• 한국IT서비스학회:학술대회논문집
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• 2008.05a
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• pp.403-408
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• 2008

중소기업의 ERP도입에 관련된 많은 요인들에 대한 연구들이 진행되어 왔다. 대부분의 연구들이 중소기업이 독립적으로 ERP를 도입하게 되는 경우를 다루고 있으나, 많은 중소기업들이 자금을 비롯한 다양한 이유로 독립적으로 ERP도입을 결정하지 못하고 있다. 따라서, 협력대기업이 공급사슬관리차원에서 공급사인 중소기업들의 ERP도입을 지원하고 있다. 협력대기업이 중소기업의 ERP 도입을 지원하는 과정에서 활용할 수 있는 방안과 과정상의 문제에 대해 국내 대기업의 지원사례와 ERP를 도입한 중소기업의 도입사례를 연구하여 중소기업 ERP도입에서의 협력대기업의 역할에 대한 탐색적인 연구를 수행하였다. 협력대기업의 지원방안으로는 도입자금지원, 도입벤더선정, 도입과정도움, 도입후 시스템 개선과정 도움, ERP활용교육 등을 활용하고 있다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.317-318
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• 2022

본 논문에서는 미국·영국의 사례를 통한 정책적 함의를 제시하는 데 그 목적이 있다. 미국의 경우 초기 대응자로서 민간 부문의 중심적인 역할, 공공과 비영리 그리고 민간 부문 조직들의 협력적 대응, 자원봉사자들의 적극적인 참여, 평소 민간 부문에 대한 훈련, 민간 기업의 기민성과 영국의 경우 위기관리를 위한 언론의 협조자 역할, 정부의 언론을 통한 위기관리의 중요성 인식 등은 우리에게 시사하는 바가 크다. 요컨대, 미국·영국의 경우 전 국가적 차원에서의 대테러활동을 위한 민·관 간의 협력적 운영이라는 사실과 더불어 우리나라 대테러 관계기관 실무자들의 민·관 협력 기능의 필요성에 대해 시민의식의 향상, 시민단체와 민간 기업의 사회적 공익 분야 강조, 언론의 역할 정립에 대한 인식이 높아지고 있는 시점에서 대테러시스템 운영을 위해 이들의 역할과 기능이 더욱 확충되는 방안을 모색해야 할 것이다.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.101-108
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• 2020

Recommender system is a must-have feature of e-commerce, since it provides customers with convenience in selecting products. Collaborative filtering is a widely-used and representative technique, where it gives recommendation lists of products preferred by other users or preferred by the current user in the past. Recently, researches on the recommendation system using deep learning artificial intelligence technologies are actively being conducted to achieve performance improvement. This study develops a collaborative filtering based recommender system using restricted Boltzmann machines of the deep learning technology by utilizing user ratings. Moreover, a learning parameter update algorithm is proposed for learning efficiency and performance. Performance evaluation of the proposed system is made through experimental analysis and comparison with conventional collaborative filtering methods. It is found that the proposed algorithm yields superior performance than the basic restricted Boltzmann machines.

• The Journal of Society for e-Business Studies
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• v.16 no.3
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• pp.129-143
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• 2011

In modern industrial society, the importance of inter enterprise collaboration is more emphasizing for the survival of companies and strengthening its competitiveness. The studies using IT systems effect on inter-enterprise collaboration are already taken several times. However, there is not much systematic research to evaluate the informatization level of B2B collaboration. In this paper, we examined the level of B2B collaboration and the use of IT systems for each business area in small and medium-sized collaborative enterprise which are classified into shipbuilding, automobile, and electronic industry. We verified that the level of collaboration between companies are significant to the level of IT use for each business area by regression analysis. The conclusion of this study is that the level of B2B collaboration and the use of IT systems for each business area are different.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.7-12
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• 2010

In this paper, we analyze and simulate the performance of a cooperative communication system adopting a maximum likelihood (ML) equalizer. In wireless communication systems, cooperative communication schemes employing several relays can be applied for extending the communication coverage. It is assumed that both relays and user terminals can move. Therefore, coverages of two or more relays can overlap each other. If wanted and interfering signals are transmitted through the same channel and there are one terminal in the overlapped region, its performance is degraded due to interference. Hence, we use a ML equalizer for rejecting the effect of interfering signal and enhancing the communication system performance. The cooperative system performance is evaluated in terms of bit error probability. From the simulation results, it is demonstrated that the ML receiver shows good interference cancellation performance although its complexity is high.

• Journal of Science and Technology Studies
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• v.13 no.2
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• pp.1-35
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• 2013

The aim of this article is to criticize the discourses and practices of the appropriate technology for international development cooperation in Korea which focus narrowly on the technologies and are oriented to the providers of technologies. To present an alternative, we will discuss the appropriate technology by the insights from 'socio-technical system' studies which underline not only technological side but also the social, institutional and user's side, and analyze the interactions between them. This research deals with several cases mainly regarding small scale's renewable energy from Laos, Thailand, Bangladesh, Mongolia and Nepal. We put out some suggestions to improve the discourse and practices of appropriate technology in field of international cooperation by Korea.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.732-737
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• 2008

As e-learning is recognized in new education form, Learning Management System that manage general activity of learning to maximize effect of education is being developed actively. Usually, Learning Management System includes course registration and learning as well as learner's learning recording and tracking, evaluation in online. But, most systems is lacking a tool that learners can collaborate with companion learners, and planning learning and set valuation basis as leading. In this paper, we can expect effective collaborative learning activities because can make debate and team project smooth by suggesting collaborative learning module that can drive voluntary participation such as group formation, learning plan, mutually estimation as leading to learner in Learning Management System of blended learning base that support online and offline environment both.

• 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 ).

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.189-196
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• 2010

Peer-to-Peer (P2P) has attracted attention as an alternative way to enable streaming videos on the Internet. Although P2P systems depend on bandwidth contribution from peers, peers are likely to refuse to contribute their bandwidth. In this paper, we proposed a P2P streaming system that encourages peers to contribute their upstream bandwidth by maintaining fairness among peers and providing different video quality between cooperative peers and selfish peers with a manageable way. Our proposed system determines if peers are cooperative or selfish by a rating mechanism based on their contributed upstream bandwidth, and offers a high quality video to cooperative peers as an incentive. Also we propose a tree reconstruction algorithm to make the system work effectively. Through simulation, we show that the tree reconstruction algorithm works effectively, and our incentive mechanism allocates more downstream bandwidth to cooperative peers and punished selfish peers with low quality video.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.149-155
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• 2022

The popularity of e-commerce systems on the Internet is increasing day by day, and the recommendation system, as a core function of these systems, greatly reduces the effort to search for desired products by recommending products that customers may prefer. The collaborative filtering technique is a recommendation algorithm that has been successfully implemented in many commercial systems, but despite its popularity and usefulness in academia, the memory-based implementation has inaccuracies in its reference neighbor. To solve this problem, this study proposes a new time-aware collaborative filtering technique that integrates and utilizes the neighbors of each item and each user, weighting the recent similarity more than the past similarity with them, and reflecting it in the recommendation list decision. Through the experimental evaluation, it was confirmed that the proposed method showed superior performance in terms of prediction accuracy than other existing methods.