故障诊断的一个PPT 来自于上海交大陈进教授。此PPT介绍了故障诊断目前应用的现状和将来的展望。 版权属于上海交大陈进教授，请只用于学习。 故障诊断是自动化领域的一个实际应用，主要是通过数学和物理知识，建立模型然后加上推理机的方法，提供故障的辅助决策。 故障诊断 自动化

手机Wifi杀手功能强大，请勿不要滥用无线路由器，此软件太邪恶，以禁止发布使用，请大家不要滥用。

来自国家统计局的省市区镇村五级联动数据库表MySQL版脚本

降低论文查重的策略，有效帮助你完美毕业，一次性通过毕业论文的书写，节省大量的时间，

此功能计算来自接收器的卫星的方位角和仰角 输入：Pos_Rcv：接收器（仪表）的XYZ位置（米） Pos_SV：GPS卫星的XYZ矩阵位置（米） 输出：E：仰角（弧度）A：方位角（弧度）

地图配色选择方案参考-来自国外地图可视化实验室，包含不同配色方案。

java开发，30个常用工具类总结，全部来自项目实践中用到的工具类：dateUtils、StringUtils、CalendarUtils、FileUtil、RandomUtil等

包括行政边界、建筑物、路网、河流、交通点等信息，从OSM上下载的。上传资源想免费的，但是好像只能选择最少1积分。有需要可以自行下载，也可以从OSM自行下载~

来自麻省理工的正则化最小二乘法讲义，讲得精炼而且较为易懂！

这是一篇来自science杂志的论文，非常经典！介绍了测地距离在流行降维中的应用。 Scientists working with large volumes of high-dimensional data, such as global climate patterns, stellar spectra, or human gene distributions, regularly confront the problem of dimensionality reduction: Þnding meaningful low-dimensional structures hidden in their high-dimensional observations. The human brain confronts the same problem in everyday perception, extracting from its high-dimensional sensory inputsÑ30,000 auditory nerve Þbers or 106 optic nerve ÞbersÑa manageably small number of perceptually relevant features. Here we describe an approach to solving dimensionality reduction problems that uses easily measured local metric information to learn the underlying global geometry of a data set. Unlike classical techniques such as principal component analysis (PCA) and multidimensional scaling (MDS), our approach is capable of discovering the nonlinear degrees of freedom that underlie complex natural observations, such as human handwriting or images of a face under different viewing conditions. In contrast to previous algorithms for nonlinear dimensionality reduction, ours efÞciently computes a globally optimal solution, and, for an important class of data manifolds, is guaranteed to converge asymptotically to the true structure.