Network traffic classification based on ensemble learning and co-training

Classification of network traffic is the essential step for many network researches. However,with the rapid evolution of Internet applications the effectiveness of the port-based or payload-based identifi-cation approaches has been greatly diminished in recent years. And many researchers begin to turn their attentions to an alternative machine learning based method. This paper presents a novel machine learning-based classification model,which combines ensemble learning paradigm with co-training tech-niques. Compared to previous approaches,most of which only employed single classifier,multiple clas-sifiers and semi-supervised learning are applied in our method and it mainly helps to overcome three shortcomings:limited flow accuracy rate,weak adaptability and huge demand of labeled training set. In this paper,statistical characteristics of IP flows are extracted from the packet level traces to establish the feature set,then the classification model is created and tested and the empirical results prove its feasibility and effectiveness.     

中小企业数据库安全性研究

针对目前中小企业中存在的数据泄露问题,该文提出了一种中小企业的数据库模式,并给出了安全后端模式的架构图。为了实现数据库的保密性,该系统设计一个二级密钥管理机制,有效防止了数据的泄露。     

Statistical learning makes the hybridization of particle swarm and differential evolution more efficient—A novel hybrid optimizer

This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics—differential evolution (DE) and particle swarm optimization (PSO). In the hybrid denoted by DEPSO, each individual in one generation chooses its evolution method, DE or PSO, in a statistical learning way. The choice depends on the relative success ratio of the two methods in a previous learning period. The proposed DEPSO is compared with its PSO and DE parents, two advanced DE variants one of which is suggested by the originators of DE, two advanced PSO variants one of which is acknowledged as a recent standard by PSO community, and also a previous DEPSO. Benchmark tests demonstrate that the DEPSO is more competent for the global optimization of multimodal functions due to its high optimization quality. Supported by the National Natural Science Foundation of China (Grant No. 60374069), and the Foundation of the Key Laboratory of Complex Systems and Intelligent Science, Institute of Automation, Chinese Academy of Sciences (Grant No. 20060104)     

中职信息技术课程学生学习能力培养的实践研究

在职业教育教学实践过程中,教师面临着"如何培养学生的信息技术学习能力?"问题。通过调查分析,发现研究适合职教学生的课堂教学的方式方法,激发学生的学习积极性是非常必要的。只有这样才能培养学生的创造力、自主学习能力,互相协作及自我约束自我管理的能力。     

基于学习对象的网络学习内容组织方法

本文在研究学习对象和学习对象元数据及参考IMS学习资源元数据标准和内容包装规范的基础上,提出了一种基于学习对象的网络学习内容组织方案,该方案利用元数据模型描述学习对象的"模式"信息,以支持对网络学习内容的访问和搜索;提出了一个学习对象包装模型对网络学习内容进行组织和包装,以支持对网络学习内容的重用和交换。     

基于工作过程的软件开发项目课程建设探究

基于工作过程的软件开发项目课程建设是一个探索中前行的过程,该文针对目前该项目课程实施效果不太理想的状况,对学习领域和学习情境的构建和设计进行分析研究,提出了改进措施。     

基于ASP．NET AJAX网络辅助学习平台

在高校校园网迅速发展情况下,传统教学模式无法满足学生的学习需求和个性化需要,网络辅助学习平台成为阜富教学手段、弥补教学缺失的必要补充。网络辅助学习平台基于网络的RIA方式,采用ASP．NET AJAX应用框架和模块化设计思想实现了管理、教师、学生三方面的功能应用。网络辅助学习平台的应用提高了教学质量,增强了教学效果,满足学生了个性化需求,运用先进的现代教育技术,培养了学生的自学能力。     

基于.NET的用户权限管理设计与实现

讨论基于角色访问控制方式的权限管理思想以及运用该思想进行权限管理系统的设计与实现。     

小城镇综合地理信息系统的设计与开发

针对小城镇管理的现状和发展需求,结合小城镇的经济承受能力和科技力量,采用组件式GIS与可视化开发语言的集成二次开发方式,设计和开发了实用的小城镇综合地理信息系统.介绍了系统的技术框架,以其中的土壤资源管理子系统为例说明系统的开发过程,讨论了系统建设需要解决的几项关键问题.通过该系统可实现小城镇的资源、规划管理及工业、农业、商业,税务.交通等的统计、查询、分析及决策功能,同时可提供相应的图文资料.     

倒立摆的迭代学习控制方法研究

针对倒立摆系统典型的非线性、多变量和自然不稳定的特点,在建立系统数学模型基础上,利用迭代学习控制方法,根据动态指标的要求设计了控制器,并完成了系统仿真,结果表明:与传统反馈控制相比较,所设计的迭代学习控制器使系统的动态性能得到了很大的改善。