• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.11-18
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• 2010

Fuzzy c-means (FCM) is a simple but efficient clustering algorithm using the concept of a fuzzy set that has been proved to be useful in many areas. There are, however, several well known problems with FCM, such as sensitivity to initialization, sensitivity to outliers, and limitation to convex clusters. In this paper, global fuzzy c-means (G-FCM) and kernel fuzzy c-means (K-FCM) are combined to form a non-linear variant of G-FCM, called kernel global fuzzy c-means (KG-FCM). G-FCM is a variant of FCM that uses an incremental seed selection method and is effective in alleviating sensitivity to initialization. There are several approaches to reduce the influence of noise and accommodate non-convex clusters, and K-FCM is one of them. K-FCM is used in this paper because it can easily be extended with different kernels. By combining G-FCM and K-FCM, KG-FCM can resolve the shortcomings mentioned above. The usefulness of the proposed method is demonstrated by experiments using artificial and real world data sets.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.327-344
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• 2007

Ridge partial least squares regression (RPLS) is a regression method which can be obtained by combining ridge regression and partial least squares regression and is intended to provide better predictive ability and less sensitive to overfitting. In this paper, explicit expressions for the shrinkage factor of RPLS are developed. The structure of the shrinkage factor is explored and compared with those of other biased regression methods, such as ridge regression, principal component regression, ridge principal component regression, and partial least squares regression using a near infrared data set.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.931-941
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• 2017

Typical Nonparametric methods for randomized block design with replications are two methods proposed by Mack (1981) and Mack and Skillings (1980). This method is likely to cause information loss because it uses the average of repeated observations instead of each repeated observation in the processing of each block. In order to compensate for this, we proposed a test method using linear placement statistics, which is a score function applied to the joint placement method proposed by Chung and Kim (2007). Monte Carlo simulation study is adapted to compare the power with previous methods.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1411-1419
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• 2016

Nonparametric procedures in randomized block design was proposed by Friedman (1937) as a general alternative. This method is used to find out the difference in treatment effect. It can cause a loss of inter block information using the ranking in each block. This paper proposed nonparametric procedures using an aligned method proposed by Hodges and Lehmann (1962) to reduce block information based on joint placement suggest by Jo and Kim (2013) in a randomized block design. We also compared the power of the test of the proposed procedures and established method through a Monte Carlo simulation.

• Proceedings of the Korean Statistical Society Conference
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• 2001.11a
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• pp.95-97
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• 2001

공간자료의 예측문제에 있어 전통적 예측방법인 크리깅방법과 최근 통계적문제 적용되기 시작한 신경망분석방법 간의 비교를 사례연구를 통해 행하였다. 일반적으로 크리깅에 의한 선형예측은 공간자료에 대한 일반적 통계모형으로서 간주되어 왔다. 한편 예측문제에 있어 뉴럴네트워크에 기초한 비모수적 방법이 관심의 대상이 되고 있으며 특히 대용량 자료의 경우 데이터마이닝 기법의 한 분야로 널리 사용되고 있는 실정이다. 본 연구에서는 공간 자료의 예측에 있어 유전자 알고리즘을 신경망분석 모형을 결합하여 기존의 크리깅방법과의 예측력을 비교한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.69-85
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• 1998

본 연구에서는 부품 및 시스템 고장률 모형에 대한 추계적 과정 접근법을 제시하고 기존의 이론 분포 중심 접근법에서 탈피하여 부품고장률을 시계열 모형으로 설정하고 이에 따른 복합시스템 고장율의 선형결합에 대한 모델을 제시하며 주요 모델에 대한 수치예를 든다. 또한 Burn-In 테스트에 사용되는 욕조(Bathtub) 고장률 모형에 대한 기존의 혼합분포 접근법의 대체 방법으로 비선형 시계열 모형을 제안한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.8 no.3
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• pp.17-26
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• 1998

본 논문에서는 DES(Data EncryptionStandard)시스템에서의 핵심부분에 해당되는f 함수에 대한 비선형 해석을 다룬다. 먼저 S-box의 입출력 형태를 비션형 결합함수 형태로 구성하여 f 함수에 대한 또 다른 형태의 분석방식을 제시한다. 이러한 분석방법은 DES뿐만 아니라 블록 암호시스템의 안전성 문제를 분석할 수 있으며, 또한 보다 안전한 블록암호 시스템을 제안하기 위한 기초자료로 사용될수 있을 것이다.

• Proceedings of the Korean Fiber Society Conference
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• 2002.04a
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• pp.414-416
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• 2002

폴리비닐알코올 (poly(vinyl alcohol), PVA)는 분해되어 대부분의 성분이 물과 이산화탄소로 전환되는 가장 이상적인 환경친화성 고분자이다. PVA만의 특유한 반응인 비누화 과정에 의해 가지가 모두 제거되기 때문에 화학적인 방법에 의해 완벽한 선형고분자를 얻는 것이 가능하다. PVA는 측쇄에 존재하는 히드록시기의 강력한 수소결합 때문에 우수한 반응성 및 결합성을 보유한 유기 고분자로서, 수용성 뿐 아니라 다양한 소재와 상용성이 있는 것으로 알려져 있다(1-4). (중략)

• The KIPS Transactions:PartD
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• v.15D no.5
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• pp.713-720
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• 2008

Fingerprinting scheme uses digital watermarks to trace originator of unauthorized or pirated copies, however, multiple users may collude and escape identification by creating an average or median of their individually watermarked copies. Previous research works are based on ACC (anti-collusion code) for identifying each user, however, ACC are shown to be resilient to average and median attacks, but not to LCCA and cannot support large number of users. In this paper, we propose a practical SACC (scalable anti-collusion code) scheme and its angular decoding strategy to support a large number of users from basic ACC (anti-collusion code) with LCCA (linear combination collusion attack) robustness. To make a scalable ACC, we designed a scalable extension of ACC codebook using a Gaussian distributed random variable, and embedded the resulting fingerprint using human visual system based watermarking scheme. We experimented with standard test images for colluder identification performance, and our scheme shows good performance over average and median attacks. Our angular decoding strategy shows performance gain over previous decoding scheme on LCCA colluder set identification among large population.

• Journal of IKEEE
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• v.22 no.1
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• pp.121-126
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• 2018

This paper addresses the consensus problem for nonlinear multi-agent systems using observer based controller. In order to solve this problem, the high gain approach is combined with the previous low gain controller. Also, it is shown that the proposed observer based controller can always guarantee the consensus of nonlinear systems with lower triangular nonlinearity.