• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.185-192
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• 2004

This paper presents face recognition using vector quantization in the eigenspace of the faces. The existing eigenface method is not enough for representing the variations of faces. For making up for its defects, the proposed method use a clustering of feature vectors by vector quantization in eigenspace of the faces. In the trainning stage, the face images are transformed the points in the eigenspace by eigeface(eigenvetor) and we represent a set of points for each people as the centroids of vector quantizer. In the recognition stage, the vector quantizer finds the centroid having the minimum quantization error between feature vector of input image and centriods of database. The experiments are performed by 600 faces in Faces94 database. The existing eigenface method has minimum 64 miss-recognition and the proposed method has minimum 20 miss-recognition when we use 4 codevectors. In conclusion, the proposed method is a effective method that improves recognition rate through overcoming the variation of faces.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.2
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• pp.179-194
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• 2009

The spatial distribution of crime incidences in urban neighborhoods is a reflection of their socio-economic environment and spatial inter-relations. Spatial interactions between offenders and victims lead to spatial autocorrelation of the crime incidences. The spatial autocorrelation among the incidences biases the interpretation of the ecological model in OLS framework. This research investigates residential crimes using residential burglaries and robberies occurred in the city of Columbus, Ohio, for 2000. In particular, the spatial distribution of incidence rates of residential crimes are accounted in OLS framework using eigenvectors, which reflect spatial dependence in crime patterns. Result presents that handling spatial autocorrelation enhanced model estimation, and both economic deprivation and crime opportunity are turned out significant in estimating residential crime rates.

• Journal of Korea Port Economic Association
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• v.32 no.1
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• pp.17-28
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• 2016

This study examines the cruise course network structure in the Asian regions and the centrality of ports using social network analysis (SNA). For network analysis of Asian cruise courses, a data network of cruise courses was constructed using data on courses of cruise ships operating in Asian ports collected from the reports of the Cruise Lines International Associations.There are 249 nodes or ports of ship companies that provide cruise courses to Asia between from October 2015 to June 2016, and these nodes connect 545 ports. Density analysis based on ports where cruise ship companies operated cruise ships showed that, from October 2015 to June 2016, the density was 0.009, which was lower than the average of global port network density (2006 to 2011) and railroad network density. In addition, was calculated to be, which means that connection with all ports was possible through 2,180 steps. In the analysis of the Asian cruise course network centrality, Singapore ranked first in both out-degree and in-degree in connection centrality, followed by Hong Kong, Shanghai, Ho Chi Minh, and Keelung. Singapore also ranked first in the result betweenness centrality analysis, followed by Penang, Dubai, and Hong Kong. From October 2015 to June 2016, the port with the highest Eigenvector centrality was Hong Kong, followed by Ho Chi Minh, Singapore, Shanghai, and Danang. In the case of the domestic ports Incheon, Busan, and Jeju, connection centrality, betweenness centrality, and Eigenvector centrality all ranked lower than their competitor Chinese ports.

• 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.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.2
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• pp.99-117
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• 2017

The present study positively analyzed the hyperlinks of 32 web sites with the purpose of analyzing the hyperlink network structure of web sites for each domestic library type. After collecting the hyperlink data using the crawler, we analyzed the overall characteristics of the websites in the network based on the characteristics of the library. The results are as follows. 1) Among all analyzed libraries, Yonsei scored the highest in degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. 2) By library type, Sejong for national library, Seoul for public library, and Yonsei for college library appeared an influential a relatively. Based on these analysis results, the present study will be utilized as basic data for establishing an operation strategy that improves the efficiency and effectiveness of library web sites in the future.

• Information Systems Review
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• v.20 no.3
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• pp.1-16
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• 2018

MICE (Meetings, Incentive trip, Convention and Exhibition & Event) industry is a multifaceted industry with a variety of stakeholders including the public and private sectors, and PCOs (Professional Convention Organizers) play a mediating role in communicating opinions of the stakeholders. For enhancing their reliability and awareness, PCOs have their stakeholders' hyperlinks on the websites. This study attempted to analyze the hyperlink networks among PCOs (Professional Convention Organizers) and their stakeholders so as to understand the MICE industry ecosystem and find out whether the network structure of PCOs' shows different levels of hyperlink use with their stakeholders' websites based upon PCO's performance and size. The results showed the hyperlink network of MICE industry and that the bigger PCOs have higher centralities in the network.

• Journal of the Korean Society for information Management
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• v.37 no.2
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• pp.71-93
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• 2020

Today, in order to more effectively cope with the emergence of various diseases and the rapidly-changing medical environment, several medical departments are conducting treatment collaborations within the university hospital. This collaborative care is very important and is already common in the medical field. Nevertheless, there is no research on this, especially how the departments are collaborating. Therefore, the purpose of this study is to investigate how the characteristics of the treatment collaboration networks vary by year and season by exploring the relationship between the medical departments within the university hospital. This study analyzed the collaboration networks of 29 medical departments of 'A' university in Korea by dividing the collaborative care by year and season. Directed networks were constructed in response to departments requesting and departments requested for collaborative care. Betweenness centrality, eigenvector centrality, closeness centrality analysis, ego network analysis, and faction analysis were also conducted. This study performed the first treatment collaboration network analysis among medical departments, and is expected to present new insights into the location and spatial composition of medical departments in consideration of the knowledge transfer paths within medical institutions.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.25-52
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• 2018

This study performs social network analysis based on consumer sentiment related to a location in Seoul using data reflecting consumers' web search activities and emotional evaluations associated with commerce. The study focuses on large commercial districts in Seoul. In addition, to consider their various aspects, social network indexes were combined with the trading area's public data to verify factors affecting the area's sales. According to R square's change, We can see that the model has a little high R square value even though it includes only the district's public data represented by static data. However, the present study confirmed that the R square of the model combined with the network index derived from the social network analysis was even improved much more. A regression analysis of the trading area's public data showed that the five factors of 'number of market district,' 'residential area per person,' 'satisfaction of residential environment,' 'rate of change of trade,' and 'survival rate over 3 years' among twenty two variables. The study confirmed a significant influence on the sales of the trading area. According to the results, 'residential area per person' has the highest standardized beta value. Therefore, 'residential area per person' has the strongest influence on commercial sales. In addition, 'residential area per person,' 'number of market district,' and 'survival rate over 3 years' were found to have positive effects on the sales of all trading area. Thus, as the number of market districts in the trading area increases, residential area per person increases, and as the survival rate over 3 years of each store in the trading area increases, sales increase. On the other hand, 'satisfaction of residential environment' and 'rate of change of trade' were found to have a negative effect on sales. In the case of 'satisfaction of residential environment,' sales increase when the satisfaction level is low. Therefore, as consumer dissatisfaction with the residential environment increases, sales increase. The 'rate of change of trade' shows that sales increase with the decreasing acceleration of transaction frequency. According to the social network analysis, of the 25 regional trading areas in Seoul, Yangcheon-gu has the highest degree of connection. In other words, it has common sentiments with many other trading areas. On the other hand, Nowon-gu and Jungrang-gu have the lowest degree of connection. In other words, they have relatively distinct sentiments from other trading areas. The social network indexes used in the combination model are 'density of ego network,' 'degree centrality,' 'closeness centrality,' 'betweenness centrality,' and 'eigenvector centrality.' The combined model analysis confirmed that the degree centrality and eigenvector centrality of the social network index have a significant influence on sales and the highest influence in the model. 'Degree centrality' has a negative effect on the sales of the districts. This implies that sales decrease when holding various sentiments of other trading area, which conflicts with general social myths. However, this result can be interpreted to mean that if a trading area has low 'degree centrality,' it delivers unique and special sentiments to consumers. The findings of this study can also be interpreted to mean that sales can be increased if the trading area increases consumer recognition by forming a unique sentiment and city atmosphere that distinguish it from other trading areas. On the other hand, 'eigenvector centrality' has the greatest effect on sales in the combined model. In addition, the results confirmed a positive effect on sales. This finding shows that sales increase when a trading area is connected to others with stronger centrality than when it has common sentiments with others. This study can be used as an empirical basis for establishing and implementing a city and trading area strategy plan considering consumers' desired sentiments. In addition, we expect to provide entrepreneurs and potential entrepreneurs entering the trading area with sentiments possessed by those in the trading area and directions into the trading area considering the district-sentiment structure.

• The Journal of shipping and logistics
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• v.34 no.4
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• pp.527-544
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• 2018

In this study, SNA analysis was conducted to examine changes in passenger movements in domestic coastal shipping. The validity of derivation of centrality rankings was enhanced by using the connection centrality that reflected weights, which had not been applied in previous research. The results of the connection centrality analysis indicated that the network composition ratio of the South Sea region was high, and the results of analysis of betweenness centrality indicated that ports belonging to the South Sea region recorded high ranks. Jeju Island, which acts as a gateway to the West Sea and the South Sea, Mokpo, which acts as a gateway between the land and islands, those ports that are geographically close to the land, and those ports that are smoothly connected to small ports, were shown to have betweenness centrality. Meanwhile, in the results of analysis of eigenvector centrality, not only ports in the South Sea region but also many ports in the West Sea region were included in the high ranked ones. Using these results, the port authority can identify major ports in domestic coastal shipping, determine the priorities support, identify the current situation of the port connection relations, and establish strategies for management of key development areas. As future studies, studies in the aspect of economy that separate general passengers and island passengers and utilize data such as fares, distances, and time are necessary.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.29-42
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• 2020

The purpose of this study is to present a qualitative research method for extracting and analyzing the comments written by YouTube video users. To do this, we used YouTube users' feedback to measure the hedonic, social, and utilitarian gratification of use and gratification theory(UGT) through by using analysis and topic modeling. The result of the measurement found that the first reason why users watch the trot singer, Cho Myung-sub's video in the KBS Korean broadcasting channel is to achieve hedonic gratification with high frequency. In word-document network analysis, the degree of centrality was high in words, such as 'cheering', 'thank you', 'fighting', and 'best'. Betweenness centrality is similar to the degree of centrality. Eigenvector centrality also shows that words such as 'love', 'heart', and 'thank you' are the most influential words of users' opinions. The results of the centrality analysis present that the majority of video users show their 'love', 'heart' and 'thank you' for the video. it indicates that the high words in centrality analysis is consistent with the high frequency words of hedonic and social gratification dimension of the UGT. The study has research methodological implication that shed light on the motivations for watching YouTube videos with UGT using text mining techniques that automate qualitative analysis, rather than following a survey-based structural equation model.