• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1042-1062
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• 2010

Cooperative spectrum sensing (CSS) is an effective technology for alleviating the unreliability of local spectrum sensing due to fading/shadowing effects. Unlike most existing solutions, this paper considers the use of CSS technology in decentralized networks where a fusion center is not available. In such a decentralized network, some attackers may sneak into the ranks of cooperative users. On the basis of recent advances in bio-inspired consensus algorithms, an attack-proof, decentralized CSS scheme is proposed in which all secondary users can maintain cooperative sensing by exchanging information locally instead of requiring centralized control or data fusion. Users no longer need any prior knowledge of the network. To counter three potential categories of spectrum sensing data falsification (SSDF) attacks, some anti-attack strategies are applied to the iterative process of information exchange. This enables most authentic users to exclude potentially malicious users from their neighborhood. As represented by simulation results, the proposed scheme can generally ensure that most authentic users reach a consensus within the given number of iterations, and it also demonstrates much better robustness against different SSDF attacks than several existing schemes.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.615-620
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• 2005

Sensor networks are usually composed of tens or thousands of tiny devices with limited resources. Because of their limited resources, there will often be some faulty nodes within the network. As nodes in some certain regions rely on each other to route the information gathered by different sensors to a base station (sink), the network should be able to detect a non-operational node in order to determine new paths for routing the information. Failure detection, which identifies the faulty nodes, is rather necessary in sensor networks and a very important research issue. The detection of a non-operational node can be performed using Consensus Algorithm with the purpose of achieving agreement about a node which is supposed to be faulty (non-operational). In this work, we discuss the application of a Consensus Algorithm to sensor node called 'mote'. Our experimental results show that it works efficiently for identifying faulty nodes in sensor networks.

• ETRI Journal
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• v.43 no.2
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• pp.357-370
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• 2021

The evolution of blockchain-based systems has enabled researchers to develop nextgeneration e-voting systems. However, the classical consensus method of blockchain, that is, Proof-of-Work, as implemented in Bitcoin, has a significant impact on energy consumption and compromises the scalability, efficiency, and latency of the system. In this paper, we propose a hybrid consensus model (PSC-Bchain) composed of Proof of Credibility and Proof of Stake that work mutually to address the aforementioned problems to secure e-voting systems. Smart contracts are used to provide a trustworthy public bulletin board and a secure computing environment to ensure the accuracy of the ballot outcome. We combine a sharding mechanism with the PSC-Bchain hybrid approach to emphasize security, thus enhancing the scalability and performance of the blockchain-based e-voting system. Furthermore, we compare and discuss the execution of attacks on the classical blockchain and our proposed hybrid blockchain, and analyze the security. Our experiments yielded new observations on the overall security, performance, and scalability of blockchain-based e-voting systems.

• Journal of the Korean Magnetic Resonance Society
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• v.24 no.4
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• pp.117-122
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• 2020

Transcription factors are proteins that bind specific sites or elements in regulatory regions of DNA, known as promoters or enhancers, where they control the transcription or expression of target genes. MEIS1 protein is a DNA-binding domain present in human transcription factors and plays important roles in various biological functions. The hydrogen exchange rate constants of the imino protons were determined for the wild-type containing the consensus DNA-binding site for the MEIS1 and those of the mutant DNA duplexes using NMR spectroscopy. The G2A-, A3G- and C4T-mutant DNA duplexes lead to clear changes in thermal stabilities of these four consensus base pairs. These unique dynamic features of the four base pairs in the consensus 5'-TGAC-3' sequence might play crucial roles in the effective DNA binding of the MEIS1 protein.

• Journal of Korean Neurosurgical Society
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• v.66 no.3
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• pp.308-315
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• 2023

Recent updates in genomic-integrated glioma classification have caused confusion in current clinical practice, as management protocols and health insurance systems are based on evidence from previous diagnostic classifications. The Korean Brain Tumor Society conducted an electronic questionnaire for society members, asking for their ideas on risk group categorization and preferred treatment for each individual diagnosis listed in the new World Health Organization (WHO) classification of gliomas. Additionally, the current off-label drug use (OLDU) protocols for glioma management approved by the Health Insurance Review and Assessment Service (HIRA) in Korea were investigated. A total of 24 responses were collected from 20 major institutes in Korea. A consensus was reached on the dichotomic definition of risk groups for glioma prognosis, using age, performance status, and extent of resection. In selecting management protocols, there was general consistency in decisions according to the WHO grade and the risk group, regardless of the individual diagnosis. As of December 2022, there were 22 OLDU protocols available for the management of gliomas in Korea. The consensus and available options described in this report will be temporarily helpful until there is an accumulation of evidence for effective management under the new classification system for gliomas.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.249-251
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• 2021

PBFT (Practical Byzantine Fault Tolerant) is a consensus algorithm that guarantees higher processing speed compared to PoW (Proof of Work) and absolute finality that records are not overturned due to the superiority of computing power. However, due to the complexity of the message, there is a limit that the network load increases exponentially as the number of participating nodes increases. PBFT is an important factor in determining the performance of a blockchain network, but studies on evaluation metrics and evaluation technologies are lacking. In this paper, we propose a PBFT evaluation framework that is convenient to change the consensus algorithm to easily evaluate quantitative indicators and improved methods for evaluating PBFT.

• Journal of Korea Water Resources Association
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• v.47 no.7
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• pp.573-585
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• 2014

In this study, we propose a consensus-building support system to engage various stakeholders, transparently disseminate information, ensure objective decision-making, and reflect the view of each stakeholder as a methodology or tool for resolving conflicts that may arise in the process of implementing water environment policies and plans. The system suggests ways to resolve issues by engaging all interested actors and not just a few influential groups of stakeholders imposing their solutions upon local users. The system provides an environment where stakeholders can find solutions to conflicts through their own efforts, mediating competing interests through the interactions such as negotiations and conciliation to reach a consensus. To verify the applicability of the proposed consensus-building support system, simulated role-playing albeit restricted was conducted on the case of the Hantangang Dam construction. The simulation validated that open discussions and negotiations with the local community or NGO by the government increased the efficacy of negotiations.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.8
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• pp.1157-1167
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• 2007

Internet communications have provoked new forms of online word-of-mouth(WOM) communication and it has become more powerful. At this point, this study analyses the effects of information characteristics(direction, consensus) of online WOM. Especially, quasi-experiment can systematically manipulate the direction and the consensus of online WOM information and it perceived the difference in the effects in this study. Female consumers who have purchased clothing at online shopping mall in past 6 months participated in the experiment by completing 4 type questionnaires(N=600). Data are analyzed using Cronbach's ${\alpha}$, t-test, one way ANOVA, two-way ANOVA, Duncan's multiple range test. The Results of this study are as follows: (1) The direction of online WOM information significantly influences consumer's reliability of information, attitude, and purchase intentions. These effects are more significant when negative WOM information than positive information and two-sided information was given. (2) Though there is the difference in reliability of information, the consensus of online WOM information does not have influences on consumer's attitude and purchase intentions. (3) Consumer's clothing involvement is related to WOM information searching. The highly involved consumer is more effected by online WOM information than the lowly one.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1406-1409
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• 2018

We have frequently encountered the rapid changes that prevalent opinion of the social community is toppled by a new and opposite opinion against the pre-exiting one. To understand this interesting process, mean-field model with infinite-interaction range has been mostly considered in previous studies S. A. Marvel et al., Phys. Rev. Lett. 110, 118702 (2012). However, the mean-field interaction range is lack of reality in the sense that any individual cannot interact with all of the others in the community. Based on it, in the present work, we consider a simple model of opinion consensus so-called basic model on the low-dimensional lattices (d = 1, 2) with finite interaction range. The model consists of four types of subpopulations with different opinions: A, B, AB, and the zealot of A denoted by $A_c$, following the basic model shown in the work by S. A. Marvel et al.. Comparing with their work, we consider the finite range of the interaction, and particularly reconstruct the lattice structure by adding new links when the two individuals have the distance < ${\sigma}$. We explore how the interaction range ${\sigma}$ affects the opinion consensus process on the reconstructed lattice structure. We find that the critical fraction of population for $A_c$ required for the opinion consensus on A shows different behaviors in the small and large interaction ranges. Especially, the critical fraction for $A_c$ increases with the size of ${\sigma}$ in the region of small interaction range, which is counter-intuitive: When the interaction range is increased, not only the number of nodes affected by $A_c$ but also that affected by B grows, which is believed to cause the increasing behavior of the critical fraction for $A_c$. We also present the difference of dynamic process to the opinion consensus between the regions of small and large interaction ranges.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.37-45
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• 2022

With the development of the Internet of Things (IoT), related network infrastructures require new technologies to protect against threats such as external hacking. This study proposes an L-PBFT consensus algorithm that can protect IoT networks based on a blockchain consensus algorithm. We designed a blockchain (private) model suitable for small networks, tested processing performance for ultra-small/low-power IoT devices, and verified stability. As a result of performance analysis, L-PBFT proved that at least the number of nodes complies with the operation of the consensus algorithm(minimum 14%, maximum 29%) and establishes a trust network(separation of secure channels) different from existing security protocols. This study is a 4th industry convergence research and will be a foundation technology that will help develop IoT device security products in the future.