• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1081-1091
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• 2007

In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and location parameter in an exponentiated logistic distribution based on multiply Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples. We also propose and compare the estimators of the reliability function by using the proposed estimators of the parameters.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.830-833
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• 2002

To solve the internal security problem such as human error and bad faith, the automation of computer system management is significant. For this purpose, we focus attention in the automation of Mail Delivery Service. Today, requirement for reliable mail delivery system becomes larger and larger. However, existing systems are too strict about their configuration. Hence, we propose the method based on Reinforcement Learning (RL) to achieve proper MX record ordering. A measure on validity of the design of system, such as network topology number of servers and so on, is also obtained as side benefit. In order to verify the usability of the presented method, we did on a small model of mail delivery system. As a result, we show that RL is available for determination of the proper MX record ordering. Additionally, we suggest that it is also available for comparing validity of setting of MTA and the network design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2258-2274
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• 2020

In this paper we first propose a new cryptosystem based on our data hiding scheme (2,9,8) introduced in 2019 with high security, where encrypting and hiding are done at once, the ciphertext does not depend on the input image size as existing hybrid techniques of cryptography and steganography. We then exploit our automata approach presented in 2019 to design two algorithms for exact and approximate pattern matching on secret data encrypted by our cryptosystem. Theoretical analyses remark that these algorithms both have O(n) time complexity in the worst case, where for the approximate algorithm, we assume that it uses ⌈(1-ε)m)⌉ processors, where ε, m and n are the error of our string similarity measure and lengths of the pattern and secret data, respectively. In searchable encryption, our cryptosystem is used by users and our pattern matching algorithms are performed by cloud providers.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.111-118
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• 2011

This paper suggests a ratio-cum product estimator of a finite population mean using information on the coefficient of variation and the fcoefficient of kurtosis of auxiliary variate in stratified random sampling. Bias and MSE expressions of the suggested estimator are derived up to the first degree of approximation. The suggested estimator has been compared with the combined ratio estimator and several other estimators considered by Kadilar and Cingi (2003). In addition, an empirical study is also provided in support of theoretical findings.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.55-62
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• 2006

Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the dong's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute a missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(wen's GRG & weighted mean) method is the best of my other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.

• Communications of the Korean Mathematical Society
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• v.9 no.2
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• pp.423-438
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• 1994

We employ the Galerkin method to solve the nonlinear Urysohn integral equation (1.1) x(t) = f(t) ＋ $∫_{D}$ k(t, s, x(s))ds (t $\in$ D), where D is a bounded domain in $R^{d}$ , the function f and k are known and x is the solution to be determined. We assume that D has a locally Lipschitz boundary ([1, p. 67]). We can rewrite (1.1) in operator notation as x = f ＋ Kx. We consider (1.1) as an operator equation on $L_{\infty$}$(D) and assume that K is defined on the closure $\Omega$ of a bounded open set $\Omega$ ⊂ $L_{\infty}$(D). Throughout our analysis we put the following assumptions on (1.1).(omitted)(1.1).(omitted)

• Journal of the Korean Mathematical Society
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• v.41 no.6
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• pp.957-976
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• 2004

It is well known that the application of the nonlinear coordinate transformations is useful for efficient numerical evaluation of weakly singular integrals. In this paper, we consider the trapezoidal rule combined with a nonlinear transformation $\Omega$$_{m}$(b;$\chi$), containing a parameter b, proposed first by Yun [14]. It is shown that the trapezoidal rule with the transformation $\Omega$$_{m}$(b;$\chi$), like the case of the Gauss-Legendre quadrature rule, can improve the asymptotic truncation error by using a moderately large b. By several examples, we compare the numerical results of the present method with those of some existing methods. This shows the superiority of the transformation $\Omega$$_{m}$(b;$\chi$).TEX>).

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.425-448
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• 2003

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. We consider hierarchical models including selection models under a skewed heavy tailed error distribution proposed originally by Chen et al. (1999) and Branco and Dey (2001). These rich classes of models combine the information of independent studies, allowing investigation of variability both between and within studies, and incorporate weight function. Here, the testing for the skewness parameter is discussed. The score test statistic for such a test can be shown to be expressed as the posterior expectations. Also, we consider the detail computational scheme under skewed normal and skewed Student-t distribution using MCMC method. Finally, we introduce one example from Johnson (1993)'s real data and apply our proposed methodology. We investigate sensitivity of our results under different skewed errors and under different prior distributions.

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.511-520
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• 2013

Detection outliers and robust estimators are crucial in regression models with outliers. In such studies the focus is on detecting outliers and estimating the coefficients using leave-one-out. Our study introduces Rice estimator which is an error variance estimator without estimating the coefficients. In particular, we study a comparison of the statistical properties for Rice estimator with and without outliers in simple regression models.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.89-100
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• 1994

In this paper we consider a new estimator of mean residual life (MRL), based on the partial moment of the distribution. The parameters of a partial moment are estimated by its maximum likelihood estimators when the underlying distribution is known. Though the new estimator is not a consistent estimator of the MRL, it is shown to have smaller mean squared error than the well known empirical MRL estimator for certain parametric families. Numerical summaries of the mean squared errors of the new estimator are presented.