• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1454-1466
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• 2016

This paper implements an estimated ranking algorithm of closeness centrality measures in large-scale workflow-supported social networks. The traditional ranking algorithms for large-scale networks have suffered from the time complexity problem. The larger the network size is, the bigger dramatically the computation time becomes. To solve the problem on calculating ranks of closeness centrality measures in a large-scale workflow-supported social network, this paper takes an estimation-driven ranking approach, in which the ranking algorithm calculates the estimated closeness centrality measures by applying the approximation method, and then pick out a candidate set of top k actors based on their ranks of the estimated closeness centrality measures. Ultimately, the exact ranking result of the candidate set is obtained by the pure closeness centrality algorithm [1] computing the exact closeness centrality measures. The ranking algorithm of the estimation-driven ranking approach especially developed for workflow-supported social networks is named as RankCCWSSN (Rank Closeness Centrality Workflow-supported Social Network) algorithm. Based upon the algorithm, we conduct the performance evaluations, and compare the outcomes with the results from the pure algorithm. Additionally we extend the algorithm so as to be applied into weighted workflow-supported social networks that are represented by weighted matrices. After all, we confirmed that the time efficiency of the estimation-driven approach with our ranking algorithm is much higher (about 50% improvement) than the traditional approach.

• Journal of Food Hygiene and Safety
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• v.33 no.1
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• pp.23-30
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• 2018

The purpose of this research was to introduce network analysis method for analyzing pesticide residues in incongruity commercial agricultural commodities. Based on the "results in pesticide residues on incongruity commercial agricultural commodities" on "Guidelines for food safety management 2017", we used centrality analysis for pesticide residues via degree, closeness and betweenness centrality measurement. In case of degree centrality result, chlorpyrifos and diazinon were the most highly "connected node" in pesticide network. For the closeness centrality result, the most pesticides showed the similar closeness trend except for 19 species of pesticides. Fludioxonil and chlorpyrifos are recognized as the "bridge" of pesticides network with their high betweenness centrality. The results of network analysis show the "relation" data, which could not represent through out the conventional statistical analysis, among the pesticide residues. We hope that the network analysis method will be appropriate and precise tool for analyzing pesticide residues via elaboration and optimization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.600-613
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• 2018

The purpose of this research was to introduce a network analysis method for analyzing the recent trend of the flexible solar cell using a scholarly database. Based on the five years from 2013 to 2017, we used centrality analysis of research papers via measurement of degree centrality, closeness centrality, and betweenness centrality. The results of network analysis show that cell has a centrality value above 0.8, which means that cell is connected with 80% of the total keywords, so it is recognized as the center of flexible solar cell research. The analysis results also indicate that perovskite and copper indium gallium diselenide (CuInGaSe2, or CIGS) are the center of the subgroup for cell. We recognize that the result refers to recent new technology called the CIGS/perovskite tandem solar cell. We hope that the network analysis method will be the appropriate and precise tool for technology and research planning via elaboration and optimization.

• Journal of Korean Academy of Nursing
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• v.49 no.5
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• pp.538-549
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• 2019

Purpose: This study aimed to explore and compare the knowledge structure of pain management nursing research, between Korea and other countries, applying a text network analysis. Methods: 321 Korean and 6,685 international study abstracts of pain management, published from 2004 to 2017, were collected. Keywords and meaningful morphemes from the abstracts were analyzed and refined, and their co-occurrence matrix was generated. Two networks of 140 and 424 keywords, respectively, of domestic and international studies were analyzed using NetMiner 4.3 software for degree centrality, closeness centrality, betweenness centrality, and eigenvector community analysis. Results: In both Korean and international studies, the most important, core-keywords were "pain," "patient," "pain management," "registered nurses," "care," "cancer," "need," "analgesia," "assessment," and "surgery." While some keywords like "education," "knowledge," and "patient-controlled analgesia" found to be important in Korean studies; "treatment," "hospice palliative care," and "children" were critical keywords in international studies. Three common sub-topic groups found in Korean and international studies were "pain and accompanying symptoms," "target groups of pain management," and "RNs' performance of pain management." It is only in recent years (2016~17), that keywords such as "performance," "attitude," "depression," and "sleep" have become more important in Korean studies than, while keywords such as "assessment," "intervention," "analgesia," and "chronic pain" have become important in international studies. Conclusion: It is suggested that Korean pain-management researchers should expand their concerns to children and adolescents, the elderly, patients with chronic pain, patients in diverse healthcare settings, and patients' use of opioid analgesia. Moreover, researchers need to approach pain-management with a quality of life perspective rather than a mere focus on individual symptoms.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.257-266
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• 2011

Over the society the trial for several systems to be connected with Network has been continued to share information and to make it various. In accordance with such a change, the concept of military warfare conduction has been changing form platform centric warfare in separate combat system based on network centric warfare in network based. We have continuously made an effort that we try to get the goal with efficient system which is linked up with network, but such a study on that one in military system analysis is still slower than the study out of military until now. So this study is searching network influence factor by using military network with application of social network analysis method which is used broadly in the society and the science as well. At this time we search co-relationships between social network and the thing that we can analyse C2 time by effectiveness measurement means. By this study it has value of network influence factor identification for the growing network composition.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.35-45
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• 2018

Research on the establishment of new governance aimed at efficient policy planning and the implementation thereof by the government has been conducted in response to social changes. Nonetheless, governance is comprehensive and encompasses different meanings; it takes various forms in the process of its actual application. Therefore, systematic classification of research on governance and analysis on its research trend are required. Accordingly, three researchers who majored in policy sciences, business informatics, and library and information science, respectively, searched for theses related to governance published since 2016 from Research Information Sharing Service and conducted a social network analysis (SNA) on them. According to their research results, the main research topics were largely classified into collaborative governance and local governance. Keywords throughout the topics included network, participation, conflict, and trust in line with the characteristics of governance. Representative subjects of governance included education, urban regeneration, and the environment. Further, measurement of betweenness centrality showed local governance was a main topic for convergent research. This study will lead to a greater understanding of research on governance and help activate such research. One limitation of this study is that it analyzed only theses with the keywords but not all theses on governance. Follow-up research should analyze all theses on governance and statistically verify them with SNA indexes.

• Spatial Information Research
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• v.23 no.3
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• pp.35-44
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• 2015

Recently, the government aims to discover and provide services to citizens on the development strategy for activating the U-City. So, this study aims to offer a service discovery direction by analyzing the service issues and trends. The target is newspaper article about U-City Service from 2009 to 2014. Prepared 723 newspaper article for analysis. Next step is frequency analysis of keyword and used that result for Network analysis and measure of information. Network analysis can show result through "Degree Centrality", "Betweenness Centrality" and "Closeness Centrality". As a result, "Information", "IT", "Environment", "Technology", "Center" is higher than another. These 5 keywords are important factors for driving the U-City the past six years. Information measurement results, Already U-City were put an emphasis on building the infrastructure and able to identify a trend that provided the center of the public service. Those Service field are "Tour(2009)", "Crime prevention and Disaster Prevention(2010)", "Facility Management(2011)", "administration(2012)" and "Facility Management(2013, 2014)". Result of this study found implications what on citizen participation. So, services field on the existing infrastructure should be discovered and provided. Finally, this study can expected to be a reference in the local government planning for U-City.