• Journal of the Korea Society for Simulation
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• v.22 no.4
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• pp.57-66
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• 2013

The needs for reusable 3D visualization tool has been being raised in various industries. Especially in the defense modeling and simulation (M&S) domain, there are abundant researches about reusable and interoperable visualization system, since it has a critical role to the efficient decision making by offering diverse validation and analyzing processes. To facilitate the effectiveness, states-of-the-arts M&S systems are applying VR (Virtual Reality) or AR (Augmented Reality) technologies. To reduce the work burden authors design a collaborative visualization environment based on a commercial game engine Unity3D. We define the requirements of the warfare simulation by analyzing pros and cons of existing tools and engines such as SIMDIS or Vega, and apply functionalities of the commercial game engine to satisfy the requirements. A prototype has been implemented as the collaborative visualization environment of iCAVE at KAIST, which is a facility for immersive virtual environment. The facility is intraoperative with smart devices.

• Information Systems Review
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• v.9 no.1
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• pp.85-103
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• 2007

The purpose of this study is to evaluate the performance of collaborative filtering recommender algorithms for better prediction accuracy of the customer's preference. The accuracy of customer's preference prediction is compared through the MAE of neighborhood based collaborative filtering algorithm and correspondence mean algorithm. It is analyzed by using MovieLens 1 Million dataset in order to experiment with the prediction accuracy of the algorithms. For similarity, weight used in both algorithms, commonly, Pearson's correlation coefficient and vector similarity which are used generally were utilized, and as a result of analysis, we show that the accuracy of the customer's preference prediction of correspondence mean algorithm is superior. Pearson's correlation coefficient and vector similarity used in two algorithms are calculated using the preference rating of two customers' co-rated movies, and it shows that similarity weight is overestimated, where the number of co-rated movies is small. Therefore, it is intended to increase the accuracy of customer's preference prediction through expanding the number of the existing co-rated movies.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.83-95
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• 2013

Supply chain management for engineering project focuses on planning acquisitions, identifying and choosing the right suppliers and subcontractors, planning and negotiating appropriate contracts, and administering the collaboration with the suppliers and subcontractors. This paper aims to identify the determinants of SCM performance of the suppliers and subcontractors participating in the project-based supply chain. This study proposes the absorptive capacity, fairness of suppliers' evaluation, the quality of collaboration and incentives as major research variables, and collected the survey responses from the suppliers and subcontractors having experiences with major engineering projects. The statistical results indicate that the incentives, absorptive capacity and the quality of collaboration influence SCM performance of suppliers, and that the fairness of suppliers' evaluation has some impact on the incentives and the absorptive capacity. But on the contrary to our expectation, the incentives have no significant impact on the level of absorptive capacity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.169-176
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• 2014

According to explosion of smart-devices, demands on N-screen services based on cooperation of multiple screens are rapidly increasing. These N-screen services can provide new user-experience (UX) to users. That is, it can provide technical advances to users. On the other hand, it causes new security problems. In this paper, we analyze conventional web-security attacks, and we propose and analyze new security requirements for migration, combination, and separation of web-contents based on N-screen service scenarios. Also, we develop N-screen cooperation service framework in order to ensure user security.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.513-516
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• 2009

본 논문에서는 사례연구를 통하여 RC구조 BIM에서의 물량정보 획득의 효율성을 분석하고 이를 기반으로 BIM 프로세스 환경에서의 철근 및 콘크리트 물량산출을 위한 데이터베이스를 구축하여 현장 시공단계에서의 공정 및 물량관리의 협업단계를 가능하도록 하는 철근 Sorting 시스템에 대한 연구를 목적으로 한다. 기존의 건설, 건축분야에서의 정보는 기호적 언어와 2차원 기반의 도면 정보체계를 통해 표현되었지만, BIM 기술을 통해 건물의 실제 형상과 정보를 가지는 3차원 기반의 정보체계로의 변화와 함께 컴퓨터 데이터베이스 내에서 프로젝트에 포함된 모든 정보를 저장하고, 다양한 형태로 필요에 따라 정보를 표현할 수 있게 변화하고 있다. 견적 및 시공을 위한 RC구조설계단계에서의 배근 모델은 협업을 위한 객체 정보의 획득 및 추출이 중요하지만 현재 상용되고 있는 BIM도구에서는 현재까지 미흡한 체계를 이루고 있다. 본 논문에서는 구조설계를 기반으로 배근된 BIM 구조모델 사례를 통하여 기존 BIM도구에서의 물량 정보획득 효율성 분석을 기반으로 객체들의 데이터베이스 구축을 통한 철근 Sorting 시스템 구축 연구를 통하여 협업단계에서의 체계적 물량정보 관리를 가능하도록 하였다.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.2
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• pp.156-173
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• 2004

Business process should support the execution of collaboration process with agility and flexibility through the integration of enterprise inner or outer applications and human resources from the collaborative workflow view. Although the dependency of enterprise activities to the automated system has been increasing, human role is as important as ever. In the workflow modelling this human role is emphasized and the structure to control human error by analysing decision-making itself is needed. Also, through the collaboration of activities agile and effective communication should be constructed, eventually by the combination and coordination of activities to the aimed process the product quality should be improved. This paper classifies human errors can be occurred in collaborative workflow by applying GEMS(Generic Error Modelling System) to control them, and suggests human error control method through hybrid based modelling as well. On this base collaborative workflow modeling tool is designed and implemented. Using this modelling methodology it is possible to workflow modeling could be supported considering human characteristics has a tendency of human error to be controlled.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.389-395
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• 2007

Collaborative filtering is a popular technique for information filtering to reduce information overload and widely used in application such as recommender system in the E-commerce domain. Collaborative filtering systems collect human ratings and provide Predictions based on the ratings of other people who share the same tastes. The quality of predictions depends on the number of items which are commonly rated by people. Therefore, it is difficult to apply pure collaborative filtering algorithm directly to dynamic collections where items are constantly added or removed. In this paper we suggest a method for managing dynamic collections. It creates taste space for items using a technique called Singular Vector Decomposition (SVD) and maintains clusters of core items on the space to estimate relevance of past and future items. To evaluate the proposed method, we divide database of user ratings into those of old and new items and analyze predicted ratings of the latter. And we experimentally show our method is efficiently applied to dynamic collections.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.211-221
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• 2016

The rapid trends toward outsourcing and collaboration have created complex multi-tier supply chains for construction and engineering industries. Working with suppliers and sub-suppliers requires continuous integration activities in order to maximize the performances of the entire supply chain. The purpose of this study is to identify the factors influencing the performances and long-term business relationship of second-tier suppliers in directed sourcing environment. This study proposes the asset specificity, trust, information-sharing and collaboration, as antecedents variables, and collected the survey responses from the second-tier suppliers in rebar manufacturing works. The statistical results indicate that the asset specificity, trust, information-sharing and collaboration have significant influences on the long-term business relationship of rebar manufacturing second-tier suppliers, but trust has no impact on the performances of second-tier suppliers at 5% significance level. Practical implications are also discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.699-708
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• 2017

The service industry, as a new growth engine, has become more important in response to changes in the global economy and the industrial environment. Developed countries have promoted the competitiveness of the service industry and have enhanced economic added value. Developing new services requires extensive resources. Therefore, cooperation and network building capabilities with customers, suppliers, and various knowledge creation agencies are critical sources of competitiveness. This study classified the Korean service industry by industrial type in order to enhance innovation competence.The Korean service industry lags behind that of developed countries, and this study analyzed the differences of innovation results according to collaboration partners by the classified industry. By adopting a method that applies industrial classification by Dialogic's innovation pattern, this study showed external cooperation results were different by industrial type. Analysis results revealed that companies cooperate with customers and competitors in many cases; however, product innovation was higher for companies that collaborated with private service companies. In the 'Innovation in services' industry, industry cooperation with universities showed organizational innovation achievements. In the 'Innovation through services' industry, cooperation with customers positively affected marketing innovation achievements. Consequently, the need to foster consulting firms and universities that can professionally collaborate with companies is implied in order to enhance the Korean service industry.

• The Journal of Society for e-Business Studies
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• v.17 no.2
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• pp.129-147
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• 2012

Collaborative filtering (CF), one of the most successful recommendation techniques, has been used in a number of different applications such as recommending web pages, movies, music, articles and products. One of the critical issues in CF is why recommendation performances are different depending on application domains. However, prior literatures have focused on only data characteristics to explain the origin of the difference. Scant attentions have been paid to provide systematic explanation on the issue. To fill this research gap, this study attempts to systematically explain why recommendation performances are different using structural indexes of social network. For this purpose, we developed hypotheses regarding the relationships between structural indexes of social network and recommendation performance of collaboration filtering, and empirically tested them. Results of this study showed that density and inconclusiveness positively affected recommendation performance while clustering coefficient negatively affected it. This study can be used as stepping stone for understanding collaborative filtering recommendation performance. Furthermore, it might be helpful for managers to decide whether they adopt recommendation systems.