• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.2923-2936
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• 2024

Modern risk management philosophy emphasizes the invulnerability of human beings to cope with all kinds of emergencies. The Nuclear Accidents Emergency Response Organization (NAERO) of Nuclear Power Plant (NPP) is the primary body responsible for nuclear accidents emergency response. The invulnerability of the organization to disturbance or attack from internal and external sources is crucial in the completion of its response missions, reduction of severity of accidents, and assurance of public and environmental safety. This paper focused on the NAERO of a certain NPP in China, and applied the complex network theory to construct the network model of the organization. The topological characteristics of the network were analyzed. Four importance evaluation indexes of network nodes including Degree Centrality (DC), Betweeness Centrality (BC), Closeness Centrality (CC) and Eigenvector Centrality (EC), along with Pearson coefficient correlation among the indexes were calculated and analyzed. Size of the Largest Connected Component (LCC) and Network Efficiency were used as measures regarding the invulnerability of the network. Simulation experiments were conducted to assess the invulnerability of network against various attack strategies. These experiments were conducted both in the absence of node protection measures and under protection measures with different node protection rates. This study evaluated the invulnerability of the NAERO network, and provided significant decision-making basis for the enhancement of the network's invulnerability.

• Journal of Korean Library and Information Science Society
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• v.51 no.2
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• pp.1-21
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• 2020

The purpose of this study is to explore semantic characteristics of IFLA school library guidelines through network analysis. There are two versions, 2002 edition and 2015 revision of the guidelines. This study analyzed the 2002 edition and 2015 revision of the IFLA school library guidelines view point of semantic network, and compared characteristics of two versions. The keywords were to extracted from two texts, semantic network were composed based on co-occurrence relations with keywords. The centrality(degree centrality, closeness centrality, betweenness centrality) was analyzed from the network. In addition, this study conducted topic modeling analysis using LDA function of NetMiner4.0. The result of this study is following these. First, When comparing the centrality, the 'Program, Teaching, Reading, Inquiry, Literacy, Media' keyword was higher in the 2015 revision than in the 2002 edition. Second, 'Inquiry' in degree centrality and 'Achievement' in closeness centrality which were not included in the 2002 edition top-ranked keyword list, have new appeared in 2015 revision. third, As a result of the analysis of topic modeling, compared to the 2002 version, the importance of topics on programs and services, teaching and learning activities of librarian teacher, and media and information literacy is increasing in the 2015 revision.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.109-128
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• 2010

The purpose of our research is to figure out the 'non-financial value' of consumers applying networks amongst consumer groups, the data-based marketing strategy to the analysis and delve into the ways for enhancing effectives in marketing activities by adapting the value to the marketing. To verify the authenticity of the points, we did the empirical test on the consumer group using 'the Essence Cosmetics Products' of high involvement that is deeply affected by consumer perceptions and the word-of-mouth activities. 1) The empirical analysis reveals the following features. First, the segmented market for 'Essence Consumer' is composed of several independent networks, each network shows to have the consumers that is high degree centrality and closeness centrality. Second, the result proves the authenticity of the non-financial value for boosting corporate profits by the high degree centrality and closeness centrality consumer's word-of-mouth activities. Lastly, we verify that there lies a difference in the network structure of 'Essence Cosmetics Market'per each product origin(domestic, foreign) and demographic characteristics. It does, therefore, indicate the need to consider the features applying mutually complementary for the network targeting.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.81-94
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• 2023

The study aims to compare and analyze the social network structures of Qatar Airways,s Singapore Airlines, Emirates Airlines, and ANA Airlines, recording the top 1 to 4, and Korean Air in ninth by Skytrax's airline evaluations in 2022. This study uses NodeXL, a social network analysis program, to analyze the social networks of 5 airlines, Vertex, Unique Edges, Single-Vertex Connected Components, Maximum Geodesic Distance, Average Geodesic Distance, Average Degree Centrality, Average Closeness Centrality, and Average Betweenness Centrality as indicators to compare the differences in these social networks of the airlines. As a result, Singapore's social network has a better network structure than the other airlines' social networks in terms of sharing information and transmitting resources. In addition, Qatar Airways and Singapore Airlines are superior to the other airlines in playing roles and powers of influencers who affect the flow of information and resources and the interaction within the airline's social network. The study suggests some implications to enhance the usefulness of social networks for marketing.

• 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.

• The Research Journal of the Costume Culture
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• v.27 no.3
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• pp.274-284
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• 2019

Research on cosmetic behavior has developed significantly since the 2000s. Reviewing cosmetic behavior research can be meaningful because it can grasp trends in the domestic cosmetics market, and it can also illuminate how domestic consumers' interest in makeup has changed over time. The purpose of this study is to investigate the links between major keywords and the keywords which affect makeup behavior of different age groups through network analysis. In this study we analyzed thesis and journal data based on makeup behavior through network analysis using Nodexl. We analyzed 10 years of journals and theses - from 2000 to 2017, and investigated age-related differences in variables related to makeup behavior. Research subjects were divided into age-based groups: 10, 20-40, and over 50. The total number of theses collected was 82. In order to perform network analysis using the Nodexl program, we extracted the frequency of representative words using the KrKwic program. The extracted core words were analyzed for degree centrality, betweenness centrality and eigenvector centrality using Nodexl. The expected result is that the network analysis using keywords will lead to different variables depending on age and the main goal of the cosmetics market, and it is expected to be used as the basis for follow-up research related to cosmetic behavior.

• Journal of Hydrogen and New Energy
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• v.33 no.4
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• pp.318-329
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• 2022

This study analyzed keyword networks and Author's Affiliation networks of hydrogen-related papers published in Korea Citation Index (KCI) journals from 2016 to 2020. The study investigated co-occurrence patterns of institutions over time to examine collaboration trends of hydrogen scholars. The study also conducted frequency analysis of keyword networks to identify key topics and visualized keyword networks to explore topic trends. The result showed Collaborative research between institutions has not yet been extensively expanded. However, collaboration trends were much more pronounced with local universities. Keyword network analysis exhibited continuing diversification of topics in hydrogen research of Korea. In addition centrality analysis found hydrogen research mostly deals with multi-disciplinary and complex aspects like hydrogen production, transportation, and public policy.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.675-685
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• 2011

This paper proposes a job matching function that calculates the job matching probability of a job-seeker to an employer taking the working conditions of a job-seeker and an employer into account. In addition, this study analysis the degree of centrality that means interactions of a job-seeker and an employer utilizing social network analysis. The results are follows. First, a degree of centrality is found to be severely concentrated in certain job-seekers or certain employers; in addition, there are many job-seekers and employers who have no matching results. Second, according to decision tree analysis, characteristics of a job-seeker that influences the degree of centrality are gender, age and degree of education in order of importance. The characteristics of a employer that influences the degree of centrality are proposed salary, industry classification and firm size in order of importance.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.58-72
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• 2021

In July 2021, UNCTAD classified Korea as a developed country. After the Korean War in the 1950s, economic development was promoted despite difficult conditions, resulting in epoch-making national growth. However, in order to respond to the rapidly changing global economy, it is necessary to continuously study the domestic industrial ecosystem and prepare strategies for continuous change and growth. This study analyzed the industrial ecosystem of the automobile industry where it is possible to obtain transaction data between companies by applying complexity spatial network analysis. For data, 295 corporate data(node data) and 607 transaction data (link data) were used. As a result of checking the spatial distribution by geocoding the address of the company, the automobile industry-related companies were concentrated in the Seoul metropolitan area and the Southeastern(Dongnam) region. The node importance was measured through degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, and the network structure was confirmed by identifying density, distance, community detection, and assortativity and disassortivity. As a result, among the automakers, Hyundai Motor, Kia Motors, and GM Korea were included in the top 15 in 4 indicators of node centrality. In terms of company location, companies located in the Seoul metropolitan area were included in the top 15. In terms of company size, most of the large companies with more than 1,000 employees were included in the top 15 for degree centrality and betweenness centrality. Regarding closeness centrality and eigenvector centrality, most of the companies with 500 or less employees were included in the top 15, except for automakers. In the structure of the network, the density was 0.01390522 and the average distance was 3.422481. As a result of community detection using the fast greedy algorithm, 11 communities were finally derived.

• The Journal of Internal Korean Medicine
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• v.42 no.4
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• pp.628-644
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• 2021

Objectives: This study analyzed, through network analysis and data mining analysis, the relationship between herbs used in osteoporosis prescriptions, diversified the analysis of osteoporosis-related prescriptions, and analyzed the combination of herbs used in osteoporosis-related prescriptions. Methods: The prescriptions used in osteoporosis treatment and experiments were established by conducting a full survey of the papers published by the OASIS site. A database for osteoporosis-related prescriptions was established, herbs were extracted, and the frequency of frequent herbs and prescriptions were investigated using Excel (MS offices ver. 2013). Using the freeware R version 4.0.3 (2020-10-10), igraph, and arules package, network analysis was performed in the first second of prescription composition. Results: Among the osteoporosis-related prescriptions, the most studied prescriptions are as follows.: Yukmijihwang-tang (六味地黃湯) and Samul-tang (四物湯). In the osteoporosis prescription network, herbs with connection centrality, proximity centrality, mediation centrality, and eigenvector centrality appeared in the order of Rehmanniae Radix Preparata, Angelicae Gigantis Radix, Poria Sclerotium, Paeoniae Radix, and Glycyrrhizae Radix et Rhizoma. After extracting the herbal combination network, including the corresponding herbs, and clustering it, it can be divided into drugs of the Yukmijihwang-tang (六味地黃湯) series and the Samul-tang (四物湯). Conclusions: This study could assist researchers in diversifyingy formula analysis in future studies. Moreover, the herbal combination used in osteoporosis prescriptions could be used to search for osteoporosis prescriptions in other databases or to create a new prescription.