• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.8
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• pp.838-848
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• 2014

We present a simulation study of an algorithm for the range and angle of arrival(AOA) estimation with an interferometric synthetic aperture radar(InSAR) altimeter using a real digital elevation model(DEM). We also illustrate a step-by-step procedure of generating raw InSAR data, as well as their range and azimuth compressed data, which is to be used for the subsequent altitude and angle estimation. The AOA is estimated using a deterministic maximum likelihood estimator(DMLE) applied to the first arrived point for each pulse in the compressed data obtained with three antennas. The range bin size and the pulse repetition interval(PRI) are much smaller than the cell size of the DEM used in this study. To make the DEM compatible to the radar parameters, we first generate a higher resolution DEM by linearly interpolating the given DEM. After a brief description of the principle of the InSAR altimeter, the algorithms for altitude and angle estimation are presented, and their performance is assessed through simulation.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.362-369
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• 2012

Recently, a target detection based on a distributed sensor network has been much studied in active sonar. Zhou et al. proposed a target localization method using line fitting based on a distributed sensor network which consists of low complexity sensors that only report binary detection results. This method has three advantages relative to ML estimator. First, there is no need to estimate propagation model parameters. Second, the computation is simple. Third, it only use sensors with "detection", which implies less data to be collected by data processing center. However, this method has larger target localization error than the ML estimator. In this paper, a target localization method which modifies Zhou's method is proposed for reducing the localization error. The modified method shows the performance improvement that the target localization error is reduced by 40.7% to Zhou's method in the point of RMSE.

• Journal of Korea Water Resources Association
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• v.32 no.1
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• pp.3-13
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• 1999

In this study, an alternative spatial analysis method against conventional methods such as Thiessen method, Inverse Distance method, and Kriging method, named Spatial-Analysis Neural-Network (SANN) is presented. It is based on neural network modeling and provides a nonparametric mean estimator and also estimators of high order statistics such as standard deviation and skewness. In addition, it provides a decision-making tool including an estimator of posterior probability that a spatial variable at a given point will belong to various classes representing the severity of the problem of interest and a Bayesian classifier to define the boundaries of subregions belonging to the classes. In this paper, the SANN is implemented to be used for analyzing a mean annual precipitation filed and classifying the field into dry, normal, and wet subregions. For an example, the whole area of South Korea with 39 precipitation sites is applied. Then, several useful results related with the spatial variability of mean annual precipitation on South Korea were obtained such as interpolated field, standard deviation field, and probability maps. In addition, the whole South Korea was classified with dry, normal, and wet regions.

• Journal of the Korean Statistical Society
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• v.20 no.2
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• pp.202-207
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• 1991

In Le Cam's earlier work on superefficiency, it is proved that if an estimate is superefficient at a given paramter value $\theta$$\_$0/, then there must exist an infinite sequence {$\theta$$\_$n/}) of values(conversing to $\theta$$\_$0/) at which this estimate is worse than M. L. E. for certain classes of loss functions. For one-dimensional cases, these classes of lass functions include squared error loss. However. for multi-dimensional cases, they do not. This note is to give an example where a superefficiest estimator of a multi-dimensional parameter is not inferior to M. L. E. along any sequence ($\theta$$\_$n/) converging to the point of superefficiency with respect to the squared error loss.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.3 s.192
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• pp.67-75
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• 2007

This paper deals with a problem of vibration suppression of a piezoelectric beam using a self-sensing algorithm. Two methods, which are PPF(positive position feedback) and SRF(strain rate feedback), are considered to suppress a residual vibration of a piezoelectric beam developed during the step positioning of a beam end point. A self-sensing algorithm treated here is basically a strain rate estimator of a beam movement and is to be used for the closed loop control. The efficacy of the proposed idea is evaluated through experiments.

• Journal of Applied Reliability
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• v.14 no.1
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• pp.1-9
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• 2014

One important measure of performance for a repairable system is steady-state availability. In this paper, a method to estimate and establish confidence interval for the steady-state availability under Weibull lifetime and lognormal repair time distributions is proposed. Also, bias and mean squared error of a point estimator for an availability are investigated. In addition, a procedure to derive the sample size and critical value for availability demonstration test is presented and illustrated with a numerical example.

• Journal of Korean Society on Water Environment
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• v.26 no.2
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• pp.297-302
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• 2010

It is very important to know mean and confidence interval of water-quality constituents such as BOD for water-quality control and management of rivers and reservoirs effectively. The mean and confidence interval of BOD at Anseong2 and Hwangguji3 sampling stations which are located at the border of local governments in Anseong Stream were estimated and analyzed in this paper using Bootstrap technique which is one of non-parametric statistics. The results of Bootstrap were compared with arithmetic mean, geometric mean, Biweight method mean as a point estimator and distribution mean came from the appropriate probability distribution of Log-normal. In Bootstrap technique 12 data set was randomly selected in each year and 1000 samples was produced to get parameter of population. Visual Basic for Applications (VBA) of Microsoft Excel was utilized in Bootstrap. It was revealed that the Bootstrap technique can be used to explain more rigorously and robustly the achievement or violation of BOD target concentration in Total Maximum Daily Load (TMDL).

• Journal of the Korean Data and Information Science Society
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• v.4
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• pp.137-146
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• 1993

The Proposed goodness-of-fit test Statistic $\hat{\lambda}_{\alpha}$ derived from the test Statistc in Kim (1992) is itself a smoothing parameter which is selected to minimize an estimated MISE for a truncated series estimator, $d_{\hat{\lambda}{n}}$, of the comparison density function. Therefore, this test statistic leads immediately to a point estimate of the density function in the event that $H_{0}$ is ejected. The limiting distribution of $\hat{\lambda}_{\alpha}$ was obtained under the null hypothesis. It is also shown that this test is consistent against fixed alternatives.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.437-450
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• 1994

The problem of testing for a change in the parameter of a stochastic process is particularly important in simulation studies. In studies of the steady state characteristics of a simulation model, it is important to identify initialization bias and to evaluate efforts to control this problem. A simulation output have the characteristics of chaotic behavior because of sensitive dependence on initial conditions. For that reason, we will apply Lyapunov exponent for diagnosis of chaotic motion to simulation output analysis. This paper proposes two methods for diagnosis of steady state in simulation output. In order to evaluate the performance and effectiveness of these methods using chaos theory, M/M/I(.inf.) queueing model is used for testing point estimator, average bias.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.5
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• pp.120-127
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• 1998

Differential inequalities occurring in problems of obstacle contact problems are recast into variational inequalities and analyzed by finite element methods. A new a posteriori error estimator, which is essential in adaptive finite element method, is introduced to capture the errors in finite element approximations of these variational inequalities. In order to construct a posteriori error estimates, saddle point problems are introduced using Lagrange parameters and upper bounds are provided. The global upper bound is localized by a special mixed formulation, which leads to upper bounds of the element errors. A numerical experiment is performed on an obstacle contact problem to check the effectivity index both in a local and a global sense.