Studies on the Oxidation of Weathered Coal with Nitric Acid

A raseach has been done on the possibility of producing nitriochumic acid fromweathered coal of Nantong,Sichuan,oxidised by nithic acid.The optimun reacting conditions,whichare found through the way of orthogonal experiment,are suggested as follows:concentration ofHON3 35%,rate of HON3 to coal 3.5,reacting take 15 min,and reaction temperature 369 K. Thecomposition of product is Wf 2. 91 %;Ag 14.06%;HAg 78.28%;Ng 1.62%.     

The Software Implementation of Neural Network Fuzzy Inference Cooperation System

This poper sets up a new Neural Network Fuzzy inference Cooperation system which is based on fuzzy inference principle in Expert Systems,take advantage of the powerful learning function, the little sensitivity to input layer's samples,and the fast convergence and so on in FCBP and take advantage of the good sort property and good suit property to fuzzy value in MFART Network.     

Practical Criterion for Voltage Stability of Substation

This paper presents a new practical criterion for voltage stability based on the real-time information at the substation and the quasi-time information from power system.By using the criterion,it is effective to predict the bus voltage stability margin.This is of great importance to raise the security operation level and prevent voltage collapse.The practical criterion for voltage stability is tested on the IEEE-14-bus test system.It needs less calculation time and is very suitable for real-time control of power systems.     

The Generalized Conjugate Direction Method for Constrained Optimization A Geometrical Approech

The conjugate direction method for solving the unconstrained optimization problem is extended to solving the constrained optimization problem by method of differential geomtry.By inducing a new class of affine connections on a constrained sub-manifold, the primary constrched optilnhation problem is converted to a unconstrained local quadratic programming problem.Based on the definition and construction of a new class of generalized conjugate directions, it isproved that optimum value of the primary constrained optimization problem must be located on thegeodesic line which is formed by the conjugate directions mentioned above and can be reached withinfinite searching step. Therefore a new curve search algorithm with generalized conjugate directions isput forward.     

The Method of Diagnosing Brain-dysfunction Based on Membership Function and BP Neural Network

Membership functions.formed with the characteristic values obtained by applying the continuous reaction time (CRT) theory from controls and heptic encephalopthy and proposedin this paper.whith these membership functions,the CRT data to be diagnosed are calculated in advance,and then discriminated by BP meural network to differentiate patients with or without braindysfunction.The troubles of low accuracy and efficiency,encountered in training BP network withfuzzy samples.scattered data and extended samples,are solved.     

车辆行驶记录仪及研究现状

概述了车辆行驶记录仪的原理、组成和功能,介绍了国内外车辆行驶记录仪的发展以及应用情况,阐述了现有记录仪的缺陷和不足,并对记录仪的发展趋势进行了展望。     

先进安全车(ASV)技术的现状与发展

先进安全车(ASV,AdvancedSafetyVehicle)是为21世纪开发使用的一种高度智能化的安全车,其主要利用电子技术进一步提高汽车的安全性能。因而,汽车安全性的研究与开发已成为汽车行业发展的主要方向。为此,介绍了先进安全车(ASV)技术的现状,并讨论了这项技术的发展趋势。     

基于YOLOv5s-ESTC的肉苁蓉检测

为了解决因梭梭和红柳等宿主遮挡、样本分布密集、样本大小不均衡等造成人工种植肉苁蓉检测精度低以及模型参数量过大难以向嵌入式设备移植等问题,该研究提出一种基于改进YOLOv5s的人工种植肉苁蓉轻量化检测方法。首先,将YOLOv5s的主干网络替换为EfficientNetv2网络,以减少模型参数量和计算复杂度进而实现模型轻量化,便于后期将模型向嵌入式设备部署;其次,为了增强模型对小目标肉苁蓉特征信息的提取能力,将C3模块与Swin Transformer Block进行整合,得到C3STR模块,将其引入主干网络,并将其输出的特征图与Neck网络中的特征图进行融合;最后,在检测头前端与颈项加强网络之间添加CA注意力机制,以弱化背景信息、聚焦目标特征,提高网络检测性能。试验结果表明,该模型对于肉苁蓉的检测精度和准确率分别为89.8%和92.3%,模型的参数量和计算量分别为5.69×10⁶ MB和6.8 GB,权重文件大小为11.9 MB,单幅图像推理时间为8.9 ms,能够实现实时性检测。同其他主流模型相比,改进后的模型的检测精度分别比SSD、Faster R-CNN、YO...     

改进YOLOv5s对病理学图像中猪只小肠绒毛的检测

为解决传统小肠绒毛需要专业人员手动检测耗时耗力且存在主观性和不稳定性等问题,同时提高在复杂病理学图像中小肠绒毛检测的准确率和效率,该研究提出基于改进YOLOv5s检测复杂病理学图像下猪只小肠绒毛的方法。首先,采用串联形式的混合池化对空间金字塔进行优化,增强特征提取与特征表达,提升检测精度;然后引入一种基于注意力机制的网络模块(simpleattentionmechanism,SimAM)与Bottleneck中的残差连接相结合,使用SimAM对Bottleneck中的特征图进行加权,得到加权后的特征表示,利用注意力机制加强模型对目标的感知。试验结果表明,该研究算法的平均精度（average precision）和每秒传输帧数（frame per second,FPS）达到92.43%和40帧/s。改进后的YOLOv5s在召回率和平均精度上相较改进前提高2.49和4.62个百分点,在不增加模型参数量的情况下,每帧图片的推理时间缩短1.04 ms。与经典的目标检测算法SSD、Faster R-CNN、YOLOv6s、YOLOX相比,平均精度分别提高15.16、10.56、2.03和4.07...