导游网（ASPnet Mvc项目）

 职责描述：，系统信息设计，学生出操考勤管理、学生上课考勤管理、学生参加活动考勤管理，学生寝室考勤管理，综合统计与查询等六大模块。  项目简述：该系统利用MFC框架 Excel工具开发，来实现学生考勤管理。()

LPC2103-IAR例程，NXPLPC2103 arm7处理器实验代码(LPC2103-IAR routines, NXPLPC2103 arm7 processor test code)

网上搞到的一个处理数据的程序，可以使用的。(Data of a processing program, you can get online.)

说明：  一实用的电子邮件程序代码，可以作为课程设计，工程开发的参考(a practical code of e-mail, as a curriculum design, engineering development of a reference)

Demo Classic Diffie-Hellman

说明：  这个源码提供了如何利用高斯混合模型去做影像辨识的参数的训练(the source how to use a Gaussian mixture model to do the imaging parameters of literacy training)

自己写了一个二维Euler方程的间断有限元程序 上次发了一个三角形单元的程序 因为不是曲边单元 所以在圆柱后面容易形成涡 现在把程序改为曲边四边形单元了 没有涡出现 单元是8节点四边形单元 节点编号顺序是 1 5 2 6 3 7 4 8 也就是四个角点依次 是1 2 3 4 然后是边的中点编号 5 6 7 8. 时间推进采用 Runge-Kutta 方法 数值通量采用全局Lax-Friedrichs通量 仍然不能捕捉激波 因为没有做重构或者加人工粘性 等这个做出来了 再发一次。 程序没有进行优化 比如说内存的消耗没有优化 比如直边单元的边界积分仍然采 用了曲边的积分方法 增加了计算量 比如面积分、线积分都是采用的是Gauss- Legendre-Lobatto积分 积分精度会比一般的Gauss-Legendre积分精度低一阶 等 等问题。 二维的 纯属交流性质 就没有考虑这些问题 ^_^ 如果物面全部是直边 那么只要改变一个参数N 就可以获得不同的计算精度 且具 有谱精度 因为单元的节点是Gauss-Legendre-Lobatto积分点。 其实就是谱元法 （物面是曲边的情况我不清楚是不是也可以通过提高基函数的阶数 也就是增加N 来提高计算精度）(Wrote a two-dimensional Euler equations with discontinuous finite element program Last made ​ ​ a triangular element of the program, not curved edge unit is so easy to form a vortex in the cylinder behind the Program to curved edge quadrilateral element vortices appear Unit is the order of 8-node quadrilateral element node number is 15,263,748 which is the four corners of the points in turn Is 1234 and then the side of the midpoint of the number 5678. Time promote the use of Runge-Kutta method Numerical flux of the overall situation of Lax-Friedrichs, flux Still can not capture the shock wave did not do the reconstruction or artificial viscosity do it Zaifayici. The program is not optimized for example, memory consumption is not optimized such as straight-edge boundary integral of the unit is still mining Integral method to increase the amount of computation such as surface integral with a curved edge, the line integral using the Gauss- The Legendr)

c++ kinectv2 vs2015 opencv3.1 ，win64 环境下kinectv2 SDK 开发的彩图调用。

C++如何连接数据库，对于初学者来说很重要。简单易懂。免费下载(C++ How to connect to the database, it is important for beginners. Easy to understand. Free download)

This function generates an Additive White Gaussian Noise (AWGN) sample at every call. Its beauty lies in its simplicity! The generated sample set will have zero mean and a standard deviation of 1. Therefore, one can simply scale the output samples by a different standard deviation to generate different noise profiles. To do this scaling, simply multiply the sample with the standard deviation of your choice. This is a very versatile function that can be used in communication system simulations and random number generation in various applications. I have used it in the past while working with channel encoder and decoder simulators.