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。     

Improved photoluminescence and multi-mode optical thermometry of Er3+/Yb3+ co-doped (Ba,Sr)3Lu4O9 phosphors

Contactless optical thermometers have attracted extensive attentions for applications in scientific research and technological fields due to their apparent advantages. Herein, a novel sequence of Ba_3-xSr_xLu₄O₉ (B_3-xS_xLO):Er³⁺/Yb³⁺ phosphors were successfully prepared to investigate the temperature sensing property. By establishing energy transfer from Yb³⁺ to Er³⁺ and regulating the local lattice environment, up-conversion luminescence of Er³⁺ is dramatically improved when excited by 980 nm laser. This can effectively promote signal-noise ratio and reduce the errors in temperature detection. Furthermore, a multi-mode optical thermometry, which includes the fluorescence intensity ratio (FIR) from two thermally coupled levels of ²H_11/2/⁴S_3/2, FIR based on non-thermally coupled system of ²H_11/2/⁴F_9/2 and fluorescence lifetime of ⁴S_3/2 state of Er³⁺, was explored systematically. The fabricated samples exhibit the superior temperature measurement performances containing wide temperature-sensing range, superior signal discriminability, high sensitivity and favorable repeatability, indicative of the enormous utilization prospects of B_3-xS_xLO:Er³⁺/Yb³⁺ for thermometry.     

基于声源定位的高校在线巡课系统设计与研究

随着网络建设以及信息化教学方法在高校教学过程中的应用普及,越来越多的高校使用在线巡课系统对教师的教学过程进行跟踪和管理,以便发现课堂教学中的亮点、问题和不足。文章提出的在线巡课系统,基于声源定位的技术,对传统的在线巡课系统做出了改进,解决了已有巡课系统中“只闻其声,不见其人”的问题,能够更直观地跟踪到教师的教学过程,包括教学行为以及师生互动过程,有效提升教务人员巡课效果和体验感受。     

某贫磁赤铁矿石选矿工艺试验研究

为了使某矿山贫磁赤铁矿资源得到合理的开发利用，针对现开采部位矿石的性质和可选性问题，进行了工艺矿物学和可选性试验研究。试验结果表明：采用弱磁、强磁—阴离子反浮选工艺可得到精矿铁品位68.55%、精矿产率36.41%、金属回收率79.92%、尾矿品位9.86%的较好选别指标，说明矿石的可选性较好，为该矿石的合理开发利用提供了可靠的技术依据。     

一种波长调制干涉仪光强实时反馈控制系统

提出了一种实时反馈控制系统,保证波长调制干涉仪的激光光强在波长调谐过程中的稳定性,以减小波长调制干涉仪因激光光强的波动产生的相位误差。该控制系统由光电探测器、数据采集卡、光电调幅器和控制软件等组成。实验结果表明,该系统的响应速度超过了干涉仪获取干涉图的速度,不仅能够稳定输出理想的光强值,而且还提高了干涉仪的测量精度。     

钢铁生产的水能关系分析

从钢铁生产过程中水资源使用时的能耗角度研究了钢铁联合企业的水能关系，提出了水能强度的概念来评价企业生产过程中水资源利用的节能水平，建立了钢铁企业的水能关系模型。以中国某大型钢铁联合企业为例，计算并分析了该企业的水能关系。该企业总的水能量为55 709 kW·h/h，重复用水水能量占整个钢铁企业全部水能量的82%，补水水能量占16%，排水水能量占1%；各工序中热轧工序占比最大，其次是炼铁、炼钢工序，冷轧、烧结和炼焦工序较低。该企业的吨钢水能强度为0.208 kW·h/m3，炼铁工序的水能强度最高，热轧、炼钢工序次之，烧结、冷轧和炼焦工序较低。最后，从钢铁生产过程水资源利用的角度得到节能的方向及措施。     

一种人工情绪模型及其电商计算实验应用

针对电子商务顾客购物人工系统的计算实验研究，提出一种基于状态类比假说的人工情绪模型，给出了情绪的产生、增强、衰落和消失过程的描述方法，研究了外部刺激、情感强度和内部驱动力的计算方法，并进行了模拟分析。基于此人工情绪模型，构建了电商顾客购物的情绪-行为影响关系模型；将其应用于电商顾客购物的计算实验分析。结果表明，该人工情绪模型能较好地应用于电商复杂人工系统顾客购物的计算实验。     

基于GA-BP的汽车风振噪声声品质预测模型

目前对于汽车风振噪声的优化研究主要以声压级（Sound pressure level，SPL）作为单一评价指标，既不能全面反映噪声的物理属性，也无法考虑人耳对噪声的主观认知过程。为准确评价风振噪声，引入声品质，运用大涡模拟（Large eddy simulation，LES）对风振噪声进行数值仿真，根据实车道路试验判断仿真的准确性；对仿真结果进行声品质客观评价与主观评价，综合声品质客观评价参数与声品质主观评价试验结果建立BP神经网络预测模型；利用遗传算法（Genetic algorithm，GA），进一步对BP神经网络的结构参数进行优化，建立GA-BP声品质预测模型。研究结果表明，GA-BP声品质预测模型在训练速度和预测精度上都优于BP神经网络预测模型。预测模型基于声品质主客观评价结果，其预测值可以代替传统的声压级评价指标，为风振噪声提供更为准确合理的评价。     

Prediction of mode I fracture toughness of rock using linear multiple regression and gene expression programming

Prediction of mode I fracture toughness (K_IC) of rock is of significant importance in rock engineering analyses. In this study, linear multiple regression (LMR) and gene expression programming (GEP) methods were used to provide a reliable relationship to determine mode I fracture toughness of rock. The presented model was developed based on 60 datasets taken from the previous literature. To predict fracture parameters, three mechanical parameters of rock mass including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and elastic modulus (E) have been selected as the input parameters. A cluster of data was collected and divided into two random groups of training and testing datasets. Then, different statistical linear and artificial intelligence based nonlinear analyses were conducted on the training data to provide a reliable prediction model of K_IC. These two predictive methods were then evaluated based on the testing data. To evaluate the efficiency of the proposed models for predicting the mode I fracture toughness of rock, various statistical indices including coefficient of determination (R²), root mean square error (RMSE), and mean absolute error (MAE) were utilized herein. In the case of testing datasets, the values of R², RMSE, and MAE for the GEP model were 0.87, 0.188, and 0.156, respectively, while they were 0.74, 0.473, and 0.223, respectively, for the LMR model. The results indicated that the selected GEP model delivered superior performance with a higher R² value and lower errors.     

Measurement of vertical and horizontal vibrations of a probe for acoustic evaluation of food texture

Two‐dimensional (vertical and horizontal) vibrations of a wedge‐type probe upon food rupture were evaluated separately using two accelerometers placed perpendicular to a guide rod of a swing‐arm device for texture evaluation of the flesh of three varieties of apples and three types of potato chips. Voltage signals from the accelerometers were filtered using a half‐octave band‐pass filter. The energy texture index (ETI), based on kinetic energy of the vertical or horizontal probe vibrations, was calculated over low to high frequency bands (no. 1–21). The spectra for the flesh of the three varieties of apples included two common peaks for vertical ETI at band no. 11 (1,120–1,600 Hz) and 19 (17,920–25,600 Hz) and horizontal ETI at band no. 1 (0–10 Hz) and 15 (4,480–6,400 Hz). The spectra for the three types of potato chips had a common ETI peak at band no. 11 (1,120–1,600 Hz) for horizontal ETI and at no. 15 (4,480–6,400 Hz) for vertical ETI. The three apple varieties gave rise to different intensities of vertical and horizontal ETIs while the two peaks were maintained. The thick potato chip type had higher vertical and horizontal ETIs than the thin and soft varieties in most bands; however, the thin type had the highest vertical ETIs only in lower bands (0–200 Hz). The soft type had the lowest vertical and horizontal ETI. The above results suggest that different food textures can be distinguished by two‐dimensional vibration analyses of probe insertion into a food sample based on frequency bands.