• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.715-720
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• 2023

The military is driving innovative changes such as AI, cloud computing, and drone operation through the Fourth Industrial Revolution. It is expected that such changes will lead to a rapid increase in the demand for information exchange requirements, reaching all lower-ranking soldiers, as networking based on IoT occurs. The flow of such information must ensure efficient information distribution through various infrastructures such as ground networks, stationary satellites, and low-earth orbit small communication satellites, and the demand for information exchange that is distributed through them must be appropriately dispersed. In this study, we redefined the DSCP, which is closely related to QoS (Quality of Service) in information dissemination, into 11 categories and performed research to map each cluster group identified by cluster analysis to the defense "information exchange requirement list" on a one-to-one basis. The purpose of the research is to ensure efficient information dissemination within a multi-layer integrated network (ground network, stationary satellite network, low-earth orbit small communication satellite network) with limited bandwidth by re-establishing QoS policies that prioritize important information exchange requirements so that they are routed in priority. In this paper, we evaluated how well the information exchange requirement lists classified by cluster analysis were assigned to DSCP through M&S, and confirmed that reclassifying DSCP can lead to more efficient information distribution in a network environment with limited bandwidth.

• The Journal of Engineering Geology
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• v.31 no.3
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• pp.307-319
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• 2021

Although it is currently conducting slope management and research using digital technologies such as drones, big data, and artificial intelligence, it is still somewhat insufficient and is still vulnerable to slope failure. For this reason, it is inevitable to present the development direction for research on prediction and analysis of slope failure using the digital technologies to effectively deal with slope failure, which requires a preemptive understanding of prediction and analysis of slope failure. In this paper, we collected literature data based on the Web of Science for five years from January 1, 2016 to December 31, 2020 and analyzed by co-word analysis to identify the domain structure of research on prediction and analysis of slope failure. Detailed subject areas were identified through network analysis, and the domain relationships between keywords were visualized to derive global and regionally oriented keywords through relationship, centrality analysis. In addition, the clusters formed by performing cluster analysis were displayed on the multidimensional scailing map, and the domain structure according to the correlation between each keyword was presented. The results of this study reveal the domain structure of research on prediction and analysis of slope failure, and are expected to be usefully used to find future research directions.

• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.41-50
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• 2020

Sentimental analysis begins with the search for words that determine the sentimentality inherent in data. Managers can understand market sentimentality by analyzing a number of relevant sentiment words which consumers usually tend to use. In this study, we propose exploring performance of feature selection methods embedded with Particle Swarm Optimization Multi Objectives Evolutionary Algorithms. The performance of the feature selection methods was benchmarked with machine learning classifiers such as Decision Tree, Naive Bayesian Network, Support Vector Machine, Random Forest, Bagging, Random Subspace, and Rotation Forest. Our empirical results of opinion mining revealed that the number of features was significantly reduced and the performance was not hurt. In specific, the Support Vector Machine showed the highest accuracy. Random subspace produced the best AUC results.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.32-32
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• 2020

하나의 수계 또는 용수구역 내에서 작물생육기간 동안 지하수자원 수요량의 집중적인 증가로 인해 지역적 지하수 고갈이 발생하여 농작물 피해가 발생하고 있으며 과잉양수로 인한 지하수위 하강으로 사용자간 갈등도 빈번하다. 또한, 기후변화로 인해 극한기후인 가뭄의 잦은 발생은 이러한 현상을 가속화 한다. 지하수 산출성이 좋은 대수층의 공간적 분포는 복잡한 지질구조로 인해 균일하지 않으며 같은 대수층 내에서도 양수 위치에 따라 산출성은 다르게 나타난다. 이러한 지하수 수요와 공급 및 대수층 분포로 인한 지하수자원 불균형의 해소를 위해 지하수가 풍부한 지역에서 부족한 지역으로 지하수를 공급하는 방법을 적용할 수 있다. 이때 기술적용 지역의 지하수 사용 상황 및 공급 가능량을 정량적으로 평가하고 이를 기반으로 지하수 공급을 제어하는 것이 매우 중요하다. 지하수자원의 수요-공급 불균형이 발생할 때 즉각적으로 대응하기 위해서는 실시간으로 지하수 현황을 감시하고 이를 기반으로 공급 가능량을 산정할 필요가 있으며 이는 정보통신기술(Information and Communication Technology, ICT)에 기반한 관정연계관리체계(Well Network System, WNS)를 구성하는 기술 중 하나인 관정군집제어 기술로 구현될 수 있다. 수계 내에 설치된 기존의 양수정과 새롭게 추가된 관측정들을 4G LTE 네트워크를 통해 하나의 관정군으로 묶고 중앙 서버를 통한 자료 분석 및 양수 펌프 제어를 통해 대수층의 공급 능력과 사용자의 수요 현황에 따른 지하수자원의 체계적 분배를 구현하고자 하였다. 관정군집제어는 관정별 지하수위 및 양수정 양수량을 실시간으로 관측하고 이를 분석서버에 전송하여 해당 지하수계의 공급 가능량 및 인접관정 간섭 등을 분석하여 양수정의 펌프를 실시간으로 제어하고 양수된 지하수를 수요 지역으로 이송한다. 본 연구를 통해 관정군집제어 기술의 구현에 필요한 구성요소를 정의하고 이에 대한 구현 방법을 기술하여 WNS를 구성하는 하나의 요소기술 모델로 제시하고자 하였다.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.49-63
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• 2017

Interdisciplinary convergence research is widely seen as a collaborative research between different disciplines, which is often driven by common agenda or problems in pursuit of a particular common objective. Thus, the purpose of interdisciplinary cooperation in convergence research is to bring each discipline's unique perspective together with the academic expertise of researchers in order to share common problems that cannot be solved effectively without research partnership. We present empirical evidence on how interdisciplinary research relationships are formed to facilitate research networking in convergence relations. In particular, we used network analysis to investigate how interdisciplinary linkages and convergence research networks has formed over time. We found that the convergence research networks were implemented by the interdisciplinary convergence research support program as intended. We did find that research field with high indegree and outdegree in a network played critical roles on the dynamics and degree of interdisciplinarity. Finally, we could find evidence that the role of liaison brokers triggered relational dynamics in interdisciplinary research collaboration.

• Informatization Policy
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• v.21 no.1
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• pp.17-34
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• 2014

The study on the structure of personal information flows is very important because government can measure and respond the risks caused by companies which collect personal information from other personal data users to operate their business. Recently, as the value of personal information is increasing, number of companies which intend to process a large scale of personal information is increasing too. Accordingly, the issue on the structure of personal data flow has become important for the leading personal information processors which receive far more personal information from others to comply the personal information protection laws. However, research on this issue has rarely performed so far. Therefore, this study proposes a framework for personal information data flow structure based on network theory. Theoretically, the results of the study may contribute to extending the application areas of the network theory to personal information area. Practically, the study may contribute to assisting regulatory authorities to find and monitor personal information processors.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.539-547
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• 2019

This study investigated the effect of small-world structure in team processes on team performance. I discussed the theoretical relationship between small-world structure in team processes and team performance and analyzed the relationship using pass data of soccer teams. I constructed the 128 pass networks from the pass data of the 2014 FIFA World Cup and then measured the structural features indicating small-world structure of the networks. Correlation analysis and regression analysis were performed in order to examine the strength and direction of the relationship. According to the results, the clustering has an exponential relationship with team performance and the connectivity has a log-function relationship with team performance. Finally, I found the positive effect of small-world structure in team processes on team performance. Through theoretical discussion and empirical analysis, this study found that small-world structure in team processes increase team performance by facilitating task coordination and collaboration between team members.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.403-428
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• 2023

This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.9-14
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• 2018

This study aims to investigate an importance of Author keyword with analysis the position of author keyword. An analysis was carried out on the position of author keyword. we examined an importance of Author keyword by using degree centrality, closeness centrality, betweenness centrality, eigenvector centrality. In the next stage, we performed analysis on correlation between network centrality measures and the position of keyword. As a result, degree centrality, closeness centrality, betweenness centrality, eigenvector centrality both has a high value in 4th author keyword order. eigenvector centrality was the comparatively effective method to separate of author keyword order method than other 3 centrality. Correlation analysis result shows that the network analysis value are increasing in order. This study has significance in that it was able to examine the author keyword behavior. Future research is needed to identify and supplement future situational factors, behavior, and psychology.

• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.37-48
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• 2014

Social emotion is being highlighted as an important factor of human life in terms of quality of communication as a variety of social networks are commonly used. To understand such social emotion, this study verifies and analyzes the significance of lexical meaning and expression of emotion basically for understanding of complex meaning of social emotion. The emotional expressions represented in SNS text messages, one of the major channel of communication, are examined in this study to create scales of meaning and expression and to understand the differences deeply. As a result of the analysis, it turned out that negative assessment factors were more than positive ones among social emotional factors while positive ones were outstandingly many in the case of social emotional expression. Social emotional factors were classified by basic emotional elements and valences while emotional expression included complex meaning and especially positive elements were dominant in general.