基于OCTEON芯片的高精度流回放系统的设计与实现

介绍网络多核处理器OCTEON和基于OCTEON开发的基本需求,讨论在Linux平台下基于该芯片开发高精度流回放系统的设计与实现过程,包括主机与OCTEON间PCI的通信,高精度流回放的时间戳实现,以及多个流同时回放的设计与实现。对该系统的性能测试表明,基于OCTEON的流回放实现高度并行并且高精度的处理,系统的实现对于在高速Gbps环境下的网络数据流检测、过滤与入侵检测系统具有很高的应用价值。     

基于Moodle的网络教学模式构建与使用

本文介绍一种功能强大、开源免费的学习管理系统(LMS)- -Moodle,阐述了利用该系统的功能模块进行课程设计的方法和构建网络教学模式的流程,并提出了这种教学模式在实际使用过程中的建议.     

Mining partial periodic correlations in time series

Recently, periodic pattern mining from time series data has been studied extensively. However, an interesting type of periodic pattern, called partial periodic (PP) correlation in this paper, has not been investigated. An example of PP correlation is that power consumption is high either on Monday or Tuesday but not on both days. In general, a PP correlation is a set of offsets within a particular period such that the data at these offsets are correlated with a certain user-desired strength. In the above example, the period is a week (7 days), and each day of the week is an offset of the period. PP correlations can provide insightful knowledge about the time series and can be used for predicting future values. This paper introduces an algorithm to mine time series for PP correlations based on the principal component analysis (PCA) method. Specifically, given a period, the algorithm maps the time series data to data points in a multidimensional space, where the dimensions correspond to the offsets within the period. A PP correlation is then equivalent to correlation of data when projected to a subset of the dimensions. The algorithm discovers, with one sequential scan of data, all those PP correlations (called minimum PP correlations) that are not unions of some other PP correlations. Experiments using both real and synthetic data sets show that the PCA-based algorithm is highly efficient and effective in finding the minimum PP correlations. Zhen He is a lecturer in the Department of Computer Science at La Trobe University. His main research areas are database systems optimization, time series mining, wireless sensor networks, and XML information retrieval. Prior to joining La Trobe University, he worked as a postdoctoral research associate in the University of Vermont. He holds Bachelors, Honors and Ph.D degrees in Computer Science from the Australian National University. X. Sean Wang received his Ph.D degree in Computer Science from the University of Southern California in 1992. He is currently the Dorothean Chair Professor in Computer Science at the University of Vermont. He has published widely in the general area of databases and information security, and was a recipient of the US National Science Foundation Research Initiation and CAREER awards. His research interests include database systems, information security, data mining, and sensor data processing. Byung Suk Lee is associate professor of Computer Science at the University of Vermont. His main research areas are database systems, data modeling, and information retrieval. He held positions in industry and academia: Gold Star Electric, Bell Communications Research, Datacom Global Communications, University of St. Thomas, and currently University of Vermont. He was also a visiting professor at Dartmouth College and a participating guest at Lawrence Livermore National Laboratory. He served on international conferences as a program committee member, a publicity chair, and a special session organizer, and also on US federal funding proposal review panel. He holds a BS degree from Seoul National University, MS from Korea Advanced Institute of Science and Technology, and Ph.D from Stanford University. Alan C. H. Ling is an assistant professor at Department of Computer Science in University of Vermont. His research interests include combinatorial design theory, coding theory, sequence designs, and applications of design theory.     

基于多Agent的世博会交通疏导决策支持系统

分析世博会交通概况,把多Agent技术引入到决策支持系统中来,给出了世博会交通疏导决策的框架,以及该系统的决策模型,使之能够更好地对交通进行决策管理,为2010年将在上海举行的世博会提供参考.     

Peterson算法在场消隐期传输中的应用

场消隐期作为应用电视有限资源的一部分,其开发潜力正逐渐为人们所重视.本文提出了一种新型的综合数据传输业务的单缆传输电视监控系统,将控制信号搭栽在视频信号通道上运行,并以Peterson算法和Chien氏搜索法为基础,将无线通信中常用的(15,7)BCH控制编码应用于底层的单片机级的信号传输中,同时给出了相应的软件解码方法,在优化控制信号的传输线路和解决时延问题的同时,大大提高了实时数据通信的有效性和可靠性,从而达到了利用电视信号逆程资源的目的.     

可重构板级支持包的设计与实现

针对传统板级支持包(BSP)的弊端,设计了一种模块化、层次化的可重构BSP,提高了BSP的开发效率,降低了开发难度,最后以课题实例加以说明和验证.     

步进频率探地雷达的实时处理器软件设计

数据预处理是探地雷达系统中的一项重要内容,针对步进频率探地雷达的数据处理工作量大的特点,引入数字信号处理器(DSP)来完成数据预处理任务.在此基础上,构建了DSP处理软件的整体框架,详细设计了软件的各功能模块,并定义了数据的通信协议.所设计软件具有良好的拓展性和可选择性,经实际数据测试,在处理时间上能够满足实时性的要求.     

Learning in an Ambient Intelligent World: Enabling Technologies and Practices

The rapid evolution of information and communication technology opens a wide spectrum of opportunities to change our surroundings into an Ambient Intelligent (AmI) world. AmI is a vision of future information society, where people are surrounded by a digital environment that is sensitive to their needs, personalized to their requirements, anticipatory of their behavior, and responsive to their presence. It emphasizes on greater user friendliness, user empowerment, and more effective service support, with an aim to bring information and communication technology to everyone, every home, every business, and every school, thus improving the quality of human life. AmI unprecedentedly enhances learning experiences by endowing the users with the opportunities of learning in context, a breakthrough from the traditional education settings. In this survey paper, we examine some major characteristics of an AmI learning environment. To deliver a feasible and effective solution to ambient learning, we overview a few latest developed enabling technologies in context awareness and interactive learning. Associated practices are meanwhile reported. We also describe our experience in designing and implementing a smart class prototype, which allows teachers to simultaneously instruct both local and remote students in a context-aware and natural way.     

Matlab遗传算法工具箱在非线性优化中的应用

投影寻踪是一种降维处理技术,通过它可以将多维分析问题通过投影方向转化为一维问题分析。应用该法的关键在于寻求最佳投影方向,这可以转化为一个复杂的非线性优化问题来进行解决。选取某地区大气环境质量评价的投影寻踪评价模型,编制相关的目标函数和约束函数,应用基于MATLAB的遗传算法和直接搜索工具箱进行优化求解。结果表明：该工具箱在求解此类非线性优化问题上的有效性和方便性,从而为各领域应用投影寻踪模型提供了强有力的优化工具。