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。     

Microstructure,wear and corrosion characteristics of multiple-reinforced (SiC–B4C–Al2O3) Al matrix composites produced by liquid metal infiltration

In this study, AA7075 aluminum matrix composites reinforced with the combination of SiC, Al₂O₃, and B₄C particles were fabricated by the liquid metal infiltration method. The effects of the relative ratio of B₄C and Al₂O₃ particles on the microstructural, wear, and corrosion features of the composite samples were analyzed using XRD, light metal microscopy, SEM, EDS, Brinell hardness, ball-on-disc type tribometer, and potentiodynamic polarization devices. It was determined that infiltration occurred more successfully, and homogenously distributed particles with reduced porosity were obtained as the amount of Al₂O₃ increased. Worn surface studies revealed that the specimens were predominantly worn by abrasion and adhesion. The increase in B₄C/Al₂O₃ ratio caused a decrease in the hardness and wear strength, whereas it increased the corrosion resistance.     

Environmental effects on the strength and impact damage resistance of alumina based oxide/oxide ceramic matrix composites

In this study the effects of high temperature and moisture on the impact damage resistance and mechanical strength of Nextel 610/alumina silicate ceramic matrix composites were experimentally evaluated. Composite laminates were exposed to either a 1050°C isothermal furnace-based environment for 30 consecutive days at 6 h a day, or 95% relative humidity environment for 13 consecutive days at 67°C. Low velocity impact, tensile and short beam strength tests were performed on both ambient and environmentally conditioned laminates and damage was characterized using a combination of non-destructive and destructive techniques. High temperature and humidity environmental exposure adversely affected the impact resistance of the composite laminates. For all the environments, planar internal damage area was greater than the back side dent area, which in turn was greater than the impactor side dent area. Evidence of environmental embrittlement through a stiffer tensile response was noted for the high temperature exposed laminates while the short beam strength tests showed greater propensity for interlaminar shear failure in the moisture exposed laminates. Destructive evaluations exposed larger, more pronounced delaminations in the environmentally conditioned laminates in comparison to the ambient ones. External damage metrics of the impactor side dent depth and area directly influenced the post-impact tensile strength of the laminates while no such trend between internal damage area and residual strength could be ascertained.     

A microfluidic approach for development of hybrid collagen-chitosan extracellular matrix-like membranes for on-chip cell cultures

To advance organ-on-a-chip development and other areas befitting from physiologically-relevant biomembranes,a microfluidic platform is presented for synthesis of biomembranes during gelation and investigation into their role as extracellular matrix supports.In this work,high-throughput studies of collagen,chitosan,and collagen-chitosan hybrid biomembranes were carried out to characterize and compare key properties as a function of the applied hydrodynamic conditions during gelation.Specifically,depending on the biopolymer material used,varying flow conditions during biomembrane gelation caused width,uniformity,and swelling ratio to be differently affected and controllable.Finally,cell viability studies of seeded fibroblasts were conducted,thus showing the potential for biological applications.     

基于阶段注意力机制的电力线提取算法

电力系统维护是电力系统稳定运行的重要保障，应用智能算法的无人机电力巡检则为电力系统维护提供便捷。电力线提取是自主电力巡检以及保障飞行器低空飞行安全的关键技术，结合深度学习理论进行电力线提取是电力巡检的重要突破点。本文将深度学习方法用于电力线提取任务，结合电力线图像特点嵌入改进的图像输入策略和注意力模块，提出一种基于阶段注意力机制的电力线提取模型（SA-Unet）。本文提出的SA-Unet模型编码阶段采用阶段输入融合策略（Stage input fusion strategy， SIFS），充分利用图像的多尺度信息减少空间位置信息丢失。解码阶段通过嵌入阶段注意力模块（Stage attention module，SAM）聚焦电力线特征，从大量信息中快速筛选出高价值信息。实验结果表明，该方法在复杂背景的多场景中具有良好的性能。     

Topology optimization of flexure hinges with a prescribed compliance matrix based on the adaptive spring model and stress constraint

This paper focuses on the configuration design of flexure hinges with a prescribed compliance matrix and preset rotational center position. A new method for the topology optimization of flexure hinges is proposed based on the adaptive spring model and stress constraint. The hinge optimization model is formulated by maximizing the bending displacement with a spring while optimizing the compliance matrix to a prescribed value. To avoid numerical instability, an artificial spring is used as an auxiliary calculation, and a new strategy is developed for adaptively adjusting the spring stiffness according to the prescribed compliance matrix. The maximum stress of flexure hinge is limited by using a normalized P-norm of the effective von Mises stress, and a position constraint of rotational center is proposed to predetermine the position of the rotational center. In addition, to reduce the error of the stress measurement, a simple but effective filtering method is presented to obtain a complete black-and-white design. Numerical examples are used to verify the proposed method. Topology results show that the obtained flexure hinges have the prescribed compliance matrix and preset rotational center position while also meeting the stress requirements.     

基于蜻蜓翅脉结构的连续碳纤维增强树脂基复合材料仿生设计与增材制造

以具有轻质高强优异性能的蜻蜓翅脉结构为设计灵感，在分析翅脉网格结构抗冲击原理的基础上，设计了传统和仿生两类对比结构。采用熔融挤出3D打印机成功制备了具有不同结构的连续碳纤维增强聚乳酸复合材料试样，并对不同结构复合材料试样的拉伸性能和抗冲击性能进行了测试和对比分析。研究分析结果表明：由于拉伸力方向上的连续碳纤维含量相对较少，限制了仿生结构复合材料抗拉强度的提高，但仿生结构的平均抗拉强度为传统结构的1.18倍；当仿生结构复合材料试样受到冲击力时，其内部六边形结构的连接角度会发生变化，从而极大消耗冲击能量，同时具有六边形网格结构的连续碳纤维可以有效阻碍裂纹的扩展，因此仿生结构的平均冲击韧性可以达到传统结构的2.46倍；仿生蜻蜓翅脉结构可以显著提高增材制造复合材料的综合力学性能，且对于抗冲击性能的提高具体突出效果。连续碳纤维增强树脂基复合材料的有效可行的仿生蜻蜓翅脉结构设计和增材制造，可极大扩展其在高冲击载荷领域中的相应应用。     

胶带斜井在冶金矿山深井开拓中的应用探讨

针对某在建矿山深井开拓方案探索需求，通过对胶带运输系统发展应用情况介绍和胶带运输系统运输特性影响因素分析，并结合深井开拓胶带斜井方案与竖井加胶带斜井方案投资经济性比较，以及对胶带运输系统在运行过程中关键问题的分析和讨论，得出随着胶带运输技术的不断发展，在大规模深井开拓中，胶带斜井开拓将大有可为，为冶金矿山深井开拓方案选择提供决策支持。