购物车代码

本项目的开发主要包括后台数据库的建立和维护以及前端应用程序的开发两个方面。对数据库的开发，要求建立起数据一致性和完整性强、数据安全性好的库。而对于前段应用程序的开发，要求应用程序功能齐全，简单易用。 不同于基于ASP.NET开发的企业中的OA系统，此项目采用C#编写，生成可执行文件。开发工具选择Microsoft Visual Studio 2008，数据库管理系统则应用对Microsoft Visual Studio 2008支持最好的SQL Server 2005。 (Development of this project mainly include database creation and maintenance, and front-end application development aspects. Database development, required consistency and integrity of the strong, good for the security of data. For the preceding application development, application functionality required complete, easy to use. Unlike ASP.NET-based enterprise development in the OA system, this project uses C# to write, build the executable file. Tools Select Microsoft Visual Studio 2008, database management system is applied to the Microsoft Visual Studio 2008 to support the best SQL Server 2005.)

通过sorket传送文件,编写代码为c#. 包含sorket握手 文件流转换 sorket文件发送 sorket文件接收 欢迎下载和研究使用！！！！！！！！！

BK4802N 是一个专为玩具对讲/玩具遥控设 计的半双工模式的射频收发芯片，采用高 度集成化的 CMOS工艺，支持 FM调制/解。射频专用IC，功能强大。(RF dedicated IC, powerful.)

聊天服务器，输入IP既可聊天，还恨好用，真的不错-Chat server, enter the IP can chat, but also hate use, really good

说明：  详细描述SPI发送和接收过程，已经经过调试通过，主要适用于PIC18FXXX(A detailed description of the process of sending and receiving SPI, debugging has been approved, mainly applicable to PIC18FXXX)

本书详细讲解c和c++的基本概念，包含三大部分，从简到繁，详细划分，适合初入门的读者以及具有一定编程经验的程序人员阅读(Book explain in detail the basic concepts of c and c++ of, contains three parts, from simple to complex, detailed breakdown of the readers, as well as some programming experience program for early entry read)

我近期从事视频开发所以将我参考的资料上传给大家看看。(I recently engaged in video development, therefore, refer to the information I upload to the U.S. to see.)

字符匹配问题为典型的字符数组的运用问题，体现了c语言面向过程的特性，在VC6.0下能够正确编译以及运行。(The problem of character matching is a typical character array, which reflects the characteristics of C language and can be compiled and run in VC6.0. )

软件登陆界面示例(带登陆密码输入错误次数限制)-software interface landing examples (with password landing limit to the number of input errors)

在VS2013+openCV2.4.9平台上运行，首先准备正负样本若干，进行预处理，提取正负样本的Hog特征，加入到SVM分类器进行训练，最终得到检测行人的分类器！