• Journal of Korea Game Society
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• v.4 no.3
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• pp.49-54
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• 2004

The social interest for collaborative teaming and educational game has been increased. In this paper, we investigated the educational value of collaborative teaming and game. Based on this investigation, we propose an educational on-line game model for collaborative teaming. Although the proposed model is still conceptual design, it sufficiently shows that on-line RPG game can be a good collaborative teaming method for young children. We will perform a comparison study on the teaming achievement between the two methods: 1) the on-line game proposed in this paper, 2) the conventional educational method performed in normal school.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.60-70
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• 2009

This paper explores the ways in which collaborative working among multiple disciplines in building projects can be more effective and efficient. It focuses on the support that can be provided by the latest development in information and communication technologies. It also considers the growing interdependence between participants in the process and their changing roles as they harness the power of the new technologies in new collaborative arrangements. It is argued that collaborative working should be addressed holistically from the technological angle, the social angle, as well as the organisational angle, to ensure its successful implementation in the construction industry. A case study is given to illustrate the use of ICT in supporting value management studies. The key issues surrounding the emerging field of research - collaborative construction information management - and the potential benefits and challenges of its wide adoption are discussed at depth.

• International Journal of Ocean System Engineering
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• v.2 no.4
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• pp.214-222
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• 2012

The shipbuilding process is changing due to changes in the development environment and technological requirements for military ships. This would also hold true for a submarine, because its shipbuilding process includes complicated design and construction conditions. System improvement efforts for the design and construction of military ships have continued with the goal of overcoming these conditions. At present, the Korea Navy is developing a 3,000 ton-class Korean type submarine, and its design is progressing by the introduction of a full 3D-ship CAD system. Although the 3D modeling system was introduced for effective design realization through the introduction of collaborative design and active utilization of M&S (modeling and simulation), the introduction effects are not yet generally obvious, according to the characteristics of ship design. The present paper discusses the collaborative environment for developing a submarine to enhance this. This paper proposes the architecture and data structure of a system for realizing collaborative design and discusses a case system developed on the basis of this.

• Korean Journal of Computational Design and Engineering
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• v.20 no.3
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• pp.254-262
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• 2015

This study proposes an approach to Product Data Management (PDM) education for collaborative product data management, which can support collaborative product development process. This approach introduces social media and a PDM system into a framework for PDM education supported by consistent product development process and product data model. It has been applied to two PDM classes and the result shows that the social media in PDM education can support not only experiences of the collaborative product data management but also interactive and informal communications among instructors and participants using integrated social media with product data during courses.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.3
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• pp.79-86
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• 2006

Especially, MTO(Make-To-Order) companies take collaborative approaches with their partner companies to make low-price products and/or technologically low intensive products. The collaborative approach to manufacturing requires collaboration with partner companies for inventory review, production plan, and manufacturing to fulfill customer's orders. However, frequent changes of partnerships binder partner companies from sharing production information in effective ways since their information systems have different data architectures and platforms. Therefore, it is required flexible and standardized system integration approach fir effective information sharing. This research studies current status and problems of collaborative production system, proposes an architecture for collaborative production systems based on Web Services which is a standard information technology, and discusses expected effects and the vision of Web Services.

• Journal of information and communication convergence engineering
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• v.17 no.2
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• pp.135-141
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• 2019

Collaborative filtering algorithms often encounter data sparsity issues. To overcome this issue, auxiliary information of relevant items is analyzed and an item attribute matrix is derived. In this study, we combine the user-item attribute preference with the traditional similarity calculation method to develop an improved similarity calculation approach and use weights to control the importance of these two elements. A collaborative filtering algorithm based on user-item attribute preference is proposed. The experimental results show that the performance of the recommender system is the most optimal when the weight of traditional similarity is equal to that of user-item attribute preference similarity. Although the rating-matrix is sparse, better recommendation results can be obtained by adding a suitable proportion of user-item attribute preference similarity. Moreover, the mean absolute error of the proposed approach is less than that of two traditional collaborative filtering algorithms.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.616-631
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• 2019

With the rapid increase of information on the World Wide Web, finding useful information on the internet has become a major problem. The recommendation system helps users make decisions in complex data areas where the amount of data available is large. There are many methods that have been proposed in the recommender system. Collaborative filtering is a popular method widely used in the recommendation system. However, collaborative filtering methods still have some problems, namely cold-start problem. In this paper, we propose a movie recommendation system by using social network analysis and collaborative filtering to solve this problem associated with collaborative filtering methods. We applied personal propensity of users such as age, gender, and occupation to make relationship matrix between users, and the relationship matrix is applied to cluster user by using community detection based on edge betweenness centrality. Then the recommended system will suggest movies which were previously interested by users in the group to new users. We show shown that the proposed method is a very efficient method using mean absolute error.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.4
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• pp.373-381
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• 2017

A Collaborative Optimization (CO) methodology for ring-stiffened composite material pressure hull of underwater vehicle is proposed. Structural stability and material strength are both examined. Lamination parameters of laminated plates are introduced to improve the optimization efficiency. Approximation models are established based on the Ellipsoidal Basis Function (EBF) neural network to replace the finite element analysis in layout optimizers. On the basis of a two-level optimization, the simultaneous structure material collaborative optimization for the pressure vessel is implemented. The optimal configuration of metal liner and frames and composite material is obtained with the comprehensive consideration of structure and material performances. The weight of the composite pressure hull decreases by 30.3% after optimization and the validation is carried out. Collaborative optimization based on the lamination parameters can optimize the composite pressure hull effectively, as well as provide a solution for low efficiency and non-convergence of direct optimization with design variables.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.618-627
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• 2014

This paper aims to construct and analyze the domestic collaborative research network in industrial engineering. Using co-authorship information contained in the papers published in the two journals of the Korean Institute of Industrial Engineers, the collaborate research network at the institutional level is constructed. The core institutions in the network are identified by means of the centrality indexes of social network analysis. In addition, the five types of roles of the institutions in industry-university-institute cooperation are examined through brokerage analysis: coordinator, consultant, gatekeeper, representative, and liaisons. The findings are expected to be fruitfully utilized in formulation of R&D strategy of relevant organizations and technology policy making for promoting collaborative research in industrial engineering.