基于多尺度双线性卷积神经网络的多角度下车型精细识别

针对多角度下车辆出现一定的尺度变化和形变导致很难被准确识别的问题，提出基于多尺度双线性卷积神经网络（MS-B-CNN）的车型精细识别模型。首先，对双线性卷积神经网络（B-CNN）算法进行改进，提出MS-B-CNN算法对不同卷积层的特征进行了多尺度融合，以提高特征表达能力；此外，还采用基于中心损失函数与Softmax损失函数联合学习的策略，在Softmax损失函数基础上分别对训练集每个类别在特征空间维护一个类中心，在训练过程中新增加样本时，网络会约束样本的分类中心距离，以提高多角度情况下的车型识别的能力。实验结果显示，该车型识别模型在CompCars数据集上的正确率达到了93.63%，验证了模型在多角度情况下的准确性和鲁棒性。     

Optimal filtering and control for wireless networked closed-loop control systems

This article studies the optimal filtering and control for wireless networked control systems (WNCSs). In WNCSs, packets may be lost in both control and feedback channels and user datagram protocol is usually used to improve the performance of the real-time control. Relevant literature indicates that the conventional optimal filtering for such a system cannot be applied in practice due to the complex calculation with Gaussian mixtures. This paper proposes a novel scheme to realize the optimal filtering and the linear quadratic Gaussian control for WNCSs, in which the controlled node performs a local estimation and the remote-control node performs the final estimation and control, and a synchronization of two estimators is guaranteed by a communication mechanism. An optimal filtering algorithm is developed, the stability condition of the filtering error covariance is obtained, optimal finite-horizon and infinite-horizon control are derived, and the stability of the closed-loop control system is proved. Numerical simulations show the validity and feasibility of the theoretical results.     

Methodology for optimization of pouring variables using bottom pour for low masses of SS304 (<300 kg) in investment casting process (case study)

Bottom pour ladles with stopper rod systems are commonly used in the metal casting industry. However, stopper rod bottom-pouring systems have not yet been developed for the lower thermal masses of alloys typically used in the investment casting industry. Large thermal masses used with bottom pour systems are typically limited for ladles larger than 700 kg and to certain alloys with higher fluidity and longer solidification time like cast iron, aluminum alloys etc. In this study, bottom pour ladle designs and low thermal mass refractory systems have been developed and evaluated in production investment foundry trials with 300 kg pouring ladle. The ladles system and pouring practices used will be described along with the results from the pouring trials for SS304 that represents typical alloys used in Investment casting industries. Optimization of the variables used in an experimentation using Genetic algorithm is also explained.     

Effects of structural characteristics on microwave dielectric properties of low-loss (Zn1-xNix)ZrNbTaO8 ceramics

Low-loss (Zn_1-xNi_x)ZrNbTaO₈ (0.02?≤?x?≤?0.10) ceramics possessing single wolframite structure are initiatively synthesized by solid-state route. Based on the results of Rietveld refinement, complex chemical bond theory is used to establish the correlation between structural characteristics and microwave performance in this ceramic system. A small amount of Ni²⁺ (x?=?0.06) in A-site with the fixed substitution of Ta⁵⁺ in B-site can effectually raise the Q?×?f value of ZnZrNb₂O₈ ceramic, embodying a dense microstructure and high lattice energy. The dielectric constant and τ_f are mainly affected by bond ionicity and the average octahedral distortion. The (Zn_0.94Ni_0.06)ZrNbTaO₈ ceramic sample sintered at 1150?°C for 3?h exhibits an outstanding combination of microwave dielectric properties: ε_r =?27.88, Q?×?f?=?128,951?GHz, τ_f =?–39.9?ppm/°C. Thus, it is considered to be a candidate material for the communication device applications at high frequency.     

基于密集神经网络的灰度图像着色算法

针对在灰度图像着色领域中，传统算法信息提取率不高、着色效果不理想的问题，提出了基于密集神经网络的灰度图像着色算法，以实现改善着色效果，让人眼更好地观察图片信息的目的。利用密集神经网络的信息提取高效性，构建并训练了一个端到端的深度学习模型，对图像中的各类信息及特征进行提取。训练网络时与原图像进行对比，以逐渐减小网络输出结果的信息、分类等各类型的损失。训练完成后，只需向网络输入一张灰度图片，即可生成一张颜色饱满、鲜明逼真的彩色图片。实验结果表明，引入密集网络后，可有效改善着色过程中的漏色、细节信息损失、对比度低等问题，所提算法着色效果较基于VGG网络及U-Net、双流网络结构、残差网络（ResNet）等性能优异的先进着色算法而言取得了显著的改进。     

低插损窄带型10.7MHz压电陶瓷滤波器的研制

介绍了低插损窄带型10.7 MHz压电陶瓷滤波器的一种设计制作方法。结合压电陶瓷能陷模理论,通过对滤波器分割电极设计和制造工艺控制技术的研究,强调了工艺控制的重要性。产品达到日本村田同类产品水平,对国产化窄带型10.7 MHz压电陶瓷滤波器的研发和生产具有十分重要的意义。认为选用高Qm值压电陶瓷材料、分割电极和耦合电容的设计、焊接和点蜡工艺的控制等是研制低插损窄带型10.7 MHz压电陶瓷滤波器的重点。     

辐射型漏泄同轴电缆的设计

总结了漏泄同轴电缆的理论研究现状。围绕使用频带和耦合损耗这两个重要电气参数，讨论辐射型漏泄同轴电缆的设计方法。基于周期性槽孔结构的空间谐波的分析，讨论了抑制高次谐波以拓展使用频带的方法。利用时域有限差分方法和Matlab软件计算耦合损耗。     

深水井控中节流管线摩阻分析及压井方法

在海洋深水钻井中，防喷器组一般安装在海底，当发生井涌进行压井作业时．由于节流管线较长、内径较小，钻井液在节流管线内存在高摩阻损失，作用在井底的压力往往大于地层的破裂压力．从而引起压井过程的复杂化，甚至造成压井作业的失败。介绍了一种新的压井方法附加流量法，在返出的节流管线流体中混入低密度流体，降低节流管线内流体的粘度和密度，从而实现安全压井；详细介绍了压井方法和步骤。数据分析表明，通过对压井参数进行优化选择能够降低节流管线中的压耗。     

连续波腔衰荡技术原理推导及实验研究

基于无源腔的Q值定义,根据能量守恒原理,对连续波腔衰荡技术测量原理进行了推导,并基于多光束干涉理论,就入射光关断时间对腔出射光强信号衰荡线形及测量结果的影响进行了数值模拟和分析,分析表明：入射光的关断时间很大程度上决定着腔出射光功率信号的衰减线形,如果要消除入射光关断时间对测量结果的影响,入射光关断必须小于腔衰荡时间的1%。根据理论分析要求建立了一套测量系统,并对腔损耗约为50ppm的低损无源腔进行了实际测量,实验结果的分析显示,该测量系统测量误差约为0．15ppm。