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。     

广东早期砖薄壳结构的建构技术研究——1957-1958年新会的"逼拱"实验

揭示1957-1958年华南工学院土木系薄壳结构研究小组在新会的砖薄壳结构实验图景.以田野调查、文献分析、三维图示、超声波检测等方法发现、确认此研究小组在新会的6处薄壳建筑及其遗存情况.它们是广东地区推广砖薄壳建筑的起点,其中的回旋砖薄壳实验是从结构角度探索中国建筑民族形式的重要案例,弥补国内结构工程史学研究的薄弱点,也是共和国早期节约"三材"约束下的薄壳建造技术自主创新设计的重要内容.     

Human responses to high levels of carbon dioxide and air temperature

In this study, 30 subjects were exposed to different combinations of air temperature (T_a: 24, 27, and 30°C) and CO₂ level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T_a = 24°C, exposure to 30°C at all CO₂ levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T_a on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO₂ from 8000 to 12 000 ppm at all T_a caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T_a and CO₂ concentration on human responses was identified.     

基于SCAE⁃ACGAN的直升机行星齿轮裂纹故障诊断

直升机行星传动轮系结构复杂、工况多变,其振动信号受工况影响大,在故障样本较少的情况下导致行星齿轮箱故障诊断准确率不高,早期故障诊断困难。针对上述问题,提出将堆栈收缩自动编码网络(stacked contractive autoencoder,简称SCAE)与辅助分类生成式对抗网络(auxiliary classifier generative adversarial networks,简称ACGAN)相结合的SCAE-ACGAN故障诊断方法。ACGAN的生成器产生与真实样本具有类似分布的生成样本,扩展训练样本集,并与真实样本一起输入至判别器进行训练。ACGAN采用SCAE作为判别器,利用SCAE良好的抗数据波动能力,从扩展样本集中挖掘出有效的深度特征,并实现样本的真伪与类别的判定。ACGAN的判别器和生成器在对抗学习训练机制下交替优化,提高方法的样本生成质量与故障判定能力。将SCAE-ACGAN应用于直升机行星轮裂纹故障诊断,结果表明,SCAE-ACGAN的故障诊断性能好,在样本数量少与工况变化情况下具有较好的健壮性和适应性。     

用于疏浚工程泥浆密度测量的电阻层析成像技术

江河湖海疏浚工程对于拓展和保障航运安全、促进生态恢复、维护/改善远海岛礁环境具有不可或缺的作用.目前,在绞吸和耙吸疏浚船上,多采用射线密度计及电磁流量计对输泥密度、产量等进行在线计量,并作为实现疏浚系统自动控制的重要参量.由于射线密度计潜在的人员健康、公共安全和环保风险,在一些国家和地区已建立了放射源的有序退出机制.电阻层析成像使用安装于管壁的电极阵列获得管道内流体的电导率分布,进而推导出管道内的泥浆密度,具有无辐射、全场测量及实时可视化的优点.电阻层析成像测量系统经过特殊设计,可适应从内陆淡水到海水的巨大电导率变化.初步测试表明,电阻层析成像测量数据与射线密度计具有良好一致性,具备了作为在线泥浆密度测量的可行性.此外,ERT可提供实时的流动成像,对于提高对疏浚管道监测能力和降低堵管概率具有重要意义.     

Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.     

回字形环山地建筑结构设计

中央美院青岛创业中心项目为角部重叠的回字形山地建筑,采用了框架-剪力墙结构体系.主体建筑结构总高度为54m,坐落在三个台地上,每两个相邻台地高差10m左右.掉层处采用"掉层脱开式且有拉梁"的方式进行结构布置.结合山地建筑结构的基本概念和受力特点,介绍了本项目的结构处理方式和设计难点,采用PKPM,MIDAS Building,SAUSAGE软件对结构进行了弹性反应谱法分析、弹性时程分析、动力弹塑性时程分析和抗震性能设计,同时针对各种不利因素采取了相应的加强措施,确保了结构安全.     

除尘器新型褶式滤筒的结构优化及系列化设计

以新型褶式滤筒为研究对象,选取滤筒褶数N_2、褶夹角θ、褶高h、过滤风速v为影响因子,除尘器压力损失为响应值,基于响应曲面法分析影响因子对压力损失的影响,建立滤筒除尘器压力损失的预测模型并得到滤筒褶皱结构最优参数。以滤筒内径D、筒体高度D_1为标准尺寸,依据相关国家标准设计滤筒筒体部分;以锥体高度D_2、锥体上圆直径D_3为系列尺寸,利用尺寸变化法设计锥体部分;通过Access软件建立滤筒产品数据库。结果表明:当θ=5.2°,N_2=50,v=0.01 m/s,h=0.035 m时,除尘器压力损失最低;当D_1=1 000 mm,D=320 mm时,D_2和D_3最佳值分别为600,130 mm,故采用D_2/D_1=0.6,D_3/D=0.4的比值设计相应滤筒锥体系列。