能够在每次登陆时切换桌面图片，桌面图片存放在特定目录下，且应为bitmap图片以保证效果。...

基于C++BUILDER环境，初学者很适用，代码简单易懂，对学习和借鉴有很大好处，可移植很强，我测试的版本是BCB60,版本窗口程序源代码-Based on the C++ BUILDER environment is applicable for beginners, easy-to-understand code, and has a lot to learn from the benefits of highly portable, I tested version BCB60, versions of source code window

移动存储安全限制功能，减少了如何访问U盘、枚举存储设备-Security restrictions removable storage functionality, a decrease of how to access the U disk, storage device enumeration

U盘过滤驱动系统源代码主要是用DDK来实现的-U disk drive system source code filter is mainly used to realize the DDK

VB写的一个开3389的源码，能够自动更改安装盘的位置，并释放安装程序，自动安装终端服务，适用于WIN2000服务器和高级服务器版。-VB wrote in a 3389 open-source, can automatically change the location of the installation disk, and the release of the installation procedure, automatic installation of terminal services, apply to Windows 2000 Server and Advanced Server.

获取系统的各种信息，包括内存，驱动器，磁盘等-Access to various information systems, including memory, drives, disks, etc.

好东西，用dephi写的，高数中的算法，包括积分，微分，极限，级数，最优化方法等-good things with dephi written in the high number of algorithms, including integral, differential, limit, series, optimization methods

钩子实际上是一个处理消息的程序段，通过系统调用，把它挂入系统。每当特定的消息发出，在没有到达目的窗口前，钩子程序就先捕获该消息，亦即钩子函数先得到控制权。这时钩子函数即可以加工处理（改变）该消息，也可以不作处理而继续传递该消息，还可以强制结束消息的传递。对每种类型的钩子由系统来维护一个钩子链，最近安装的钩子放在链的开始，而最先安装的钩子放在最后，也就是后加入的先获得控制权。要实现Win32的系统钩子，必须调用SDK中的API函数SetWindowsHookEx来安装这个钩子函数，这个函数的原型是HHOOK SetWindowsHookEx(int idHook,HOOKPROC lpfn,HINSTANCE hMod,DWORD dwThreadId);，其中，第一个参数是钩子的类型；第二个参数是钩子函数的地址；第三个参数是包含钩子函数的模块句柄；第四个参数指定监视的线程。

c语言源代码集锦：内含c语言程序中的一些算法，有许多函数的编程实现功能，值得一看。-c language source code Collection : c language program includes some of the algorithm, there are many functions in functional programming overseas.

自己写的一个控件，支持自定义格式剪贴板。-himself in a control, support from the definition format clipboard.

This a code for feature selection. Which combines minimum redundency and max relevance and Ftest. Originally it is written for gene selection but can be used for any kind of feature selection.-This is a code for feature selection. Which combines minimum redundency and max relevance and Ftest. Originally it is written for gene selection but can be used for any kind of feature selection.