• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10B
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• pp.630-638
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• 2005

As real-time media applications based on IP multicast networks spread widely, the end-to-end QoS (quality of service) provisioning for these applications have become very important. To guarantee the end-to-end QoS of multi-party media applications, it is essential to monitor the time-varying status of both network metrics (i.e., delay, jitter and loss) and system metrics (i.e., CPU and memory utilization). In this paper, targeting the multicast-enabled AG (Access Grid) group collaboration tool based on multi-Party real-time media services, a hybrid monitoring scheme that can monitor the status of both multicast network and node system is investigated. It combines active monitoring and passive monitoring approaches to measure multicast network. The active monitoring measures network-layer metrics (i.e., network condition) with probe packets while the passive monitoring checks application-layer metrics (i.e., user traffic condition by analyzing RTCP packets). In addition, it measures node system metrics from system API. By comparing these hybrid results, we attempt to pinpoint the causes of performance degradation and explore corresponding reactions to improve the end-to-end performance. The experimental results show that the proposed hybrid monitoring can provide useful information to coordinate the performance improvement of multi-party real-time media applications.

• Journal of Astronomy and Space Sciences
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• v.30 no.4
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• pp.255-267
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• 2013

In this research, the ground contact opportunity for the fictitious low lunar orbiter is analyzed to prepare for a future Korean lunar orbiter mission. The ground contact opportunity is basically derived from geometrical relations between the typical ground stations at the Earth, the relative positions of the Earth and Moon, and finally, the lunar orbiter itself. Both the cut-off angle and the orbiter's Line of Sight (LOS) conditions (weather orbiter is located at near or far side of the Moon seen from the Earth) are considered to determine the ground contact opportunities. Four KOMPSAT Ground Stations (KGSs) are assumed to be Korea's future Near Earth Networks (NENs) to support lunar missions, and world-wide separated Deep Space Networks (DSNs) are also included during the contact availability analysis. As a result, it is concluded that about 138 times of contact will be made between the orbiter and the Daejeon station during 27.3 days of prediction time span. If these contact times are converted into contact duration, the duration is found to be about 8.55 days, about 31.31% of 27.3 days. It is discovered that selected four KGSs cannot provide continuous tracking of the lunar orbiter, meaning that international collaboration is necessary to track Korea's future lunar orbiter effectively. Possible combinations of world-wide separated DSNs are also suggested to compensate for the lack of contact availability with only four KGSs, as with primary and backup station concepts. The provided algorithm can be easily modified to support any type of orbit around the Moon, and therefore, the presented results could aid further progress in the design field of Korea's lunar orbiter missions.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1908-1918
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• 2022

Recently, ASEAN is not only a new production base but also a consumer market for Korea, and interest in the utilization of production networks in each region is increasing. In particular, urbanization in ASEAN countries is progressing at a relatively fast pace. Each country is promoting smart city projects combined with ICT to improve outdated basic infrastructure facilities such as housing, transportation, logistics, crime prevention, and disaster prevention. The purpose of this study is to develop a web-based smart city export HUB platform so that companies with excellent domestic smart city solutions can participate in smart city construction through networks with ASEAN countries. These platforms can secure the demand for smart city construction in ASEAN countries, and through the establishment of the Korea-ASEAN public-private network, smart cities planned in ASEAN countries can be promoted more innovative. In addition, it is expected to be positioned as a Global smart city platform model by applying to real cities through collaboration with excellent domestic companies.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.375-390
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• 2024

Edge computing architecture has effectively alleviated the computing pressure on cloud platforms, reduced network bandwidth consumption, and improved the quality of service for user experience; however, it has also introduced new security issues. Existing anomaly detection methods in big data scenarios with cloud-edge computing collaboration face several challenges, such as sample imbalance, difficulty in dealing with complex network traffic attacks, and difficulty in effectively training large-scale data or overly complex deep-learning network models. A lightweight deep-learning model was proposed to address these challenges. First, normalization on the user side was used to preprocess the traffic data. On the edge side, a trained Wasserstein generative adversarial network (WGAN) was used to supplement the data samples, which effectively alleviates the imbalance issue of a few types of samples while occupying a small amount of edge-computing resources. Finally, a trained lightweight deep learning network model is deployed on the edge side, and the preprocessed and expanded local data are used to fine-tune the trained model. This ensures that the data of each edge node are more consistent with the local characteristics, effectively improving the system's detection ability. In the designed lightweight deep learning network model, two sets of convolutional pooling layers of convolutional neural networks (CNN) were used to extract spatial features. The bidirectional long short-term memory network (BiLSTM) was used to collect time sequence features, and the weight of traffic features was adjusted through the attention mechanism, improving the model's ability to identify abnormal traffic features. The proposed model was experimentally demonstrated using the NSL-KDD, UNSW-NB15, and CIC-ISD2018 datasets. The accuracies of the proposed model on the three datasets were as high as 0.974, 0.925, and 0.953, respectively, showing superior accuracy to other comparative models. The proposed lightweight deep learning network model has good application prospects for anomaly traffic detection in cloud-edge collaborative computing architectures.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.23-39
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• 2021

This study aims to explore research trends in Blockchain studies in South Korea using dynamic topic modeling and network analysis. To achieve this goal, we conducted the university & institute collaboration network analysis, the keyword co-occurrence network analysis, and times series topic analysis using dynamic topic modeling. Through the university & institute collaboration network analysis, we found major universities such as Soongsil University, Soonchunhyang University, Korea University, Korea Advanced Institute of Science and Technology (KAIST) and major institutes such as Ministry of National Defense, Korea Railroad Research Institute, Samil PricewaterhouseCoopers, Electronics and Telecommunications Research Institute that led collaborative research. Next, through the analysis of the keyword co-occurrence network, we found major research keywords including virtual assets (Cryptocurrency, Bitcoin, Ethereum, Virtual currency), blockchain technology (Distributed ledger, Distributed ledger technology), finance (Smart contract), and information security (Security, privacy, Personal information). Smart contracts showed the highest scores in all network centrality measures showing its importance in the field. Finally, through the time series topic analysis, we identified five major topics including blockchain technology, blockchain ecosystem, blockchain application 1 (trade, online voting, real estate), blockchain application 2 (food, tourism, distribution, media), and blockchain application 3 (economy, finance). Changes of topics were also investigated by exploring proportions of representative keywords for each topic. The study is the first of its kind to attempt to conduct university & institute collaboration networks analysis and dynamic topic modeling-based times series topic analysis for exploring research trends in Blockchain studies in South Korea. Our results can be used by government agencies, universities, and research institutes to develop effective strategies of promoting university & institutes collaboration and interdisciplinary research in the field.

• Korean Journal of Health Education and Promotion
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• v.29 no.2
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• pp.71-81
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• 2012

Objectives: Effective and efficient response for public health crisis necessitate planning how to respond and mobilize the resources in schools. We preformed this study to develop the strategies to improve efficiency of school health education in an outbreak of pandemic disease. Methods: We tried to review the policies, regulations and response systems of all related sectors, and advanced cases associated with pandemic disease control measures by searching databases and on-line networks connected with the Korean Ministry of Education, Science and Technology. Results: It was important to implement a consistent and systematic approach for educational offices and schools to prevent confusion resulted from the inaccurate information. First, the systems and action plans for school health should be established to prepare and respond to an outbreak of pandemic disease. Secondly, the strategies to improve the efficiency of school health education in public health crisis should be in place. Finally, the personnel pool would be needed to provide the crisis management programs. Conclusion: In order for staffs and students to have abilities to respond in an outbreak of pandemic disease, comprehensive school health approaches and efficient educational efforts should be prepared in collaboration with related sectors.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.15 no.5
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• pp.1-17
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• 2012

This study sought to discover new directions for management and operation national urban parks in Korea by analyzing the reality of the national government parks of Japan where these parks are already well established and managed. In the case of a Japanese national government park, its supporting system was established after the park was built. The means of management also shifted their direction from putting more priority to the administrative body to the residents. The management practices are changing process of its character with focus on residents as the main entity of activity from their existing position of participants. In other words, the national government parks of Japan are going beyond the previous practice of providing maintenance activities to providing experience, interpretation functions to these activities. Especially, they were establishing local networks to plan and execute programs in collaboration with the park management and NPOs. However, they fall short of tangible outcomes despite their continuous efforts to expand the community involvement and reduce the cost in maintenance. To facilitate the effective management of the urban parks in Korea in the near future, much thought needs to go into the management practices ensuring conservation of resources in the land of Korea, as well as people's use of recreation, community revitalization, and development and transfer of advanced technology to provide appropriate preparations to create urban parks in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3446-3451
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• 2011

Nowadays, industry clusters have been considered as critical factors for regional competitiveness and economic revitalization. It should be important to evaluate strategic positioning and establish competition strategies for Korean industry clusters. I proposed strategic positioning, identified problems, and established strategic directions by analyzing potential attractiveness based on growth and productivity and retained capabilities of proximity, networks, correlation and revenue increase for 7 regional industry clusters. In addition, I analyzed best practices of global industry clusters to provide implications on establishing competition strategies.

• Journal of Digital Convergence
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• v.12 no.7
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• pp.267-272
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• 2014

Many people have used a internet at various purposes. Internet have been used the optimal space to share informations by information producer or consumer. But, recently, through the development of networks and devices, The Internet is expanding beyond PCs and mobile devices into enterprise assets such as field equipment, and consumer items such as cars and televisions. The Internet of Things will enable forms of collaboration and communication between people and things, and between things themselves, hitherto unknown and unimagined. This paper presents various meanings of IoT, and describe the electronic and car domain of internet of things.