No-reference stereoscopic image quality assessment using quaternion wavelet transform and heterogeneous ensemble learning

As the demand for high-quality stereo images has grown in recent years, stereoscopic image quality assessment (SIQA) has become an important research area in modern image processing technology.In this paper, we propose a no-reference stereoscopic image quality assessment (NR-SIQA) model using heterogeneous ensemble learning ‘quality-aware’ features from luminance image, chrominance image, disparity and cyclopean images via quaternion wavelet transform (QWT). Firstly, luminance image and chrominance image are generated by CIELAB color space as monocular perception, and the novel disparity and cyclopean images are utilized to complement with monocular information. Then, a number of ‘quality-aware’ features in the quaternion wavelet domain are discovered, including entropy, texture features, energy features, energy differences features and MSCN coefficients of high frequency sub-band. Finally, a heterogeneous ensemble model via support vector regression (SVR) & extreme learning machine (ELM) & random forest (RF) is proposed to predict quality score, and bootstrap sampling and rotated feature space are used to increase the diversity of data distribution. Comparing with the state-of-the-art NR-SIQA models, experimental results on four public databases prove the accuracy and robustness of the proposed model.     

Response correction techniques for surrogate‐based design optimization of microwave structures

Simulation‐based optimization has become an important design tool in microwave engineering. However, using electromagnetic (EM) solvers in the design process is a challenging task, primarily due to a high‐computational cost of an accurate EM simulation. In this article, we present a review of EM‐based design optimization techniques exploiting response‐corrected physically based low‐fidelity models. The surrogate models created through such a correction can be used to yield a reasonable approximation of the optimal design of the computationally expensive structure under consideration (high‐fidelity model). Several approaches using this idea are reviewed including output space mapping, manifold mapping, adaptive response correction, and shape‐preserving response prediction. A common feature of these methods is that they are easy to implement and computationally efficient. Application examples are provided. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.     

Efficient design of SIW filters with knowledge‐embedded space mapping technique

This article presents an optimization technique for the design of substrate‐integrated waveguide (SIW) filters using knowledge‐embedded space mapping. An effective coarse model is proposed to represent the SIW filter. The proposed coarse model can be analyzed in the available commercial software ADS. The embedded knowledge includes not only formulas but also extracted design curves, which help to build the mapping between the coarse and fine models. The effectiveness of the proposed method is demonstrated through a design example of a six‐pole SIW filter. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.     

Robust pose invariant face recognition using coupled latent space discriminant analysis

We propose a novel pose-invariant face recognition approach which we call Discriminant Multiple Coupled Latent Subspace framework. It finds the sets of projection directions for different poses such that the projected images of the same subject in different poses are maximally correlated in the latent space. Discriminant analysis with artificially simulated pose errors in the latent space makes it robust to small pose errors caused due to a subject’s incorrect pose estimation. We do a comparative analysis of three popular latent space learning approaches: Partial Least Squares (PLSs), Bilinear Model (BLM) and Canonical Correlational Analysis (CCA) in the proposed coupled latent subspace framework. We experimentally demonstrate that using more than two poses simultaneously with CCA results in better performance. We report state-of-the-art results for pose-invariant face recognition on CMU PIE and FERET and comparable results on MultiPIE when using only four fiducial points for alignment and intensity features.     

机器人三维路径规划问题的一种改进蚁群算法

本文研究移动机器人三维空间路径规划问题,针对三维空间的复杂地形特点,提出了一种基于改进蚁群算法的路径规划算法。文中首先描述了一种简单有效的环境建模方法,然后给出了算法在信息素呈现、路径点选取、信息素更新以及启发式函数设计等方面的改进方法。仿真结果证明了算法的可行性和可靠性。     

高空作业平台臂架伸缩运动的横向振动特性

为了探究高空作业平台做伸缩运动时变幅平面内的横向振动动力学特性,针对臂架的实际搭接和支承情况,将臂架等效为根部铰接、中间弹性支承且带有集中参数的变截面变长度梁. 基于牛顿第二定律建立各臂段的运动微分方程,采用模态叠加法、结合边界条件求解臂架一系列时刻的瞬态振型函数,曲线拟合时变参数以近似表示梁的振型,并依据伽辽金截断方法,得到广义坐标下的状态空间方程. 在Matlab/Simulink环境下进行动态仿真,得到伸缩过程中臂架头部的变幅平面横向振动动态响应. 结果表明,就横向振动振幅而言,搭接简化会带来15.63%计算结果误差;支承简化会加大臂架整体刚度、减小臂架振动响应,不可取。     

高温混合障碍空间中的移动机器人路径规划

为了解决高温场景中移动机器人全局路径规划所面临的安全与效率问题,提出高温热源虚拟障碍的定义,建立混合障碍空间模型,将高温场景中的路径规划问题转化为高温混合障碍空间中考虑路径温度代价和长度代价的多目标优化问题. 改进NSGA-Ⅱ算法,通过选取优秀非可行解扩展种群,提高了种群多样性和进化效率,提出新的交叉和变异概率计算方法. 根据种群进化进程和个体代价函数值调整概率,实现了种群前期搜索能力和后期收敛性的平衡. 仿真所得的最优路径结果表明,该改进算法的路径长度代价虽然比原算法和其他改进算法略有增加,但温度代价大幅降低,更有效地避免了陷入局部最优.     

弹性半无限空间中矩形孔收缩的复变函数解答

随着城市建设的发展,矩形隧道的应用越来越多,但针对矩形隧道的理论研究却鲜有见闻。针对矩形隧道,建立了半无限空间矩形隧道的弹性理论计算模型,采用最小二乘迭代方法确定共形映射函数的各项系数,并将计算区域映射为复平面上的一个同心圆环;运用Muskhelishvili复变函数方法,将计算区域内的应力函数展开成为Laurant级数的形式,给定了地表零应力边界和矩形孔口径向位移边界,求得了半无限空间矩形隧道在给定位移条件下的应力场和位移场。分析了不同高宽比、不同泊松比、不同埋深对位移场和应力场的影响,总结了矩形隧道位移场和应力场的一般规律。结果表明：高宽比偏小、泊松比偏大、埋深偏小都会使得沉降槽不再是类高斯曲线的形状,这些参数的变化也会在不同程度上影响应力场和位移场的大小和分布。     

抗菌灭病毒涂料的研制及表征

在评价多种杀菌剂的抗病毒性能的基础上,筛选出杀菌和抗病毒性能均优异的功能助剂三氯苯基马来酰亚胺,用以研制成一种杀菌灭病毒功能内墙涂料。