• Interdisciplinary Bio Central
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• v.3 no.4
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• pp.15.1-15.11
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• 2011

Background: Histone deacetylase (HDAC) 8 is one of its family members catalyzes the removal of acetyl groups from N-terminal lysine residues of histone proteins thereby restricts transcription factors from being expressed. Inhibition of HDAC8 has become an emerging and effective anti-cancer therapy for various cancers. Application computational methodologies may result in identifying the key components that can be used in developing future potent HDAC8 inhibitors. Results: Facilitating the discovery of novel and potential chemical scaffolds as starting points in the future HDAC8 inhibitor design, quantitative structure-activity relationship models were generated with 30 training set compounds using genetic function approximation (GFA) and Bayesian algorithms. Six GFA models were selected based on the significant statistical parameters calculated during model development. A Bayesian model using fingerprints was developed with a receiver operating characteristic curve cross-validation value of 0.902. An external test set of 54 diverse compounds was used in validating the models. Conclusions: Finally two out of six models based on their predictive ability over the test set compounds were selected as final GFA models. The Bayesian model has displayed a high classifying ability with the same test set compounds and the positively and negatively contributing molecular fingerprints were also unveiled by the model. The effectively contributing physicochemical properties and molecular fingerprints from a set of known HDAC8 inhibitors were identified and can be used in designing future HDAC8 inhibitors.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.333-333
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• 2000

When the generalized singular perturbation method is used for model reduction, the state variables of the original system is reconstructed from the reduced order model. The state reduction error is defined, which shows how well the reconstructed state variables approximate the state variables of the original system equation.

• Korean Journal of Mathematics
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• v.22 no.4
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• pp.599-609
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• 2014

We refer to the saturation assumptions on the finite element approximation for a one dimensional convection-diffusion model. By examining piecewise linear finite elements with refined mesh by half and hierarchical bases, we verify the saturation results, respectively.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.419-437
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• 1995

Given the specific mean shift outlier model, several standard approaches to obtaining test statistic for outliers are discussed. Each of these is developed in detail for the nonlinear regression model, and each leads to an equivalent distribution. The geometric interpretations of the statistics and accuracy of linear approximation are also presented.

• Geophysics and Geophysical Exploration
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• v.2 no.2
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• pp.86-95
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• 1999

This paper presents an efficient three-dimensional (3-D) modeling algorithm using the extended approximation to an electric field integral equation. Numerical evaluations of Green's tensor integral are performed in the spatial wavenumber domain. This approach makes it possible to reduce computing time, to handle smoothly varying conductivity model and to remove singularity problems encountered in the integration of Green's tensor at a source point. The responses obtained by 3-D modeling algorithm developed in this study are compared with those by the full integral equation for a thin-sheet EM scattering. The extensive analyses on the performance of modeling algorithm are made with the conductivity contrasts and source frequencies. These results show that the modeling algorithm are accurate up to the conductivity contrast of 1:16 and the frequency range of 100 Hz-100 kHz. The extended Born approximation, however, may produce inaccurate results for some source and model configurations in which the electric field is discontinuous across the conductivity boundary. We performed the modeling of a composite model of which conductivity varies continuously and this shows the modeling algorithm developed in this study is efficient for 3-D EM modeling. For a cross-hole source-receiver configuration a composite model of which conductivity varies continuously can be successfully simulated using this algorithm.

• The Korean Journal of Rheology
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• v.11 no.1
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• pp.18-27
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• 1999

Predicting the deformation behaviors of sheets in thermoforming processes has been a daunting challenge due to the strong nonlinearities arising from very large deformations, mold-polymer contact condition and hyperelasticity constitutive equations. Nonlinear numerical analysis is always required to face this challenge especially for realistic processing conditions. In this study a 3-D algorithm and the membrane approximation are developed for thermoforming processes. The constitutive equation is expressed in terms of the 2nd Piola-Kirchhoff stress tensor and the Cauchy-Green deformation tensor. The 2-term Mooney-Rivlin model is used for the material model equation. The algorithm is established by the finite element formulation employing the total Lagrangian coordinate. The deformation behavior and the stress distribution results of 3-D algorithm with various point boundary conditions are compared to those of the membrane approximation algorithm. Also, the slip boundary condition and the no-slip boundary condition are applied for the systems that have molds. Finally, the effect of sheet temperatures on the final thickness distribution is investigated for the ABS material.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.1
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• pp.68-74
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• 2000

The STL file format is an approximation of 3-D model with triangular facets. STL is a standard input file format of Rapid Prototyping(RP) equipment In computer graphics a circle has been approximated with an inscribed polygon which causes an error between the real and approximated circles. In this study an intersecting polygon has been used to approximate the circle and applied to produce more accurate RP part. The newly proposed method shows it's excellence in part accuracy.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.131-136
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• 2011

The original Bates-Watts framework applies only to the complete parameter vector. Thus, guidelines developed in that framework can be misleading when the adequacy of the linear approximation is very different for different subsets. The subset curvature measures appear to be reliable indicators of the adequacy of linear approximation for an arbitrary subset of parameters in nonlinear models. Given the specific mean shift outlier model, the standard approaches to obtaining test statistics for outliers are discussed. The accuracy of outlier tests is investigated using subset curvatures.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.2
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• pp.102-109
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• 2000

This paper describes two different theories used to model the scattering of ultrasound by a volumetric flaw and a crack-like flaw. The elastodynamic Kirchhoff approximation (EKA) and the geometrical theory of diffraction (GTD) are applied respectively to a cylindrical cavity and a semi-infinite crack. These methods are known as high frequency approximations. The 2-D elastodynamic scattering problems of a plane wave incident on these model defects are considered and the scattered fields are expressed in terms of the reflection and diffraction coefficients. The ratio of the scattered far field amplitude to the incident wave amplitude is computed as a function of the angular location and compared with the boundary element solutions.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.952-957
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• 2006

The present study applied wavelet transform and artificial neural networks (ANNs) for the prediction of daily TOC data. TOC data were transformed into denoised data by the wavelet transform and the noise-reduced data were used for the prediction model by artificial neural networks. For the application of wavelet transform, Daubechies wavelet of order 10 ('db10') was used as a basis function and decomposed the TOC data up to fifth level with five detail components and one approximation component. ANNs were calibrated with the input data of the segregated TOC data corresponding to the details from second to fifth level and the approximation. Consequently, the ANNs model for the prediction of daily TOC data showed the best result when it had seventeen hidden nodes in its layer.