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.     

Electrolytic cell engineering and device optimization for electrosynthesis of e-biofuels via co-valorisation of bio-feedstocks and captured CO2

Utilizing CO₂ in an electro-chemical process and synthesizing value-added chemicals are amongst the few viable and scalable pathways in carbon capture and utilization technologies.CO₂ electro-reduction is also counted as one of the main options entailing less fossil fuel consumption and as a future electrical energy storage strategy.The current study aims at developing a new electrochemical platform to produce low-carbon e-biofuel through multifunctional electrosynthesis and integrated co-valorisation of biomass feedstocks with captured CO₂.In this approach,CO₂ is reduced at the cathode to produce drop-in fuels(e.g.,methanol)while value-added chemicals(e.g.,selective oxidation of alcohols,aldehydes,carboxylic acids and amines/amides)are produced at the anode.In this work,a numerical model of a continuous-flow design considering various anodic and cathodic reactions was built to determine the most techno-economically feasible configurations from the aspects of energy efficiency,environment impact and economical values.The reactor design was then optimized via parametric analysis.     

含钼废渣冶炼钼铁的优化试验

利用含钼废料钼酸钙为原料,采用碳还原法冶炼钼铁,通过单因素分析试验及正交试验优化得出最佳的试验条件,钼酸钙加入量应低于10%,熔炼温度为1 525 ℃,保温时间为25 min,碱度为1.3。通过XRD、SEM、EDS分析得出用此方法生产得到的钼铁合金中,钼以Mo₂C、Fe₃Mo以及Fe₃Mo₃C的形式存在,渣系为二元玻璃渣系,具有与普通玻璃相似的成分系统。经测定合金中钼的回收率大于99%,钼资源回收效益可观。