• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.05a
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• pp.335-356
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• 2017

본 연구에서는 4차 산업혁명에서 가장 중요하게 대두될 수 있는 융합R&D정책에 대해 소셜 네트워크 분석을 통해 새로운 대안을 제시하려고 한다. 연구장비, 연구성과의 자료들을 활용하여 연구장비 네트워크 분석을 실시하여 융합R&D의 특성 및 구조분석을 실시하며, 연구장비 공동활용 및 다학제 협력연구를 통해 창출될 수 있는 새로운 융합R&D정책에 대한 접근을 시도하려고 한다. 나아가, 연구개발과 사업화 사이에서 더욱 중요한 역할을 할 수 있는 분석과학기술에 대한 정책적 플랫폼 구축관점 대한 시사점을 찾아내려고 한다. 이를 위해 계량적 접근과 비계량적 접근을 동시에 활용하여 연구주제에 대한 타당성을 확보할 것이며, 앞으로 미래산업 및 유망기술에 대한 전략적 선별에 있어 일부 근거를 제시해줄 수 있을 것이다. 이러한 연구결과를 통해 우리나라 기초과학 및 기초과학인프라에 대한 발전적 정책방안과 융합연구 및 융합연구의 사업화에 대한 정책적 관점을 제시하도록 한다. 분석자료는 한국기초과학지원연구원(KBSI) 현황자료를 중심으로 살펴보며, 분석방법은 소셜네트워크분석(SNA:Socail Network Analysis)을 활용한다.

• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.181-188
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• 2016

This study investigated consumer convergence preferences for healthcare information service in social media using the multi-attribute utility theory. The multi-attribute utility theory is an approach for compositional modeling attributes wherein researchers compute the overall service utility by aggregating the evaluation results for attribute values. We found that healthcare information service consumers in social media evaluate the service preference through the multi attributes - Update, Cost, Usefulness, Usability, Reliability. And the study shows that individual preference by estimating weight of each attribute in the services influences the service use intention. So we believe that estimating preferences with multi-attribute utility theory will predict business success of the services in a new media, and for a successful business of the social media services marketers should assess the consumer's preference using the multi-attributes.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.4
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• pp.245-262
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• 2015

As the topics of general education in universities become more diverse, it is not an easy task to identify the topics of general education courses. This study aims to identify and visualize the topics of A university's general education courses using informetric analysis methods. 214 syllabi were collected and titles, course introduction, goals, and weekly plans were analyzed. 278 topic words were extracted from the data set and grouped into 8 clusters. In the network analysis, topic clusters were divided into two areas, personal and social. Personal area has 14 sub-topic clusters and social area has 11 sub-topic clusters. In personal area, 'language', 'science', and 'personality' were major topic clusters. In social area, 'multi-culture' cluster was the core cluster with connected to four other clusters. The topic network generated in this study can be used for the university and the university library to enhance general education or to develop collections for general education.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.413-416
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• 2020

COVID-19(Coronavirus Disease 2019)는 RNA 형 바이러스로써 점막감염(粘膜感染)과 비말전파(飛沫傳播)로 전염되는 급성 호흡기성 질병이다. 2019 년 12 월 중국 후베이 우한에서 처음 감염이 보고된 후 빠르게 글로벌로 확산되었고, 현재 여러 국가와 지역이 Lockdown 상태에 있다. COVID-19 의 치사율은 국가별, 연령별 차이는 있으나 사스(SARS-CoV), 메르스(MERS-CoV) 등과 비교하여 높다고 할 수 없다. 그러나 COVID-19 는 신종 코로나바이러스로써 아직 백신(Vaccine)과 항바이러스제가 개발되지 않았고 다른 질병과 비교하여 빠른 감염 속도때문에 의료 공백, 사회적 혼란, 경제적 손실을 크게 일으키고 있다. 따라서 바이러스의 확산 양상을 데이터 분석을 통하여 예측할 수 있다면 사회·경제적인 폐해를 줄일 수 있어 Bass 모델과 R 패키지를 이용하여 COVID-19 확산 예측 모형을 계량적으로 제시하였다.

• Journal of the Korean Institute of Landscape Architecture
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• v.15 no.1
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• pp.39-67
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• 1987

The purpose of this thesis is to suggest objective basic data for the environmental design through the quantitative analysis of the visual quality included in the physical environment of forest landscape. For this, landscape values of forest landscape have been evaluated by using the Iverson method, the images structure of forest landscape's main utilizing space have been analysed by the factor analysis algorithm, degree of visual preferences have been pleasured mainly by questionnaries and SBE method, and finally these thesis can be summarized as fallow LCP with high values of Iverson factors I and IV yield high landscape value. Specifically, Iverson factor IV has been found to play the dominant. For all experimental points, significant seasonal variations in S.D. scale values have been observed. In natural parks, where artificial structures are complementary to the natural landscape, main factors of image are S.D. scales such as the visual sequence, the formal simplicity of structures, the emphasis, the unification of heterogeneous factors and the assimilation. Factors covering the spatial image of natural parks have been found to be the overall evaluation, the individual characteristics, the tidiness, the potentiality, the dignity, the intimacy and the space volume. For all seasons, factors such as the individual characteristics, the dignity, the tidiness, the potentiality, yield high factor scores. As for factors determining the degree of visual preference, variables such as the summit, the skyline, rocks, the water and the degree of natural destruction by artificial structures yield high values for all seasons.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.181-187
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• 2011

In this thesis, digital in-line holographic microscopy has been implemented with enhanced phase shifting technique. It was demonstrated that the zero-order diffraction noise and the twin image can be eliminated by phase-shifting interferometry very effectively. Also the experimental and numerical reconstruction has been incorporated into one set-up operating in real time. Experimental results and the analysis of the phase map indicate that the proposed system can be very useful for the measurement of microscopic objects and 3-D microscopy.

• Journal of Digital Convergence
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• v.13 no.6
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• pp.125-132
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• 2015

It is current situation that a number of issues are being raised how the weight is calculated from customer satisfaction survey. This study investigated how the weight of satisfaction for each quantile is different by comparing ordinary least square regression model to quantile regression model and carried out bootstrap verification to find the influence difference of regression coefficient for each quantile. As the analysis result of using R(Quantreg package) that is open software, it appeared that there was the influence size of satisfaction factor along study result and quantile and there was the significant difference statistically regarding regression coefficient for each quantile. So, to use quantile regression model that offers the influence of satisfaction factor for each customer group along satisfaction level would contribute to plan the quantitative convergence policy for customer satisfaction.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.259-268
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• 2020

The purpose of our study is to conduct a general·quantitative analysis of fandom activities and verify their organization types and effects. The results are as follows. With regard to the comparison of effect size, the variable related to the social and economic field showed the greatest effect size, which was followed by individual behavior and individual mentality. In terms of influential factors of fandom activities, the effect size of positive variables was intermediate level while the effect size of negative variables was low level. In addition, the effect size of fandom supporting idol groups was the greatest, which was followed by of fandoms supporting sports stars, and actors. In terms of the effect size with regard to the influence on fandom among the objects of study, the effect size of university students was the greatest, which was followed by the whole, adult, middle and high school student, and middle school student. Meanwhile, the result of the analysis according to the classification by country showed that China had the greatest effect size, and the US also showed quite a big effect size. On the other hand, South Korea showed a low level of effect size.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.167-198
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• 2022

Convergence science research is activated, and digital humanities research is also encouraged in humanities. Therefore, this study attempted to propose a experimental study that applies Text mining and Entitymetrics methods to historical materials. Annals of King Seonjo, revised Annals of King Seonjo, Miscellaneous Record of the War and Writings on Imjin War were used, also network analysis and DMR topic models were used to explore topic changes and common entities in historical sources. Through the results, it was possible to propose the availability of quantitative analysis for text data, presenting a timing change of a specific topic, and an undiscovered relationship between person entities.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.165-171
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• 2019

The purpose of this study was to analyse a causal relationship between collective emotion and behavior to sport issues in SNS. For the purpose, 5 sports issues with obvious collective behavior and 5 concerned articles in typical portal sites were selected. From those, each 100 comments with highest recommendation and 5 obvious actions made by the crowd were sampled as the analysis subjects. The results of statistical analyses on collective emotion and behavior materials were as follows. First, collective emotions showed differences by the sports issues. Second, there was a significant causal relationship between collective emotion and behavior in SNS. This study could receive a favorable evaluation due to the statistical analysis on a causal relationship between collective emotion and behavior.