基于机器视觉技术的音圈电机磁钢自动检测系统

为实现音圈电机磁钢轮廓的快速检测,提出了一个由图像采集、系统照明、图像处理和单片机控制下的分拣模块等几个部分构成的自动检测系统,简要介绍了系统硬件模块的设计方法,并根据实际VCM磁钢的轮廓特征提出了软件设计的具体算法．最后给出了音圈电机磁钢轮廓检测的实验结果,表明此系统设计方案简易可行．     

基于支持向量机的栗属树种分类研究

形状特征是物体识别的重要依据。同时,分类算法的选择也将对识别的性能造成很大影响。围绕上述两个问题,以栗属树种的果实图像为例,在准确分割出目标图像的基础上,分别应用不变矩和边界矩提取其形状特征值,并使用支持向量机算法对栗属树种果实图像进行分类。实验结果表明:基于支持向量机的栗属树种果实图像分类识别准确率可达到87.5%,识别的结果较为理想。     

支持向量机在意大利葡萄酒种类识别中的应用

葡萄酒的化学成分是辨别葡萄酒品种的主要依据。考虑到常规检测方法复杂、繁琐,准确率低,选择机器学习方法识别葡萄酒种类。针对目前常用的K均值算法在葡萄酒识别中存在的问题,尝试使用支持向量机进行分类,并与K均值算法进行对比分析。结果表明,基于支持向量机的模型分类性能更好,准确率达到98.15%。     

Low-leakage diode-triggered silicon controlled rectifier for electrostatic discharge protection in 0.18-μm CMOS process

A diode-triggered silicon controlled rectifier （DTSCR） is being developed as an electrostatic discharge （ESD） protection device for low voltage applications. However, DTSCR leaks high current during normal operation due to the Darlington effect of the triggering-assist diode string. In this study, two types of diode string triggered SCRs are designed for low leakage consideration; the modified diode string and composite polysilicon diode string triggered SCRs （MDTSCR ＆ PDTSCR）. Compared with the conventional DTSCR （CDTSCR）, the MDTSCR has a much lower substrate leakage current with a relatively large silicon cost, and the PDTSCR has a much lower substrate leakage current with similar area and shows good leakage performance at a high temperature. Other DTSCR ESD properties are also investigated, especially regarding their layout, triggering voltage and failure current.     

数控车床实训故障排除分析

在数控实训中应尽可能避免学生在操作时产生故障,要采取对策切实提高学生的数控加工能力,避免故障的发生。     

试析数控编程及应注意的几个问题

从几个方面就在数控加工编程过程中如何灵活运用数控机床的编程功能以及如何简化编程作了一定的探索,并针对在数控编程过程中应该注意的问题进行了分析.     

中国制造业结构的演进特征分析及其趋势预测

摘要：探究产业结构的一般演进规律一直是经济学家关注的焦点。目前关于产业结构的研究较多,但在产业划分上过于粗略,在预测方法上对数据的要求苛刻而与现实不符。针对上述问题,本文首先搜集整理了1988-2005年中国制造业内部细分行业的产值数据,细致地刻画了近20年来中国制造业内部结构的变动趋势,结果发现我国制造业结构一直处于高度化的演进过程。此外,针对产业结构变动的影响因素错综复杂而难以建立有效的计量经济预测模型的难题,本文提出了一种基于微分进化算法的支持向量机预测模型,并利用中国制造业结构数据对该预测方法进行了检验。结果表明,基于微分进化算法的支持向量机预测模型能够有效地把握趋势信息而克服不确定及短期因素的影响,具有较强的可操作性和较高的预测精度。     

一种教育/娱乐机器人控制器的设计与实现

本文所研究的是一种具有较高性价比的教育/娱乐机器人控制系统,控制器的核心是基于ARM的可扩展的控制平台,并以机器人小车为载体集成了多种外围设备.     

基于机器学习的自适应个性化数字图书馆模型研究

由于信息数量和种类增加,用户对数字图书馆期待更多的智能服务.本文提出通过引入机器学习技术来解决此问题,首先简要介绍了机器学习技术,说明了可适应个性化数字图书馆局限性,然后提出基于机器学习的自适应个性化数字图书馆模型,最后探讨了用户模型的自动创建.实践表明,此模型可满足用户对信息的需要,简化信息查找过程.     

Autonomic machine learning platform

Acquiring information properly through machine learning requires familiarity with the available algorithms and understanding how they work and how to address the given problem in the best possible way. However, even for machine-learning experts in specific industrial fields, in order to predict and acquire information properly in different industrial fields, it is necessary to attempt several instances of trial and error to succeed with the application of machine learning. For non-experts, it is much more difficult to make accurate predictions through machine learning.In this paper, we propose an autonomic machine learning platform which provides the decision factors to be made during the developing of machine learning applications. In the proposed autonomic machine learning platform, machine learning processes are automated based on the specification of autonomic levels. This autonomic machine learning platform can be used to derive a high-quality learning result by minimizing experts’ interventions and reducing the number of design selections that require expert knowledge and intuition. We also demonstrate that the proposed autonomic machine learning platform is suitable for smart cities which typically require considerable amounts of security sensitive information.