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.     

On optical flow techniques applied to breaking surges

Surface wave breaking is a challenging two-phase flow process which plays an important role in numerous physical processes. A highly-turbulent unsteady breaking surge was investigated experimentally in a large facility, and substantial aeration occurred in the roller. The application of three optical flow techniques (Lucas-Kanade, Horn-Schunck and Farnback) to the air-water region was tested. The results indicated that the Farnback technique provided most accurate results, although some misleading results could be obtained near the air-water boundaries of the roller. The bore generation by a rapid gate closure showed a highly-unsteady complicated velocity field, with substantial free-surface deformations, wave breaking and formation of large coherent structures before the surge detached from the gate. Further upstream, the surge propagated as a hydraulic jump in translation and the data showed a marked shear region with a recirculation zone above, showing air-water flow features comparable to stationary hydraulic jumps. The upper and lower bounds of air-water flow region yielded data implying an air-to-water velocity ratio about 4–5 for a Froude number Fr₁ = 2.1.     

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。     

Evolution of linear edge dislocation in atmospheric turbulence and free space

In accordance with the extended Huygens–Fresnel principle, the evolution of linear edge dislocation propagating through atmospheric turbulence is studied, and the effects of waist width and the slope of linear edge dislocation are investigated. It is shown that when linear edge dislocation beams propagate through atmospheric turbulence, if the waist width is not equal and the slope is not zero, then the linear edge dislocation vanishes and transforms into an optical vortex with a topological charge of ?1 or +1. The optical vortex and an optical vortex that is created annihilate when the transmission distance is far enough. The linear edge dislocation vanishes when the slope is zero. If the waist width is equal, then the linear edge dislocation will vanish regardless of the slope value. For linear edge dislocation beams in free space, when selecting specific parameters, linear edge dislocation always exists.     

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。     

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.     

On the bright side: The influence of brightness on overall taste intensity perception

Ambient light luminance (i.e., brightness or dimness) is a frequently used tool by managers to enhance the overall ambience in their restaurants. The current research explores how a change in a restaurant’s ambient brightness influences the overall taste intensity perception of the food that is being served there. We conducted a between-group experiment in a field setting (i.e., a fine-dining restaurant), where we manipulated the illuminance level of the ambient light (dim vs. bright). Guests were served a dish—tailored to our research question—and asked to evaluate its overall taste intensity. The results demonstrate that guests exposed to the bright ambient light perceived the overall taste of the dish as more intense as opposed to guests exposed to the dim ambient light. The results thus show that modifying the ambient illuminance level in a restaurant does not only affect the overall ambience but also changes the overall taste experience of the food being served. This finding is not only theoretically relevant for research on multisensory integration, but it also provides tools for taste modulation, and—as such—for strategies to decrease salt and sugar consumption among diners.