• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.211-222
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• 2013

We consider the problem of nonparametrically estimating the conditional quantile function from censored data and propose new estimators here. They are based on local logistic regression technique of Lee et al. (2006) and "double-kernel" technique of Yu and Jones (1998) respectively, which are modified versions under random censoring. We compare those with two existing estimators based on a local linear fits using the check function approach. The comparison is done by a simulation study.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.652-657
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• 2013

In this paper the design methode of a separated composition state machine based on the compositive map with two chaotic maps together and the result of that is proposed. The digital circuits of chaotic composition map for the use of chaotic binary stream generator are designed in this work. The discretized truth table of chaotic composition function which is composed of two chaotic functions - the saw tooth function and skewed logistic function - is made out, and also simplefied Boolean algebras of digital circuits are obtained as a mathematical model. Consequently, the digital circuits of the map for chaotic composition function are presented in this paper.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1998.05a
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• pp.199-204
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• 1998

최근 화석연료의 과다한 사용으로 인한 온실효과 등 지구환경문제가 대두되면서 원자력은 온실가스를 배출하지 않는 에너지원으로서 다시 조망을 받고 있다. 특히 부존 에너지자원이 부족하고 전력의 수요가 급증하고 있는 우리의 사정을 고려한다면 원자력은 향후 수십년간 주요 발전원으로 상당한 역할을 수행할 것으로 기대된다. (중략)

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.469-472
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• 2002

본 논문에서는 카오스에 기반을 둔 ELM(Expanding Logistic Map) 암호화 알고리즘을 개선하기 위해 CELM(Cascade Expanding Logistic Map)을 제안한다. 제안된 암호화 시스템은 3차 방정식에 기반을 둔 ELM의 차수를 증가시켜 키의 범위를 확대하고, 서로 다른 Key 값과 초기 값의 함수를 Cascade연결하여 안정성을 높일 수 있었다.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2924-2926
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• 2005

몇몇 논문을 통하여 테스트 노력을 고려한 소프트웨어의 신뢰도 평가가 중요한 인자인 것으로 발표되었다. 여러 산업 현장의 경험 데이타에 의하면 그 형태가 지수함수형, 레일레이형, 웨이불형, 로지스틱형 테스트 노력 함수 중 하나인 것으로 보고되었다. 그러므로 연구자들은 각각의 소프트웨어 테스트 형태에 따라 이중하나의 적합한 형태를 사용해왔다. 테스트 노력이 어떤 형태의 그래프를 따르냐에 의해 신뢰도 예측 및 성장에 대한 평가가 달라지고 그에 따라 인도시기도 변한다. 따라서, 본 논문에서는 이 네 가지 형태의 테스트 노력을 가진 소프트웨어의 신뢰도 성장에 필요한 각종 파라미터를 구하는 방법에 대하여 고찰한다. 개발 현장에서 관찰된 테스트 노력 데이터와 결함검출을 비교하여 어느 형태의 테스트 노력 곡선이 그 경우에 적합한가를 연구하는 한편, 목표 신뢰도에 맞는 발행시기를 결정하는 문제를 연구한다.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2006.06a
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• pp.717-729
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• 2006

소프트웨어 신뢰도 성장 모델을 비동차 포아송 프로세스(NHPP)로 공식화하고, 이 모델을 이용하여 소프트웨어 신뢰도 척도에 대한 데이터 분석기법을 개발한다. 그간 여러 문헌에서 소프트웨어 신뢰도 성장 모델을 연구할 때 소프트웨어 테스트 중에 소요되는 테스트노력의 양으로서 지수함수형, 레일레이형, 웨이불형, 로지스틱형 테스트노적함수를 고려하여, 경우에 따라 이 중 하나의 적합한 형태를 사용해 왔다. 본 논문에서는 이 네 가지 형태에 대해서 최소자승평가자(LSE)와 최대가능성평가자(MLE)를 써서 파라미터를 구하는 방법을 검토한다.

• Journal of Advanced Navigation Technology
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• v.17 no.3
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• pp.292-297
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• 2013

In this paper, The design of digital circuits for chaotic composition function which is used for the key-stream generator is studied in this work. The overall design concept and procedure due to the mathematical model of chaotic key-stream generator is to be the explained in detail, and also the discretized truth table of chaotic composition function is presented in this paper. consequently, a composition state machine based on the compositive map with connecting two types of one dimensional and two dimensional chaotic maps together is designed and presented.

• 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.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.775-791
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• 2017

We frequently encounter binary data in real life. Logistic, Probit, Cauchit, Complementary log-log models are often used for binary data analysis. In order to analyze binary data, Liu (2004) proposed a Robit model, in which the inverse of cdf of the Student's t distribution is used as a link function. Kim et al. (2008) also proposed a generalized t-link model to make the binary regression model more flexible. The more flexible skewed distributions allow more flexible link functions in generalized linear models. In the sense, we propose a binary data regression model using skewed generalized t distributions introduced in Theodossiou (1998). We implement R code of the proposed models using the glm function included in R base and R sgt package. We also analyze Pima Indian data using the proposed model in R.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.159-166
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• 2013

In this paper, make a study decision problem called an optimal release policies after testing a software system in development phase and transfer it to the user. When correcting or modifying the software, finite failure non-homogeneous Poisson process model, presented and propose release policies of the life distribution, half-logistic property model which used to an area of reliability because of various shape and scale parameter. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, the parameters estimation using maximum likelihood estimation of failure time data, make out estimating software optimal release time. Software release time is used as prior information, potential security damages should be reduced.