• Structural Engineering and Mechanics
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• 제44권2호
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• pp.219-238
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• 2012

Objective of this paper is to compare linear buckling analysis formulations, available in commercial finite element programs. Modern steel design codes, including Eurocode 3, make abundant use of linear buckling loads for calculation of slenderness, and of linear buckling modes, used as shapes of imperfections for nonlinear analyses. Experience has shown that the buckling mode shapes and the magnitude of buckling loads may differ, sometimes significantly, from one algorithm to another. Thus, three characteristic examples have been used in order to assess the linear buckling formulations available in the finite element programs ADINA and ABAQUS. Useful conclusions are drawn for selecting the appropriate algorithm and the proper reference load in order to obtain either the classical linear buckling load or a good approximation of the actual geometrically nonlinear buckling load.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.719-729
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• 2001

Overlap Maximization is a sampling technique to reduce survey costs and costs associated with the survey. It was first studied by Keyfitz(1951). Ernst(1998) presented a remarkable procedure for maximizing the overlap when the sampling units can be selected for two identical stratified designs simultaneously, But the approach involves mimicking the behaviour of nonlinear function by linear function and so it is less direct, even though the stratification problem for the overlap corresponds directly to the linear programming problem. furthermore, it uses the controlled selection algorithm that repeatedly needs zero-restricted controlled roundings, which are solutions of capacitated transportation problems. In this paper we suggest a comparatively simple procedure to use linear programming in order to maximize the overlap. We show how this procedure can be implemented practically.

• 대한수학회보
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• 제53권6호
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• pp.1831-1844
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• 2016

In this paper, we improve the full-Newton step infeasible interior-point algorithm proposed by Mansouri et al. [6]. The algorithm takes only one full-Newton step in a major iteration. To perform this step, the algorithm adopts the largest logical value for the barrier update parameter ${\theta}$. This value is adapted with the value of proximity function ${\delta}$ related to (x, y, s) in current iteration of the algorithm. We derive a suitable interval to change the parameter ${\theta}$ from iteration to iteration. This leads to more flexibilities in the algorithm, compared to the situation that ${\theta}$ takes a default fixed value.

• Journal of Power Electronics
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• 제15권6호
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• pp.1619-1627
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• 2015

This paper presents a power system harmonic elimination using the mixed adaptive linear neural network and variable step-size leaky least mean square (ADALINE-VSSLLMS) control algorithm based active power filter (APF). The weight vector of ADALINE along with the variable step-size parameter and leakage coefficient of the VSSLLMS algorithm are automatically adjusted to eliminate harmonics from the distorted load current. For all iteration, the VSSLLMS algorithm selects a new rate of convergence for searching and runs the computations. The adopted shunt-hybrid APF (SHAPF) consists of an APF and a series of 7^th tuned passive filter connected to each phase. The performance of the proposed ADALINE-VSSLLMS control algorithm employed for SHAPF is analyzed through a simulation in a MATLAB/Simulink environment. Experimental results of a real-time prototype validate the efficacy of the proposed control algorithm.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2005년도 추계학술발표대회 논문집
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• pp.268-271
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• 2005

Researches based on genetic algorithms have been performed in composite laminated structures optimization since 1990. However, conventional genetic algorithms have a disadvantage that its augmentation of calculation costs. A lot of variations have been proposed to improve the performance and efficiency, and micro genetic algorithm is one of them. In this paper, micro Genetic Algorithm was employed in the optimization of laminated stiffened composite structures to maximize the linear critical buckling load and the results from both conventional genetic algorithm and micro genetic algorithm were compared.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.425-428
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• 1997

Effectiveness of corrective machining algorithm is verified experimentally in this paper by performing corrective lapping work to single side and double sides hydrostatic tables. Lapping is applied as machining method. Machining information is calculated from measured motion errors by applying the algorithm, without information on rail profile. It is possible to acquire 0.13pm of linear motion error, 1.40arcsec of angular motion error in the case of single side table, and 0.07pm of linear motion error, 1.42arcsec of angular motion error in the case of double sides table. The experiment is performed by the unskilled person after he experienced a little of preliminary machining. Experimental results show that corrective machining algorithm is very effective, and anyone can improve the accuracy of hydrostatic table by using the algorithm.

• Communications for Statistical Applications and Methods
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• 제9권1호
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• pp.291-304
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• 2002

This article is concerned with an effective algorithm for the identification of multiple outliers in linear regression. It proposes a hybrid algorithm which employs the least median of squares estimator, instead of the least squares estimator, to construct an Initial clean subset in the stepwise forward search scheme. The performance of the proposed algorithm is evaluated and compared with the existing competitor via an extensive Monte Carlo simulation. The algorithm appears to be superior to the competitor for the most of scenarios explored in the simulation study. Particularly it copes with the masking problem quite well. In addition, the orthogonal decomposition and Its updating techniques are considered to improve the computational efficiency and numerical stability of the algorithm.

• 한국가시화정보학회지
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• 제8권4호
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• pp.26-30
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• 2010

A PTV algorithm was constructed using a linear transformation, in which the merits of the conventional PIV and PTV were adopted. In PIV calculations, the obtained velocity vectors are affected by the filtering effects by its calculation principle. PTV techniques are widely used for their excellences of measuring small scaled flows, such as nano and bio flows. However, PTVs produce vector errors due to interpolation process. To overcome these problems, a hybrid PTV algorithm was constructed by combining PTVs' and PIVs' benefits using a linear transformation. The Taylor-Green vortex flows were generated for the tests of vorticity calculations. The conventional gray-level cross-correlation PIV technique and 2-Frame PTV technique were tested for the same flows for comparisons with those obtained by the constructed hybrid algorithm. The excellence of the constructed hybrid algorithm was validated through an actual experiment on the cylinder wake.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 춘계학술대회
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• pp.697-702
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• 2009

Filtered-x LMS algorithm maybe the most popular control algorithm used in DSP implementations of active noise and vibration control system. The algorithm converges on a timescale comparable to the response time of the system to be controlled, and is found to be very robust. If the pure tone reference signal is synchronously sampled, it is found that the behavior of the adaptive system can be completely described by a matrix of linear, time invariant, transfer functions. This is used to explain the behavior observed in simulations of a simplified single input, single output adaptive system, which retains many of the properties of the multichannel algorithm.

• Journal of information and communication convergence engineering
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• 제20권2호
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• pp.73-78
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• 2022

Based on experimental measurements conducted on many different practical wireless communication systems, ambient noise has been shown to be decidedly non-Gaussian owing to impulsive phenomena. However, most multiuser detection techniques proposed thus far have considered Gaussian noise only. They may therefore suffer from a considerable performance loss in the presence of impulsive ambient noise. In this paper, we consider a large-scale multiuser multiple-input multiple-output system in the presence of non-Gaussian noise and propose a genetic algorithm (GA) based detector for large-dimensional multiuser signal detection. The proposed algorithm is more robust than linear multi-user detectors for non-Gaussian noise because it uses a multi-directional search to manipulate and maintain a population of potential solutions. Meanwhile, the proposed GA-based algorithm has a comparable complexity because it does not require any complicated computations (e.g., a matrix inverse or derivation). The simulation results show that the GA offers a performance gain over the linear minimum mean square error algorithm for both non-Gaussian and Gaussian noise.