• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.391-396
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• 2008

A level set based topological shape optimization using extended B-spline basis functions is developed for steady state heat conduction problems. The only inside of complicated domain is identified by the level set functions and taken into account in computation. The solution of Hamilton-Jacobi equation leads to an optimal shape according to the normal velocity field determined from the sensitivity analysis, minimizing a thermal compliance while satisfying a volume constraint. To obtain exact shape sensitivity, the precise normal and curvature of geometry need to be determined using the level set and B-spline basis functions. The nucleation of holes is possible whenever and wherever necessary during the optimization using a topological derivative concept.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.721-733
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• 2022

In this paper we compare parameter estimation by Grassmann manifold optimization and sequential candidate set algorithm in a structured principal fitted component (PFC) model. The structured PFC model extends the form of the covariance matrix of a random error to relieve the limits that occur due to too simple form of the matrix. However, unlike other PFC models, structured PFC model does not have a closed form for parameter estimation in dimension reduction which signals the need of numerical computation. The numerical computation can be done through Grassmann manifold optimization and sequential candidate set algorithm. We conducted numerical studies to compare the two methods by computing the results of sequential dimension testing and trace correlation values where we can compare the performance in determining dimension and estimating the basis. We could conclude that Grassmann manifold optimization outperforms sequential candidate set algorithm in dimension determination, while sequential candidate set algorithm is better in basis estimation when conducting dimension reduction. We also applied the methods in real data which derived the same result.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.391-398
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• 2023

In this paper, a penalized maximum likelihood estimation (PMLE) method that applies a penalty to increase the accuracy of a basis-screening-based Kriging model (BSKM) is introduced. The maximum order and set of basis functions used in the BSKM are determined according to their importance. In this regard, the cross-validation error (CVE) for the basis functions is employed as an indicator of importance. When constructing the Kriging model (KM), the maximum order of basis functions is determined, the importance of each basis function is evaluated according to the corresponding maximum order, and finally the optimal set of basis functions is determined. This optimal set is created by adding basis functions one by one in order of importance until the CVE of the KM is minimized. In this process, the KM must be generated repeatedly. Simultaneously, hyper-parameters representing correlations between datasets must be calculated through the maximum likelihood evaluation method. Given that the optimal set of basis functions depends on such hyper-parameters, it has a significant impact on the accuracy of the KM. The PMLE method is applied to accurately calculate hyper-parameters. It was confirmed that the accuracy of a BSKM can be improved by applying it to Branin-Hoo problem.

• Steel and Composite Structures
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• v.47 no.5
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• pp.569-585
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• 2023

This paper proposes an efficient approach for the structural topology optimization of bi-directional functionally graded structures by incorporating popular radial basis functions (RBFs) into an implicit level set (ILS) method. Compared to traditional element density-based methods, a level set (LS) description of material boundaries produces a smoother boundary description of the design. The paper develops RBF implicit modeling with multiquadric (MQ) splines, thin-plate spline (TPS), exponential spline (ES), and Gaussians (GS) to define the ILS function with high accuracy and smoothness. The optimization problem is formulated by considering RBF-based nodal densities as design variables and minimizing the compliance objective function. A LS-RBF optimization method is proposed to transform a Hamilton-Jacobi partial differential equation (PDE) into a system of coupled non-linear ordinary differential equations (ODEs) over the entire design domain using a collocation formulation of the method of lines design variables. The paper presents detailed mathematical expressions for BiDFG beams topology optimization with two different material models: continuum functionally graded (CFG) and mechanical functionally graded (MFG). Several numerical examples are presented to verify the method's efficiency, reliability, and success in accuracy, convergence speed, and insensitivity to initial designs in the topology optimization of two-dimensional (2D) structures. Overall, the paper presents a novel and efficient approach to topology optimization that can handle bi-directional functionally graded structures with complex geometries.

• Coupled systems mechanics
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• v.6 no.3
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• pp.369-376
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• 2017

Intermolecular interaction energies and conformer geometries of the hydrogen bonded acrylamide dimers have been studied by using the second-order Møller-Plesset (MP2) perturbation theory and the density functional theory (DFT) with 17 density functionals. Dunning's correlation consistent basis sets (up to aug-cc-pVTZ) have been used to study the basis set effects. The DFT calculated interaction energies are compared to the reference energy data calculated by the MP2 method and the coupled cluster method at the complete basis set (CCSD(T)/CBS) limit in order to determine the relative performance of the studied density functionals. Overall, dispersion-energy-corrected density functionals outperform uncorrected ones. The ${\omega}B97XD$ density functional is particularly effective in terms of both accuracy and computational cost in estimating the reference energy values using small basis sets and is highly recommended for similar calculations for larger systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.19-22
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• 2006

Type-2 fuzzy 이론은 기존의 퍼지 이론보다 패턴의 불확실성에 대한 제어를 더 향상시킬 수 있다. 반면에 계산 량이 커지는 문제점 때문에 본 논문에서는 type-2 fuzzy set 대신에 secondary membership이 interval의 형태를 갖는 interval type-2 fuzzy set을 기존의 radial basis function(RBF) neural network에 적용시킨 interval type-2 fuzzy RBF neural network를 제안한다. 제안한 알고리즘은 interval type-2 fuzzy membership function에 의하여 패턴들의 불확실성을 좀 더 잘 제어하여 기존의 RBF neural network의 성능을 향상시킬 수 있다. 본 논문에서는 제안한 알고리즘의 타당성을 보이기 위하여 여러 데이터 집합에 대한 분류 결과를 보인다.

• Journal of the Korean Home Economics Association
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• v.33 no.2
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• pp.159-166
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• 1995

The purpose of the present study is to investigate how closely care labels comply with the 1984 version of the Care Labeling Rule, as well as the change in degree of compliance prior to and after the 1988 IFI care label campaign. Label information was analyzed on the basis of country of origin. The information was also divided into two sets. The basis for dividing the data into two sets was the beginning of the IFI care label campaign in 1988 The data were obtained from 1147 checklists. The information for 1147 samples in six clothing categories were collected from department, specialty, and discount stores. Chi-square analyses were conducted to test hypotheses. While there was no significant difference in the number of incorrect labels on domestically produced garments compared to imported garments in set 1, there was a significant difference in set 2. Also, there was a significnat differnece in the number of incorrect labels between in set 1 and in set 2.

• Journal of the Chungcheong Mathematical Society
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• v.6 no.1
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• pp.25-43
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• 1993

This paper introduces a numerical method approximating the minimum norm solution to the first kind integral equation Kf = g with its kernel satisfying a certain property, where g belongs to the range space of K. Most of the existing expansion methods suffer from choosing a set of basis functions, whereas this method automatically provides an optimal set of basis functions approximating the minimum norm solution of Kf = g. Perturbation results and numerical experiments are also provided to analyze this method.

• Bulletin of the Korean Chemical Society
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• v.12 no.1
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• pp.67-70
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• 1991

A hexagonal hexamer of water cluster is optimized by ab initio method using the 4-31G basis set. At this geometry the nonadditive many-body interactions are calculated. The ab initio calculation with large basis set [T. H. Dunning, J. Chem. Phys., 53, 2823 (1970); 54, 3958 (1971)] shows that a pentagonal unit is rather stable among several kinds of clustering units of water molecules.

• Bulletin of the Korean Chemical Society
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• v.12 no.2
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• pp.211-213
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• 1991

The ground state of the oxygen molecule is calculated by various methods of coupled cluster approaches and many body perturbation theory using a double zeta plus polarization basis set and the UHF reference state. All the methods employed are capable of describing the oxygen molecule near the equilibrium bond length and the separated atom, but do not correctly depict the breaking of the multiple bond. For this basis set, including more correlations does not necessarily improve the agreement with experiment for molecular properties such as bond lengths and dissociation energies.