• Structural Engineering and Mechanics
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• v.64 no.6
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• pp.683-693
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• 2017

According to a generalized nonlocal strain gradient theory (NSGT), dynamic modeling and free vibrational analysis of nanoporous inhomogeneous nanoplates is presented. The present model incorporates two scale coefficients to examine vibration behavior of nanoplates much accurately. Porosity-dependent material properties of the nanoplate are defined via a modified power-law function. The nanoplate is resting on a viscoelastic substrate and is subjected to hygro-thermal environment and in-plane linearly varying mechanical loads. The governing equations and related classical and non-classical boundary conditions are derived based on Hamilton's principle. These equations are solved for hinged nanoplates via Galerkin's method. Obtained results show the importance of hygro-thermal loading, viscoelastic medium, in-plane bending load, gradient index, nonlocal parameter, strain gradient parameter and porosities on vibrational characteristics of size-dependent FG nanoplates.

• Steel and Composite Structures
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• v.47 no.6
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• pp.795-811
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• 2023

When studying the resonance problem of nanoplates, the existing papers do not consider the influences of geometric nonlinearity and initial geometric imperfection, so this paper is to fill this gap. In this paper, based on the nonlocal strain gradient theory (NSGT), the nonlinear resonances of functionally graded (FG) nanoplates with initial geometric imperfection under different boundary conditions are established. In order to consider the small size effect of plates, nonlocal parameters and strain gradient parameters are introduced to expand the assumptions of the first-order shear deformation theory. Subsequently, the equations of motion are derived using the Euler-Lagrange principle and solved with the help of perturbation method. In addition, the effects of initial geometrical imperfection, functionally graded index, strain gradient parameter, nonlocal parameter and porosity on the nonlinear forced vibration behavior of nanoplates under different boundary conditions are discussed.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.49-55
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• 2009

In this paper, we investigate an optimal allocation of constant service resources in stochastic system to optimize the expected performance of interest. For this purpose, we use the control variates to estimate the gradients of expected performance with respect to given resource parameters, and apply these estimated gradients in stochastic optimization algorithm to find the optimal allocation of resources. The proposed gradient estimation method is advantageous in that it uses simulation results of a single design point without increasing the number of design points in simulation experiments and does not need to describe the logical relationship among realized performance of interest and perturbations in input parameters. We consider the applications of this research to various models and extension of input parameter space as the future research.

• Smart Structures and Systems
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• v.20 no.6
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• pp.709-728
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• 2017

This disquisition proposes a nonlocal strain gradient beam theory for thermo-mechanical dynamic characteristics of embedded smart shear deformable curved piezoelectric nanobeams made of porous electro-elastic functionally graded materials by using an analytical method. Electro-elastic properties of embedded curved porous FG nanobeam are assumed to be temperature-dependent and vary through the thickness direction of beam according to the power-law which is modified to approximate material properties for even distributions of porosities. It is perceived that during manufacturing of functionally graded materials (FGMs) porosities and micro-voids can be occurred inside the material. Since variation of pores along the thickness direction influences the mechanical and physical properties, so in this study thermo-mechanical vibration analysis of curve FG piezoelectric nanobeam by considering the effect of these imperfections is performed. Nonlocal strain gradient elasticity theory is utilized to consider the size effects in which the stress for not only the nonlocal stress field but also the strain gradients stress field. The governing equations and related boundary condition of embedded smart curved porous FG nanobeam subjected to thermal and electric field are derived via the energy method based on Timoshenko beam theory. An analytical Navier solution procedure is utilized to achieve the natural frequencies of porous FG curved piezoelectric nanobeam resting on Winkler and Pasternak foundation. The results for simpler states are confirmed with known data in the literature. The effects of various parameters such as nonlocality parameter, electric voltage, coefficient of porosity, elastic foundation parameters, thermal effect, gradient index, strain gradient, elastic opening angle and slenderness ratio on the natural frequency of embedded curved FG porous piezoelectric nanobeam are successfully discussed. It is concluded that these parameters play important roles on the dynamic behavior of porous FG curved nanobeam. Presented numerical results can serve as benchmarks for future analyses of curve FG nanobeam with porosity phases.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.8 no.2
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• pp.7-13
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• 2004

A Conjugate Gradient (CG) algorithm for unconstrained minimization is proposed which is invariant to a nonlinear scaling of a strictly convex quadratic function and which generates mutually conjugate directions for extended quadratic functions. It is derived for inexact line searches and is designed for the minimization of general nonlinear functions. It compares favorably in numerical tests with the original Dixon algorithm on which the new algorithm is based.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2393-2398
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• 2003

In this paper, we proposes a new fuzzy inference system for modeling nonlinear systems given input and output data. In the suggested fuzzy inference system, the number of fuzzy rules and parameter values of membership functions are automatically decided by using the kernel-based method. The kernel-based method individually performs linear transformation and kernel mapping. Linear transformation projects input space into linearly transformed input space. Kernel mapping projects linearly transformed input space into high dimensional feature space. The structure of the proposed fuzzy inference system is equal to a Takagi-Sugeno fuzzy model whose input variables are weighted linear combinations of input variables. In addition, the number of fuzzy rules can be reduced under the condition of optimizing a given criterion by adjusting linear transformation matrix and parameter values of kernel functions using the gradient descent method. Once a structure is selected, coefficients in consequent part are determined by the least square method. Simulated result illustrates the effectiveness of the proposed technique.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.41-46
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• 2005

Deinterlacing is the conversion from interlaced to progressive scan image that is considered to be 2 times image interpolation. In this paper, the simple and effective deinterlacing method is proposed based on the local gradient information of neighborhood pixels. In the proposed method, the weights for directions around the pixel to be interpolated are estimated, and the weighted sum for the neighborhood pixels is the final intensity value of the pixel to be interpolated. The proposed method has the structure suitable to practical implementation and can avoid the artifacts due to the wrong detection of edge direction. In the simulation, it showed improved subjective and objective performance than the ELA method and comparable performance compared with the variation of ELA method which has more complex structure and requires a couple of parameters that is determined by experience.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.517-523
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• 2012

Biometrics is a study of identifying individual by using the features of human body. It has been studied for an alternative or complementary method for the classical method based on password, ID card, etc. In comparison with the fingerprint, iris, ear, palmprint, finger-knuckle print has been recently studied. This paper proposes an effective method for recognizing finger-knuckle print based on the feature of Gradient orientation. The main features of finger-knuckle print are the size and direction of winkles. In order to extract these features stably, we make a feature vector consisted of Gradient orientations after the preprocessing of enhancing non-uniform brightness and low contrast. Total 790 images acquired from 158 persons have been used at the experiment for evaluating the performance of the proposed method. The experimental results show the recognition rate of 99.69% and the relatively high decidability index of 1.882. These results demonstrate that the proposed method is effective in recognizing finger-knuckle print.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.87-92
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• 2021

Bias, variance, error and learning are important factors for performance in modeling a big data based recommendation system. The recommendation model in this system must reduce complexity while maintaining the explanatory diagram. In addition, the sparsity of the dataset and the prediction of the system are more likely to be inversely proportional to each other. Therefore, a product recommendation model has been proposed through learning the similarity between products by using a factorization method of the sparsity of the dataset. In this paper, the generalization ability of the model is improved by applying the max-norm regularization as an optimization method for the loss function of this model. The solution is to apply a stochastic projection gradient descent method that projects a gradient. The sparser data became, it was confirmed that the propsed regularization method was relatively effective compared to the existing method through lots of experiment.

• Steel and Composite Structures
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• v.31 no.5
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• pp.469-488
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• 2019

We in this paper study nonlinear bending of a functionally graded porous nanobeam subjected to multiple physical load based on the nonlocal strain gradient theory. For more reasonable analysis of nanobeams made of porous functionally graded magneto-thermo-electro-elastic materials (PFGMTEEMs), both constituent materials and the porosity appear gradient distribution in the present expression of effective material properties, which is much more suitable to the actual compared with the conventional expression of effective material properties. Besides the displacement function regarding physical neutral surface is introduced to analyze mechanical behaviors of beams made of FGMs. Then we derive nonlinear governing equations of PFGMTEEMs beams using the principle of Hamilton. To obtain analytical solutions, a two-step perturbation method is developed in nonuniform electric field and magnetic field, and then we use it to solve nonlinear equations. Finally, the analytical solutions are utilized to perform a parametric analysis, where the effect of various physical parameters on static bending deformation of nanobeams are studied in detail, such as the nonlocal parameter, strain gradient parameter, the ratio of nonlocal parameter to strain gradient parameter, porosity volume fraction, material volume fraction index, temperature, initial magnetic potentials and external electric potentials.