• Smart Structures and Systems
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• v.19 no.1
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• pp.21-31
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• 2017

To control the stochastic vibration of a vibration-sensitive instrument supported on a beam, the beam is designed as a sandwich structure with magneto-rheological visco-elastomer (MRVE) core. The MRVE has dynamic properties such as stiffness and damping adjustable by applied magnetic fields. To achieve better vibration control effectiveness, the optimal bounded parametric control for the MRVE sandwich beam with supported mass under stochastic and deterministic support motion excitations is proposed, and the stochastic and shock vibration suppression capability of the optimally controlled beam with multi-mode coupling is studied. The dynamic behavior of MRVE core is described by the visco-elastic Kelvin-Voigt model with a controllable parameter dependent on applied magnetic fields, and the parameter is considered as an active bounded control. The partial differential equations for horizontal and vertical coupling motions of the sandwich beam are obtained and converted into the multi-mode coupling vibration equations with the bounded nonlinear parametric control according to the Galerkin method. The vibration equations and corresponding performance index construct the optimal bounded parametric control problem. Then the dynamical programming equation for the control problem is derived based on the dynamical programming principle. The optimal bounded parametric control law is obtained by solving the programming equation with the bounded control constraint. The controlled vibration responses of the MRVE sandwich beam under stochastic and shock excitations are obtained by substituting the optimal bounded control into the vibration equations and solving them. The further remarkable vibration suppression capability of the optimal bounded control compared with the passive control and the influence of the control parameters on the stochastic vibration suppression effectiveness are illustrated with numerical results. The proposed optimal bounded parametric control strategy is applicable to smart visco-elastic composite structures under deterministic and stochastic excitations for improving vibration control effectiveness.

• Journal of the Korean Statistical Society
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• v.26 no.1
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• pp.1-22
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• 1997

In the linear regression model $y_{i}$ = .alpha. $x_{i}$ $^{T}$ .beta. + .epsilon.$_{i}$ , i = 1,2,...,n, the weighted pairwise absolute deviation (WPAD) estimator was defined by minimizing the dispersion function D (.beta.) = .sum..sum.$_{{i $w_{{ij}}$$\mid$ $r_{j}$ (.beta.) $r_{i}$ (.beta.)$\mid$, where $r_{i}$ (.beta.)'s are residuals and $w_{{ij}}$'s are weights. This estimator can achive bounded total influence with positive breakdown by choice of weights $w_{{ij}}$. In this paper, we consider a more general type of dispersion function than that of D(.beta.) and propose a pairwise GM-estimator based on the dispersion function. Under some regularity conditions, the proposed estimator has a bounded influence function, a high breakdown point, and asymptotically a normal distribution. Results of a small-sample Monte Carlo study are also presented. presented.

• Health Policy and Management
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• v.5 no.2
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• pp.18-34
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• 1995

To clarify the relationship between the medical supply(medical persons and goods) and the use of bed, the author has made comparison among OECD 24 countries. Per Capita Bed-days can be divided into Average Length of Stay and Admission Rate, and these three variables were regressed upon both In-patient Care Beds of all medical institutions including acute somatic, psychiatric, special, nursing homes and other long-term care and Share of Total Health Employment in Total Employment. The result of regression analysis shows a statistically significant positive relationship between In-patient Care Beds and Average Length of Stay, and negative relationship between Share of Total Health Employment and Admission Rate. In addition to Ordinary Least Square(OLS) estimation, amended Bounded Influence Estimation(BIE) was also made to adjust the influence of outliers. Japan shows a very large number of In-patient Care Beds and a very low Share of Total Health Employment, and this medical situation is judged to have close relation to her long Average Length of Stay and low Admission Rate.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.169-179
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• 2005

In this study, we investigate the effects of the weight function in the bounded influence regression quantile (BIRQ) estimator for the AR(l) model with additive outliers. In order to down-weight the outliers of X -axis, the Mallows' (1973) weight function has been commonly used in the BIRQ estimator. However, in our Monte Carlo study, the BIRQ estimator using the Tukey's bisquare weight function shows less MSE and bias than that of using the Mallows' weight function or Huber's weight function. Thus, the use of the Tukey's weight function is recommended in the BIRQ estimator for our model.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.273-280
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• 2005

Robust magneto-telluric (MT) response function estimators are now in standard use in electromagnetic induction research. Properly devised and applied, these methods can reduce the influence of unusual data (outlier) in the response (electric field) variable, but often not sensitive to exceptional predictor (magnetic field) data, which are termed leverage points. A bounded influence estimator is described which simultaneously limits the influence of both outlier and leverage point, and has proven to consistently yield more reliable MT response function estimates than conventional robust approach. The bounded influence estimator combines a standard robust M-estimator with leverage weighting based on the statistics of the hat matrix diagonal, which is a standard statistical measure of unusual predictors. Further extensions to MT data analysis are proposed, including a establishment of data rejection criterion which minimize the influence of both electric and magnetic outlier in frequency domain based on statistical distribution of electromagnetic field. The rejection scheme made in this study seems to have an effective performance on eliminating extreme data, which is even not removed by BI estimator, in frequency domain. The effectiveness and advantage of these developments are illustrated using real MT data.

• Structural Engineering and Mechanics
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• v.51 no.4
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• pp.651-662
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• 2014

The main goal of this study is to extend the domain of influence result to cover the micropolar thermoelastic diffusion. So, we prove that for a finite time t>0 the displacement field $u_i$, the microrotation vector ${\varphi}_i$, the temperature ${\theta}$ and the chemical potential P generate no disturbance outside a bounded domain $B_t$.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.3
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• pp.90-103
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• 1998

The purposes of this study are to estimate the economic value and reasonable entrance fee of the Yeido Park, which is under construction in Seoul, by conduct the face-to-face interview. A total of 645 daults were selected by two stage cluster sampling. The senario was designed to meet the requirements for doubgle-bounded dichotomous choice CVM, and distributed with the photograph to epict and compare the current and suggested conditions. A donation vehicle and entrance fee were utilized to find the possibility of strategic behaviors and protest zero, and to make the data estimatable tfor interval censored survival analysis. Date was calibrated by the survival analysis to eleminate the 'fat-tail problem'. Weibull distribution was assumed as a baseline distrubution. The mean WTP of donation and entrance fee was ￦5,281 and ￦783, respectively. The economic value of this park was determined by aggregating the mean value, giving a total WTP for the population of ￦36,861,645,000. This economic value was composed with the use value and existence value. The calibrationi of the Weibull proportional hazard model showed that nearness to the park, age, intention to isit the park, and educational attainment were significant independent variable to influence an amount of donation.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.43-56
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• 2005

In this study, a robust estimation method for the first-order autocorrelation coefficient in the time series model following AR(l) process with additive outlier(AO) is investigated. We propose the L-type trimmed least squares estimation method using the preliminary estimator (PE) suggested by Rupport and Carroll (1980) in multiple regression model. In addition, using Mallows' weight function in order to down-weight the outlier of X-axis, the bounded-influence PE (BIPE) estimator is obtained and the mean squared error (MSE) performance of various estimators for autocorrelation coefficient are compared using Monte Carlo experiments. From the results of Monte-Carlo study, the efficiency of BIPE(LAD) estimator using the generalized-LAD to preliminary estimator performs well relative to other estimators.

• Journal of the Korean Statistical Society
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• v.28 no.2
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• pp.265-277
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• 1999

Classical and inverse estimation methods are two well known methods in statistical calibration problems. When there are outliers, both methods have large MSE's and could not estimate the input value correctly. We suggest median calibration estimation based on the LD-statistics. To investigate the robust performances, the influence function of the median calibration estimator is calculated and compared with other methods. When there are outliers in the response variables, the influence function is found to be bounded. In simulation studies, the MSE's for each calibration methods are compared. The estimated inputs as well as the performance of the influence functions are calculated.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.507-520
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• 1997

In this paper we propose a robust Wald-type test which is based on an efficient Mallows-type one-step GM-estimator. The proposed estimator based on the weight function of Song, Park and Nam (1996) has a bounded influence function and a high breakdown point. Under some regularity conditions, we compute the finite-sample breakdown point, and drive asymptotic normality of the proposed estimator. The level and power breakdown points, influence function and asymptotic distribution of the proposed test statistic are main points of this paper. To compare the performance of the proposed test with other tests, we perform some Monte Carlo simulations.