• Atmosphere
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• v.25 no.2
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• pp.375-387
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• 2015

A Selected Multi-model CONsensus (SMCON) technique was developed and verified for the tropical cyclone track forecast in the western North Pacific. The SMCON forecasts were produced by averaging numerical model forecasts showing low 70% latest 6 h prediction errors among 21 models. In the homogeneous comparison for 54 tropical cyclones in 2013 and 2014, the SMCON improvement rate was higher than the other forecasts such as the Non-Selected Multi-model CONsensus (NSMCON) and other numerical models (i.e., GDAPS, GEPS, GFS, HWRF, ECMWF, ECMWF_H, ECMWF_EPS, JGSM, TEPS). However, the SMCON showed lower or similar improvement rate than a few forecasts including ECMWF_EPS forecasts at 96 h in 2013 and at 72 h in 2014 and the TEPS forecast at 120 h in 2013. Mean track errors of the SMCON for two year were smaller than the NSMCON and these differences were 0.4, 1.2, 5.9, 12.9, 8.2 km at 24-, 48-, 72-, 96-, 120-h respectively. The SMCON error distributions showed smaller central tendency than the NSMCON's except 72-, 96-h forecasts in 2013. Similarly, the density for smaller track errors of the SMCON was higher than the NSMCON's except at 72-, 96-h forecast in 2013 in the kernel density estimation analysis. In addition, the NSMCON has lager range of errors above the third quantile and larger standard deviation than the SMCON's at 72-, 96-h forecasts in 2013. Also, the SMCON showed smaller bias than ECMWF_H for the cross track bias. Thus, we concluded that the SMCON could provide more reliable information on the tropical cyclone track forecast by reflecting the real-time performance of the numerical models.

• Journal of The Korean Association For Science Education
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• v.20 no.2
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• pp.250-261
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• 2000

In this study, a concept learning strategy emphasizing social consensus during discussion (SCS) was developed. The instructional effects of this strategy were compared with those of cognitive conflict strategy (CCS) and traditional instruction in the aspects of students' achievement, conceptions, communication apprehension, perceptions of science learning environment, and perceptions of small group discussion. There were no significant differences in the scores of an achievement test. For the students of low communication competency, however, the scores of the CCS group were significantly higher than those of the traditional group. The adjusted mean of the SCS group was higher than those of the other groups in a conceptions test. The social consensus strategy was also found to be more effective in learning concept for those who were more competent in communicating. No significant differences were found in the communication apprehension. The scores of three groups did not differ significantly in the subcategories of 'personal relevance' and 'students' negotiation' of the test of the perceptions of science learning environment. However, the students in the SCS group scored higher in 'participation'. The students in the SCS group perceived small group discussions more positively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.45-53
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• 2020

Blockchain can control transactions in a decentralized way and is already being considered for manufacturing, finance, banking, logistics, and medical industries due to its advantages such as transparency, security, and flexibility. And it is predicted to have a great economic effect. However, Blockchain has a Trilemma that is difficult to simultaneously improve scalability, decentralization and security characteristics. Among them, the biggest limitation of blockchain is scalability, which is very difficult to cope with the constantly increasing number of transactions and nodes. To make the blockchain scalable, higher performance should be achieved by modifying existing consensus methods or by improving the characteristics and network efficiency that affect many ways of scaling. Therefore, in this paper, we propose a cluster-based scalable PBFT consensus algorithm called CBS-PBFT which reduces the message complexity O(n²) of PBFT to O(n), which is a representative consensus algorithm of blockchain, and the validity is verified through simulation experiments.

• Journal of Families and Better Life
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• v.30 no.1
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• pp.65-76
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• 2012

The purpose of this study was to investigate effects of maladaptive personality (borderline personality, narcissistic personality, and dependent personality) and conflict behavior on marital adjustment(dyadic satisfaction, dyadic consensus, dyadic cohesion, and affectional expression) among married women. Subjects in this study were 725 married women who lived in Cheong-buk, in Gyeonggi province, Korea. Data were analyzed by the methods of frequency, percentage, Cronbach's ${\alpha}$, and factor analysis, Pearson's correlation, and hierarchical regression using SPSS-WIN version 12.0. The results of this study were as follows: 1) the less borderline personality was perceived, the more narcissistic personality was perceived, In addition, a greater perceived amount of destructive conflict behavior of wives was linked to highdyadic satisfaction in the wives'. Wives' destructive conflict- behavior was the most important parameter to predict dyadic satisfaction. 2) The less borderline personality was perceived, the less dependent personality was perceived, while the more narcissistic personality was perceived, the more destructive conflict behavior of husbands was perceived, with the, wives' incidence of dyadic consensus appearing high. Husbands' destructive conflict behavior was the most important parameter to predict a dyadic consensus. 3) The less borderline personality was perceived, the more narcissistic personality was perceived, In addition, more destructive conflict behavior of the husbands was linked to highdyadic cohesion in the wives'. Husbands' destructive conflict behavior was the most important to predict dyadic cohesion relatively. 4) The more destructive conflict behavior of wives was perceived, the higher the wives' affectional expression appeared. The wives' destructive conflict behavior was the most important parameter to predict affectional expression.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.25-32
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• 2019

The core of the block chain technology is solving the problem of agreement on double payment, and the PoW, PoS and DPoS algorithms used for this have been studied. PoW in-process proofs are consensus systems that require feasible efforts to prevent minor or malicious use of computing capabilities, such as sending spam e-mail or initiating denial of service (DoS) attacks. The proof of the PoS is made to solve the Nothing at stake problem as well as the energy waste of the proof of work (PoW) algorithm, and the decision of the sum of each node is decided according to the amount of money, not the calculation ability. DPoS is that a small number of authorized users maintain a trade consensus through a distributed network, whereas DPS provides consent authority to a small number of representatives, whereas PoS has consent authority to all users. If PoS is direct democracy, DPoS is indirect democracy. This study aims to contribute to the continuous development of the related field through the study of the algorithm of the block chain agreement.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.168-177
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• 2020

In recent years, importance of blockchain systems has been grown after success of bitcoin. Distributed consensus algorithm is used to achieve an agreement, which means the same information is recorded in all nodes participating in blockchain network. Various algorithms were suggested to resolve blockchain trilemma, which refers conflict between decentralization, scalability, security. An algorithm based on Byzantine Agreement among Decentralized Agents (BADA) were designed for the same manner, and it used limited committee that enables an efficient consensus among considerable number of nodes. In addition, election of committee based on Proof-of-Nonce guarantees decentralization and security. In spite of such prominence, application of BADA in actual blockchain system requires further researches about performance and essential features affecting on the performance. However, performance assessment committed in real systems takes a long time and costs a great deal of budget. Based on this motivation, we designed and implemented a simulator for measuring performance of BADA. Specifically, we defined a simulation framework including three components named simulator Command Line Interface, transaction generator, BADA nodes. Furthermore, we carried out response surface analysis for revealing latent relationship between performance measure and design parameters. By using obtained response surface models, we could find an optimal configuration of design parameters for achieving a given desirable performance level.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.73-85
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• 2022

In the era of the 4th industrial revolution, where automation and connectivity are maximized with artificial intelligence, the importance of data collection and utilization for model update is increasing. In order to create a model using artificial intelligence technology, it is usually necessary to gather data in one place so that it can be updated, but this can infringe users' privacy. In this paper, we introduce federated learning, a distributed machine learning method that can update models in cooperation without directly sharing distributed stored data, and introduce a study to optimize distributed consensus among participants without an existing server. In addition, we propose a pattern and group-based distributed consensus optimization algorithm that uses an algorithm for generating patterns and groups based on the Kirkman Triple System, and performs parallel updates and communication. This algorithm guarantees more privacy than the existing distributed consensus optimization algorithm and reduces the communication time until the model converges.

• The Journal of Bigdata
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• v.7 no.1
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• pp.1-14
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• 2022

The proof-of-work consensus algorithm used by most blockchains is causing a massive waste of computing resources in the form of mining. A useful proof-of-work consensus algorithm has been studied to reduce the waste of computing resources in proof-of-work, but there are still resource waste and mining centralization problems when creating blocks. In this paper, the problem of resource waste in block generation was solved by replacing the relatively inefficient computation process for block generation with distributed artificial intelligence model learning. In addition, by providing fair rewards to nodes participating in the learning process, nodes with weak computing power were motivated to participate, and performance similar to the existing centralized AI learning method was maintained. To show the validity of the proposed methodology, we implemented a blockchain network capable of distributed AI learning and experimented with reward distribution through resource verification, and compared the results of the existing centralized learning method and the blockchain distributed AI learning method. In addition, as a future study, the thesis was concluded by suggesting problems and development directions that may occur when expanding the blockchain main network and artificial intelligence model.

• Korean Journal of Radiology
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• v.25 no.4
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• pp.331-342
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• 2024

The Asian Society of Cardiovascular Imaging-Practical Tutorial (ASCI-PT) is an instructional initiative of the ASCI School designed to enhance educational standards. In 2021, the ASCI-PT was convened with the goal of formulating a consensus statement on the assessment of coronary stenosis and coronary plaque using coronary CT angiography (CCTA). Nineteen experts from four countries conducted thorough reviews of current guidelines and deliberated on eight key issues to refine the process and improve the clarity of reporting CCTA findings. The experts engaged in both online and on-site sessions to establish a unified agreement. This document presents a summary of the ASCI-PT 2021 deliberations and offers a comprehensive consensus statement on the evaluation of coronary stenosis and coronary plaque in CCTA.

• Information Systems Review
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• v.21 no.3
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• pp.27-47
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• 2019

The purpose of this study is to propose a conceptual model for the tourism application of the block chain consensus construct and to test the intention of technology acceptance of potential consumers. First, we have tried to investigate the security, reliability, functionality was derived. Secondary, structural validation of the proposed model confirmed the factors influencing the acceptance of block chain technology in terms of consumers. Based on this, we apply the Unified Theory of Acceptance and Use of Technology to evaluate. Individual innovation and block-chain technology have a strong causal relationship with the proposed block chain acceptance intentions based on the Hybrid Block Chain Consensus system, which shows strong innovation and strong cognitive status. In addition, the factors directly affecting the acceptance of block-chain are the benefits expected from the block chain, the technical infrastructure required to use the service, the perceived benefits available. The influence of the surrounding environment on the adoption of technology and ease of use on new technology did not affect the acceptance intention significantly.