the application of artificial intelligence and robotics technologies to the development of computer interfaces. This involves utilizing many forms of media, integrating speed input, natural language, graphics, hand pointing gestures, and other methods for interactive dialogues. Although current human-computer communication methods include computer keyboards, mice, and other traditional devices, the two basic ways by which people communicate with each other are voice and gesture. This paper reports on research focusing on the development of an intelligent multimedia interface system modeled based on the manner in which people communicate. This work explores the interaction between humans and computers based only on the processing of speech(Work uttered by the person) and processing of images(hand pointing gestures). The purpose of the interface is to control a pan/tilt camera to point it to a location specified by the user through utterance of words and pointing of the hand, The systems utilizes another stationary camera to capture images of the users hand and a microphone to capture the users words. Upon processing of the images and sounds, the systems responds by pointing the camera. Initially, the interface uses hand pointing to locate the general position which user is referring to and then the interface uses voice command provided by user to fine-the location, and change the zooming of the camera, if requested. The image of the location is captured by the pan/tilt camera and sent to a color TV monitor to be displayed. This type of system has applications in tele-conferencing and other rmote operations, where the system must respond to users command, in a manner similar to how the user would communicate with another person. The advantage of this approach is the elimination of the traditional input devices that the user must utilize in order to control a pan/tillt camera, replacing them with more "natural" means of interaction. A number of experiments were performed to evaluate the interface system with respect to its accuracy, efficiency, reliability, and limitation.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.82-93
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• 2019

Fashion cannot encourage co-consumption with other people as a personal item, but it can lead to new consumer needs if fashion sharing service can professionally replace the time and cost of purchasing and managing goods. The purpose of this study is to empirically investigate the factors influencing the acceptance of fashion-sharing services based on the integration theory of user acceptance and utilization (UTAUT), and to discuss the virtuous cycle and sustainability pursuit of resources through the activation of the sharing. In this study, the research model for the acceptance of fashion sharing applications is schematized, and the survey was conducted 300 women aged 20~49 years. The screens of 'Project Anne', a representative fashion sharing service in Korea, were provided as a visual data. Reliability analysis, correlation analysis, confirmatory factor analysis, structural equation analysis, and multiple group analysis were performed using SPSS 23.0 and AMOS 22.0 statistical package for statistical analysis. As a result, efficiency and social influence positively influenced behavioral intention to use, and age has found that efficiency and social influences modulate the intensity of behavioral intention to use. Therefore, for the consumer acceptance and activation of fashion sharing services, marketing activities emphasizing efficiency and strengthening social influence factors are essential. Also, it is necessary to maintain the existing target group, 30~40s, and also construct additional products and price services for the 20s. This study is of academic significance in presenting basic data for empirical research on consumer acceptance of fashion sharing, and suggests a study on the influence relationship among user experience components for real users in the future.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.