• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3159-3161
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• 1999

This paper aims at developing remote control system to control and monitor distributed various devices through internet or information communication network. SNMP (Simple Network Management Protocol) and UPS (Uninterruptible Power Supply) are adopted for network management protocol and applied device, respectively. For controlling and monitoring distributed devices in real-time, Java-environment software is constructed. Also, general-use interface controller between network device and applied device is proposed. Finally, serial communication such as RS-232 and RS-485 is used between controller and applied device.

• Journal of the Korea Safety Management & Science
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• v.25 no.1
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• pp.1-6
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• 2023

This study tried to analyze the keywords of the papers published in the Korea Safety Management Science by using the social network analysis. In order to extract the keywords, information on journal articles published from 2018 to 2021 was extracted from the SCIENCE ON. Among the keywords extracted from a total of 129 papers, the keywords with similar meanings were standardized. The keywords used in the same paper were visualized by connecting them through a network. Four centrality indicators of the social network analysis were used to analyze the effect of the keyword. Safety, Safety management, Apartment, Fire hose, SMEs, Virtual reality, Machine learning, Waterproof time, R&D capability, and Job crafting were selected as the keywords analyzed with high influence in the four centrality indicators.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.467-468
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• 2023

현재 게임 시장에서 VR 게임이 가지는 영향력은 점차 증가하는 추세이다. 기존의 VR게임들은 대부분 Multi-Play를 지원하지 않는다. 이에 따라 본 논문에서는 Photon Network와 XR Plugin을 사용하여 2명의 플레이어가 함께 즐길 수 있는 Arcade 장르의 VR 경쟁 Multi-Game을 구현하였다. 이에 필요한 서버는 리슨 서버 방식으로 Master Client가 게임을 시작하면, Game에 참가한 다른 Client Player는 Photon Network의 RPC 기능을 사용하고 Player의 동작, Game 진행 상황 등을 실시간으로 Server에 동기화하여 Multi-Play게임을 할 수 있다.

• BMB Reports
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• v.41 no.3
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• pp.184-193
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• 2008

Living organisms are comprised of various systems at different levels, i.e., organs, tissues, and cells. Each system carries out its diverse functions in response to environmental and genetic perturbations, by utilizing biological networks, in which nodal components, such as, DNA, mRNAs, proteins, and metabolites, closely interact with each other. Systems biology investigates such systems by producing comprehensive global data that represent different levels of biological information, i.e., at the DNA, mRNA, protein, or metabolite levels, and by integrating this data into network models that generate coherent hypotheses for given biological situations. This review presents a systems biology framework, called the 'Integrative Proteomics Data Analysis Pipeline' (IPDAP), which generates mechanistic hypotheses from network models reconstructed by integrating diverse types of proteomic data generated by mass spectrometry-based proteomic analyses. The devised framework includes a serial set of computational and network analysis tools. Here, we demonstrate its functionalities by applying these tools to several conceptual examples.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7775-7780
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• 2014

This paper addresses cancer prediction based on radial basis function neural network optimized by particle swarm optimization. Today, cancer hazard to people is increasing, and it is often difficult to cure cancer. The occurrence of cancer can be predicted by the method of the computer so that people can take timely and effective measures to prevent the occurrence of cancer. In this paper, the occurrence of cancer is predicted by the means of Radial Basis Function Neural Network Optimized by Particle Swarm Optimization. The neural network parameters to be optimized include the weight vector between network hidden layer and output layer, and the threshold of output layer neurons. The experimental data were obtained from the Wisconsin breast cancer database. A total of 12 experiments were done by setting 12 different sets of experimental result reliability. The findings show that the method can improve the accuracy, reliability and stability of cancer prediction greatly and effectively.

• Journal of Communications and Networks
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• v.18 no.2
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• pp.227-237
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• 2016

Data collection is a key function for wireless sensor networks. There has been numerous data collection scheduling algorithms, but they fail to consider the deep and complex relationship among network lifetime, sink aggregated information and sample cycle for wireless sensor networks. This paper gives the upper bound on the sample period under the given network topology. An optimal schedule algorithm focusing on aggregated information named OSFAI is proposed. In the schedule algorithm, the nodes in hotspots would hold on transmission and accumulate their data before sending them to sink at once. This could realize the dual goals of improving the network lifetime and increasing the amount of information aggregated to sink. We formulate the optimization problem as to achieve trade-off among sample cycle, sink aggregated information and network lifetime by controlling the sample cycle. The results of simulation on the random generated wireless sensor networks show that when choosing the optimized sample cycle, the sink aggregated information quantity can be increased by 30.5%, and the network lifetime can be increased by 27.78%.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.111-118
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• 2021

Banking systems are sensitive to data privacy since users' data, if not well protected, may be used to perform fake transactions. Blockchains, public and private, are frequently used in such systems thanks to their efficiency and high security. Public blockchains fail to fully protect users' data, despite their power in the accuracy of the transactions. The private blockchain is better used to protect the privacy of the sensitive data. They are not open and they apply authorization to login into the blockchain. However, they have a lower security compared to public blockchain. We propose in this paper a hybrid public-private architecture that profits from network virtualization. The main novelty of this proposal is the use of network virtualization that helps to reduce the complexity and efficiency of the computations. Simulations have been conducted to evaluate the performance of the proposed solution. Findings prove the efficiency of the scheme in reducing complexity and enhancing data privacy by guarantee high security. The contribution conducted by this proposal is that the results are verified by the centralized controller that ensures a correct validation of the resulted blockchains. In addition, computation complexity is to be reduced by profiting from the cooperation performed by the virtual agents.

• Journal of Information Science Theory and Practice
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• v.11 no.3
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• pp.29-42
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• 2023

This study explored issues related to the library in the COVID-19 era in YouTube videos in Korea. This study performed social network analysis and topic modeling analysis by collecting 479 YouTube videos, 20,545 words, and 8,379 channels related to COVID-19 and the library from 2019 to 2020. The study results confirmed that YouTube, a social media platform, was used as an important medium to connect users and physical libraries and provide/promote online library services. In the study, major topics and keywords such as quarantine, vlog, and library identity during the COVID-19 pandemic, library services and functions, and introductions and user guides of libraries were derived. Additionally, it was identified that videos about COVID-19 and the library are being produced by various actors (news and media channels, libraries, government agencies, librarians, and individual users). However, the study also identified that the actor network is fragmented through the channel network, showing a low density or weak linkage, and that the centrality of the library in the actor network is weak.

• Journal of applied mathematics & informatics
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• v.41 no.1
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• pp.95-105
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• 2023

To make the network energy efficient and to protect the network from malignant user's energy efficient grid based secret key sharing scheme is proposed. The cost function is evaluated to select the optimal nodes for carrying out the data transaction process. The network is split into equal number of grids and each grid is placed with certain number of nodes. The node cost function is estimated for all the nodes present in the network. Once the optimal energy proficient nodes are selected then the data transaction process is carried out in a secured way using malicious nodes filtration process. Therefore, the message is transmitted in a secret sharing method to the end user and this process makes the network more efficient. The proposed work is evaluated in network simulated and the performance of the work are analysed in terms of energy, delay, packet delivery ratio, and false detection ratio. From the result, we observed that the work outperforms the other works and achieves better energy and reduced packet rate.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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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.