• Journal of information and communication convergence engineering
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• 제19권4호
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• pp.241-247
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• 2021

Particulate matter has emerged as a serious global problem, necessitating highly reliable information on the matter. Therefore, various algorithms have been used in studies to predict particulate matter. In this study, we compared the prediction performance of neural network models that have been actively studied for particulate matter prediction. Among the neural network algorithms, a deep neural network (DNN), a recurrent neural network, and long short-term memory were used to design the optimal prediction model using a hyper-parameter search. In the comparative analysis of the prediction performance of each model, the DNN model showed a lower root mean square error (RMSE) than the other algorithms in the performance comparison using the RMSE and the level of accuracy as metrics for evaluation. The stability of the recurrent neural network was slightly lower than that of the other algorithms, although the accuracy was higher.

• 한국산업보건학회지
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• 제10권2호
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• pp.1-17
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• 2000

We investigated dissatisfaction of elements of local exhaust system, needs for local exhaust system, and information networks for local exhaust system from June 1998 to September 1999 using the questionnaire structured. It contained questions concerning general characteristics of factory and local exhaust system, troubles and dissatisfaction of elements of local exhaust system, and information networks for local exhaust system. The collected data were analyzed by descriptive statistics analysis. Information networks for local exhaust system were analyzed by multidimensional scaling using path distance of network analysis and by graph analysis using Krackplot. Among complaints of local exhaust system, that of duct has show the highest percentage of complaint. In the information network for local exhaust system, Seoul is positioned in the center of network with mediating role.

• 산업공학
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• 제18권3호
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• pp.277-287
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• 2005

In this paper, we deal with a new techno-economic modeling and analysis for optical access networks. In deploying the fiber-to-the-home (FTTH) architecture, network planner needs to consider the following techno-economic issues: when do we need to upgrade existing local access network to FTTH network? how much do we invest to maximize profit? In order to answer these techno-economic questions, we need to consider the impact of emerging technologies and business environment. Toward this end, we develop a new techno-economic modeling to deal with the inherent complexity of technology evolution and cost economics. In particular, the new modeling approach provides us with an techno-economic analysis of technology alternatives such as ethernet passive optical network (E-PON) and wavelength division multiplex passive optical network (WDM-PON). In this analysis, we focus on the impact of critical factors such as the cost characteristic of proposed architecture and digital subscriber line (DSL) subscriber's churn-in to FTTH service and churn-out. We develop mixed integer-programming models for finding the evolution path of local access networks to broadband network architectures.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.139-142
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• 2005

Recently research interest in Knowledge Management (KM) has grown rapidly. Companies regard intellectual capital as important asset and strive to deploy KM in an organization to gain a competitive edge. Many organizations currently engage in knowledge management in order to leverage knowledge both within their organization and externally to their shareholders and customers. Most of the previous research related to KM are dedicated to investigate the role of information technology in extracting, capturing, sharing, coverting organizational knowledge. Knowledge workers, however, are paid less attention though they are the key players in KM activities such as knowledge creation, dissemination, capture and conversion. We regard knowledge workers as a major component of KM and starting point of understanding organizational knowledge activities. Therefore we adopt a method to understand and analyze knowldge workers' social relationships. In this paper we investigate Social Network Analysis (SNA) as a tool for analyzing knowledge network. We introduce the basic concept of SNA and suggest a framework for implementing knowledge network by explaining how SNA can be used for analyzing knowledge network. We also propose a numerical method for identifying knowledge workers using SNA after classifying knowledge workers. The suggested method is expected to help understanding key knowledge players within an organization.

• Journal of Information Science Theory and Practice
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• 제10권spc호
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• pp.12-24
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• 2022

This study attempted to investigate changes in collaboration structure for each stage of national Research and Development (R&D) in the artificial intelligence (AI) field through analysis of a co-author network for papers written under national R&D projects. For this, author information was extracted from national R&D outcomes in AI from 2014 to 2019. For such R&D outcomes, NTIS (National Science & Technology Information Service) information from the KISTI (Korea Institute of Science and Technology Information) was utilized. In research collaboration in AI, power function structure, in which research efforts are led by some influential researchers, is found. In other words, less than 30 percent is linked to the largest cluster, and a segmented network pattern in which small groups are primarily developed is observed. This means a large research group with high connectivity and a small group are connected with each other, and a sporadic link is found. However, the largest cluster grew larger and denser over time, which means that as research became more intensified, new researchers joined a mainstream network, expanding a scope of collaboration. Such research intensification has expanded the scale of a collaborative researcher group and increased the number of large studies. Instead of maintaining conventional collaborative relationships, in addition, the number of new researchers has risen, forming new relationships over time.

• 한국정보보호학회:학술대회논문집
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• 한국정보보호학회 1996년도 종합학술발표회논문집
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• pp.65-74
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• 1996

Risk analysis is time-consuming and expensive process〔1〕〔6〕. Automated risk analysis tools have been widely used in industry and government to support decision making process and reduce cost. However, difficulties in materializing impact of threats and fast-changing network environments make analysis process more complicated and less trusted since impacts are relative in network environments. HAWK system is developed to improve the accuracy of analysis result in network-oriented environment. It provides user-friendly environments and considers network environments as primary assets.

• 한국컴퓨터정보학회논문지
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• 제24권7호
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• pp.125-133
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• 2019

Because military weapons systems for special purposes are small and complex, they are not easy to maintain. Therefore, it is very important to maintain combat strength through quick maintenance in the event of a breakdown. In particular, naval ships are complex weapon systems equipped with various equipment, so other equipment must be considered for maintenance in the event of equipment failure, so that skilled maintenance personnel have a great influence on rapid maintenance. Therefore, in this paper, we analyzed maintenance data of defense equipment maintenance information system through text mining and social network analysis(SNA), and tried to identify the naval ship maintenance expertise. The defense equipment maintenance information system is a system that manages military equipment efficiently. In this study, the data(2,538cases) of some naval ship maintenance teams were analyzed. In detail, we examined the contents of main maintenance and maintenance personnel through text mining(word cloud, word network). Next, social network analysis(collaboration analysis, centrality analysis) was used to confirm the collaboration relationship between maintenance personnel and maintenance expertise. Finally, we compare the results of text mining and social network analysis(SNA) to find out appropriate methods for finding and finding naval ship maintenance expertise.

• 한국정보시스템학회지:정보시스템연구
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• 제31권1호
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• pp.115-146
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• 2022

Purpose The purpose of this study is to find meaningful insights using regression analysis to resolve the digital divide between generations. In the analysis process of this study, social network analysis was applied to approach it with a perspective differentiated from the existing statistical techniques. Design/methodology/approach This study used a social network analysis methodology that transforms and analyzes government-led survey data into relational data. First, the cross-sectional data were converted into relational data, and a continuous core-periphery model and multidimensional scaling method were applied. Afterwards, the relationship between various factors affecting the digital divide and the difference in influence were analyzed by generation. Findings According to the network analysis results, it can be seen that all generations commonly use 'information and news search' and 'living information service'. However, it can be seen that the centrally used services of each generation are clearly different from each other, and the degree of linkage between the services is also clearly different. In addition, it can be seen that the relationship between factors influencing the digital divide by generation is also different.

• 한국정보시스템학회지:정보시스템연구
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• 제21권4호
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• pp.109-132
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• 2012

Social Network Analysis is an increasingly important part of a broader 'toolbox' of evaluation methods available to R&D policymakers to support decision-making. The aim of this research is to be an accessible, 'beginner's guide' to social network theory and application in the area of mobile telecommunication research and development (R&D) decision-making. This research suggests the methodology of investigation into new technology, and the methodology suggested by this research is believed to be a meaningful first step toward the establishment of the information analysis structure, which is in desperate need.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (3)
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• pp.142-144
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• 2004

To provide more qualified data service on the HFC(Hybrid-Fiber Coaxial) access network, the channel characteristics of upstream transmission band should be carefully investigated and analysed. It will be easier to do network management if the monitoring system for noise measurement in the network is available, In this paper, noise analysis method and the frequency selection method in the upstream band for duplex transmission are suggested. And, Data aquisition device for the signal measurement Is implemented. With this network monitoring system, field test and the result from the collected data are described.