WPF 自定义屏幕

生成128条形码-Generate 128 bar code

大家都知道键盘上几个的事件吧。 今天我就作了一个用上下左右键控制图标的小程序，帮助你理解这几个事件。。很好玩的。-we all know several of the keyboard events. Today I made a key up and down around the small icon control procedures to help you understand these events. . Very fun.

程序运行初期，程序首先会通过LoadLibrary函数加载动态链接库Shell32.dll，并且把加载后的操作句柄存储在LibHandle中。然后通过@SHEmptyRecycleBin:=GetProcAddress (LibHandle, SHEmptyRecycleBinA )语句读取SHEmptyRecycleBinA函数的地址，如果以上语句能够正确执行(也就是@SHEmptyRecycleBin不等于nil)，那么就调用SHEmptyRecycleBin完成清空回收站的操作。最后释放动态链接库。-The early run, the program will first of all through the LoadLibrary function to load dynamic link library Shell32.dll, and after the load operation is stored in the handle of LibHandle. Then @ SHEmptyRecycleBin: = GetProcAddress (LibHandle, SHEmptyRecycleBinA) statement read function SHEmptyRecycleBinA address, If the above statement to the correct implementation (that is, @ SHEmptyRecycleBin does not mean nil), then call the Empty Recycle Bin SHEmptyRecycleBin complete operation. Finally the release of a dynamic link library.

非常不错的自动更新程序.该有的都有了.十分好用-Very good automatic updates. That everything I had. Very easy to use

本实例实现了一中微秒级的精确定时,利用多媒体定时器的基本功能，可以通过两种方法实现精确定时。1）使用timeGetTime()函数，该函数定时精度为ms级，返回从Windows启动开始所经过的时间。2）使用timeSetEvent()函数.-Achieved one of the examples in the microsecond-level precision timing, use the basic functions of multimedia timer can be two ways to achieve precise timing. 1) Use timeGetTime () function, which ms timing accuracy for the class, to return from the Windows start after the beginning of time. 2) the use of timeSetEvent () function.

2004042323420918natas,从事局域网开发，多媒体技术工程师- 2004042323420918natas,who is engaged in the development of the LAN, engineer of the multimedia technology

用C#编写的学习正则表达式的小工具-C# study prepared by the regular expression is a small tool

在编辑框输入绘图命令，当单击“绘图”按钮时，能在左边坐标轴绘制所对应的图形-In the edit box enter the drawing commands, when you click " Drawing" button, be able to draw on the left axis corresponds to the graphic

这是一款魔方的游戏C源代码，希望对有需要的人有所帮助。-This is a Rubik

通过基于tensorflow的keras深度学习框架，自己动手搭建自己的深度神经网络，通过对网络逐层的可视化，理解卷积层池化层的作用，可以看到梯度传播算法的参数对最后分类结果的影响。