pipe_rw

说明：  职工信息管理系统职工信息管理系统职工信息管理系统(Information management system foremployees)

部分win7/win8用户 运行时报错 可能是 权限问题,所以运行项目的时候 要右键>>以管理员身份运行 部分用户 运行该项目的时候 可能提示：协定需要双工 但是绑定 NetTcpBinding 不支持 这是只需要将host项目app.config中协议部分 改为wsDualHttpBinding 即可，如下代码： 另外使用wcf时，最好不要使用 using 因为使用using会屏蔽掉很多错误，误导用户，参考链接：http://www.codeproject.com/Tips/197531/Do-not-use-using-for-WCF-Clients 相关代码改为：using System;using System.Collections.Generic;using System.Linq;using System.Windows.Forms;using System.ServiceModel;namespace WcfUploadServiceHost{ static class Program { /// /// The main entry point for the application. /// [STAThread] static void Main() { try { var host = new ServiceHost(typeof (WcfUploadServiceLib.UpLoadService)); host.Open(); Console.WriteLine("Server is opened..."); Console.Read(); //using (var host = new ServiceHost(typeof(WcfUploadServiceLib.UpLoadService))) //{ // host.Open(); // Console.WriteLine("Server is opened..."); // Console.Read(); //} } catch (Exception ex) { Console.WriteLine(ex.ToString()); Console.Read(); } } }}

说明：  对IEEE33节点的电压暂降监测点的优化配置(Optimal configuration of voltage sag monitoring points in ieee33 bus)

说明：  实现深度学习中，对图像的注意力机制，强化网络的学习能力，提高网络精度和泛化能力。(It can improve the classification accuracy of deep learning network, and can be easily embedded into other networks such as densenet,resnet and etc.)

说明：  使用KERAS为框架搭建深度学习网络进行脊柱分割(Using keras as to build a deep learning network for spine segmentation)

SVM的参数优化——如何更好的提升分类器的性能，含有源程序和代码(SVM parameter optimization - how to better improve the performance of the classifier, containing source code and code)

2014年6月发表在Science论文上的聚类算法源代码，非常有参考价值， Clustering by fast search and find of density peaks (matlab code of Clustering by fast search and find of density peaks )

均值变点是统计学中常用的变点分析方法，其主要思想如下： 假设有一组数据，随着某个指标变化（增大），其值逐渐增加并趋于稳定，如何判断在这个过程中是否出现了突变的情况，异样的情况？ 均值变点分析方法提供了一种思路，大概如下： 1 计算总的均值和方差； 2 循环将这组有序数据分成两组，X1，X2 计算各组的均值和方差， 计算总方差与分组方差之和的差； 3 得到变点(The change point of mean is a commonly used change point analysis method in statistics. Its main ideas are as follows: If there is a set of data, as a certain index changes (enlargement), its value increases gradually and tends to be stable. How to judge whether there is a sudden change in the process and the unusual situation? The mean change point analysis method provides a way of thinking, which is as follows: 1 the total mean and variance are calculated. The 2 cycle divides the ordered data into two groups, X1, X2. Calculate the mean and variance of each group. The difference between the sum of the total variance and the group variance is calculated. 3 get a change point)

非常著名的视频压缩标准:H.263,全部的源码，非常适合视频编码的学习-CODEC H.263

神经网络跟踪理论及应用.PDF,神经网络一本不错的书，有目标跟踪。(Theory and Application of Neural Network Tracking. PDF, neural networks a good book, a target tracking.)