• Journal of the Economic Geographical Society of Korea
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• v.15 no.4
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• pp.628-641
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• 2012

This research investigates a dynamic mechanism underlying the co-evolution between network and space by applying hype-curve model, typical phenomenon which shows how new technologies and ideas initially adapted in the society. This study analysis the knowledge intensive industry of digital contents using social network analysis (SNA) in terms of structural, spatial, and temporal aspects, year of 2000, 2005, and 2010 focused on Seoul area. First of all, network and space establish 'inter-feedback' as a result of evolution and differentiation process. Second, it happen temporal 'delay' through the learning process stage of 'peak of inflated expectation' and 'trough of disillusionment.' As a result, Seoul develops with the technology commercialized-orient strategy affect government policy. This trend changes to technology-oriented development in Seoul area in the late of 2000 established 'self-organization' with geographical proximity organizations through learning process.

• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.1-10
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• 2021

Analysis and Tracking of bug reports is a challenging field in software repositories mining. It is one of the fundamental ways to explores a large amount of data acquired from defect tracking systems to discover patterns and valuable knowledge about the process of bug triaging. Furthermore, bug data is publically accessible and available of the following systems, such as Bugzilla and JIRA. Moreover, with robust machine learning (ML) techniques, it is quite possible to process and analyze a massive amount of data for extracting underlying patterns, knowledge, and insights. Therefore, it is an interesting area to propose innovative and robust solutions to analyze and track bug reports originating from different open source projects, including Mozilla and Eclipse. This research study presents an ML-based classification model to analyze and track bug defects for enhancing software engineering management (SEM) processes. In this work, Artificial Neural Network (ANN) and Naive Bayesian (NB) classifiers are implemented using open-source bug datasets, such as Mozilla and Eclipse. Furthermore, different evaluation measures are employed to analyze and evaluate the experimental results. Moreover, a comparative analysis is given to compare the experimental results of ANN with NB. The experimental results indicate that the ANN achieved high accuracy compared to the NB. The proposed research study will enhance SEM processes and contribute to the body of knowledge of the data mining field.

• The Korea Journal of Herbology
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• v.34 no.6
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• pp.1-23
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• 2019

Objectives : The purpose of this study was to document the use of medicinal plants in traditional practices and to analyze and evaluate medicinal traditional knowledge of indigenous people in Wolchulsan National Park. Methods : Data were collected through interviews, informal meetings, open and group discussions, and observations guided by semi-structured questionnaires. Data were analyzed via quantitative analysis of use value (UV), informant consensus factor (ICF) and fidelity level (FL), and network analysis. Results : A total of 580 methods of usage recorded in this study were classified into 55 families, 95 genera, and 104 species. Plants with the highest recorded UVs were Glycine max (L.) Merr., Leonurus japonicus Houtt., and Artemisia princeps Pamp.. The informant consensus factor about using medicinal plants ranged from 0.55 to 0.92, which showed a high level of agreement among the informants on respiratory system disorders and pains. There were 22 species of plants with a fidelity level of 100 %, after eliminating the plants that were mentioned only once from the analysis. Finally, using network analysis, Glycine max (L.) Merr. and Artemisia princeps Pamp. were defined as species with meaningful medicinal use, while lumbago and leg pain were defined as significant ailments in the study area. Conclusions : This study highlights the diversity and importance of medicinal traditional knowledge for communities of Wolchulsan National Park, Korea. The results of this study will provide basic data for phytochemical and pharmaceutical studies, such as new medicines and therapies.

• ETRI Journal
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• v.27 no.1
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• pp.110-113
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• 2005

The resilient packet ring (RPR) is a data optimized ring network, where one of the key issues is on load balancing for competing streams of elastic traffic. This paper suggests three efficient traffic loading algorithms on the RPR. For the algorithms, we evaluate their efficiency via analysis or simulation.

• Journal of Mechanical Science and Technology
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• v.20 no.10
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• pp.1534-1540
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• 2006

Concurrent Engineering (CE) is a popular method employed in product development. It treats the whole product design process by the consideration of product quality, cost, rate of progress, and demands of customers. The development of computer and network technologies provides a strong support to the realization of CE in practice. Aiming at the characteristics of CE and network collaborative design, this paper built network collaborative design system frame. Through the analysis of the network collaborative design modes based on CE, this paper provided a novel network collaborative design integration model. This model can integrate the product design information, design process, and knowledge. Intelligent collaboration was considered in the proposed model. The study showed that the proposed model considered main factors such as information, knowledge, and design process in collaborative design. It has potential application in CE fields.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.164-169
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• 2003

In this paper, we propose the integrated Bayesian network framework to reconstruct genetic regulatory networks from genome expression data. The proposed model overcomes the dimensionality problem of multivariate analysis by building coherent sub-networks from confined gene clusters and combining these networks via intermediary points. Gene Shaving algorithm is used to cluster genes that share a common function or co-regulation. Retrieved clusters incorporate prior biological knowledge such as Gene Ontology, pathway, and protein protein interaction information for extracting other related genes. With these extended gene list, system builds genetic sub-networks using Bayesian network with MDL score and Sparse Candidate algorithm. Identifying functional modules of genes is done by not only microarray data itself but also well-proved biological knowledge. This integrated approach can improve there liability of a network in that false relations due to the lack of data can be reduced. Another advantage is the decreased computational complexity by constrained gene sets. To evaluate the proposed system, S. Cerevisiae cell cycle data [1] is applied. The result analysis presents new hypotheses about novel genetic interactions as well as typical relationships known by previous researches [2].

• Information Systems Review
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• v.10 no.2
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• pp.1-19
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• 2008

The purpose of this research is to schematize and suggest the new trends of study and changing aspects of science and technology hidden in a bibliographical phenomenon of documentation to researchers and policy-makers all through the Knowledge Map. The field of study to be analyzed in this research is the Access Network field. The reason why this field has been selected as the main target of study is that the Access Network field is economically important and characterized by its wide sphere where a variety of fields are interconnected. In addition, it is important to measure the applied as well as fundamental aspects of technology by using bibliographical method and technique. Knowledge Map successfully visualizes the inter-relations of the keywords and sub-fields of Access Network. The importance of visualizing methods in the convincing presentation of results has not been sufficiently understood in the past. Knowledge Map opens a new opportunity for cartography of science and information visualization. The Knowledge Map results have produced a great deal more than statistical artifact. We aimed to exploit the visualization effect of the Knowledge Maps to the aid of searchers in Access Network domain, and the results are quite encourging.

• Research in Community and Public Health Nursing
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• v.29 no.4
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• pp.429-439
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• 2018

Purpose: The aim of this study is to identify core keyword of frailty research in the past 35 years to understand the structure of knowledge of frailty. Methods: 10,367 frailty articles published between 1981 and April 2016 were retrieved from Web of Science. Keywords from these articles were extracted using Bibexcel and social network analysis was conducted with the occurrence network using NetMiner program. Results: The top five keywords with a high frequency of occurrence include 'disability', 'nursing home', 'sarcopenia', 'exercise', and 'dementia'. Keywords were classified by subheadings of MeSH and the majority of them were included under the healthcare and physical dimensions. The degree centralities of the keywords were arranged in the order of 'long term care' (0.55), 'gait' (0.42), 'physical activity' (0.42), 'quality of life' (0.42), and 'physical performance' (0.38). The betweenness centralities of the keywords were listed in the order of depression' (0.32), 'quality of life' (0.28), 'home care' (0.28), 'geriatric assessment' (0.28), and 'fall' (0.27). The cluster analysis shows that the frailty research field is divided into seven clusters: aging, sarcopenia, inflammation, mortality, frailty index, older people, and physical activity. Conclusion: After reviewing previous research in the 35 years, it has been found that only physical frailty and frailty related to medicine have been emphasized. Further research in psychological, cognitive, social, and environmental frailty is needed to understand frailty in a multifaceted and integrative manner.

• Journal of Physiology & Pathology in Korean Medicine
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• v.26 no.5
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• pp.615-620
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• 2012

This research aims to analyze the trend of subhealth and meebyung(未病) research as a method of network analysis from 2007 to 2011 in China. A total of 3,933 papers were involved in analysis from 5,465 searched papers, which title have '未病', '亞健康' in CNKI (China National Knowledge Infrastructure). It is carried out that counts annual paper number, authors' publicized papers, and journals paper number related to subhealth. Network analysis was performed to reveal collaboration research trend and relations between Authors, Affiliations, and Regions. As a result, Number of related studies have increased for the last 5 years. East and south regions of China, which include Beijing, Guangxi, and Zhejiang have participated most in their studies, and also as collaborated researches. As affiliations, Researches done by College of Traditional Chinese medicine and their hospital's collaborations are most counted. Because of distance limit, many colleges or institutes seem to make contacts with nearby affiliations. This study is the first attempt to perform network analysis on subhealth research trend in CNKI. This study would contribute to related studies in case of network analysis method.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.4
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• pp.89-104
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• 2005

This article identifies an emerging research paradigm and monitors the changes in digital preservation area using CiteSpace, a Java application which supports visual exploration with knowledge discovery in bibliographic databases. 74 articles on digital preservation field covering the time period from 1990-2005 were extracted from Web of Science. According to the result of analysis, core knowledge domains in digital preservation are technical preservation strategies, information network and preservation system, knowledge management and electronic government.