• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.1019-1023
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• 2014

The issue of safety insurance in PES(Programmable Electronic Systems) has been provoked because PES is difficult to define failure modes which are appeared in many different ways. But the PES applications extend rapidly in various areas. One of the solutions for PES safety insurance is voting which PES is used by comparing the outputs of several PES. The time synchronization of the PES is necessary for this reliable voting. The voting must be carried out with the outputs from same time inputs. There are several methods for time synchronization of the PES. In this paper, we discussed two modes of the time synchronization which are mutual synchronization of several PES and using UTC(Universal Time Clock).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1169-1176
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• 2013

PES have been recently required to implement railway industry for its application flexibility. The PES should be commensurated with railway safety requirements. It achieved its safety through redundant PES. The redundant systems run with voting functions. The successful major voting result becomes the output of the redundant system. The redundant system have to be synchronized to vote each output results. This paper proposed an algorithm for synchronizing and a voter. The proposed algorithm and the voter are verified using simulation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.16-17
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• 2011

온라인을 통한 이미지 공유는 사용자들이 활발하게 이용하고 있는 분야 중 하나이다. 사용자의 활발한 참여로 거대해진 이미지 데이터 베이스 내에서 효율적으로 이미지 검색을 수행하기 위해서는 이미지를 정확하기 표현하고 있는 태그의 존재가 매우 중요하다. 하지만, 최근 이미지에 등록 태그 중에서 상당 부분이 이미지와는 직접 관련이 없는 노이즈 태그라는 조사결과는 노이즈 태그로 인해서 이미지 검색의 정확성이 저하될 수 있다는 가능성을 암시한다. 그래서 노이즈 태그를 효과적으로 구분하기 위해서는 태그의 종류에 적합한 태그 정제 기술을 도입할 필요가 있다. 본 연구는 이를 위해서 이미지의 시각적 유사도에 기반한 Visually weighted neighbor voting 방법을 제안했다. 이를 통해서 이미지와 태그 사이의 관련성을 효과적으로 측정할 수 있었다. 그리고 기존 기술보다 안정적으로 노이즈 태그를 구분할 수 있음을 실험을 통해서 증명하였다.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.97-113
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• 2014

Circular shareholding refers to a situation where at least three member firms in a business group have stock in other member firms and establish a series of ownership in a circular way. Although many studies have focused on the ultimate effect of circular shareholding on firm's value and profitability, there have been few studies which address how to resolve circular shareholding from the perspective of optimization theory. This paper proposes a heuristic method for identifying shareholdings which need to be cleared in order to settle the problem of circular shareholding in a business group. The proposed heuristic tries to maximize the sum of voting rights the controlling family has in its business group firms. The applications results confirm that the heuristic provides near-optimal solutions for most of 16 Korean large business groups involving circular shareholding.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.115-117
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• 2001

기존의 인터넷 웹사이트에서는 사용자의 만족을 극대화시키기 위하여 사용자별로 개인화 된 서비스를 제공하는 협력적 필터링 방식을 적용하고 있다. 협력적 필터링 기술은 사용자의 취향에 맞는 아이템을 예측하여 추천하며, 비슷한 선호도를 가진 다른 사용자들과의 상관관계를 구하기 위하여 일반적으로 피어슨 상관계수를 많이 이용한다. 그러나, 피어슨 상관계수를 이용한 방법은 사용자가 평가를 한 아이템이 있을 때에만 상관관계를 구할 수 있다는 단점과 예측의 정확성이 떨어진다는 단점을 가지고 있다. 따라서, 본 논문에서는 피어슨 상관관계 기반 예측 기법을 보완하여 보다 정확한 사용자 유사도를 구하는 방법을 제안한다. 제안된 방법에서는 사용자들을 대상으로 사용자가 평가를 한 아이템의 선호도를 사용해서 엔트로피를 적용하였고, 사용자가 선호도를 표시하지 않은 상품에 대해서는 Default Voting 방법을 이용하여 보다 정확한 헙력적 필터링 방식을 구현하였다.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.237-242
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• 2003

Various kinds of estimation methods have been developed for imputation of categorical missing data. They include modal category method, logistic regression, and association rule. In this study, we propose two imputation methods (neural network fusion and voting fusion) that combine the results of individual imputation methods. A Monte-Carlo simulation is used to compare the performance of these methods. Five factors used to simulate the missing data are (1) true model for the data, (2) data size, (3) noise size (4) percentage of missing data, and (5) missing pattern. Overall, neural network fusion performed the best while voting fusion is better than the individual imputation methods, although it was inferior to the neural network fusion. Result of an additional real data analysis confirms the simulation result.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.1075-1078
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• 2005

The Global IT revolution is growing rapidly. Government and business have to be ready to meet the increased demand for effective and secure online services. With the E-Government practicing, day-by-day the public demand is also increasing simultaneously. Now this present moment, one of important research part is secure E-Voting for E-Government service, but for this important factor or Government Issue, it needs information privacy for secure information transaction of citizen’s opinions and secure authentication. This paper has analyzed several approaches E-voting protocols, those are implemented with many digital signature mechanism and maintained many types of cryptographic rules, which are main factor for information privacy. In this paper we have discussed them with a view to voter anonymity and protection from manipulations. The paper then developed an algorithm designed to guarantee anonymity of the voter and to avoid the risk of manipulation of votes. In this paper the proposed algorithm is based upon the strict separation of voter’s registration and submission of votes, which means that certain information has to be stored on a secure storage media.

• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.258-267
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• 2013

New incremental learning algorithm using extended data expression, based on probabilistic compounding, is presented in this paper. Incremental learning algorithm generates an ensemble of weak classifiers and compounds these classifiers to a strong classifier, using a weighted majority voting, to improve classification performance. We introduce new probabilistic weighted majority voting founded on extended data expression. In this case class distribution of the output is used to compound classifiers. UChoo, a decision tree classifier for extended data expression, is used as a base classifier, as it allows obtaining extended output expression that defines class distribution of the output. Extended data expression and UChoo classifier are powerful techniques in classification and rule refinement problem. In this paper extended data expression is applied to obtain probabilistic results with probabilistic majority voting. To show performance advantages, new algorithm is compared with Learn++, an incremental ensemble-based algorithm.

• International Journal of Contents
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• v.9 no.2
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• pp.8-13
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• 2013

Locating text data in images automatically has been a challenging task. In this approach, we build a three stage system for text detection purpose. This system utilizes tensor voting and Completed Local Binary Pattern (CLBP) to classify text and non-text regions. While tensor voting generates the text line information, which is very useful for localizing candidate text regions, the Nearest Neighbor classifier trained on discriminative features obtained by the CLBP-based operator is used to refine the results. The whole algorithm is implemented in MATLAB and applied to all images of ICDAR 2011 Robust Reading Competition data set. Experiments show the promising performance of this method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.3
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• pp.417-425
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• 2012

In 2010, Sebe et al. proposed an efficient and lightweight mixnet scheme for remote voting systems. The scheme based on a cryptographic secure hash function, does not require complex and costly zero-knowledge proofs of their correct mixing operations, thus they claimed that their scheme is simple and efficient. In this paper, we propose more efficient and fast mixnet scheme than Sebe et al.'s scheme under the same assumption.