• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.141-146
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• 2003

In this paper, we propose an adaptive search range decision algorithm for motion vector estimation in video coding. The performance of general motion estimation method in video coding mechanism is evaluated with respect to the motion vector accuracy and the complexity, which is trade-off. The proposed algorithm that plays as a role of pre-processing for motion vector estimation determines the motion search range by the local statistics of motion vector of neighboring blocks, resulting in more than 60(%) reduction of the computational cost without the loss of visual quality. Experimental results show the capability of the proposed algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.1
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• pp.63-74
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• 1996

Automatic transmission for heavy duty vehicles is a part of the power pack which includes steering and braking systems. This transmission in different from the one for passenger car. Therefore, in order to understand the trend of the important design parameters, maneuverability, acceleration performance and maximum speed, we need to analyze the total performance characteristics of the power transmission systems. In this study, modeling of the automatic transmission in heavy duty vehicle is carried out and the performance analysis method is presented. Results can be used for performance estimation data in the analysis for several combination method which determines the optimal parameters on the basis of penalty functions and weightings. And the estimation method of the important performance parameters such as engine inertia or power loss of engine by experiments is presented.

• Journal of the Korean Solar Energy Society
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• v.30 no.6
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• pp.95-101
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• 2010

This paper presents performance estimation approach of grid-connected photovoltaic(PV) system to predict energy yield from irradiance to PV system using normalized yield model for changing meteorological conditions. The accuracy and validity of proposed performance estimation method is identified by compared measured with estimated yield using monitored data. These results will indicate that it is useful to estimate various loss factors causing the system performance obstruction and enhance the lifetime yield of PV system.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.277-283
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• 2019

In this paper, we propose a distributed fusion estimation for sensor networks using a receding horizon strategy. Communication channels were modelled as Markov jump systems, and a posterior probability distribution for communication channel characteristics was calculated and incorporated into the filter to allow distributed fusion estimation to handle path loss observation situations automatically. To implement distributed fusion estimation, a Kalman-Consensus filter was then used to obtain the average consensus, based on the estimates of sensors randomly distributed across sensor networks. The advantages of the proposed algorithms were then verified using a large-scale sensor network example.

• Journal of applied mathematics & informatics
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• v.41 no.2
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• pp.449-468
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• 2023

This paper deals in the study of the estimation of the parameters of Erlang distribution based on rank set sampling and some of its modifications. Here we considered Maximum Likelihood (ML) and the Bayesian technique to estimate the shape and scale parameter of Erlang distribution based on RSS and its some modifications such as ERSS, MRSS, and MRSSu. The derivation for unknown parameters of Erlang distribution is well presented using normal approximation to the asymptotic distribution of ML estimators. But due to the complexity involves in the integral, the Bayes estimator of unknown parameters is obtained using MCMC method. Further, we compared the MSE of estimation in different sampling schemes with different set sizes and cycle size. A real-life data application is also given to illustrate the efficiency of the proposed scheme.

• Journal of the Korean Statistical Society
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• v.10
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• pp.128-139
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• 1981

The Bayesian sequential estimation problem for k parameters exponential families is considered using loss related to the Fisher information. Tractable expressions for the Bayes estimator and the posterior expected loss are found, and the myopic or one-step-ahead stopping rule is defined. Sufficient conditions are given for optimality of the myopic procedure, and the myopic procedure is shown to be asymptotically optimal in all cases considered.

• Journal of the Korean Statistical Society
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• v.15 no.2
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• pp.97-106
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• 1986

Assume that $X_1, X_2, \cdots, X_N$ are iid p-dimensional normal random vectors ($p \geq 3$) with unknown covariance matrix. The problem of estimating multivariate normal mean vector in an empirical Bayes situation is considered. Empirical Bayes estimators, obtained by Bayes treatmetn of the covariance matrix, are presented. It is shown that the estimators are minimax, each of which domainates teh maximum likelihood estimator (MLE), when the loss is nonsingular quadratic loss. We also derive approximate credibility region for the mean vector that takes advantage of the fact that the MLE is not the best estimator.

• Journal of the Korean Data and Information Science Society
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• v.4
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• pp.75-86
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• 1993

This paper deals with the problem of estimating a reliability function for the Rayleigh distribution. Using the priors about a reliabity of real interest some Bayes estimators and Bayes credible sets are proposed and studied under squared error loss and Harris loss.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.211-218
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• 1998

This paper deals with the problem of obtaining some Bayes estimators of exponential reliability in a time censored sampling with incomplete information. Some Bayes estimators are proposed and studied under squared error loss and Harris loss.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.1-10
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• 2002

A Bayes estimator of the scale parameter in an exponential distribution will be considered by a LINEX error, then the risk of the Bayes estimator using a LINEX loss will be compared with that of a Bayes estimator using a square error.