• Journal of Digital Convergence
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• v.14 no.11
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• pp.297-304
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• 2016

The aim of the study is to combine software reuse with agile methods through reuse in the early stage of agile development. Although agile methods and software reuse have different practices and principles, these methods have common goals, such as reducing development time and costs and improving productivity. Both approaches are expected to serve as viable solutions to the demand for fast development or embracing requirement changes in the rapidly changing environments. In the present paper, we identify economical agile reuse and its type and study a reuse technique for input queue in Kanban board at the early stage of hybrid agile methods. Based on our results, we can integrate software reuse with agile methods by backlog factoring for input queue item in the hybrid Scrum and Kanban method. The proposed technique can be effectively applied to e-class applications and can reuse the input queue items, showing the combination of the two approaches. With this study, we intend to contribute to reuse in the early stage of agile development. In the future, we plan to develop a software tool for economical agile reuse.

• Fashion & Textile Research Journal
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• v.17 no.2
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• pp.247-257
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• 2015

This study conducted a questionnaire survey on the real condition of clothing with focus on related to general motorcycle wear and motorcycle jacket targeting a quick service carrier affiliated with a quick service business in Seoul. In addition, this study is aimed at providing basic data on developing the motorcycle jacket, whose motional flexibility, safety and functionality are excellent, exclusively for a quick service carrier by grasping inconveniences and problems and deducting improvements on the basis of the questionnaire survey. This study, on the basis of the questionnaire survey results, grasped the general part related to quick service and motorcycle wear, such as their general matters, whether they were having on the motorcycle wear in the middle of doing business, whether it's necessary to wear the motorcycle wear, where they had a driving accident, and kinds of external injuries, etc. From the gathered results of analysis of the collected questionnaires, the item which got the lowest satisfaction was the inconvenience from the chafed front neck when driving. Besides, the results showed carriers' complaints like the elbow part felt tight, discomfort in the horizontal movement of the shoulders or back, and wind admission in between zippers. In addition, the respondents showed complaints in the item about hygroscopic property and air permeability at the armpits and back part, and 5 items about material flexibility, wind shielding property, living water repellency, weighty sensation, and night visibility were found to be low in respondents' satisfaction.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.95-104
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• 2019

Recently, software education has been emphasized as a key element of the fourth industrial revolution. Many universities are strengthening the software education for all students according to the needs of the times. The use of online content is an effective way to introduce SW education for all students. However, the provision of uniform online contents has limitations in that it does not consider individual characteristics(major, sw interest, comprehension, interests, etc.) of students. In this study, we propose a recommendation method that utilizes the directional similarity between contents in the boolean view history data environment. We propose a new item-based recommendation formula that uses the confidence value of association rule analysis as the similarity level and apply it to the data of domestic paid contents site. Experimental results show that the recommendation accuracy is improved than when using the traditional collaborative recommendation using cosine or jaccard for similarity measurements.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.201-206
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• 2019

While many users searched for insurance information online, there were not many cases of contents recommendation researches on insurance companies' websites. Therefore, this study proposed a page recommendation system with high possibility of preference to users by utilizing page visit history of insurance companies' websites. Data was collected by using client-side storage that occurs when using a web browser. Collaborative filtering was applied to research as a recommendation technique. As a result of experiment, we showed good performance in item-based collaborative (IBCF) based on Jaccard index using binary data which means visit or not. In the future, it will be possible to implement a content recommendation system that matches the marketing strategy when used in a company by studying recommendation technology that weights items.

• Archives of design research
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• v.17 no.2
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• pp.363-372
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• 2004

In the new millenium of information and digital age, the vogue cycle has been gelling shorter and shorter and the individualistic and high quality preference of contemporary consumers drive the small quantity production by order. The traditional screen printing system can not hold the competitive edge anymore. In order to actively meet the demand of the fast evolving market, compete with other nations, and produce high value-added products, we need the new production system to meet the individual needs promptly. Mass production using the traditional screen printing system has the economic advantage of the production speed and cost. The digital textile printing system digitalizes the total process from the design to the printing and omits the separation and engraving. It is more suitable to produce the multiple item-small quantity and add more values to its products. It has also the advantage of less pollution problem.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.55-64
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• 2009

In this paper, we design and implement verification and interface application for interactive data broadcasting middleware. This application implements ACAP and OCAP verification item according to their types (format, protocol. resource, presentation). Therefore, using this application, we can verify whether digital settop-boxes used in digital terrestrial television and digital cable television conforms to the ACAP and OCAP standards. In this paper, we evaluate our proposed application using TVPLUSiTM verifier which can verify interactive TV application in real broadcasting environment. Through performance evaluation, we show that the DTB-H650F set-top-box supports OCAP and ACAP standard 80% and 95%, respectively.

• The Journal of the Korea Contents Association
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• v.8 no.3
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• pp.1-7
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• 2008

Due to the development of ubiquitous computing, a wide variety of information is being produced and distributed rapidly in digital form. In this excess of information, it is not easy for users to search and find their desired information in short time. In this paper, we propose the personalized item recommendation using the image based filtering. This research uses the image based filtering which is extracting the feature from the image data that a user is interested in, in order to improve the superficial problem of content analysis. We evaluate the performance of the proposed method and it is compared with the performance of previous studies of the content based filtering and the collaborative filtering in the MovieLens dataset. And the results have shown that the proposed method significantly outperforms the previous methods.

• 한국디지털정책학회:학술대회논문집
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• 2006.06a
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• pp.319-353
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• 2006

The purpose of this study is to generate a proper regulation improvement direction of the public IT project contract law through the current four contract methods and three methods of the awarding party of a contract method. The research method for this paper is derived from the written materials of the present public IT project contract law. Two problems have been processed in order to produce the results: the current contract methods and the awarding party of a contract method. The current contract methods consist of a competition contract, a private contract, and a supply methodology contract. The methods of the awarding party of a contract display a qualified evaluation regulation, the 2nd step competition bid, a standard cost separation tender, and a contract by a negotiation. The results exhibit that the general competition contract consists of four improvement items. The contract by a negotiation contains five improvement items. The group private contract has one improvement item. And the private contract includes one improvement item. These results implicate that the current public IT project contract law demands better improvement work for the ubiquitous Korea.

• 한국디지털정책학회:학술대회논문집
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• 2005.11a
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• pp.231-242
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• 2005

The purpose of this study is to generate a proper regulation improvement direction of the public IT project contract law through the current four contract methods and three methods of the awarding party of a contract method. The research method for this paper is derived from the written materials of the present public IT project contract law. Two problems have been processed in order to produce the results: the current contract methods and the awarding party of a contract method. The current contract methods consist of a competition contract, a private contract, and a supply methodology contract. The methods of the awarding party of a contract display a qualified evaluation regulation, the 2nd step competition bid, a standard cost separation tender, and a contract by a negotiation. The results exhibit that the general competition contract consists of four improvement items. The contract by a negotiation contains five improvement items. The group private contract has one improvement item. And the private contract includes one improvement item. These results implicate that the current public IT project contract law demands better improvement work for the ubiquitous Korea.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.33-39
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• 2020

The paper is to build recommendation systems leveraging Deep Learning and Big Data platform, Spark to predict item ratings of the Amazon e-commerce site. Recommendation system in e-commerce has become extremely popular in recent years and it is very important for both customers and sellers in daily life. It means providing the users with products and services they are interested in. Therecommendation systems need users' previous shopping activities and digital footprints to make best recommendation purpose for next item shopping. We developed the recommendation models in Amazon AWS Cloud services to predict the users' ratings for the items with the massive data set of Amazon customer reviews. We also present Big Data architecture to afford the large scale data set for storing and computation. And, we adopted deep learning for machine learning community as it is known that it has higher accuracy for the massive data set. In the end, a comparative conclusion in terms of the accuracy as well as the performance is illustrated with the Deep Learning architecture with Spark ML and the traditional Big Data architecture, Spark ML alone.