• Journal of Korea Water Resources Association
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• v.45 no.4
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• pp.383-391
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• 2012

This study aims to present the sensitivity analysis approach for multi-criteria decision making (MCDM) method to reduce the uncertainty of weighting and performance values. This study focuses on two major problems of the uncertainty for MCDM method. The first major problem is how to determine the most critical criterion and the second is how to determine the most critical measure of performance. This study used the application of weighted sum method for water resources planning. The criticality degrees and the sensitivity coefficients of criterion and alternative are used. This results of sensitivity analysis can be applied to the general water resources planning in real.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.5
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• pp.442-449
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• 2009

A two-dimensional cross-section analysis program based on the finite element method has been developed for composite blades with solid, thin-walled and compound cross-sections. The weighted-modulus method is introduced to determine the laminated composite material properties. The shear center and the torsion constant for any given section are calculated according to the Trefftz' definition and the St. Venant torsion theory, respectively. The singular value problem of cross-section stiffness properties faced during the section analysis has been solved by performing an eigenvalue analysis to remove the rigid body mode. Numerical results showing the accuracy of the program obtained for stiffness, offset and inertia properties are compared in this analysis. The current analysis results are validated with those obtained by commercial software and published data available in the literature and a good correlation has generally been achieved through a series of validation study.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.17-25
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• 2009

This paper presents a methodology for a fall detection using the feature extraction method based on the neural network with weighted fuzzy membership functions (NEWFM). The distributed non-overlap area measurement method selects the minimized number of input features by removing the worst input features one by one. Nineteen number of wavelet transformed coefficients captured by a triaxial accelerometer are selected as minimized features using the non-overlap area distribution measurement method. The proposed methodology shows that sensitivity, specificity, and accuracy are 95%, 97.25%, and 96.125%, respectively.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.129-135
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• 2008

This paper presents a methodology to forecast KOSPI index by extracting fuzzy rules based on the neural network with weighted fuzzy membership functions (NEWFM) and the minimized number of input features using the distributed non-overlap area measurement method. NEWFM classifies upward and downward cases of KOSPI using the recent 32 days of CPPn,m (Current Price Position of day n for n-1 to n-m days) of KOSPI. The five most important input features among CPPn,m and 38 wavelet transformed coefficients produced by the recent 32 days of CPPn,m are selected by the non-overlap area distribution measurement method. For the data sets, from 1991 to 1998, the proposed method shows that the average of forecast rate is 67.62%.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.6
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• pp.789-799
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• 2007

In this paper, we propose a stochastic finite element formulation which takes into account the randonmess in the material and geometrical parameters. The formulation is proposed for plate structures, and is based on the weighted integral approach. Contrary to the case of elastic modulus, plate thickness contributes to the stiffness as a third-order function. Furthermore, Poisson's ratio is even more complex since this parameter appears in the constitutive relations in the fraction form. Accordingly, we employ Taylor's expansion to derive decomposed stochastic field functions in ascending order. In order to verify the proposed formulation, the results obtained using the proposed scheme are compared with those in the literature and those of Monte Carlo analysis as well.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.2
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• pp.387-395
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• 1991

Large deflection behavior of cylindrically orthotropic thin circular plates is investigated by the numerical technique of differential quadrature. Governing equations are derived in terms of transverse deflection and stress function and a Newton-Raphson technique is used to solve the nonlinear systems of equations. For small values of degree of differential quadrature (N.leq.13), as the degree of differential quadrature increases, the center deflection converges. However, as N increases further, the center deflection diverges by ill-conditioning in the weighting coefficients. As the orthotropic parameter increases, the center deflection decreases and behaves linear for the loads. At center, the stress is affected mainly by orthotropic parameter, while the stress is affected mainly by boundary condition at edge.

• Water for future
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• v.24 no.1
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• pp.109-117
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• 1991

The governing equation of flow in porous media is developed on the bases of the continuity equation of fluid for transient flow through a saturated-unsaturated zone, and substitution of Darcy's law. The numerical solutions are obtained by finite element method based on the Galerkin principles weighted residuals. The analysis are carried out by using the unsteady storm data observed and rainfall intensities which are obtained by using the rainfall excess model in considering of the initial losses. The functional relationships between the hydraulic conductivity, capillary pressure head and volumetric water content are applied to the flow of water through unsaturated soil varied with changes of water content.

• Journal of Internet Computing and Services
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• v.8 no.1
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• pp.125-132
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• 2007

This paper presents an approach to detect premature ventricular contractions(PVC) using the neural network with weighted fuzzy membership functions(NEWFM), NEWFM classifies normal and PVC beats by the trained weighted fuzzy membership functions using wavelet transformed coefficients extracted from the MIT-BIH PVC database. The eight most important coefficients of d3 and d4 are selected by the non-overlap area distribution measurement method. The selected 8 coefficients are used for 3 data sets showing reliable accuracy rates 99,80%, 99,21%, and 98.78%, respectively, which means the selected input features are less dependent to the data sets. The ECG signal segments and fuzzy membership functions of the 8 coefficients enable input features to interpret explicitly.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.11 no.2
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• pp.73-84
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• 1992

This paper studies noise subtraction methods and distance measures for speech recognition in a noisy environment, and investigates noise robustness of the distance measures applied to the problem of isolated word recognition in white Gaussian and colored noise (vehicle noise) environments. Noise subtraction methods which can be used as a pre-processor for the speech recognition system, such as the spectral subtraction method, autocorrelation subtraction method, adaptive noise cancellation and acoustic beamforming are studied, and distance measures such and Log Likelihood Ratio ($d_{LLR}$), cepstral distance measure ($d_{CEP}$), weighted cepstral distance measure ($d_{WCEP}$), spectral slope distance measure ($d_{RPS}$) and cepstral projection distance measure ($d_{CP},\;d_{BCP},\;d_{WCP},\;d_{BWCP}$) are also investigated. Testing of the distance measures for speaker-dependent isolated word recognition in a noisy environment indicate that $d_{RPS}\;and\;d_{WCEP}$ which weigh higher order cepstral coefficients more heavily give considerable performance improvement over $d_{CEP}and\;d_{LLR}$. In addition, when no pre-emphasis is performed, the recognizer can maintain higher performance under high noise conditions.