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A Hybrid Approach for Fault Diagnosis of Railway Rolling Bearings Using STWD-EMD-GA-LSSVM

Vibration signals resulting from railway rolling bearings are nonstationary by nature; this paper proposes a hybrid approach for the fault diagnosis of railway rolling bearings using segment threshold wavelet denoising (STWD), empirical mode decomposition (EMD), genetic algorithm (GA), and least squares support vector machine (LSSVM). The original signal is first denoised using...

A Hybrid Approach for Fault Diagnosis of Railway Rolling Bearings Using STWD-EMD-GA-LSSVM

Vibration signals resulting from railway rolling bearings are nonstationary by nature; this paper proposes a hybrid approach for the fault diagnosis of railway rolling bearings using segment threshold wavelet denoising (STWD), empirical mode decomposition (EMD), genetic algorithm (GA), and least squares support vector machine (LSSVM). The original signal is first denoised using...

A New Synthetic Amphiploid (AADDAA) between Gossypium hirsutum and G. arboreum Lays the Foundation for Transferring Resistances to Verticillium and Drought

Gossypium arboreum, a cultivated cotton species (2n = 26, AA) native to Asia, possesses invaluable characteristics unavailable in the tetraploid cultivated cotton gene pool, such as resistance to pests and diseases and tolerance to abiotic stresses. However, it is quite difficult to transfer favorable traits into Upland cotton through conventional methods due to the cross...

A class of generalized pseudo-splines

In this paper, a class of refinable functions is given by smoothening pseudo-splines in order to get divergence free and curl free wavelets. The regularity and stability of them are discussed. Based on that, the corresponding Riesz wavelets are constructed.

Automated Flare Prediction Using Extreme Learning Machine

Extreme learning machine (ELM) is a fast learning algorithm of single-hidden layer feedforward neural networks (SLFNs). Compared with the traditional neural networks, the ELM algorithm has the advantages of fast learning speed and good generalization. At the same time, an ordinal logistic regression (LR) is a statistical method which is conceptually simple and algorithmically...

Automated Flare Prediction Using Extreme Learning Machine

Extreme learning machine (ELM) is a fast learning algorithm of single-hidden layer feedforward neural networks (SLFNs). Compared with the traditional neural networks, the ELM algorithm has the advantages of fast learning speed and good generalization. At the same time, an ordinal logistic regression (LR) is a statistical method which is conceptually simple and algorithmically...

Construction of Affine Invariant Functions in Spatial Domain

Editor: Bin Fang Copyright © 2012 Jianwei Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and

Convergence of a Singular Euler-Maxwell Approximation of the Incompressible Euler Equations

Water Resources and Electric Power, Zhengzhou 450011, China Received 15 June 2011; Accepted 27 October 2011 Academic Editor: Vu Phat Copyright © 2011 Jianwei Yang and Hongli Wang. This is an open

Cutting Affine Moment Invariants

The extraction of affine invariant features plays an important role in many fields of image processing. In this paper, the original image is transformed into new images to extract more affine invariant features. To construct new images, the original image is cut in two areas by a closed curve, which is called general contour (GC). GC is obtained by performing projections along...

Estimation of Large Scalings in Images Based on Multilayer Pseudopolar Fractional Fourier Transform

Accurate estimation of the Fourier transform in log-polar coordinates is a major challenge for phase-correlation based motion estimation. To acquire better image registration accuracy, a method is proposed to estimate the log-polar coordinates coefficients using multilayer pseudopolar fractional Fourier transform (MPFFT). The MPFFT approach encompasses pseudopolar and multilayer...

Estimation of Large Scalings in Images Based on Multilayer Pseudopolar Fractional Fourier Transform

Accurate estimation of the Fourier transform in log-polar coordinates is a major challenge for phase-correlation based motion estimation. To acquire better image registration accuracy, a method is proposed to estimate the log-polar coordinates coefficients using multilayer pseudopolar fractional Fourier transform (MPFFT). The MPFFT approach encompasses pseudopolar and multilayer...

Extraction of Affine Invariant Features Using Fractal

Editor: Chen Wensheng Copyright © 2013 Jianwei Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and

Genome-Wide Identification and Characterization of microRNAs in Developing Grains of Zea mays L.

The development and maturation of maize kernel involves meticulous and fine gene regulation at transcriptional and post-transcriptional levels, and miRNAs play important roles during this process. Although a number of miRNAs have been identified in maize seed, the ones involved in the early development of grains and in different lines of maize have not been well studied. Here, we...

Global Solutions to the Spherically Symmetric Compressible Navier-Stokes Equations with Density-Dependent Viscosity and Discontinuous Initial Data

We consider the initial boundary value problem for the spherically symmetric isentropic compressible Navier-Stokes equations with density-dependent viscosity coefficients and discontinuous initial data in this paper. For piecewise regular initial density with bounded jump discontinuity, we show that there exists a unique global piecewise regular solution. In particular, the jump...

Global Solutions to the Spherically Symmetric Compressible Navier-Stokes Equations with Density-Dependent Viscosity and Discontinuous Initial Data

We consider the initial boundary value problem for the spherically symmetric isentropic compressible Navier-Stokes equations with density-dependent viscosity coefficients and discontinuous initial data in this paper. For piecewise regular initial density with bounded jump discontinuity, we show that there exists a unique global piecewise regular solution. In particular, the jump...

Global solution to the exterior problem for spherically symmetric compressible Navier-Stokes equations with density-dependent viscosity and discontinuous initial data

Lian Jianwei Yang In this paper, we consider the exterior problem for spherically symmetric isentropic compressible Navier-Stokes equations with density-dependent viscosity coefficients and

Highly Conductive PEDOT:PSS Transparent Hole Transporting Layer with Solvent Treatment for High Performance Silicon/Organic Hybrid Solar Cells

Efficient Si/organic hybrid solar cells were fabricated with dimethyl sulfoxide (DMSO) and surfactant-doped poly(3,4-ethylenedioxythiophene): polystyrene (PEDOT:PSS). A post-treatment on PEDOT:PSS films with polar solvent was performed to increase the device performance. We found that the performance of hybrid solar cells increase with the polarity of solvent. A high conductivity...

Local Smooth Solution and Non-Relativistic Limit of Radiation Hydrodynamics Equations

We investigate a multidimensional nonisentropic radiation hydrodynamics model. We study the local existence and the convergence of the nonisentropic radiation hydrodynamics equations via the non-relativistic limit. The local existence of smooth solutions to both systems is obtained. For well-prepared initial data, the convergence of the limit is rigorously justified by an...

Modeling and Experimental Study of Soft Error Propagation Based on Cellular Automaton

Aiming to estimate SEE soft error performance of complex electronic systems, a soft error propagation model based on cellular automaton is proposed and an estimation methodology based on circuit partitioning and error propagation is presented. Simulations indicate that different fault grade jamming and different coupling factors between cells are the main parameters influencing...