• Journal of applied mathematics & informatics
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• v.31 no.3_4
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• pp.417-424
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• 2013

Giuliano Antonini et al.(2008) have introduced the concept of extended acceptability and the results show that the extended acceptability structure has no effect on the exponential inequality except replacing a constant M = 1 with a constant M > 0. We discuss the complete convergence for extended acceptable random variables by using the exponential inequality.

• Journal of the Optical Society of Korea
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• v.14 no.2
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• pp.90-96
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• 2010

Joint transform correlator (JTC) has been the most suitable technique for real time pattern recognition. This paper proposes a new phase adjustment which adopts two steps of random phase adjustment in the spatial domain and additional phase adjustment in the Fourier domain. Simulated results are presented to show the optimum condition of the phase adjustment and the effect on the correlation peaks, the peak signal-to-noise ratio and the level of discrimination.

• Communications for Statistical Applications and Methods
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• v.3 no.1
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• pp.87-99
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• 1996

We construct bootstrap confidence intervals for reliability, R= P{X>Y}, where X and Y are independent normal random variables. One way ANOVA random effect models are assumed for the populations of X and Y, where standard deviations $\sigma_{x}$ and $\sigma_{y}$ are unequal. We investigate the accuracy of the proposed bootstrap confidence intervals and classical confidence intervals work better than classical confidence interval for small sample and/or large value of R.

• Communications for Statistical Applications and Methods
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• v.7 no.3
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• pp.817-827
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• 2000

In this paper, we investigate the Bayesian approach to random effect binomial regression models with improper prior due to the absence of information on parameter. We also propose a method of estimating the posterior moments and prediction and discuss some general methods for studying model assessment. The methodology is illustrated with Crowder's Seeds Data. Markov Chain Monte Carlo techniques are used to overcome the computational difficulties.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.697-710
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• 2021

Relative error prediction is preferred over ordinary prediction methods when relative/percentile errors are regarded as important, especially in econometrics, software engineering and government official statistics. The relative error prediction techniques have been developed in linear/nonlinear regression, nonparametric regression using kernel regression smoother, and stationary time series models. However, random effect models have not been used in relative error prediction. The purpose of this article is to extend relative error prediction to some of generalized linear mixed model (GLMM) with panel data, which is the random effect models based on gamma, lognormal, or inverse gaussian distribution. For better understanding, the real auto insurance data is used to predict the claim size, and the best predictor and the best relative error predictor are comparatively illustrated.

• Journal of electromagnetic engineering and science
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• v.10 no.2
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• pp.61-66
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• 2010

This paper is concerned with an analysis of the back scattering of electromagnetic waves from a target moving along random rough surfaces such as the desert, and sea. First, the discrete ray tracing method(DRTM) is introduced, and then, this method is applied to the back scattering problem in order to investigate the effect of the back scattering from random rough surfaces on the electric field intensities. Finally, numerical examples of various height deviations of the Gaussian type of rough surfaces are shown. It is numerically demonstrated that the back scattering is dominated by the diffractions related to the reflections from the random rough surfaces.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.886-889
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• 2002

In order to evaluate absorption coefficient, experimental works for normal and random incident absorption coefficient are made. An investigation for correlation between normal and random incident absorption was carried out by experiment and analysis. It appears that at the low frequencies, the random incident absorption is higher than the normal one, whileas at the high frequencies, the random incident absorption is decreased due to the effect of grazing incident components.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.262-264
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• 2005

We propose a filter design method to suppress the effect of gyroscope mixed random errors at INS system level. It is based on the result that mixed random errors can be represented by a single equivalent ARMA model. At first step, the time difference of equivalent ARMA process is performed, which consider the characteristic of indirect feedback Kalman filter used in INS filter. Next, a state space conversion of time differenced ARMA model is achieved. If the order of AR is greater than that of MA, the controllable or observable canonical form is used. Otherwise, we introduce the state equation of which the state variable is composed of the ARMA model output and several step ahead predicts of that. At final step, a complete form state equation is presented. The simulation results shows that the proposed method gives less transient error and better convergence compared to the conventional filter which assume the mixed random errors as white noise.

• Journal of Mechanical Science and Technology
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• v.16 no.5
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• pp.583-590
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• 2002

When a mechanical structure is driven by stationary wide band random point forces, the resulting vibration depends upon the number, location, and joint statistical properties of the exciting forces. In this study, under the assumption of light damping, an approximate procedure for analyzing plates is briefly outlined. The effects of number, location and correlation of the force field on the vibration level are then investigated for various cases in which random point forces with band limited white noise are applied, and the optimal spacing between input forces that produces a relative minimum in the vibration response is predicted.

• Journal of Sensor Science and Technology
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• v.29 no.4
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• pp.227-231
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• 2020

Silver nanowire random networks are promising candidates for replacing indium tin oxide (ITO) as transparent and conductive electrodes. They can also be used as transparent heating films with self-cleaning and defogging properties. By virtue of the Joule heating effect, silver nanowire random networks can be heated when voltage bias is applied; however, they are unsuitable for long-term use. In this work, we study the Joule heating of silver nanowire random networks embedded in polymers. Silver nanowire random networks embedded in polymers exhibit breakdown under the application of electric current. Their surface morphological changes indicate that nanoparticle formation may be the main cause of this electrical breakdown. Numerical analyses are used to investigate the temperatures of the silver nanowire and substrate.