• Current Optics and Photonics
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• v.7 no.6
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• pp.692-700
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• 2023

We present a method for improving the accuracy of the modal wavefront reconstruction in the radial shearing interferometers (RSIs). Our approach involves expanding the reduced radial terms of Zernike polynomials to high-order, which enables more precise reconstruction of the wavefront aberrations with high-spatial frequency. We expanded the reduced polynomials up to infinite order with symbolic variables of the radius, shearing amount, and transformation matrix elements. For the simulation of the modal wavefront reconstruction, we generated a target wavefront subsequently, magnified and measured wavefronts were generated. To validate the effectiveness of the high-order Zernike polynomials, we applied both low- and high-order polynomials to the wavefront reconstruction process. Consequently, the peak-to-valley (PV) and RMS errors notably decreased with values of 0.011λ and 0.001λ, respectively, as the order of the radial Zernike polynomial increased.

• Journal of applied mathematics & informatics
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• v.42 no.2
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• pp.457-469
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• 2024

In this paper, we construct higher-order (p, q)-poly-tangent numbers and polynomials and give several properties, including addition formula and multiplication formula. Finally, we explore the distribution of roots of higher-order (p, q)-poly-tangent polynomials.

• Kyungpook Mathematical Journal
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• v.55 no.3
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• pp.597-614
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• 2015

In this paper, we study some properties of the generalized Apostol type Hermite-based polynomials. which extend some known results. We also deduce some properties of the generalized Apostol-Bernoulli polynomials, the generalized Apostol-Euler polynomials and the generalized Apostol-Genocchi polynomials of high order. Numerous properties of these polynomials and some relationships between $F_n{^{({\alpha})}}(x;{\lambda};{\mu};{\nu};c)$ and $_HF_n{^{({\alpha})}}(x;{\lambda};{\mu};{\nu};c)$ are established. Some implicit summation formulae and general symmetry identities are derived by using different analytical means and applying generating functions.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.2
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• pp.67-75
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• 2004

This study aims to investigate the dynamic behaviour of a parabolic arch with initial deflection by using the elasto-plastic finite element model where the von-Mises yield criteria have been adopted. The initial deflection of arch was assumed by the high order polynomial of ${\omega}_i$ = ${\omega}_o$${(1-{(2x/L)}^m)}^n$) and the sinusoidal profile of ${\omega}_i$ = ${\omega}_o$$\sin$(n$\pi$x/L). Several numerical examples were tested considering symmetric initial deflection modes when the maximum initial deflection of an arch is fixed as L/500, L/1000, L/2000 or L/5000. The effects of polynomials order on the dynamic behavior of arch were not conspicuous. The most unfavorite dynamic response occurs when the maximum initial deflection varies from L/1000 to L/4000 if the initial deflection mode is represented by high order polynomials.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.15-15
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• 2000

In the past couple of years, there has been increasing interest in the fusion of neural networks and fuzzy logic. Most of the existing fused models have been proposed to implement different types of fuzzy reasoning mechanisms and inevitably they suffer from the dimensionality problem when dealing with complex real-world problem. To overcome the problem, we propose the self-organizing networks with activation nodes based on fuzzy inference and polynomial function. The proposed model consists of two parts, one is fuzzy nodes which each node is operated as a small fuzzy system with fuzzy implication rules, and its fuzzy system operates with Gaussian or triangular MF in Premise part and constant or regression polynomials in consequence part. the other is polynomial nodes which several types of high-order polynomials such as linear, quadratic, and cubic form are used and are connected as various kinds of multi-variable inputs. To demonstrate the effectiveness of the proposed method, time series data for gas furnace process has been applied.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.4
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• pp.245-251
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• 2018

In this paper, we address some issues in existing seismic hazard closed-form equations and present a novel seismic hazard equation form to overcome these issues. The presented equation form is based on higher-order polynomials, which can well describe the seismic hazard information with relatively high non-linearity. The accuracy of the proposed form is illustrated not only in the seismic hazard data itself but also in estimating the annual probability of failure (APF) of the structural systems. For this purpose, the information on seismic hazard is used in representative areas of the United States (West : Los Angeles, Central : Memphis and Kansas, East : Charleston). Examples regarding the APF estimation are the analyses of existing platform structure and nuclear power plant problems. As a result of the numerical example analyses, it is confirmed that the higher-order-polynomial-based hazard form presented in this paper could predict the APF values of the two example structure systems as well as the given seismic hazard data relatively accurately compared with the existing closed-form hazard equations. Therefore, in the future, it is expected that we can derive a new improved APF function by combining the proposed hazard formula with the existing fragility equation.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.54 no.7
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• pp.339-342
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• 2005

We present a new high-frequency equivalent circuit model for 52pin QFP used in typical IC's and extract R, L, and C values of this circuit model using a 3-D E & M field simulator. Futhermore, L and C value variations as a function of Pin number due to the shape differences of the leads have been fitted to 2nd order polynomials in order to extend the applicability of this model.

• Journal of computational fluids engineering
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• v.12 no.3
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• pp.29-40
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• 2007

An implicit discontinuous Galerkin method for the two-dimensional Euler equations was developed on unstructured triangular meshes. The method can achieve high-order spatial accuracy by using hierachical basis functions based on Legendre polynomials. Numerical tests were conducted to estimate the convergence order of numerical solutions to the Ringleb flow and the supersonic vortex flow for which analytic solutions are available. Also, the flows around a 2-D circular cylinder and an NACA0012 airfoil were numerically simulated. The numerical results showed that the implicit discontinuous Galerkin methods couples with a high-order representation of curved solid boundaries can be an efficient method to obtain very accurate numerical solutions on unstructured meshes.

• Computational Structural Engineering
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• v.10 no.1
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• pp.185-191
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• 1997

Beam - and arch-like structures are two-dimensional bodies characterized by the fact of small thickness compared to the length of structures. Owing to this geometric feature, linear displacement approximations through the thickness such as Kirchhoff and Reissner-Mindlin theories which are more accessible one dimensional problems have been used. However, for accurate analysis of the behavior in the regions where the state of stresses is complex, two-dimensional linear elasicity or relatively high order of thickness polynomials is required. This paper analyses accuracy according to the order of thickness polynomials and introduces a technique for model combination for which several different polynomial orders are mixed in a single structure.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.7
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• pp.424-433
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• 2003

Evolutionary design related to the optimal design of Polynomial Neural Networks (PNNs) structure for model identification of complex and nonlinear system is studied in this paper. The PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be changable according to the system environments. three types of polynomials such as linear, quadratic, and modified quadratic is used in each node that is connected with various kinds of multi-variable inputs. Inputs and order of polynomials in each node are very important element for the performance of model. In most cases these factors are decided by the background information and trial and error of designer. For the high reliability and good performance of the PNN, the factors must be decided according to a logical and systematic way. In the paper evolutionary algorithm is applied to choose the optimal input variables and order. Evolutionary (genetic) algorithm is a random search optimization technique. The evolved PNN with optimally chosen input variables and order is not fixed in advance but becomes fully optimized automatically during the identification process. Gas furnace and pH neutralization processes are used in conventional PNN version are modeled. It shows that the designed PNN architecture with evolutionary structure optimization can produce the model with higher accuracy than previous PNN and other works.