• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.3
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• pp.444-450
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• 1996

A digital hardware architecture for artificial neural network with learning capability is described in this paper. It is a modified hardware architecture known as HANNIBAL(Hardware Architecture for Neural Networks Implementing Back propagation Algorithm Learning). For implementing an efficient neural network hardware, we analyzed various type of multiplier which is major function block of neuro-processor cell. With this result, we design a efficient digital neural network hardware using serial/parallel multiplier, and test the operation. We also analyze the hardware efficiency with logic level simulation. (author). refs., figs., tabs.

• Radiation Oncology Journal
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• v.29 no.3
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• pp.164-173
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• 2011

Purpose: This research aimed to analyze the patterns of co-authorship network among the Korean radiation oncologists and to identify attributing factors for the formation of networks. Materials and Methods: A total of 1,447 articles including contents of ‘Radiation Oncology' and 'Therapeutic Radiology' were searched from the KoreaMed database. The co-authorship was assorted by the author's full name, affiliation and specialties. UCINET 6.0 was used to fi gure out the author's network centrality and the cluster analysis, and KeyPlayer 1.44 program was used to get a result of key player index. Sociogram was analyzed with the Netdraw 2.090. The statistical comparison was performed by a t-test and ANOVA using SPSS 16.0 with p-value < 0.05 as the significant value. Results: The number of articles written by a radiation oncologist as the first author was 1,025 out of 1,447. The pattern of coauthorship was classified into five groups. For articles of which the first author was a radiation oncologist, the number of singleauthor articles (type-A) was 81; single-institution articles (type-B) was 687; and multiple-author articles (type-C) was 257. For the articles which radiation oncologists participated in as a co-author, the number of single-institution articles (type-D) was 280 while multiple-institution articles (type-E) were 142. There were 8,895 authors from 1,366 co-authored articles, thus the average number of authors per article was 6.51. It was 5.73 for type-B, 6.44 for type-C, 7.90 for type-D, and 7.67 for type-E (p = 0.000) in the average number of authors per article. The number of authors for articles from the hospitals published more than 100 articles was 7.23 while form others was 5.94 (p = 0.005). Its number was 5.94 and 7.16 for the articles published before and after 2001 (p = 0.000). The articles written by a radiation oncologist as the first author had 5.92 authors while others for 7.82 (p = 0.025). Its number was 5.57 and 7.71 for the Journal of the Korean Society for Therapeutic Radiology and Oncology and others (p = 0.000), respectively. Among the analysis, a significant difference in the average number of author per article was indicated. The out-degree centrality of network among authors was 4.26% (2.03-7.09%) while in-degree centrality was 1.31% (0.53-2.84%). The three significant nodes were classified and listed as following: Choi, Eun Kyung for 1991-1995, Kim, Dae Young for 1998-2001, Park, Won and Lee, Sang Wook for 2003-2010. Choi, Eun Kyung and Kim, Dae Young appeared in two cases, and ranked as the highest degree in centrality. In the key player analysis, Choi, Eun Kyung and Lee, Sang Wook appeared in two cases, and ranked as the highest. From the cluster analysis, Sungkyunkwan University, Seoul National University and Yonsei University revealed as the three large clusters when Ulsan University, Chonnam National University, and Korea Institute of Radiological & Medical Science as the medium clusters. Conclusion: The Korean radiation oncologist's society shows a closed network with numerous relationships among the particular clusters, and the result indicates it is different from other institutions in the pattern of co-authorship formation of the major hospitals.

• Journal of Preventive Medicine and Public Health
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• v.41 no.1
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• pp.1-9
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• 2008

Objectives : This study evaluated knowledge structure and its effect factor by analysis of co-author and keyword networks in Korea's preventive medicine sector. Methods : The data was extracted from 873 papers listed in the Journal of Preventive Medicine and Public Health, and was transformed into a co-author and keyword matrix where the existence of a 'link' was judged by impact factors calculated by the weight value of the role and rate of author participation. Research achievement was dependent upon the author's status and networking index, as analyzed by neighborhood degree, multidimensional scaling, correspondence analysis, and multiple regression. Results : Co-author networks developed as randomness network in the center of a few high-productivity researchers. In particular, closeness centrality was more developed than degree centrality. Also, power law distribution was discovered in impact factor and research productivity by college affiliation. In multiple regression, the effect of the author's role was significant in both the impact factor calculated by the participatory rate and the number of listed articles. However, the number of listed articles varied by sex. Conclusions : This study shows that the small world phenomenon exists in co-author and keyword networks in a journal, as in citation networks. However, the differentiation of knowledge structure in the field of preventive medicine was relatively restricted by specialization.

• Knowledge Management Research
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• v.1 no.1
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• pp.47-64
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• 2000

As the Knowledge Economy grows bigger, studies and practices of knowledge management flourish in almost every organizations. Yet, the studies of fundamental relationships between knowledge and organization have not been sufficiently developed. It is partly because current knowledge management mainly focus on the technical aspects of the theme. This paper tries to find the possible organizing principles and theoretical foundations of knowledge-intensive organizations through the perspective of knowledge market and knowledge community. Based on the differentiation of "knowledge" and "knowing", the author draws several propositions about knowledge creation and knowledge use. Then, the author relates these propositions to the design and implementation of two theoretical models of organizations, i. e. knowledge market and knowledge community. Major claims are: 1) Knowledge use and knowledge creation process are conceptually separable, so that different conceptual models (market & community) need to be applied. 2) Since knowledge use and creation should be integrated, organizations in the Knowledge Economy should be the efficient knowledge market and, at the same time, knowledge community with care and cooperations. 3) The network of independent small KIFs(knowledge-intensive firms) could be considered as the possible organizational model of the future.

• International Journal of Contents
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• v.2 no.2
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• pp.6-9
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• 2006

The style of war in the $21^{st}$ century became digitalized cooperative union tactic, which relies heavily on the system providing real time information. Critical information is provided during the war from sensing to shooting. Therefore, epochal development in observation, reconnaissance (ISR), commanding (C4I) and precision strike (PGM) are necessary. Application of ubiquitous computing and network technologies in national defense is necessary for carrying out with various types of wars in the $21^{st}$ century. Therefore, the author wants to research core technology sector that can be developed and applied in preparation of ubiquitous national defense era. Also plans for applying recent u-Defense technology to the military sector had been suggested. Particularly, the author have suggested plans for utilizing combined future information technologies such as ad-hoc network, RFID for the logistic supply in construction of u-Defense system. By utilizing these information technologies, combat power and strategic capabilities of the military can be enhanced greatly.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.994-998
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• 2005

A new control method, called a simple model matching, has been recently developed by the author. This is very simple and be applied for linear and nonlinear discrete time systems with/without time lag. Based on this formulation, identification is examined in this paper using an interconnected neural network with the EBP-EWLS learning algorithm. With this result, a control method is also presented for a nonlinear discrete time system.

• Journal of the Korean Society for information Management
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• v.30 no.2
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• pp.207-225
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• 2013

Due to the development of science and technology, the convergence of various disciplines has been fostered. Accordingly, interdisciplinary studies have increasingly been expanded by integrating knowledge and methodology from different disciplines. The primary focus of biblimetric methods is on investigating the intellectual structure a field, and analysis of the characterization of interdisciplinary studies is overlooked. In this study, we aim to identify the intellectual structure of the field of medical informatics through author co-citation analysis and co-word analysis by the representative journal "IEEE ENG MED BIOL." In addition, we examine authors and MeSH Terms of top three representative journals for further analysis of the field. We examine the intellectual structure of the medical informatics field by author and word clusters to identify the network structure of medical informatics disciplines.

• Journal of Information Management
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• v.42 no.4
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• pp.75-94
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• 2011

The purpose of this study is to analyze the domain on the field of Electrical Engineering in Korea by the author bibliographic coupling analysis. The data set contains a total of 2,157 articles from two core journals with 23,411 citation data from 2005 to 2009 published in two prestigious journals. In order to achieve the purpose of this study, MDS analysis, clustering analysis and network analysis were used to examine core subject areas. In addition, the centrality analysis in the weighted networks was used to explore the key authors in this field such as the top global centrality authors and the top local centrality authors. The findings of this study can be utilized to guide the current research trend and author network for collection development and information services in the field of Electrical Engineering.

• Journal of Korea Technology Innovation Society
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• v.17 no.2
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• pp.334-354
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• 2014

This study aims to analyze the research trend of Korean medicine based on social network analysis. To do this, a dataset has been collected from KCI (Korea Citation Index) database. According to the results, we have identify the longitudinal trend of the number of papers, journals, organizations and key words in this field. Moreover, based on the nodes' centrality of co-author network, we have found a core journal (i.e. Korean Journal of Oriental Physiology and Pathology), a hub institution (i.e. Kyunghee university) and two main key words (i.e. anti-oxidation and acupuncture) in the research network. In conclusion, integrating field experts' tacit knowledge in Korean medicine studies with the results of the explicit social network analysis on the research trend, we put forward further policy implications with regard to R&D strategies in this field.

• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.57-77
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• 2014

As co-authorship has been prevalent within science communities, counting the credit of co-authors appropriately is an important consideration, particularly in the context of identifying the knowledge structure of fields with author-based analysis. The purpose of this study is to compare the characteristics of co-author credit counting methods by utilizing correlations, multidimensional scaling, and pathfinder networks. To achieve this purpose, this study analyzed a dataset of 2,014 journal articles and 3,892 cited authors from the Journal of the Architectural Institute of Korea: Planning & Design from 2003 to 2008 in the field of Architecture in Korea. In this study, six different methods of crediting co-authors are selected for comparative analyses. These methods are first-author counting (m1), straight full counting (m2), and fractional counting (m3), proportional counting with a total score of 1 (m4), proportional counting with a total score between 1 and 2 (m5), and first-author-weighted fractional counting (m6). As shown in the data analysis, m1 and m2 are found as extreme opposites, since m1 counts only first authors and m2 assigns all co-authors equally with a credit score of 1. With correlation and multidimensional scaling analyses, among five counting methods (from m2 to m6), a group of counting methods including m3, m4, and m5 are found to be relatively similar. When the knowledge structure is visualized with pathfinder network, the knowledge structure networks from different counting methods are differently presented due to the connections of individual links. In addition, the internal validity shows that first-author-weighted fractional counting (m6) might be considered a better method to author clustering. Findings demonstrate that different co-author counting methods influence the network results of knowledge structure and a better counting method is revealed for author clustering.