• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.68-74
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• 2019

The purpose of this study was to identify research trends of 892 domestic articles (2009-2018) related to emotional labor by using text-mining and network analysis. To this end, the keyword of these papers were collected and coded and eventually converted to 871 nodes and 2625 links for network text analysis. First, network text analysis revealed that the top four main keyword, according to co-occurrence frequency, were burnout, turnover intention, job stress, and job satisfaction in order and that the frequency and the top four core keyword by degree centrality were all relatively the high. Second, based on the top four core keyword of degree centrality the ego network analysis was conducted and the keyword for connection centroid of each network were presented.

• The KIPS Transactions:PartC
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• v.11C no.1
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• pp.123-134
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• 2004

The synchronized clock performance in the synchronization network and SDH transmission network design is an important element in aspect of guaranteeing network stability and data transmission. Consequently the simulator which can applicable various parameters and several input levels from the best state to the worst state for performance analysis of the synchronized clock is required in case of network design. Therefore, in this paper, 1 developed the SNCA and TNCA for analysis of the synchronized clock in the synchronization network and transmission network. And utilizing these simulators with various wander generation, node number and clock state, 1 obtained the synchronized clock characteristics and maximum network nodes In NE1, NE2 and NE3 transmission network and DOTS1, DOTS2 synchronization network.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5A
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• pp.441-450
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• 2007

In this paper, it is proposed the link performance analysis results using SNRAT(Satellite Network Resource Allocation & Analysis Tool) and verified the anticipated results by satellite communication network simulator. A communication satellite cannot be corrected or fixed for the error in orbit operation after launching unlike the ground operation equipment and has a restricted operation life. So, it is important to make possible to use satellite communications in the proper time. It is expected the link BER(Bit Error Rate), throughput and AJ(Anti-Jamming) performance using SNRAT tool before launching. And it is verified the performance of the repeaters and ground equipment specification using the satellite network simulator and is extracted the optimum operational scenarios through the tests of various network operational plans.

• Journal of Society of Preventive Korean Medicine
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• v.25 no.2
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• pp.33-43
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• 2021

Objectives : This study seeks to grasp the current status of Koryo medical research in North Korea, by focusing on researchers and research topics. Methods : A network analysis of co-authors and keyword which were extracted from Koryo Medicine - a North Korean traditional medicine journal, was conducted. Results : The results of author network analysis was a sparse network due to the low correlation between authors. The domain-wide network density of co-authors was 0.001, with a diameter of 14, average distance between nodes 4.029, and average binding coefficient 0.029. The results of the keyword network analysis showed the keyword "traditional medicine" had the strongest correlation weight of 228. Other keywords with high correlation weight was common acupuncture (84) and intradermal acupuncture(80). Conclusions : Although the co-authors of the Koryo Medicine did not have a high correlation with each other, they were able to identify key researchers considered important for each major sub-network. In addition, the keywords of the Koryo Medicine journals had a very high linkage to herbal medicines.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.73-86
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• 2024

With the acceleration of regional economic integration, the agricultural trade network within the RCEP region presents new opportunities and challenges for member countries. This study focuses on agricultural trade among RCEP members from 2011 to 2020, utilizing social network analysis to explore the structural characteristics and evolutionary trends of the trade network. Additionally, an extended gravity model is employed to empirically analyze the key factors influencing South Korea's agricultural trade with other member countries. The findings reveal that: (1) Agricultural trade relationships within the RCEP region are stable and mature, with high interconnectivity in the trade network, indicating a trend towards balanced development. (2) The positions of member countries within the agricultural trade network are characterized by both high density and heterogeneity. (3) South Korea's agricultural trade with RCEP member countries is positively influenced by the economic size, population size, and governance level of its trading partners, while South Korea's own indicators show no significant effect. The trade distance between South Korea and member countries also has a positive impact on agricultural trade. By combining social network analysis with an extended gravity model, this study provides a multi-faceted quantitative analysis of the RCEP agricultural trade network, offering new insights into regional agricultural trade. It also provides empirical evidence for agricultural trade cooperation between South Korea and other RCEP countries.

• Korean Journal of Biological Psychiatry
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• v.12 no.2
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• pp.165-172
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• 2005

Objectives:The purpose of this study is to 1) conduct a discrimination analysis of schizophrenia and bipolar affective disorder using MMPI profile through artificial neural network analysis and logistic regression analysis, 2) to make a comparison between advantages and disadvantages of the two methods, and 3) to demonstrate the usefulness of artificial neural network analysis of psychiatric data. Procedure:The MMPI profiles for 181 schizophrenia and bipolar affective disorder patients were selected. Of these profiles, 50 were randomly placed in the learning group and the remaining 131 were placed in the validation group. The artificial neural network was trained using the profiles of the learning group and the 131 profiles of the validation group were analyzed. A logistic regression analysis was then conducted in a similar manner. The results of the two analyses were compared and contrasted using sensitivity, specificity, ROC curves, and kappa index. Results:Logistic regression analysis and artificial neural network analysis both exhibited satisfactory discriminating ability at Kappa index of greater than 0.4. The comparison of the two methods revealed artificial neural network analysis is superior to logistic regression analysis in its discriminating capacity, displaying higher values of Kappa index, specificity, and AUC(Area Under the Curve) of ROC curve than those of logistic regression analysis. Conclusion:Artificial neural network analysis is a new tool whose frequency of use has been increasing for its superiority in nonlinear applications. However, it does possess insufficiencies such as difficulties in understanding the relationship between dependent and independent variables. Nevertheless, when used in conjunction with other analysis tools which supplement it, such as the logistic regression analysis, it may serve as a powerful tool for psychiatric data analysis.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.3
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• pp.151-171
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• 2016

This study investigated the contents of twitters of metropolitans by year and city using language network analysis. The possibility of twitter as a medium of information provision was also explored. This study employed KrKwic, Ucinet6, and Netdraw programs to conduct language network analysis. As the results, the network was mainly formed with information about civic administration (citizen, management, opening service, participation) and information about citizens living (cultural events, parks, way to work) in 2014. However, information about civic service and announcement (citizen, civic opinion, opening service, civic service, events) occupied a central role in the network of 2015. The results showed that different keywords were derived by year and city in network analysis by city.

• Proceedings of the Technology Innovation Conference
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• 1997.12a
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• pp.133-158
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• 1997

This paper analyzes the characteristics of technological knowledge flow-structure of Korean manufacturing in dynamic perspective. In doing that, the concept of the knowledge network is introduced which is defined as a set of industries and their interaction(knowledge flow) or linkage. The analysis of the inter-industrial knowledge flows is based on the technological similarity by using R&D researchers'academic background in the year of 1984, 1987, 1990. The analysis is carried out by such methodology as network analysis, indicator analysis and simple statistical analysis. And the final results are drawn both in absolute terms(dimension effect) and in relative terms (proportion effect) respectively. The main findings are as follow. First, the Korean manufacturing knowledge network appears to strengthen existing inter-industrial knowledge linkages rather than to construct new linkages. Second, the network seems to form a dualistic structure in that some high-technology sectors (knowledge production sectors) emerge along with traditional sectors (knowledge absorbing sectors). Third, since the mid-1980s, an inter-industrial fusion is witnessed among technologically intensive sectors, indicating that some sophisticated innovation modes are emerging in Korean manufacturing system.

• Herbal Formula Science
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• v.28 no.3
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• pp.243-254
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• 2020

Objectives : Network pharmacology analysis is commonly used to investigate the synergies and potential mechanisms of multiple compounds by analyzing complex, multi-layered networks. We used TCMSP and BATMAN-TCM databases to compare results of network pharmacological analysis between White Ginseng(WG) and Red Ginseng(RG). Methods : WG and RG were compared with components and their target molecules using TCMSP database, and compound-target-pathway/disease networks were compared using BATMAN-TCM database. Results : Through TCMSP, 104 kinds of target molecules were derived from WG and 38 kinds were derived from RG. Using the BATMAN-TCM database, target pathways and diseases were screened, and more target pathways and diseases were screened compared to RG due to the high composition of WG ingredients. Analysis of component-target-pathway/disease network using network analysis tools provided by BATMAN-TCM showed that WG formed more networks than RG. Conclusions : Network pharmacology analysis can be effectively performed using various databases used in system biology research, and although the materials that have been reported in the past can be used efficiently for research on diseases related to targets, the results are unreliable if prior studies are focused on limited or narrow research areas.

• Korean Journal of Environmental Biology
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• v.36 no.3
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• pp.370-376
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• 2018

It is important to consider interaction between species in understanding structure and function of the biological community. Current ecological issues such as climate change and habitat loss emphasize the significance of the concept of species interaction in that varying species' interaction across environmental gradients may lead to altered ecological function and services. However, most community studies have focused on species diversity through analysis of quantitative indices based on species composition and abundance data without considering species interactions in the community. 'Ecological network analysis' based on network theory enables exploration of structural and functional properties of ecosystems composed of various species and their interactions. In this paper, network analysis of Cheonggye stream as a case study was presented to promote uses of network analysis on ecological studies in Korea. Cheonggye stream has a simple biological structure with link density of 1.48, connectance 0.07, generality 4.43, and vulnerability 1.94. The ecological network analysis can be used to provide ecological interpretations of domestic long-term monitoring data and can contribute to conserving and managing species diversity in ecosystems.