• Information and Communications Magazine
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• v.31 no.6
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• pp.69-74
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• 2014

기후변화에 적극 대처하여 지속적이고 안정적인 용수 공급을 위해 기존의 용수 생산 공급망에 정보통신 기술(Information & Communication Technologies, ICT)을 접목한 지능형 물관리를 위해 '스마트 워터 그리드(smart water grid)'를 구축하고자 하는 다양한 노력이 최근 들어 지속되고 있다. 즉, 스마트 워터 그리드는 기존의 수자원 관리 시스템의 한계를 극복하기 위해 첨단 정보통신기술을 이용하는 고효율의 차세대 인프라 시스템으로 다양한 수원을 활용하고 물을 효율적으로 배분 관리 운송하여 수자원의 불균형을 해소하고, 첨단 센서 네트워크를 이용해 실시간으로 수자원망의 안정성을 모니터링하는 등 용수관리 전분야에 걸쳐 양방향 실시간으로 용수정보를 감시 대응하여 용수관리와 에너지 효율의 최적화된 메가시티(mega-city)에 적합한 지능형 물관리가 가능할 것으로 예상되는 시스템이다. 따라서 본 고에서는 선진화된 상수도시스템 운영을 위해서는 현장설비의 관측값을 감시하고 제어하는 시스템에서, 운영 방식이 변경될 때마다 운영 변수간의 인과관계를 분석하고 예측할 수 있는 시뮬레이션 기능이 탑재된 상수도 운영시스템이 요구되고 있는 실정에서 용수공급 시스템의 운영 상황을 모의할 수 있는 모형 개발 및 용수공급시스템의 운영룰 모의 및 운영의사결정에 적용할 수 있는 다중수원 워터루프 시스템과 운영관리할 수 있는 S/W를 개발 내용을 소개하였다.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.131-145
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• 2020

The numbers of SNS (Social Network Service) users and usage amounts are increasing every year. The influence of SNS is increasing also. SNS has a wide range of influences from daily decision-making to corporate management activities. Therefore, proper analysis of SNS can be a very meaningful work, and many studies are making a lot of effort to look into various activities and relationships in SNS. In this study, we analyze the SNS following relationships using Twitter, one of the representative SNS services. In other words, unlike the existing SNS analysis, our intention is to analyze the interests of the accounts by extracting and visualizing the accounts that two accounts follow in common. For this, a common following account was extracted using Microsoft Excel macros, and the relationship between the extracted accounts was defined using an adjacency matrix. In addition, to facilitate the analysis of the following relationships, a direction graph was used for visualization, and R programming was used for such visualization.

• Journal of Korea Port Economic Association
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• v.32 no.3
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• pp.47-66
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• 2016

Once it has been built, a container terminal is impossible to move to another location. It is hard to rectify wrong decisions in a container terminal. This highlights the importance of decision making for a container terminal. The port management about a container terminal has developed from a cargo interface location between sea and land transport, to the standardization of information and procedures due to globalization among global shipping and terminal operators. This research focuses on the current states of market and management for global container terminal operators by investigating up-to-date data for them. The current market states for global container terminal operators are analyzed by using by Herfindahl-Hirschman Index. The analyses of current management states for global container terminal operators are divided into profitability analysis, activity analysis, and bankruptcy risk analysis. Finally, global container terminal operators are clustered into three groups by the current management states.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.508-515
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• 2020

This study examined the research trends of "Microplastic in food" with a scholar databaseusing the centrality analysis method. The data was based on research papers published from 2011 to 2020, sorted by "microplastic" and "food". The centrality analysis methodology(Degree centrality, Closeness centrality, Betweenness centrality) was applied, followed by a keyword-based frequency occurrence analysis. The results suggested that more than 30% of the total keywords were related to "marine" and "pollution". Therefore, research on the effects of microplastic pollution on the ecosystem had mainly been conducted. On the other hand, only 6% of the keywords were related to "toxicity" and "ingestion". Hence,the number of studies on microplastic exposure caused by bioaccumulation or food are still insufficient. These results can be used to provide directions for future research, as well as provide basic data for political decision-making on the environmental hazards of microplastic.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.99-106
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• 2014

Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.99-106
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• 2018

In the process of acquiring information through the cyber ISR (Intelligence Surveillance Reconnaissance) and research into the agent to help decision-making, periodic communication between the C&C (Command and Control) server and the agent may not be possible. In this case, we have studied how to effectively surveillance and reconnaissance. Due to the network configuration, agents planted on infiltrated computers can not communicate seamlessly with C&C servers. In this case, the agent continues to collect data continuously, and in order to analyze the collected data within a short time in When communication is possible with the C&C server, it can utilize limited resources and time to continue its mission without being discovered. This research shows the superiority of incremental learning method over batch method through experiments. At an experiment with the restricted memory of 500 mega bytes, incremental learning method shows 10 times decrease in learning time. But at an experiment with the reuse of incorrectly classified data, the required time for relearn takes twice more.

• Knowledge Management Research
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• v.23 no.1
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• pp.1-26
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• 2022

With the spread of social networks, platform-based social commerce has grown rapidly with the use of multiple smart devices. Given the rapid growth of social commerce sites such as Coupang and Ticket Monster, it is very important to understand the user's purchase decision-making process in a social commerce environment. The purpose of this study is to develop a richer understanding of the goals of users using social commerce. Second, a methodological alternative for analyzing the user's goals is introduced. In this study, laddering interview and means-end chain analysis were used. As a result of interview conducted on 40 users who have more than 6 months of purchasing experience using social commerce, a hierarchical goal map showing the user's goal structure was derived. This map contains 22 ultimate goals of social commerce, including warm relationships with others, fun and enjoyment of shopping, accomplishment, satisfaction, financial saving, and convenience. In addition, there are various paths from activities to ultimate goals, so investigating the goals pursued by users can give us insight into understanding user.

• The Journal of Society for e-Business Studies
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• v.17 no.2
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• pp.129-147
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• 2012

Collaborative filtering (CF), one of the most successful recommendation techniques, has been used in a number of different applications such as recommending web pages, movies, music, articles and products. One of the critical issues in CF is why recommendation performances are different depending on application domains. However, prior literatures have focused on only data characteristics to explain the origin of the difference. Scant attentions have been paid to provide systematic explanation on the issue. To fill this research gap, this study attempts to systematically explain why recommendation performances are different using structural indexes of social network. For this purpose, we developed hypotheses regarding the relationships between structural indexes of social network and recommendation performance of collaboration filtering, and empirically tested them. Results of this study showed that density and inconclusiveness positively affected recommendation performance while clustering coefficient negatively affected it. This study can be used as stepping stone for understanding collaborative filtering recommendation performance. Furthermore, it might be helpful for managers to decide whether they adopt recommendation systems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.515-523
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• 2015

This study reviewed 612 DP LOP(Loss of Position) incident reports which submitted to IMCA from 2001~2010 and identified 103 human error caused incidents and classified it through HFACS. And, this study analysis of conditional probability of human error on DP LOP incidents through application of bayesian network. As a result, all 103 human error related DP LOP incidents were caused by unsafe acts, and among unsafe acts 70 incidents(68.0 %) were related to skill based error which are the largest proportion of human error causes. Among skill based error, 60(58.3%) incidents were involved inadvertent use of controls and 8(7.8%) incidents were involved omitted step in procedure. Also, 21(20.8%) incidents were involved improper maneuver because of decision error. Also this study identified that unsafe supervision(68%) is effected as the largest latent causes of unsafe acts through application to bayesian network. As a results, it is identified that combined analysis of HFACS and bayesian network are useful tool for human error analysis. Based on these results, this study suggest 9 recommendations such as polices, interpersonal interaction, training etc. to prevent and mitigate human errors during DP operations.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.3 s.30
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• pp.61-67
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• 2004

Satellite and aerial images are effectively used to monitor ecological and environmental situation. More and more officials in the Ministry of Environment thus need to utilize these image data for various administrative affairs. However, it is difficult not only to deliver to the officials these image data mostly of large capacity through network but also for them to actively use the delivered data without specialized knowledge in remote sensing and image processing. Therefore, we established a large rapacity image data service system employing image compressive transmission and web-based image processing techniques. This system allows the officials to rapidly access all the associated image data and conveniently utilize the data using various functions implemented for remote sensing, image processing, GIS operations. Consequently, this system have been actively utilized for the decision making processes of the officials and hence accomplished a great reduction in the resources required for the data analysis for various administrative affairs.