• 전기학회논문지
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• 제58권6호
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• pp.1223-1229
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• 2009

The performance of Radial Basis Function Neural Networks depends on setting up the Radial Basis Functions over the input space which are the important design procedure of Radial Basis Function Neural Networks. The existing method to initialize the location of the radial basis functions over the input space is to use the conditional fuzzy C-means clustering. However, the researchers which are interested in the conditional fuzzy C-means clustering cannot get as good modeling performance as they expect because the conditional fuzzy C-means clustering cannot project the information which is extracted over the output space into the input space. To compensate the above mentioned drawback of the conditional fuzzy C-means clustering, we apply a fuzzy K-nearest neighbors approach to project the auxiliary information defined over the output space into the input space without lose of the information.

• 한국언어정보학회지:언어와정보
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• 제15권1호
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• pp.13-29
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• 2011

Conditional sentences also can be formed by inversion of subject and auxiliary, but it happens only in a limited environment. This paper addresses grammatical constraints in conditional inversion and how they behave differently from the regular conditional clauses based on corpus investigations. Our corpus search reveals many different types of conditional inversion constructions, indicating the difficulties of deriving inverted conditionals from movement operations. In this paper, we provide a construction-based approach to the inverted conditional construction. The paper shows that the most optimal way of describing the general as well as idiosyncratic properties of the inverted conditional constructions is an account in the spirit of construction grammar in which a grammar is a repertory of constructions forming a network connected by links of inheritance.

• 정보보호학회논문지
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• 제16권3호
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• pp.87-99
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• 2006

본 논문에서는 암호화된 SVC (Scalable video coding) 비트스트림을 이용한 조건적 접근제어 방법을 제안한다. 제안한 방법은 새로운 비디오 코딩 기법인 SVC에 적합한 암호화와 암호화된 SVC 비트스트림에서 비트스트림 추출 (Extraction) 후 복호화를 통해 효과적인 조건적 접근제어(Conditional Access Control) 방법을 제공하는데 그 목적이 있다. 제안하는 SVC 조건적 접근제어는 SVC 비트스트림의 암호화에 대한 요구사항을 분석하여 SVC 코딩기법에 적합하게 암호화를 시행하고 암호화된 SVC비트스트림의 적응변환 수행 시 비트스트림 추출과 선택적 복호화를 통해 수행 된다. 본 논문은 SVC비트스트림에 대해 암호화를 시행한 후 다양한 비디오로 접근을 시도하는 실험을 통하여 제안한 방법의 유효성을 검증하였다.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.783-791
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• 2004

In this paper we review recent developments in nonlinear time series modeling on both conditional mean and conditional variance. Traditional linear model in conditional mean is referred to as ARMA(autoregressive moving average) process investigated by Box and Jenkins(1976). Nonlinear mean models such as threshold, exponential and random coefficient models are reviewed and their characteristics are explained. In terms of conditional variances, ARCH(autoregressive conditional heteroscedasticity) class is considered as typical linear models. As nonlinear variants of ARCH, diverse nonlinear models appearing in recent literature including threshold ARCH, beta-ARCH and Box-Cox ARCH models are remarked. Also, a class of unified nonlinear models are considered and parameter estimation for that class is briefly discussed.

• Communications for Statistical Applications and Methods
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• 제22권5호
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• pp.507-518
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• 2015

It is not easy to select a linear mixed model since the main interest for model building could be different and the number of parameters in the model could not be clearly defined. In this paper, performance of conditional Akaike Information Criteria and its bias-corrected version are compared with marginal Bayesian and Akaike Information Criteria through a simulation study. The results from the simulation study indicate that bias-corrected conditional Akaike Information Criteria shows promising performance when candidate models exclude large models containing the true model, but bias-corrected one prefers over-parametrized models more intensively when a set of candidate models increases. Marginal Bayesian and Akaike Information Criteria also have some difficulty to select the true model when the design for random effects is nested.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권7호
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• pp.3497-3515
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• 2018

Differential privacy has broadly applied to statistical analysis, and its mainly objective is to ensure the tradeoff between the utility of noise data and the privacy preserving of individual's sensitive information. However, an individual could not achieve expected data utility under differential privacy mechanisms, since the adding noise is random. To this end, we proposed an adaptive Gaussian mechanism based on expected data utility under conditional filtering noise. Firstly, this paper made conditional filtering for Gaussian mechanism noise. Secondly, we defined the expected data utility according to the absolute value of relative error. Finally, we presented an adaptive Gaussian mechanism by combining expected data utility with conditional filtering noise. Through comparative analysis, the adaptive Gaussian mechanism satisfies differential privacy and achieves expected data utility for giving any privacy budget. Furthermore, our scheme is easy extend to engineering implementation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.583-584
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• 2008

This paper presents a low-power and high-speed pulsed flip-flop based on dual-precharging and conditional discharging. The dual-precharging operation minimizes the parasitic capacitance of each precharge node, resulting in high-speed operation. The conditional-discharging operation minimizes the redundant transitions of precharge nodes, resulting in low-power operation. Linear feedback shift register (LFSR) designed in a $0.18{\mu}m$ CMOS technology using the proposed flip-flop achieves 32% power reduction as compared to conventional design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권9호
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• pp.4548-4559
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• 2018

Conditional differential attack against NFSR-based cryptosystems proposed by Knellwolf et al. in Asiacrypt 2010 has been widely used for analyzing round-reduced Grain v1. In this paper, we present improved conditional differential attacks on Grain v1 based on a factorization simplification method, which makes it possible to obtain the expressions of internal states in more rounds and analyze the expressions more precisely. Following a condition-imposing strategy that saves more IV bits, Sarkar's distinguishing attack on Grain v1 of 106 rounds is improved to a key recovery attack. Moreover, we show new distinguishing attack and key recovery attack on Grain v1 of 107 rounds with lower complexity O($2^{34}$) and appreciable theoretical success probability 93.7%. Most importantly, our attacks can practically recover key expressions with higher success probability than theoretical results.

• 한국인터넷방송통신학회논문지
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• 제14권6호
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• pp.47-54
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• 2014

러프집합을 구성하는 식별불가능 관계를 표현하는 정보시스템에서 데이터의 중복이나 비일관성은 피할 수 없기 때문에 속성의 감축은 매우 중요하다. 러프집합이론에 있어서 일관적인 정보시스템과 비일관적인 정보시스템의 속성감축의 차이를 극복하고 자, 본 연구에서는 조건 및 결정속성에 대한 상관분석에 베이지언 사후확률을 적용한 새로운 불확실성 척도와 속성감축 알고리즘을 제안한다. 정보시스템의 불확실성에 대하여 제안된 척도와 기존의 조건부 정보엔트로피 척도를 비교해 본 결과, 정보시스템의 조건속성과 결정속성의 상호정보를 이용하여 속성간의 불확실성을 측정하는데 있어 제안된 방법이 조건부 정보엔트로피에 의한 방법보다 정확성이 있음을 보여준다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
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• pp.18-21
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• 2003

We propose some properties of fuzzy conditional expectation of hybrid number the addition of fuzzy number and random variable using Cartesian product distance for ${\alpha}$-level sets.