本件能够使得你的应用程序同时只能运行一个

半透明窗口,短小精悍,使用方便,操作简单! -translucent window, small and easy to use, simple!

基于web的数据挖掘，获取信 XHTML 格式的源信息，将数据 从 HTML 转换成 XML-Web-based data mining, to obtain a letter format XHTML source of information, data from XML into HTML

该程序用贪心算法来求解二分覆盖问题. 采用贪婪准则：每次从A中选择一个顶点加入覆盖，选择时：选取能覆盖B中还未被覆盖的顶点的数目最多的顶点。-procedures with the greedy algorithm to solve two hours coverage. Using greed criteria : A time to choose from a peak accession coverage options : To B coverage can not be covered by the largest number of vertices of the vertex.

C/C++应用编程200例-C/C Application Programming 200 cases

资源管理的界面代码 资源管理的界面代码 资源管理的界面代码-Resources management, resource management interface code interface code resource management interface code

7段数码管显示，时钟控制及显示，温度测量及显示-digital LED display，Clock，temperature。

1、本程式无须安装。 2、请将HELP文件与软件置于同一文件夹下。 3、请将TEMP文件夹拷贝至D盘根目录下 4、报表生成请另存 5、谢谢使用，本软件归李莉所有。-one, the programs do not need to install. Two, please HELP documents and software under the same folder. 3, I would be grateful if the TEMP folder copy to D NOTE 4 under, Report Generation Please Save 5, thank you use the software under all Li Li.

指纹识别的程序,原文件是参考别人的，做了一点点修改，版权归原作者，仅供大家参考-fingerprint identification procedures, the original document is the reference to people, doing a little bit of a change Lastings original author. we only reference

PocketNester的c++源代码,很好的学习例子,仅供大家学习-PocketNester the c source code, examples of good learning, and learning is for everyone

FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分。在介绍FCM具体算法之前我们先介绍一些模糊集合的基本知识。-FCM algorithm is a clustering algorithm based on the division of its thinking is that it is making is divided into clusters with the greatest similarity between the object, and different similarity between the smallest cluster. Fuzzy C-means algorithm is an ordinary C-means algorithm, the general C-means algorithm for data delineation is rigid, while the FCM is a soft fuzzy partition. FCM in the introduction prior to the specific algorithm we first introduce some basic knowledge of fuzzy sets.