• Information Systems Review
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• v.13 no.3
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• pp.141-163
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• 2011

The advancement of information technologies including the Internet has affected the way of social information processing as well as brought about the paradigm shift to the information society. Accordingly, it is very important to study the process of social information processing over the digital media through which social information is generated, distributed, and led to social consensus. In this study, we analyze the mechanism of social information processing, identify a process model of social consensus and institutionalization of the results, and finally propose a set of information processing characteristics on the internet media. We deploy the ethnographic approach to analyze the meaning of group behavior in the context of society to analyze two major events which happened in Korean society. The formation process of social consensus is found to consist of 5 steps: suggestion of social issues, selective reflection on public opinion, acceptance of the issues and diffusion, social consensus, and institutionalization and feedback. The key characteristics of information processing in the Internet is grouped into proactive response to an event, the changes in the role of opinion leader, the flexibility of proposal and analysis, greater scalability, relevance to consensus making, institutionalization and interaction. This study contributes to the literature by proposing a process model of social information processing which can be used as the basis for analyzing the social consensus making process from the social network perspective. In addition, this study suggests a new perspective where the utility of the Internet media can be understood from the social information processing so that other disciplines including politics, communications, and management can improve the decision making performance in utilizing the Internet media.

• Korean Journal of Construction Engineering and Management
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• v.4 no.1 s.13
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• pp.81-89
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• 2003

This research suggests the FD-AHP decision making model for Construction Projects which is composed of two main method to prevent a ranking invert situation ; First, to make the consensus of the experts consistent, we utilize Fuzzy-Delphi method to adjust the fuzzy rating of every expert to achive the consensus condition with the fuzzy linguistic presentation. Second, to handle vague linguistic presentation caused by expert's experiences and subjective judgement, we propose Fuzzy-AHP which is able to enhance precision of construction projects decision mating situation. Moreover, with the correlation analysis, we show that the validity of the FD-AHP model under a decision making task specially on where highly demanded expert's experiences and intuition.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.1
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• pp.131-148
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• 2008

Today, it is not difficult to use information technology (IT), especially, Internet based ones. Many people can not only access IT without learning how to use it but also find and develop new techniques and usages which couldn't be expected by system engineers or designers. This is owing to social interactions among users as well as advancement of IT. Theoretically, such social interactions in using IT can be well explained by adaptive structuration theory (AST) which has been considered as one of trying to capture the change of using IT due to social interactions between users and system. This study is to analyze the relationship between social interactions and motivation in using IT which can determine attitude and intention of using IT. For this purpose we provide a research model, in which two AST related variables, faithfulness of appropriation and consensus on appropriation, are independent variables and three beliefs for using IT, usefulness, ease of use and playfulness, are dependent ones. Additionally, for reflection of changing uses, usefulness is formed as second order factor by two first order factors-usefulness of self-expression and communication. An empirical test of our model for blog users which is analyzed by Partial Least Square method shows supporting most of hypotheses except one, consensus-ease of use.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.133-138
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• 2013

This paper addresses a state consensus controller design technique of Takagi-Sugeno fuzzy model-based multi-agent systems in a continuous-time domain. We express the interconnection topology among the agents through graph theory. The design condition is represented in terms of linear matrix inequalities. Numerical example is provided to demonstrate the effectiveness of the proposed method.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.128-134
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• 2023

The widespread usage of blockchain technology in cryptocurrencies has led to the adoption of the blockchain concept in data storage management systems for secure and effective data storage and management. Several innovative studies have proposed solutions that integrate blockchain with distributed databases. In this article, we review current blockchain databases, then focus on two well-known blockchain databases-BigchainDB and FalconDB-to illustrate their architecture and design aspects in more detail. BigchainDB is a distributed database that integrates blockchain properties to enhance immutability and decentralization as well as a high transaction rate, low latency, and accurate queries. Its architecture consists of three layers: the transaction layer, consensus layer, and data model layer. FalconDB, on the other hand, is a shared database that allows multiple clients to collaborate on the database securely and efficiently, even if they have limited resources. It has two layers: the authentication layer and the consensus layer, which are used with client requests and results. Finally, a comparison is made between the two blockchain databases, revealing that they share some characteristics such as immutability, low latency, permission, horizontal scalability, decentralization, and the same consensus protocol. However, they vary in terms of database type, concurrency mechanism, replication model, cost, and the usage of smart contracts.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.487-496
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• 2003

The promoter that plays a very important role in gene expression as a signal part has various binding sites for transcription factors. These binding sites are located on various parts in promoter region and have highly conserved consensus sequence patterns. This paper presents a new method for the consensus pattern search in promoter regions using genetic algorithm, which adopts the assumption of N-occurrence-per-dataset model of MEME algorithm and employs the advantage of Wataru method in determining the pattern length. Our method will be employed by genome researchers who try to predict the promoter region on anonymous DNA sequence and to find out the binding site for a specific transcription factor.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.35-40
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• 2003

In this paper, I raise an issue regarding the relationships between the Election problem and the Consensus problem in asynchronous systems with unreliable failure detectors. First, I describe our system model, and then define Leader Election. After then, I show that the Election problem is harder to resolve than the Consensus problem. Each correct process eventually gets into the state in which it considers only one process to be a leader. Therefore a Perfect Failure Detector is the weakest failure detector which is sufficient to solve the Election. In order to show that the Election problem is harder to resolve than the Consensus problem, I utilize the Reduction protocol in this paper.

• 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.

• 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.

• Analyses & Alternatives
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• v.5 no.1
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• pp.3-24
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• 2021

This paper introduces a multilevel item-response-theory (IRT) model as a unifying model for hypothesis testing using legislative voting data. This paper shows that a probit or logit model is a special type of multilevel IRT model. In particular, it is demonstrated that, when a probit or logit model is applied to multiple votes, it makes unrealistic assumptions and produces incorrect coefficient estimates. The advantages of a multilevel IRT model over a probit or logit model are illustrated with a Monte Carlo experiment and an example from the U.S. House. Finally, this paper provides a practical guide to fitting this model to legislative voting data.