As many existing research fields are matured academically, researchers have encountered numbers of academic, social and other problems that cannot be addressed by internal knowledge and methodologies of existing disciplines. Earlier, pioneers of researchers thus are following a new paradigm that breaks the boundaries between the prior disciplines, fuses them and seeks new approaches. Moreover, developed countries including Korea are actively supporting and fostering the convergence research at the national level. Nevertheless, there is insufficient research to analyze convergence trends in national R&D support projects and what kind of content the projects mainly deal with. This study, therefore, collected and preprocessed the research proposal data of National Research Foundation of Korea, transforming the proposal documents to term-frequency matrices. Based on the matrices, this study derived detailed research topics through Latent Dirichlet Allocation, a kind of topic modeling algorithm. Next, this study identified the research topics each proposal mainly deals with, visualized the convergence relationships, and quantitatively analyze them. Specifically, this study analyzed the centralities of the detailed research topics to derive clues about the convergence of the near future, in addition to visualizing the convergence relationship and analyzing time-varying number of research proposals per each topic. The results of this study can provide specific insights on the research direction to researchers and monitor domestic convergence R&D trends by year.

Net neutrality, which has not been a problem, has recently become a problem for ISPs (Internet Service Providers), and their complaints have been paid by domestic platform companies, but overseas global IT companies such as Google and YouTube, generate huge revenues from domestic markets. In this situation, domestic IT companies claim that it is natural to impose more expensive charges or restrict speed on users who generate huge traffic. On the other side, however, the telecommunication network has become an essential public good that is essential to our everyday life, and because it has been given a monopoly position by a private company to efficiently respond to the explosive demand for telecommunication services, It is necessary to provide equal and universal service and fulfill public duty. In this paper, we deal with the network neutrality problem, focusing on the price elasticity between the CP (Contents Provider) and the ISP, rather than the user who is one side of the two-sided market for the already saturated satellites communication market. We present a game model that determines the optimal price for each platform by Nash equilibrium and analyze how the net neutrality affects CP according to the change of exogenous variables through the proposed game model.

It is important to consider interaction between species in understanding structure and function of the biological community. Current ecological issues such as climate change and habitat loss emphasize the significance of the concept of species interaction in that varying species’ interaction across environmental gradients may lead to altered ecological function and services. However, most community studies have focused on species diversity through analysis of quantitative indices based on species composition and abundance data without considering species interactions in the community. ‘Ecological network analysis’ based on network theory enables exploration of structural and functional properties of ecosystems composed of various species and their interactions. In this paper, network analysis of Cheonggye stream as a case study was presented to promote uses of network analysis on ecological studies in Korea. Cheonggye stream has a simple biological structure with link density of 1.48, connectance 0.07, generality 4.43, and vulnerability 1.94. The ecological network analysis can be used to provide ecological interpretations of domestic long-term monitoring data and can contribute to conserving and managing species diversity in ecosystems.

이 연구는 1991년부터 2017년까지 발간된 「교정연구」를 대상으로 언어 네트워크 분석 (Semantic Network Analysis)을 통해 핵심 키워드의 중심성 분석을 하고자 한다. 이를 통해 우리나라 교정학 연구의 경향성을 파악하고 미래의 교정정책에 대한 방향성을 제시해 줄 수 있는 균형 잡힌 연구를 선택하도록 근거를 제공하는데 그 목적이 있다. 분석결과, 전반적으로 ‘교정’, ‘처우’, ‘방안’, ‘수형자’, ‘개선’ 등의 빈도수가 상대적 으로 높다는 것을 알 수 있다. 이는 「교정연구」의 연구주제들이 주로 수형자의 교정처우와 그 개선방안에 관련된 연구들이 많았음을 시사한다고 볼 수 있다. 각 시기별로 분석한 결과를 보면, 1991년부터 2000년까지는 ‘교정’이라는 키워드를 중심으로 ‘방안’, ‘처우’, ‘문제’, ‘방향’ 등의 순으로 연결중심성이 높게 나타났으며, 특히 ‘법’, ‘수형자’, ‘제도’, ‘개선’, ‘실태’, ‘범죄’, ‘행형’ 등의 키워드가 높은 연결관계를 형성하고 있었다. 초기의 연구는 주로 교정관련 제도나 정책, 교정의 이념 및 이론들이 연구주제로 주목받으면서 교정학의 정체성 확립을 위한 기반 연구들이 많이 진행된 것으로 보인다. 2001년부터 2010년 사이에 이루어진 연구들을 살펴보면 ‘교정’이라는 핵심 키워드 를 중심으로 ‘사회’, ‘개선’, ‘방안’, ‘소년’, ‘범죄’, ‘처우’, ‘제도’, 청소년’, ‘시설’, ‘프로그램’, ‘수형자’, ‘고찰’, ‘문제점’, ‘효과’ 등의 키워드가 연결중심성이 높게 나타났 는데, 이 역시 교정과 관련된 법･제도의 개선 및 당시 사회적 관심이 연구주제에 반영 되었다고 볼 수 있다. 특히, 이전 시기와 다르게 ‘프로그램’, ‘효과’, ‘영향’, ‘요인’ 등 의 키워드가 새롭게 등장하였다. 즉, 이 시기에서는 교정학의 연구주제가 프로그램의 효과성 분석이나 수형자 및 소년범 등의 행태에 초점을 맞춘 실증적 연구가 서서히 증대되고 있는 것으로 나타나 교정학 분야에 다양한 경험적 연구들이 다루어지기 시작했다는 것을 알 수 있었다. 또한 이 시기에 ‘지역사회’, ‘약물’, ‘보호관찰’ 등의 키워 드가 새로이 등장하면서, 당시 사회내 처우와 보호관찰 등에 대한 관심이 증가하고 있 었음을 알 수 있었으며, 약물범죄자의 교정 등 수형자의 개별처우 프로그램에 대한 실 증적 연구가 점차 연구주제로 선택되기 시작했음을 알 수 있었다. 마지막으로 2011년부터 2017년까지의 연구에서는 ‘교정’을 중심으로 ‘소년’, ‘방안’, ‘범죄’, ‘수용’, ‘시설’, ‘제도’, ‘재범’, ‘보호’, ‘치료’, ‘개선’, ‘효과’, ‘프로그램’ 등 의 순으로 가장 높은 연결중심성을 보여주고 있다. 2001-2010년 시기와 다르게 ‘소 년’이나 ‘청소년’ 등의 키워드가 연결중심성이 많이 높아진 것으로 분석되었으며, 특 히 이 시기에서는 ‘재범’, ‘치료’, ‘예방’, ‘가석방’ 등의 키워드가 새로이 연구주제로 등장하게 되는데, 이전 시기에 비해 범죄자의 재범방지에 관한 연구와 수형자의 치료 감호 등에 대한 연구주제가 선택되고 있으며, 범죄에 대한 사후적 분석보다 소년비행 이나 성인 범죄에 대한 사전적 예방이 근본적인 범죄대책으로 인식되면서 이에 대한 연구들도 활발히 이루어진 것으로 판단된다.

4차 산업혁명의 시대에 기업들은 다양한 기술들이 복잡하게 융합하면서 진 화하는 기술 환경을 이해하고 이로 인한 비즈니스 환경의 변화에 대응하는 것이 중요하다. 이를 위해 본 연구에서는 최근 기술개발 경쟁이 가속화되고 있는 자동차 분야의 10대 기업을 대상으로, 이들의 최근 6년간 미국등록특허 중 2개 이상의 이종 기술 분야에 동시 분류된 융합특허를 추출하여 소셜네트워크 분석을 수행하였다. 그 결과, 자동차 분 야의 융합에 관계된 기술의 수가 크게 증가하고 있으며, 기술간 융합이 더욱 강하게 이루어지고 있음을 확인하였다. 또한 Volkswagen, Ford, Hyundai 등 3개 기업은 기술융합 의 변화가 큰 기업으로, 특히 친환경 자동차 관련 기술에서 전략의 변화가 있는 것으로 분석되었다. 본 연구는 기업들이 네트워크 분석의 결과를 더욱 의미있게 활용할 수 있는 다양한 방법을 제시한 점에서 연구의 의의가 있다.

As brands’ use of social media to connect with customers becomes increasingly important, there is a need to continually monitor and examine activities in social networks. An important aspect of the social network communications is its unique ways of concentrating and dispersing information among participants (actors) – density and centrality of the network. By looking at both density and centrality, the relationships among actors and their ability to influence others are revealed, allowing deeper understanding into networked behaviors. In this manner, examining whole and ego network patterns, the unique roles of individual actors, can provide brands significant insight in understanding how influencers form and how users connect and spread information. Based on the social network analysis, which represents a combination of theory and analytical methods of networked relationships, this study analyzed Twitter networks of two multi-brand cosmetics and beauty retailers, Sephora (global brand) and Ulta Beauty (U.S. domestic brand). Using NodeXL, daily Twitter data for both brands were gathered to investigate network activities. By examining both ego-networks and the whole networks, the results showed that while ego-networks for brands were quite similar to one another, there was a big difference between the ego-networks and whole networks in regards to the number of actors, type of connectivity, as well as the prominence of brands. Sephora was often not an important part of its hashtag network, and thus was not able to maintain strong control over communications and messages in these networks whereas Ulta maintained its control over its networks. The findings from analyzing these network patterns, the unique roles of individual actors, and the brands within the networks provide significant insights in understanding how influencers form and develop the ability to connect and spread information.

Using social network analysis, the current study examines the image of a unique festival in a well-established tourist destination on the East coast of the United State of America, the Myrtle Beach area of South Carolina. Social Network Analysis (SNA) emphasizes the importance of constructing interconnectedness among concepts and knowledge networks in respondents’ minds (Hanneman & Riddle, 2011; Scott & Carrington, 2011). The technique visualizes complicated perception of tourists in a most simple but scientific way. Using concept maps and degree centralities derived from social network analysis as well as dendrograms, this study provides insights on wine and food festival in Myrtle Beach Area. Together with cluster analysis, the SNA suggests unique contributions to the understanding of tourist behaviour in tourism destination research.

The proliferation of information technologies made it possible to produce information products of different versions at much lower cost comparing to traditional physical products. Thus it is common for information product manufacturers to consider vertically differentiated product line for more profit through improved market coverage. Another salient characteristic of most information product is network externality. Existing researches dealing with vertical differentiation and network externality usually assumed oligopolistic market where vertically differentiated products are provided by competing companies, respectively. Moreover, they analyzed the essentially dynamic characteristic of network externality statically. In this study, different from the previous researches, the vertical differentiation strategy of a monopolistic company under network externality is dynamically analyzed. We used a two-period model to accommodate the dynamic feature of network externality. Based on the two-period model, the profit maximizing solutions are analyzed. The results showed that a monopolistic company has no incentive to differentiate products vertically when the network externality is absent. On the contrary, when the network externality exists, the monopolistic company can derive more profit by vertically differentiating the product line. It is also shown that, for more profit, the monopolistic company should keep the quality difference between the high quality product and the low quality product as greater as possible.

Using network betweenness centrality we attempt to analyze the characteristics of Seoul metropolitan subway lines. Betweenness centrality highlights the importance of a node as a transfer point between any pairs of nodes. This ‘transfer’ characteristic is obviously of paramount importance in transit systems. For betweenness centrality, both traditional betweenness centrality measure and weighted betweenness centrality measure which uses monthly passenger flow amount between two stations are used. By comparing traditional and weighted betweenness centrality measures of lines characteristics of passenger flow can be identified. We also investigated factors which affect betweenness centrality. It is the number of passenger who get on or get off that significantly affects betweenness centrality measures. Through correlation analysis of the number of passenger and betweenness centrality, it is found out that Seoul metropolitan subway system is well designed in terms of regional distribution of population. Four measures are proposed which represent the passenger flow characteristics. It is shown they do not follow Power-law distribution, which means passenger flow is relatively evenly distributed among stations. It has been shown that the passenger flow characteristics of subway networks in other foreign cities such as Beijing, Boston and San Franciso do follow power-law distribution, that is, pretty much biased passenger flow traffic characteristics. In this study we have also tried to answer why passenger traffic flow of Seoul metropolitan subway network is more homogeneous compared to that of Beijing.

In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of gas energy consumption in an air handling unit. To this end, we consider the volatility of the time series and demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the gas consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the gas consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of “context units” in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the gas consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.

본 연구 목적은 마리나항만법을 대상으로 언어 네트워크 방법을 적용하여 법조문에 대한 내용을 분석하고 법률 특징과 구 조적 모습을 계량적으로 제시하는데 있다. 언어 네트워크 분석은 단어와 단어사이의 네트워크 구조를 파악하여 그 구조와 형태를 파악할 수 있으며, 전통적 내용 분석이 지닌 단점을 보완하는데도 용이하다. 분석 대상은 최근 개정된 마리나항만법 전문(1 4장)이며 부분 적으로는 구분된 장중 분석에 의미가 있는 일부(제2장, 제3장, 제4장)로 설정하였다. 분석 결과 마리나항만법은 마리나항만개발에 집중된 구조적 특징을 지니고 있고 마리나산업의 육성에 관한 종합적 관점보다는 하드웨어적 시설적 설치에 집중된 구조를 지니고 있었다. 또한, 사업체 및 인력 양성 등이 일부 포함되었으나 시설 설치보다는 상대적 중요성이 다소 낮은 것으로 나타났다. 다만, 연구 방 법상 법구조적 시각에 국한된 결과만을 도출하는 한계도 있으나, 현재 법률의 구조와 특징을 파악하고 진단함으로써 후속 연구의 기초 자료로 활용될 수 있다는데 의의가 있다. 향후 연구에서는 본 연구 결과를 토대로 마리나 정책에 대한 정부 성과나 추진 실적과 비교등이 진행되기를 기대한다.

We analyzed research topics, temporal distribution of field sites, and researcher network of 1,508 limnology publications in the Korean Journal of Limnology (1968~2012) and the Korean Journal of Ecology and Environment (2013~2017). We found that water quality and sediment, phytoplankton, invertebrates, and fish were major subjects during the study periods. Survey of flora and fauna and physiological experiment of freshwater species were the largest subjects during 1970~80s, while other subjects including production, behavior, modeling, and ecological assessment have been rapidly increased since the 1990s. Most of the biological taxa equally studied lotic and lentic system, however, invertebrates and fish related studies more focused on the lotic system. Spatially, the field site of Korean limnology studies was found to be concentrated in main river channels runs through urban areas and artificial lakes than preserved natural areas. Freshwater system, located at the elevation range of 301~400m(upstream of main channels), had the lowest number of field sites. Collaboration among researchers and different institution types have been steadily increased and expanded as the number of publications increased.

In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of power energy consumption. To this end, we consider the volatility of the time series and apply the sample variance and the detrended fluctuation analyses to the volatilities. We demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the power consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the power consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of “context units” in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the power consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. To further confirm the experimental results, we performed two types of the cross validations designed for the time series data. We also support the validity of the model by analyzing the multi-step forecasting. We found that the prediction errors tend to be saturated although they increase as the prediction time step increases. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.

본 논문에서는 유통 농산물 잔류농약 부적합 현황 분석을 위하여 네트워크 분석 기법을 적용하였다. 분석용 데이터는 『2017년도 식품안전관리지침』내 “유통농산물별 잔류농약 부적합 현황”을 참고하였으며, 주요 분석 기법 으로는 중심성 분석(연결정도 중심성, 근접 중심성, 매개 중심성)을 적용하였다. 연결정도 중심성 분석결과 chlorpyrifos와 diazinon에서 “연결된 노드”가 가장 많은 것으로 확인되었다. 근접 중심성에서는 19종을 제외한 농약성분들 사이에서 유사한 정도를 보여주고 있었다. 매개 중심 성 분석 결과에서는 fluioxonil과 chlorpyrifos가 가장 높은 경향을 보여주어 이들이 농약성분 네트워크에서 “가교” 역 할을 수행 하는 것으로 파악되었다. 네트워크 분석 결과, 기존의 통계분석을 통해서는 분석 할 수 없었던 농약성분 들 사이의 “관계” 데이터를 확인 할 수 있었다. 향후 이러한 분석기법은 최적화/정교화 과정을 통해서 보다 정밀하게 농약성분 부적합 현황 분석을 위한 도구로서 적용되리라 기대한다.

The major purpose of this study is to find and analyze the characteristics of Fisheries Business Administration Research based on using social network analysis. This study examines every paper of The Journal of Fisheries Business Administration from 2007 to 2016. This study analyzes fisheries business administration research through bibliometric data including research trends, researcher characteristics, and key words. The 229 source articles are all papers published from 2007 to 2016 in The Journal of Fisheries Business Administration in Korea. Comparing with previous research, the major research areas of Korean fisheries business administration have a little changed and the topics of recent research are much diversified. Through basically based on frequency analysis and SNA(Social Network Analysis) method, most of the bibliographical characteristics were founded. And based on the result of this study showed that 1) increasement on number of researcher and organization 2) climate change and economic related topics are most popular terms 3) DEA is most adopted methodology in recent papers 4) joint research among the organizations has somewhat been increased 5) human resource management, history of fisheries management and education still have been conducted in terms of sustainability.

Understanding biotic interactions is important to illustrate ecological functions of stream environments. The purposeof this study is to compare the ecological functions of natural and artificial streams. For linking species, we used bioticinteraction databases and made food-webs for species lists of 18 streams in Seoul, Korea. We conducted species removalanalysis of networks and compared network beta-diversity between watersheds. The results showed that natural streamswere more affected by a removal of keystone species than artificial streams. The cheonggye watershed including artificialstreams had high dissimilarities among streams, presenting that artificial streams had different functions from natural streams.

This study conducted a social network analysis to investigate stem cell research which was actively being studied as an alternative for the treatment of intractable diseases due to infinite proliferation and differentiation ability. Papers was extracted from the PubMed database (DB) on the subject of ‘Induced Pluripotent Stem Cells (iPS) and Embryonic Stem Cells (ES)’, and ‘Adult Stem Cell (AS) and Mesenchymal Stem Cell (MS)’. Medical Subject Headings (MeSH) term was filtrated from each area. MeSH term of iPS and ES field was 148 (international), 71 (domestic), otherwise AS and MS were 89 (international), 78 (domestic). Keyword networks were visualized using degree centrality value and the core keywords compared. There was no difference in iPS and ES field compared with the domestic and international high-ranked keywords. Gene Therapy in the international level, Liver Regeneration and the Umbilical Cord in domestic were highly centered. In AS and MS fields, Neuron was high degree centrality both. Time lagged high ranked 30 keywords in slope were different, ‘Adipose Tissue’ increased both, otherwise ‘Stem Cell Transplantation’ did domestically. Although the absolute amounts of the research papers are different, research subjects had become similar to international trends following certain time lags. On the other hand research is conducted on the specific subjects in Korea. Keyword analysis will be useful method for searching a subject to actively being studied in stem cell research area.