• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.5 no.4
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• pp.351-357
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• 2007

The Japanese Government selected Mutsu, Aomori Prefecture as a provisional spent-fuel repository site. This comes as a result of the prefecture's five-year campaign to host the site since 2000. Korea stores spent nuclear fuel within sites of nuclear power plants, and expects the storage capacity to reach its limit by the year 2016. This compels Korea to learn the cases of Japan. Having successfully hosted Gyeongju as a site for low-to-intermediate-level nuclear waste repository, Korea has already learned the potential process of hosting spent fuel storage site. The striking difference between the two countries in the process of hosting the site is that the Korean government had to offer the local city a large amount of subsidy for hosting through competitive citizens' referendum among candidate cities while it was the leadership of the local municipality that enabled the controversial decision in Japan. It is also a distinguishable characteristics of Japan that not a huge subsidy is provided to the local host city. I hope this study offers an idea to Korea's future effort to select a spent-fuel host site.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.80-89
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• 2017

Television viewing affects viewers' attitudes and opinions on their political issues. Since the beginning of General Programming TV services in 2011, they are criticized of their politically biased programming. In order to investigate the effect of General Programming TV on voters' behavior, we analyzed whether or not there is a change in the voting behavior of the conservative parties among the areas with high and low TV ratings of general programming TV. Based on the result of 18th presidential election in December 2012, we could not find any difference in voting behavior on the Saenuri party among the areas with high and low ratings of general programming TV channels. However, in the 6th provincial election in June 2014, while the voting shares of the Saenuri party were higher in the areas with high ratings of TV Chosun, Channel A, and JTBC than in those areas with low ratings.

• Journal of Internet Computing and Services
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• v.5 no.1
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• pp.51-57
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• 2004

Mobile Internet allows users to request critical information and receive swift responses at any places, but mobile users could suffer from unreliable and ill-timed services due to the characteristics of wireless media, One way that reduces possibility of the unsatisfactory services is data replication. Data Replica1ion, however, inevitably induces the overhead of maintaining replica consistency which requires more expensive synchronization mechanism. We propose a new replicated data management scheme in distributed mobile environment, In order to alleviate negative impact of synchronization message overhead in fault-prone mobile Internet environment, we devise a new replication control scheme called proxy quorum consensus (PQC), PQC minimizes the message overhead by coordinating quorum access activities by means of proxy mediated voting (PMV) which exploits reliable proxy hosts instead of unreliable mobile hosts in voting process, We also propose a simulation model to show the performance of PQC. Based on the results of the performance evaluation, we conclude that PQC scheme outperforms the traditional schemes.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.33-43
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• 2002

Various kinds of estimation methods have been developed for imputation of categorical missing data. They include category method, logistic regression, and association rule. In this study, we propose two fusions algorithms based on both neural network and voting scheme that combine the results of individual imputation methods. A Mont-Carlo simulation is used to compare the performance of these methods. Five factors used to simulate the missing data pattern are (1) input-output function, (2) data size, (3) noise of input-output function (4) proportion of missing data, and (5) pattern of missing data. Experimental study results indicate the following: when the data size is small and missing data proportion is large, modal category method, association rule, and neural network based fusion have better performances than the other methods. However, when the data size is small and correlation between input and missing output is strong, logistic regression and neural network barred fusion algorithm appear better than the others. When data size is large with low missing data proportion, a large noise, and strong correlation between input and missing output, neural networks based fusion algorithm turns out to be the best choice.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.173-179
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• 2013

In a biometric authentication scheme, a user's biometric data that is unique to the user is used to prove the user's identity to the third party. Since the user should have to participate in every authentication sessions, it's not possible to delegate other users to authenticate instead of himself/herself. In a biometric signature scheme, contrary to authentication scheme, a user's biometric data is used to prove that "this message is signed by the signer who claims to be" to the third party. However, once the biometric key is created, it can be accessed by the signer. Thus, it's possible to lend the biometric key to other users. In this study, the server based biometric realtime signature scheme is proposed. The proposed scheme can be applied to sign the vote in electronic voting or to authenticate the copyright owner in DRM enabled mobile commerce where the proxy signatures are not allowed.

• Journal of KIISE
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• v.42 no.9
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• pp.1124-1132
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• 2015

In order to train a supervised machine learning algorithm, it is necessary to have non-biased labels and a sufficient amount of training data. However, it is difficult to collect the required non-biased labels and a sufficient amount of training data to develop an automatic English Composition scoring system. In addition, an English writing assessment is carried out using a multi-faceted evaluation of the overall level of the answer. Therefore, it is difficult to choose an appropriate machine learning algorithm for such work. In this paper, we show that it is possible to alleviate these problems through ensemble learning. The results of the experiment indicate that the ensemble technique exhibited an overall performance that was better than that of other algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.427-432
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• 2019

In this paper, we propose three approaches to modeling Android malware. The first method involves human security experts for meticulously selecting feature sets. With the second approach, we choose 300 features with the highest importance among the top 99% features in terms of occurrence rate. The third approach is to combine multiple models and identify malware through weighted voting. In addition, we applied a novel method of eliminating permission information which used to be regarded as a critical factor for distinguishing malware. With our carefully generated feature sets and the weighted voting by the ensemble algorithm, we were able to reach the highest malware detection accuracy of 97.8%. We also verified that discarding the permission information lead to the improvement in terms of false positive and false negative rates.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1183-1189
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• 2021

There have been recently an increasing number of people working out at home. However, many of them do not have face-to-face guidance from experts, so they cannot effectively correct their wrong pose. This may lead to strain and injury to those doing home training. To tackle this problem, this paper proposes a video data-based pose classification and correction system for home training. The proposed system classifies poses using the multi-layer perceptron and pose estimation model, and corrects poses based on joint angels estimated. A voting algorithm that considers the results of successive frames is applied to improve the performance of the pose classification model. Multi-layer perceptron model for post classification shows the highest accuracy with 0.9. In addition, it is shown that the proposed voting algorithm improves the accuracy to 0.93.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.290-292
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• 2019

Since the advent of blockchain and bitcoin, decentralization has been accelerating around the world as a public blockchain ethereum with smartcontract has begun. Developers can use Ethereum's blockchain development platform to develop "distributed applications" (DApp) running on a decentralized P2P network, and various types of devices from IoT to mobile can participate in a block-chain distributed environment have. Using Ethereum's blockchain development platform, developers can develop "Decentralized Application (DApp)" that run on a decentralized P2P network and various types of devices from IOT to mobile can participate in distributed blockchain environments. There are many ways to interact with the blockchain and the smart contract, but users tend to prefer the mobile methods due to their convenience and accessibility advantages. Therefore, the author developed an Android based voting DApp and researched related issues. Since the current development methods of DApp are not adequately researched and standardized, efficient methods for developing user-friendly DApp were studied. Because DApp has to spend a certain amount of fees to interact with blockchain, it has intensively investigated the gas problem of Smart Contract code and the security problem of code, and author would like to introduce it in this paper.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.895-905
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• 2018

Public opinion polls have a strong influence on modern society as a means of examining the tendency of social groups on specific issues. As the influence of the polls increases, the problem of forgery and falsification of the results becomes an important issue. So, to guarantee the reliability of the results, our society needs novel mechanisms. As one of such mechanisms, the Ethereum blockchain is an environment for developing decentralized applications with the reliable blockchain technology. Ethereum decentralized applications can utilize smart contracts to provide services for users in transparent and reliable ways. In this paper, we propose a polling method that guarantees reliability using the blockchain technology, which is a distributed ledger technique that makes forgery or falsification actually impossible. The proposed method provides a robust verification function on the results of the associated polls for individual voters and verification organizations. Also, we present a distributed opinion polling application running on our private Ethereum blockchain network, showing the effectiveness of the proposed method.