基于卷积神经网络的5G蜂窝网络无线定位方法

5G蜂窝网络发展迅猛，其覆盖面积将逐渐增大，因此使用5G蜂窝网络进行定位是有研究潜力的研究方向。本文提出一种新的深度学习技术来实现高效、高精度和低占用的定位，以代替传统指纹定位过程中繁重的指纹库生成以及距离计算。该方法建立了一个特殊的卷积神经网络，并根据5G天线信号的接收信号强度指示、相位和到达角等特征量，选择合适的输入数据格式构造样本组建训练集，对该卷积神经网络进行训练。训练得到的卷积神经网络可以替代指纹定位中的庞大指纹库，非常有利于直接在5G移动设备端实现定位。虽然卷积神经网络在训练过程中需要大量时间，但在训练完毕后直接进行分类定位的速度非常快，可以保障定位实现的实时性。本文所实现的卷积神经网络权重与偏置所占内存不到0.5 MB，且能够在实际应用环境中以95%的定位准确率以及0.1 m的平均定位精度实现高精度定位。     

Plasma-assisted CO2 reforming of methane over Ni-based catalysts: Promoting role of Ag and Sn secondary metals

Carbon dioxide (CO₂) and methane (CH₄) are the primary greenhouse gases (GHGs) that drive global climate change. CO₂ reforming of CH₄ or dry reforming of CH₄ (DRM) is used for the simultaneous conversion of CO₂ and CH₄ into syngas and higher hydrocarbons. In this study, DRM was investigated using Ag–Ni/Al₂O₃ packing and Sn–Ni/Al₂O₃ packing in a parallel plate dielectric barrier discharge (DBD) reactor. The performance of the DBD reactor was significantly enhanced when applying Ag–Ni/Al₂O₃ and Sn–Ni/Al₂O₃ due to the relatively high electrical conductivity of Ag and Sn as well as their anti-coke performances. Using Ag–Ni/Al₂O₃ consisting of 1.5 wt% Ag and 5 wt% Ni/Al₂O₃ as the catalyst in the DBD reactor, 19% CH₄ conversion, 21% CO₂ conversion, 60% H₂ selectivity, 81% CO selectivity, energy efficiency of 7.9% and 0.74% (by mole) coke formation were achieved. In addition, using Sn–Ni/Al₂O₃, consisting of 0.5 wt% Sn and 5 wt% Ni/Al₂O₃, 15% CH₄ conversion, 19% CO₂ conversion, 64% H₂ selectivity, 70% CO selectivity, energy efficiency of 6.0%, and 2.1% (by mole) coke formation were achieved. Sn enhanced the reactant conversions and energy efficiency, and resulted in a reduction in coke formation; these results are comparable to that achieved when using the noble metal Ag. The decrease in the formation of coke could be correlated to the increase in the CO selectivity of the catalyst. Good dispersion of the secondary metals on Ni was found to be an important factor for the observed increases in the catalyst surface area and catalytic activities. Furthermore, the stability of the catalytic reactions was investigated for 1800 min over the 0.5 wt% Ag-5 wt% Ni/Al₂O₃ and 0.5 wt% Sn-5 wt% Ni/Al₂O₃ catalysts. The results showed an increase in the reactant conversions with an increase in the reaction time.     

Surface treatment of titanium dioxide nanopowder using rotary electrode dielectric barrier discharge reactor

Titanium dioxide (TiO2) nanopowder (P-25;Degussa AG) was treated using dielectric barrier discharge (DBD) in a rotary electrode DBD (RE-DBD) reactor.Its electrical and optical characteristics were investigated during RE-DBD generation.The treated TiO2 nanopowder properties and structures were analyzed using x-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR).After RE-DBD treatment,XRD measurements indicated that the anatase peak theta positions shifted from 25.3° to 25.1°,which can be attributed to the substitution of new functional groups in the TiO2 lattice.The FTIR results show that hydroxyl groups (OH) at 3400 cm-1 increased considerably.The mechanism used to modify the TiO2 nanopowder surface by air DBD treatment was confirmed from optical emission spectrum measurements.Reactive species,such as OH radical,ozone and atomic oxygen can play key roles in hydroxyl formation on the TiO2 nanopowder surface.     

Electrochemical Quantification of Neurotransmitters in Single Live Cell Vesicles Shows Exocytosis is Predominantly Partial

Exocytosis plays an essential role in the communication between cells in the nervous system. Understanding the regulation of neurotransmitter release during exocytosis and the amount of neurotransmitter content that is stored in vesicles is of importance, as it provides fundamental insights to understand how the brain works and how neurons elicit a certain behavior. In this minireview, we summarize recent progress in amperometric measurements for monitoring exocytosis in single cells and electrochemical cytometry measurements of vesicular neurotransmitter content in individual vesicles. Important steps have increased our understanding of the different mechanisms of exocytosis. Increasing evidence is firmly establishing that partial release is the primary mechanism of release in multiple cell types.     

Effect of Reynolds number and boundary layer thickness on the performance of V-cone flowmeter using CFD

The effect of Reynolds number and boundary layer thickness on the performance of V-cone flowmeter has been evaluated using computational fluid dynamics (CFD). The shear stress transport k-ω (SST k-ω) turbulence model has been adopted for closure. The performance of two V-cone flowmeters with different beta ratios (β) viz., 0.6 and 0.7 for a fixed vertex angle (ϕ) of 60° has been analysed as a function of Reynolds number (Re). The results show that the coefficient of discharge (C_d) increases with Reynolds number in the laminar and transition flow regimes whereas it is nearly constant in turbulent flow regime. From the results, it can be concluded that C_d is independent of Re for values equal to 4000 and beyond. Further, it is also seen that the performance of the V-cone flowmeter is not affected by the upstream boundary layer thickness if the velocity profiles having different boundary layer thickness are extracted from an axial distance of 10D and more are fed at 5D upstream of the meter. However, the meter is sensitive to the extracted velocity profile from an axial distance of 5D and uniform velocity profile being fed at 5D upstream. The value of C_d may be sensitive as a result of the pressure variation due to the obstruction.     

干扰条件下的“北斗”信号解扩重构DOA估计

在干扰条件下，卫星导航抗干扰波束形成算法往往需要卫星信号波达方向（Direction-of-Arrival，DOA）的先验信息。但当存在低信噪比信号或主动干扰源时，常规的DOA估计算法性能急剧下降甚至失效。针对此问题，提出了一种被干扰信号压制的低信噪比“北斗”信号的DOA估计算法。该算法首先通过对接收信号进行子空间投影抑制干扰信号，然后对抑制干扰后的信号进行解扩重构处理，最后通过多重信号分类算法完成对“北斗”信号的DOA估计。仿真结果表明，在干扰信号干信比80 dB条件下，“北斗”信号DOA估计误差在5°以内，为下一步进行波束形成计算提供了高精度的入射角信息。     

Multi-discharge EDM coring of single crystal SiC ingot by electrostatic induction feeding method

A new technique of EDM coring of single crystal silicon carbide (SiC) ingot was proposed in this paper. Currently single crystal SiC devices are still of high cost due to the high cost of bulk crystal SiC material and the difficulty in the fabrication process of SiC. In the manufacturing process of SiC ingot/wafer, localized cracks or defects occasionally occur due to thermal or mechanical causes resulted from fabrication processes which may waste the whole piece of material. To save the part of ingot without defects and maximize the material utilization, the authors proposed EDM coring method to cut out a no defect ingot from a larger diameter ingot which has localized defects. A special experimental setup was developed for EDM coring of SiC ingot in this study and its feasibility and machining performance were investigated. Meanwhile, in order to improve the machining rate, a novel multi-discharge EDM coring method by electrostatic induction feeding was established, which can realize multiple discharges in single pulse duration. Experimental results make it clear that EDM coring of SiC ingot can be carried out stably using the developed experimental setup. Taking advantage of the newly developed multi-discharge EDM method, both the machining speed and surface integrity can be improved.     

基于信号增强的缓慢泄漏检测方法

目前管道泄漏检测方法可有效检测突发泄漏，对于缓慢泄漏则存在检测灵敏度低、定位不准确等问题。基于此，提出了一种基于信号增强的缓慢泄漏检测方法。通过信号压缩（抽取及移位）克服缓慢泄漏压力信号下降平缓的缺点；根据声波信号具有波形尖锐突出、对突发泄漏敏感的优点，通过建立以压力为输入、虚拟声波为输出的声波信号变送器模型，将压力信号转换为声波信号，克服了泄漏压力信号容易被淹没在管道压力波动及背景噪声中的缺点，实现了缓慢泄漏信号的增强；利用临近插值方法重构虚拟声波信号，基于延时互相关分析实现了缓慢泄漏的准确定位。实验结果表明，该方法具有显著的信号增强效果和定位精度，实现了缓慢泄漏的准确检测。     

水下图像处理技术研究综述

随着自主式水下机器人的发展，水下探测技术成为新的研究热点。然而，吸收效应和散射效应导致水下获取的图像存在雾化和色彩偏差等缺陷。降质的水下图像在一定程度上降低了水下目标识别的准确性。为了改善水下图像质量，国内外学者对水下图像处理方法进行了深入研究。因水下图像处理方法对提升水下目标识别准确性具有良好的促进作用，故其具有重要的研究与分析价值。介绍了水下成像模型，分析了水下图像视觉质量下降的原理；根据水下物理成像模型将水下图像处理方法分为水下图像增强与水下图像复原，并分别对两类方法的研究现状进行分析与归纳；最后，总结与讨论了各类方法的优缺点，并展望了未来的发展方向。