• Journal of KIBIM
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• v.10 no.2
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• pp.1-11
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• 2020

BIM(Building Information Modeling) is a salient technology for influential innovation in the construction industry. The patent network analysis is useful for suggesting the direction of technology development and exploring the research and development field. Therefore, the purpose of this study is to analyze the BIM technology structure and core technologies according to the convergence of BIM technology and market expansion. In this study, social network analysis was conducted by establishing a co-classification IPC network for the United States BIM patent. In particular, the characteristics of the major technical areas in the BIM technology network were identified through centrality analysis. G06F017/00, digital computing or data processing method, is a core technology field in the BIM network. Arrangements, apparatus or systems for transmission of digital information, H04L029/00 is an influential technology across the network. B25J009/00 for program controlled manipulators is an intermediary technology field and G06T019/00, manipulating 3D models or images for computer graphics, is an important field for technological development competitiveness.

• Asian Journal of Innovation and Policy
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• v.6 no.2
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• pp.111-137
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• 2017

This study analyzes a language network of Science and Technology Basic Plan, which is the basis for science and technology policy in Korea, for the next Science and Technology Basic Plan. Language network analysis was adopted for a quantitative approach measuring the trend of policies. Several techniques such as keyword analysis, language network map analysis, quantitative characteristics analysis and keyword-related major-word analysis have been performed. Results show that there are common policies emphasized by all Science and Technology Basic Plans in the past, and there are also specific policies emphasized in each period of the Science and Technology Basic Plan. These specific policies come from a 'change of times' when the Science and Technology Basic Plans were established, as well as the philosophy of the national government.

• International Journal of Knowledge Content Development & Technology
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• v.8 no.4
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• pp.75-98
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• 2018

In this study, the network analysis of researchers, institutions, and research principal agent was conducted to understand structure characteristics of international cooperation research project implemented from 1997 to 2018. The network of researchers and institutions were decentralized structure. On the other hands, the network of research principal agent was centralized structure. The Soul National University is the leading organization of international cooperation research project. In terms of research principal agent, corporation is the leading principal agent. In additions, the results of the network centroid analysis of the researchers and institutions were correlated with the research funds. As a result, it was confirmed that the network centroid of research organization was linearly related to research funds.

• Journal of Platform Technology
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• v.11 no.5
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• pp.84-96
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• 2023

Network slicing refers to a technology that divides network infrastructure into multiple parts. Network slicing enables flexible network configuration while minimizing the physical resources required for network division. For this reason, network slicing technology has recently been developed and introduced in a form suitable for the 5G environment for efficient management of large-scale network environments. However, systematic analysis of network slicing research in the 5G environment has not been conducted, resulting in a lack of systematic analysis of the technology. Accordingly, in this paper, we provide insight into network slicing technology in the 5G network environment by conducting a comparative analysis of the technology. In this study's comparative analysis, 13 literatures on network slicing in the 5G environment was identified and compared and analyzed through a systematic procedure. As a result of the analysis, three network slicing technologies frequently used for 5G networks were identified: RAN (radio access network) slicing, CN (core network) slicing, and E2E (end-to-end) sliding. These technologies are mainly used for network services. It was confirmed that research is being conducted to achieve quality improvement and network isolation. It is believed that the results of this comparative analysis study can contribute to 6G technology research as a future direction and utilization plan for network slicing research.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.88-95
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• 2017

As the safety fields are expanding to a variety of industrial fields, safety technology has been developed by convergence between industrial safety fields such as mechanics, ergonomics, electronics, chemistry, construction, and information science. As the technology convergence is facilitating recently advanced safety technology, it is important to explore the trends of safety technology for understanding which industrial technologies have been integrated thus far. For studying the trends of technology, the patent is considered one of the useful sources that has provided the ample information of new technology. The patent has been also used to identify the patterns of technology convergence through various quantitative methods. In this respect, this study aims to identify the convergence patterns and fields of safety technology using association rule mining(ARM)-based patent co-classification(co-class) analysis. The patent co-class data is especially useful for constructing convergence network between technological fields. Through linkages between technological fields, the core and hub classes of convergence network are explored to provide insight into the fields of safety technology. As the representative method for analyzing patent co-class network, the ARM is used to find the likelihood of co-occurrence of patent classes and the ARM network is presented to visualize the convergence network of safety technology. As a result, we find three major convergence fields of safety technology: working safety, medical safety, and vehicle safety.

• 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.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.154-163
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• 2022

The purpose of this paper is to illuminate the role and importance of National Research & Education Network (NREN) in the national research and education field and to establish the future strategy of KREONET in Korea. To this end, we first carefully analyze the footsteps of NREN in major overseas countries, KREONET achievements, and future demand for KREONET. The history of NREN's development is divided into the 2000s, 2010s, and present by era, and classified into network infrastructure, network service, and next-generation network technology by subject. KREONET achievements are divided into advanced research support, network backbone and operation, and network service. Future demand analysis of users who use KREONET was conducted through Korea Research International Incorporation, a survey company. This paper presents the future development strategy of KREONET by analyzing KREONET achievements and future demand.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.12-12
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• 1994

Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.3
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• pp.156-169
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• 2016

The objective of this study is to investigate patent trends of Daegu city which tries to introduce environment friendly energy and to develop new technology or new industry sprung from technology convergence on smart decentralized energy technology and other technologies. After applying network analysis to corresponding groups of technology or industry convergence, strategy for future energy convergence industry is provided. Patent data applied in Daegu city area are used to obtain research goal. The technology which contains several IPC codes (IPC Co-occurrence) is considered as a convergence technology. Path finder network analysis is used for visualizing and grouping by using IPC codes. The analysis results categorized 13 groups in energy convergence industry and reclassified them into 3 cluster groups (Smart Energy Product Production Technology Group, Smart Energy Convergence Supply Technology Group, Smart Energy Indirect Application Technology Group) considering the technical characteristics and policy direction. Also, energy industry has evolved rapidly by technological convergence with other industries. Especially, it has been converged with IT industry, and there is a trend that energy industry will be converged with service industry and manufacturing industry such as textile, automobile parts, mechanics, and logistics by employing infrastructure as well as network. Based on the research results on core patent technology, convergence technology and inter-industry analysis, the direction of core technology research and development as well as evolution on decentralized energy industry is identified. By using research design and methodology in this study, the trend of convergence technology is investigated based on objective data (patent data). Above all, we can easily confirm the core technology in the local industry by analyzing the industrial competitiveness in the macro level. Based on this, we can identify convergence industry and technology by performing the technological convergence analysis in the micro level.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.688-701
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• 2020

This study analyzes the characteristics and change factors of technological cooperation networks in the automotive industry. Using Social Network Analysis (SNA) of 112,009 autonomous driving-related patents filed from 2000 to 2017 by major automotive firms in the world, we investigate the structure of the technological cooperation network. Network characteristics such as density are analyzed through structural characteristic analysis among the network analysis indicators. The structural characteristics of the technology cooperation network are confirmed through analysis of status characteristic indicators, such as the degree of centrality, betweenness centrality, and closeness centrality. Results show that car makers such as Toyota and Hyundai Motors, as well as parts suppliers such as Bosch and Continental, have high-performance technology developments related to autonomous driving. The structural characteristics of the network show that companies participating in cooperative networks for autonomous driving technology development have increased in number and are diversified, and all of the status characteristics indicators have decreased. This can be interpreted as an increasing number of horizontal and complementary forms of technological cooperation between firms. In addition, it was confirmed that the number of participants in the field of autonomous driving technology has increased, and the networks have become more complex.