• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2298-2303
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• 2003

In this paper, very simple methods based on the exponential analysis are presented by which transfer function models for processes can easily be obtained. These methods employ step responses or impulse responses of the processes. These can also give a more precise transfer function model compared to the well-known graphical methods. Transfer functions are determined based on Prony method, which is one of the oldest and the most representative methods in the exponential analysis. Here, the method is reformed and applied to obtain the so-called low-order transfer function with pure time delay from the data of the step response. The effectiveness of the proposed method is examined through several numerical examples and experiments of the 2-tank level control process.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.553-560
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• 2007

In this paper, we consider two components system which lifetimes have Freund's bivariate exponential model with equal failure rates. We propose Bayesian multiple comparisons procedure for the failure rates of I Freund's bivariate exponential populations based on Dirichlet process priors(DPP). The family of DPP is applied in the form of baseline prior and likelihood combination to provide the comparisons. Computation of the posterior probabilities of all possible hypotheses are carried out through Markov Chain Monte Carlo(MCMC) method, namely, Gibbs sampling, due to the intractability of analytic evaluation. The whole process of multiple comparisons problem for the failure rates of bivariate exponential populations is illustrated through a numerical example.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.103-110
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• 2011

Exponential distribution is widely adopted as a lifetime model. Many authors have considered the interval estimation of the parameters of two-parameter exponential distribution based on complete and censored samples. In this paper, we consider the interval estimation of the location and scale parameters and the joint confidence region of the parameters of two-parameter exponential distribution based on upper records. A simulation study is done for the performance of all proposed confidence intervals and regions. We also propose the predictive intervals of the future records. Finally, a numerical example is given to illustrate the proposed methods.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.107-113
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• 2009

This paper deals with noninformative priors for such as Jeffres' prior, reference prior and probability matching prior for scale parameter of exponential distribution when the data are collected in multiple step stress accelerated life tests. We find the noninformative priors for this model and show that the reference prior satisfies first order matching criterion. Using artificial data, we perform Bayesian analysis for proposed priors.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.507-514
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• 2007

We shall propose several estimators for the scale parameter in the Pareto distribution with an unidentified exponential outlier when the scale parameter is functions of a known exposure level, and obtain expectations and variances for their proposed estimators. And we shall compare numerically efficiencies for proposed estimators of the scale and shape parameters in the small sample sizes.

• Journal of Information Science Theory and Practice
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• v.1 no.3
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• pp.6-11
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• 2013

A new explanation, using exponential functions, is given for the S-shaped functional relation between the mean citation score and the proportion of top 10% (and other percentages) publications for the 500 Leiden Ranking universities. With this new model we again obtain an explanation for the concave or convex relation between the proportion of top $100{\theta}%$ publications, for different fractions of ${\theta}$.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.107-114
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• 2005

We shall consider parametric estimations for the scale parameter in the exponential distribution when the parameter is function of a known exposure level, and obtain expectations and variances for their proposed estimators. And we shall compare numerically efficiencies for proposed estimators of the scale parameter in the small sample sizes.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1217-1222
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• 2011

In this paper, we show that any circular density can be closely approximated by an exponential family of distributions. Therefore we propose an exponential family of distributions as a new family of circular distributions, which is absolutely suitable to model any shape of circular distributions. In this family of circular distributions, the trigonometric moments are found to be the uniformly minimum variance unbiased estimators (UMVUEs) of the parameters of distribution. Simulation result and goodness of fit test using an asymmetric real data set show usefulness of the novel circular distribution.

• Magazine of the Korean Society of Agricultural Engineers
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• v.26 no.3
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• pp.90-98
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• 1984

In this paper, the anthor made a basic study of the storage function model and examined several constants in applying the storage function model to flood run-off analysis by dealing with the data in the Supyung and Hoyng Syung watershed, the applicabilities of the storage function model are examined by searching this optimum model parameters in two watersheds. The results are summarized as follows, 1) The optimum values of the exponential constants, P, in the storage function model showed to be 0.77 to 0.87 in two watersheds observed, therefore it was confirmed that the storage fumction model was approaching to the surface runoff model. 2) It was confirmed that the interval of variation of the storage constant, K, Showed to be larger than that of the exponential constant, p. 3) Relative erros in the discharge obtained by using the storage function model and the SDFP mothod showed to be 20 and 17 percent respectively to the observed discharge, therefore it was confirmed that the applicability of the storage function model using the SDFP method are excellent for runoff analysis. 4) A simple method is proposed for estimating the lag time in the storage function model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.5
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• pp.761-773
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• 2023

This paper proposes a method to increase the power-analysis resistance of the neural network model's feedforward process by replacing the exponential-based activation function, used in the deep-learning field, with an approximated function especially at the multi-layer perceptron model. Due to its nature, the feedforward process of neural networks calculates secret weight and bias, which already trained, so it has risk of exposure of internal information by side-channel attacks. However, various functions are used as the activation function in neural network, so it's difficult to apply conventional side-channel countermeasure techniques, such as masking, to activation function(especially, to exponential-based activation functions). Therefore, this paper shows that even if an exponential-based activation function is replaced with approximated function of simple form, there is no fatal performance degradation of the model, and than suggests a power-analysis resistant feedforward neural network with exponential-based activation function, by masking approximated function and whole network.