3D MHD cross flow over an exponential stretching porous surface

The present study aims to investigate the effects of thermal‐diffusion and diffusion‐thermo onan magnetohydrodynamic convective flow of viscous fluids over an exponentially stretching sheet. Thermal radiation effects are also considered in the study. This analysis is carried out in three dimensions and a similarity transformation is adopted to get a set of ordinary differential equations from a set of partial differential equations. And the Fourth‐order Runge‐Kutta method and shooting technique along with the secant method are employed to find out an iterative solution. We also analyze here the influence of the variable magnetic field, nonuniform permeability and variable chemical reaction on the fluid flow. The impact of various pertinent parameters of interest has extensively been explored through graphs and tables. The major findings of the present study are that resistive Lorentz force diminishes the fluid velocity and uplifts the thermal as well as concentration fields. Inclusion of porous matrix improves the viscous drag force which in turn augments wall shear stresses and peters out the heat and mass transfer rates from the sheet. In addition, the thermal expansion coefficient has an inverse relation with temperature.     

基于多尺度的贝叶斯模型显著性检测

针对传统基于贝叶斯模型的显著性检测算法存在准确率不理想的问题,提出了一种基于多尺度的贝叶斯模型显著性检测算法。通过超像素分割算法(SLIC)将原图分割成不同尺度的超像素,根据超像素边界信息得到背景种子,进而通过距离计算和多尺度融合得到背景先验;对原图进行颜色增强,采用Harris算子对增强图进行检测角点求得凸包,融合不同尺度下的超像素得到凸包先验;融合背景先验和凸包先验得到最终先验;利用颜色直方图和凸包计算似然概率;将最终先验和似然概率通过贝叶斯模型计算显著图。在公开数据集MSRA1000、ECSSD上与多种传统算法进行准确率和召回率对比,该算法有更好的表现。     

基于自适应阈值活动语音检测和最小均方误差对数谱幅度估计的低信噪比降噪算法

针对低信噪比(SNR)环境下传统方法对声信号降噪的局限性，提出了一种联合自适应阈值活动语音检测（VAD）算法和最小均方误差对数谱幅度估计（MMSE-LSA）的实时降噪算法。首先，在VAD算法中通过基于能量概率最大值的概率统计来对背景噪声进行估计，对得到的背景噪声进行实时更新并保存；然后，将实时更新的背景噪声作为MMSE-LSA的参考噪声，并对噪声幅度谱进行自适应更新，最后进行降噪处理。通过在真实场景中对四类声信号进行实验，结果表明，该算法在保证对低SNR声信号的实时处理的情况下，相较于传统MMSE-LSA算法，降噪信号的SNR能够提高10~15 dB，且不存在信号过减的情况，可应用于实际工程。     

Heat transfer in dusty fluid with suspended hybrid nanoparticles over a melting surface

The melting effect with the magnetic field performs a significant role in various manufacturing and industrial applications, such as welding, casting, magma-solidification, nuclear engineering, and so forth. The present study focuses on the impact of the melting effect and magnetic field with inhomogeneous heat origination and sink. The formulation of the mathematical model is done by considering fluid with hybrid nanoparticles and dust particles in two different phases. We have considered Fe₂SO₄ and Cu as nanoparticles dispersed in the base fluid water along with suspended dust particles. The set of partial differential equations is reduced by using apt similarity variables and boundary conditions to obtain ordinary differential equations. The numerical solution is approximated using MATLAB-bvp4c adopting the shooting technique. The impact of numerous pertinent physical parameters on the velocity and thermal profiles is plotted and deliberated. Furthermore, the rate of heat flow and friction factor is also tabulated and visualized through the graphs. Streamlines are also drawn to know the behavior of the fluid flow. The rise in values of M_E quickly increases the velocity of the fluid motion but declines the thermal gradient and thickness of its related boundary layer. Also, inclining values of Pr enhance the thermal profile due to the impact of melting.     

Gradient-based recursive parameter estimation for a periodically nonuniformly sampled-data Hammerstein–Wiener system based on the key-term separation

The identification of the Hammerstein–Wiener (H-W) systems based on the nonuniform input–output dataset remains a challenging problem. This article studies the identification problem of a periodically nonuniformly sampled-data H-W system. In addition, the product terms of the parameters in the H-W system are inevitable. In order to solve the problem, the key-term separation is applied and two algorithms are proposed. One is the key-term-based forgetting factor stochastic gradient (KT-FFSG) algorithm based on the gradient search. The other is the key-term-based hierarchical forgetting factor stochastic gradient (KT-HFFSG) algorithm. Compared with the KT-FFSG algorithm, the KT-HFFSG algorithm gives more accurate estimates. The simulation results indicate that the proposed algorithms are effective.     

Second order velocity slip and thermal jump of Cu–water nanofluid over a cone in the presence of nonlinear radiation and nonuniform heat source/sink using homotopy analysis method

The purpose of the present paper is to explore the second order slip effects on nanofluid flow over a vertical cone. The effects of nonlinear thermal radiation and nonuniform heat source/sink are also taken into account. Water with copper nanoparticles is used as nanofluid in this investigation. The governing partial differential equations for the flow are converted into ordinary differential equations by using transformations and then are solved using homotopy analysis method. The influence of various important parameters on velocity, temperature, skin‐friction, and Nusselt number are presented through graphs. Results indicate that the velocity and magnitude of skin friction decrease with a rise in first and second order velocity slips. A raise in either first or second order temperature jump causes a fall in temperature. Nonlinear radiation increases the more rapidly when compared to the linear radiation case.     

Fault estimation and accommodation for networked control systems with nonuniform sampling periods

This paper deals with the problem of fault estimation and accommodation for a class of networked control systems with nonuniform uncertain sampling periods. Firstly, the reason why the adaptive fault diagnosis observer cannot be applied to networked control systems is analyzed. Based on this analysis, a novel robust fault estimation observer is constructed to estimate both continuous‐time fault and system states by using nonuniformly discrete‐time sampled outputs. Furthermore, using the obtained states and fault information, a nonuniformly sampled‐data fault tolerant control law is designed to preserve the stability of the closed‐loop system. The proposed scheme can not only guarantee the impact of continuous‐time uncertainties and discrete‐time sampled estimation errors on the faulty system to satisfy a H _∞ performance index but also repress the negative effect of the unknown intersample behavior of continuous‐time fault by use of an inequality technique. Finally, simulation results are included to demonstrate the feasibility of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.     

改善某机涡轮叶片荧光渗透检测背景过度的试验

荧光渗透检测某机高压涡轮叶片时,批量性出现荧光背景过度导致无法检测叶片的问题。采用理论和工艺试验相结合的方法,分析了荧光背景过度产生的原因,制定了有效的解决方法,较好地改善了该高压涡轮叶片的荧光背景。     

筛分法和激光粒度法联合测定陆源碎屑岩粒度

用筛分法和激光粒度法联合测定陆源碎屑岩粒度,对激光粒度法的分析数据进行了校正,以保证两种方法的分析数据配套衔接。通过对比不同地质年代沉积岩的岩心校正前后概率累积频率曲线,校正后的曲线能更好地表征碎屑岩粒度的分布。对影响马尔文Mastersizer 2000激光粒度仪背景测量的进样器搅拌转速A、泵速B、超声强度C三个因子进行L9(34)正交优化设计,筛选出最优的测量条件是A取600r/min,B取2000r/min,可使背景测量稳定,并得出它们对背景测量影响程度可用B>A>误差>C表示。用仪器自带的9个标准物质校正了粒度标准曲线,粒度标准曲线与仪器标准曲线的加权残差小,在0.795%～2.934%之间。该方法相对标准偏差在0.24%～0.33%之间,适用于各种地质年代陆源碎屑岩的粒度分析。     

空间曲线的特征识别与高质量非均匀采样

为避免传统均匀采样方法因忽视曲线重要特征而生成不理想的采样结果,获得给定数量且由特征点和辅助点组成的采样点序列,提出基于特征识别的高质量空间曲线非均匀采样方法.首先使用抛物线插值法得到曲线上所有曲率极大值点和挠率极大值点的近似位置,经筛选后产生特征点,以更好地抓住空间曲线的轮廓特征.然后定义基于弧长、曲率和挠率加权组合的特征函数,并以此自适应地选取曲线上的辅助点.与3种主流采样方法比较的实验结果表明,该方法能够获得更高质量的采样结果且具有更好的实用性,从而进一步改善空间曲线的B样条拟合效果.