• Journal of Digital Convergence
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• v.14 no.9
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• pp.301-308
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• 2016

Writing high-quality papers and publishing them at prestigious academic journals would be something that every scholar strives for. This study made a network with nine academic journals in South Korea in the field of public administration and public policy and analyzed the influence of academic journals through social network analysis. Using centrality measures, such as degree centrality, beta centrality, and eigenvector centrality, this study found that Korean Public Administration Review has the highest influence on the journal network, followed by Korean Public Studies Review. However, different choice of centrality measure led to different ranking of journals in terms of their influence.

• Journal of Korea Port Economic Association
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• v.31 no.3
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• pp.155-166
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• 2015

This study selected container terminals of Gwangyang and Busan Ports to evaluate the influence of efficient container terminals. For the study, after data envelopment analysis (DEA) using the CCR and BCC models, the decision-making unit (DMU) system was used to define nodes; and with the use of a reference group in DEA (BCC model) and a lambda value, this study created a social network and analyzed the influences of efficient DMUs through a centrality analysis of eigenvectors. The results are presented as follows: First, as a result of the DEA, CCR efficiencies in PNC, HJNC, and HPNT container terminals of Busan Port were 1 and BCC efficiencies at Singamman Terminal, Wooam Terminal, PNC, HJNC, HPNT, and BNCT container terminals of Busan Port were 1. Second, as a result of undertaking social network analysis (SNA), according to an eigenvector centrality analysis, HJNC Terminal was referred to the most (influence score of 0.515), which indicates that it is the most influential as a container terminal. The influence of PNC Terminal was 0.512, while that of Wooam Terminal was 0.379. CJ Korea Express in Gwangyang Port was ranked fourth in influence, but its influence score of 0.256 indicates that it was the most influential of the container terminals at Gwangyang Port.

• Proceedings of the KIPE Conference
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• 2018.11a
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• pp.179-180
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• 2018

유도모터의 벡터제어를 위해서는 회전자 자속에 대한 정확한 추정이 필요하다. 일반적으로 전압모델을 이용한 자속 추정기 구성하면 고속 구간에서 파라미터 오차에 대해 강인한 특성을 갖는다고 알려져 있다. 그러나 약계자 운전에서 부하가 증가할 경우 자속 추정에서 누설 자속에 의한 영향력이 커지게 되며, 심한 경우 누설 계속 오차로 인한 약계자 운전 불능을 야기시킨다. 따라서 본 논문은 유도모터의 누설계수 오차에 의한 벡터제어 성능 영향을 약계자 영역에 집중해서 분석하였다.

• Journal of Korea Port Economic Association
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• v.27 no.3
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• pp.135-146
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• 2011

A voluminous research on efficiency employs the DEA(Data Envelope Analysis) models. There are, however, only very few that have an interest in the factors influencing such efficiencies. We, furthermore, do not see any studies which analyze the long-term efficiency of the logistics providers using the panel cointegration techniques. The purpose of this paper, hence, is to evaluate the efficiency, analyse its determinants and show a long-term relationship between turnover and the other variables employing the SBM(Slack Based Measure) model, Tobit model, the panel procedure and the FMOLS(Fully Modified OLS). The panel data are composed of 9 individuals and 6 years. The panel cointegrating vectors show that the group coefficient of asset and employees is not only significant but has expected signs, while some of the individual coefficients are insignificant or/and exhibit wrong signs. The panel cointegrating vectors from fully modified OLS also indicate that the estimated coefficients of the panel analysis tend to be overvalued and the asset influences the turnover far greater than the employee does.

• Journal of Korea Technology Innovation Society
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• v.16 no.4
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• pp.937-953
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• 2013

The theoretical discussion of generation process and development directions of economic fluctuations are actively discussed. This study describes the economic changes applied to empirical research on economic volatility in Korea under the economic theory of network theory [Acemoglu, et al. 2012, 2010]. For the three years in 2000, 2005, and 2010, the network analysis were applied to industry input-output tables. The research results show that the network economic structures in Korea is shifted from a high connectivity among sectors to a lower connectivity. Also, the impact of key industries and the mutual connectivity of input and out among industrial sectors are weaken. Implications for industry and technology policy are derived form the study results.

• The Journal of the Korea Contents Association
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• v.9 no.3
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• pp.1-8
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• 2009

This paper proposes a new document clustering system using fuzzy logic-based genetic algorithm (GA) and semantic vector expansion technology. It has been known in many GA papers that the success depends on two factors, the diversity of the population and the capability to convergence. We use the fuzzy logic-based operators to adaptively adjust the influence between these two factors. In traditional document clustering, the most popular and straightforward approach to represent the document is vector space model (VSM). However, this approach not only leads to a high dimensional feature space, but also ignores the semantic relationships between some important words, which would affect the accuracy of clustering. In this paper we use latent semantic analysis (LSA)to expand the documents to corresponding semantic vectors conceptually, rather than the individual terms. Meanwhile, the sizes of the vectors can be reduced drastically. We test our clustering algorithm on 20 news groups and Reuter collection data sets. The results show that our method outperforms the conventional GA in various document representation environments.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.259-261
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• 2005

수천개의 Gene Expression Measurement를 생성해 내는 DNA Microarray 연구는 조직과 세포의 표본으로부터 진단에 유용한 Gene Expression 정보를 모으게 된다. 이런 종류의 Data를 분석하기 위하여 SVM(Support Vector Machine)을 사용한 새로운 방법이 연구되어왔다. 본 논문에서는 Gene Expression Data에 대한 고유벡터(Eigen Vector)를 이용하여 SVM의 성능을 향상시키고 질병진단에 유용한 Gene을 찾아 내는 알고리즘을 기술한다. 고유벡터를 통하여 Gene을 선택적으로 SVM Learning에 참가 시키고 분류의 결과를 통하여 추가된 Gene이 질병 진단에 미치는 영향력을 알아냄으로써 질병에 대한 Gene 역할을 파악 하는데 활용할 수 있다.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.1
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• pp.1-10
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• 2006

To reduce the complexity of video transcoder, transcoding techniques generally use intermediate data such as macroblock types, motion vectors, DCT coefficients, which are extracted from incoming video bitstream. In this Paper, we Propose a new adaptive INTRA update scheme utilizing the importance of each macroblock in a given frame. The importance measure is calculated from the motion vectors which are extracted from the decoding procedure of a incomming video data.'rho ratio of the macroblock to be referred by the next frame is calculated by the motion vectors of the next frame and the macroblocks to be refered higher ratio has more effect on the next frame and the followed frames. The proposed scheme can obtain transcoded bitstreams which has better image quality and more improved resilience against transmission errors.

• Journal of the Korean Regional Science Association
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• v.35 no.1
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• pp.47-57
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• 2019

Daegu Metropolitan City has been continuously carrying out core functions of Yeongnam region, and especially plays a role as export base of textile and chemical products in Korea. Also Daegu Metropolitan City has contributed greatly to the expansion of Korea's import and export trade and the growth of the national economy. The purpose of this study is to analyze the influence of major factors affecting GRDP in Daegu Metropolitan City through regression analysis. For this purpose, this study uses the Vector Error Correction Model(VECM) to estimate the long-run equilibrium function that affects the GRDP in Daegu Metropolitan City. This study is meaningful in that it uses the statistics related to Daegu provided by Province of Gyeongsangbuk-do and explains the dynamic characteristics of major factors affecting the GRDP in Daegu.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.383-392
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• 2000

Since late 1970, methods of influence or sensitivity analysis for detecting influential observations have been studied not only in regression and related methods but also in various multivariate methods. If results of multivariate analyses sometimes depend heavily on a small number of observations, we should be very careful to draw a conclusion. Similar phenomena may also occur in the case of incomplete data. In this research we try to study such influential observations in multivariate statistical analysis of incomplete data. Case of principal component analysis is studied with a numerical example.