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。     

A new metaheuristic for optimization: Optics inspired optimization (OIO)

Due to the law of reflection, a concave reflecting surface/mirror causes the incident light rays to converge and a convex surface/mirror causes the light rays to reflect away so that they all appear to be diverging. These converging and diverging behaviors cause that the curved mirrors show different image types depending on the distance between the object and the mirror. We model such optical phenomena metaphorically into the searching process of numerical optimization by a new algorithm called optics inspired optimization (OIO). OIO treats the surface of the numerical function to be optimized as a reflecting surface in which each peak is assumed to reflect as a convex mirror and each valley to reflect as a concave one. Each individual is assumed to be an artificial object (or light point) that its artificially glittered ray is reflected back by the function surface, given that the surface is convex or concave, and the artificial image is formed (a candidate solution is generated within the search domain) based on the mirror equations adopted from physics of optics. Besides OIO, we introduce different variants of it, called ROIO (Rotation based OIO), and COIO (Convex combination based OIO) algorithms and conduct an extensive computational effort to find out the merit of the new algorithms. Our comparisons on benchmark test functions and a real world engineering design application (i.e., optimization of a centrifuge pump) demonstrate that the new algorithms are efficient and compete better than or similar to most of state of the art optimization algorithms with the advantage of accepting few input parameters.     

驱动压电陶瓷的高压放大器

概述了高压放大器的基本组成，以及采用高压稳压电源措施，提高高压放大器的性能，并简述了高压放大器输出级的工作原理，给出了过渡保护方法。     

HS－2000型双反射镜补偿式高速摄影系统研究

介绍ＨＳ─２０００双反射镜补偿式高速摄影系统的补偿原理、结构及其试验结果。     

椭球反射镜膜厚均匀性

本文分析了椭球反射镜膜层厚度均匀性对反射率的影响,从理论上得到膜厚计算公式。根据计算的膜厚分布设计了遮蔽板,获得较好的反射特性。     

提高大口径金属主镜面形精度的方法

分析了影响Ｒｉｔｃｈｅｙ－Ｃｈｒｅｉｔｉｅｎ光学系统中金属主反射镜面形精度因素，采用有限元法对立交易的加工过程及其安装进行了模拟，指出提高主镜的面形镜度，既要合理主镜材料的热处理工艺，也要对加工参数进行控制。良好的稳定化处理可以有效地消除材料内部的残余应力，保证主镜尺寸的稳定性。提高加工基准的精度，并采用组合加工镜面，可以大大提高主镜的面形精度，最后，给出了主镜的干涉仪检测结果。     

刀倾全展成准双曲面齿轮的切齿设计

为提高准双曲面齿轮的啮合性能,对刀倾全展成(HGT)准双曲面齿轮进行切齿设计研究.以局部综合法(Local Synthesis)为基础,并依据格里森准双曲面齿轮的加工原理,得到满足一定啮合性能的加工参数,并采用该参数对齿轮副进行轮齿接触分析(TCA).从齿面印痕和传动误差曲线可以看出,齿轮副重合度大,传动平稳,可通过调整局部控制参数来改变齿轮的啮合性能,验证了切齿设计的正确性.该方法可通过对设计参考点及其领域内的啮合条件进行预控,达到对齿面啮合质量的控制.     

光稳系统中视轴漂移的数值模拟

基于坐标变换公式和矢量旋转公式,分析了视轴稳定系统中各光学器件对于光线矢量传输的影响,并对光线矢量传输进行追踪,建立了视轴稳定系统的光学传输模型,数值模拟了光学平台角度振动对探测视轴漂移的影响,从而获到了基于快速倾斜反射镜的视轴校正系统的角度补偿量.模拟结果表明,对该光学系统的视轴校正,快速倾斜反射镜绕轴旋转的角度补偿量为0,绕轴旋转的角度补偿量与位敏传感器上沿方向的投影是一种简单的线性关系.     

Fuzzy ARTMAP classification of invariant features derived using angle of rotation from a neural network

Conventional regular moment functions have been proposed as pattern sensitive features in image classification and recognition applications. But conventional regular moments are only invariant to translation, rotation and equal scaling. It is shown that the conventional regular moment invariants remain no longer invariant when the image is scaled unequally in the x- and y-axis directions. We address this problem by presenting a technique to make the regular moment functions invariant to unequal scaling. However, the technique produces a set of features that are only invariant to translation, unequal/equal scaling and reflection. They are not invariant to rotation. To make them invariant to rotation, moments are calculated with respect to the principal axis of the image. To perform this, the exact angle of rotation must be known. But the method of using the second-order moments to determine this angle will also be inclusive of an undesired tilt angle. Therefore, in order to correctly determine the amount of rotation, the tilt angle which differs for different scaling factors in the x- and y-axis directions for the particular image must be obtained. In order to solve this problem, a neural network using the back-propagation learning algorithm is trained to estimate the tilt angle of the image and from this the amount of rotation for the image can be determined. Next, the new moments are derived and a Fuzzy ARTMAP network is used to classify these images into their respective classes. Sets of experiments involving images rotated and scaled unequally in the x- and y-axis directions are carried out to demonstrate the validity of the proposed technique.