数控加工工艺与传统加工工艺相结合

随着科学技术的不断发展,社会对产品的加工精度要求也越来越高。通过对数控加工工艺和特点及传统的加工和工艺进行分析,充分论述了在零件的生产和加工过程中,要发挥数控机床加工工艺的优势,把数控加工工艺和传统加工工艺相结合。     

适用于数据分类的极限学习机优化算法

针对极限学习机参数优化问题,提出量子遗传算法优化极限学习机的方法（QGA-ELM）。在该方法中,对ELM的输入权值和隐含层阈值采用量子比特编码,并将其映射为QGA的染色体,QGA的适应度函数为对应ELM的分类精度;通过QGA的量子旋转门优化出输入权值与隐含层阈值,以此训练出分类精度更高的ELM,从而改善ELM的泛化性能。通过ELM和QGA-ELM对数据集的仿真结果对比表明,QGA-ELM有效地提升了ELM网络的分类精度。     

培训前沿扫描系列（二）：国家计算机软件专业考试概述

初级：程序员、网络管理员中级：软件设计师、网络工程师、数据库工程师高级：系统分析师     

浅析细长轴在车床上快速车削

本文讨论了影响细长轴加工精度的因素熏并从装夹方式、刀具角度、切削用量,以及新加工方法等方面,阐述了提高细长轴加工精度的措施.     

差压变送器在超微压时精度及误差

对于量程0～50Pa及0～100Pa的超微差压变送器是否能够实现0.075%精度性能.     

影响机械加工精密度的原因分析

影响机械加工精度的因素有很多,在诸多误差因素中,机床的几何误差、工艺系统的受力变形和受热变形占有突出的位置,通过了解造成误差因素的原因,可以使工件的加工达到质量要求.     

绝妙的纳米画

你听说过"米上刻字"吗?熟练的工匠能在一粒大米表面刻上好几个甚至近百个字。现在,科学家借助最新科技,把这门手艺发展到了极致——在比头发丝的直径还小得多的纳米空间里画画。     

多物体系统机械能守恒的误区扫描

多个物体组成的系统满足机械能守恒定律时,在解题过程中除了要注意机械能守恒条件的判断、零势能面的选取、不能漏掉各物体的各项机械能等常见误区外,还应注意系统机械能守恒中的以下几种典型误区．     

Dependence of electrical and optical properties of IGZO films on oxygen flow

Amorphous InGaZnO (a-IGZO) films were deposited on the corning eagle XG (EXG) glass substrates using magnetron sputtering method. The structure, surface morphology, electrical and optical properties of these films were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), semiconductor parameter analyzer and spectrophotometry, respectively. The influence of oxygen flow on the electrical properties of IGZO thin films was studied, showing that increasing oxygen flow changes the resistivity with six orders of magnitude. The contact resistance of ITO/IGZO is 7.35×10⁻² Ω·cm², which suggests that a good ohmic contact exists between In₂O₃: Sn (ITO) and IGZO film.     

Searching high gray scale FPD scanning matrix based on PSO

With the increase of gray scale and flat panel display (FPD) size, subspace bitwise scanning strategy can be replaced traditional scanning method to cut down frame frequency. However, the direct searching strategy (DSS) becomes unfeasible to obtain corresponding high gray scale scanning matrix. Thus, particle swarm optimization (PSO) is introduced to accelerate searching for high gray scale weights scanning matrix (WSM) with its parallelism and global optimization feature. Finally a WSM of 256 gray scales is found out successfully with Matlab, which both gray linearity and scanning efficiency are satisfied.