A dynamic holding strategy in public transit systems with real-time information

Holding strategies are among the most commonly used operation control strategies in transit systems. In this paper, a dynamic holding strategy is developed, which consists of two major steps: (1) judging whether an early bus should be held, and (2) optimizing the holding times of the held bus. A model based on support vector machine (SVM), which contains four input variables (time-of-day, segment, the latest speed on the next segment, and the bus speed on the current segment) for forecasting the early bus departure times from the next stop is also developed. Then, in order to determine the optimal holding times, a model aiming to minimize the user costs is constructed and a genetic algorithm is used to optimize the holding times. Finally, the dynamic holding strategy proposed in this study is illustrated with the microscopic simulation model Paramics and some conclusions are drawn.

Towards capacity and profit optimization of video-on-demand services in a peer-assisted IPTV platform

This paper studies the conditions under which peer-to-peer (P2P) technology may be beneficial in providing IPTV services over typical network architectures. It has three major contributions. First, we contrast two network models used to study the performance of such a system: a commonly used logical “Internet as a cloud” model and a “physical” model that reflects the characteristics of the underlying network. Specifically, we show that the cloud model overlooks important architectural aspects of the network and may drastically overstate the benefits of P2P technology. Second, we propose an algorithm called Zebra that pre-stripes content across multiple peers during idle hours to speed up P2P content delivery in an IPTV environment with limited upload bandwidth. We also perform simulations to measure Zebra’s effectiveness at reducing load on the content server during peak hours. Third, we provide a cost-benefit analysis of P2P video content delivery, focusing on the profit trade-offs for different pricing/incentive models rather than purely on capacity maximization. In particular, we find that under high volume of video demand, a P2P built-in incentive model performs better than any other model, while the conventional no-P2P model generates more profits when the request rate is low. The flat-reward model generally falls in between the usage-based model and the built-in model in terms of profitability except for low request rates. We also find that built-in and flat-reward models are more profitable than the usage-based model for a wide range of subscriber community sizes. Funding for J. Rahe’s research has been provided by AT&T Labs, the State of California under the MICR Oprogram, and by the Toshiba Corporation. Zhen Xiao is partially supported by China MOST project (2006BAH02A10).     

基于频繁项挖掘的未知P2P流量识别方法

提出一种基于多维聚类的频繁项挖掘算法,利用聚类思想自动挖掘网络中的显著流量及其规则,并在此基础上,对显著流量进行P2P疑似性判别,同时结合应用层特征识别技术,对高度疑似的P2P显著流量类进行过滤,实现未知P2P流量检测。实验结果表明,该方法是有效的。     

基于Python的实时嵌入式软件测试脚本

基于Python语言设计一种实时测试脚本,开发扩展模块,实现测试脚本与嵌入式软件仿真测试环境（ESSTE）的接口。该测试脚本使用简便,实时性高、描述能力强、具有良好的可复用性,目前已成功应用到ESSTE中。对多个实时嵌入式软件进行测试,结果验证了该测试脚本的正确性和实时性。     

基于GIS和神经网络的泥石流危险性评价系统

基于ArcEngine组件和．Net集成开发天山公路泥石流危险性评价系统,将GIS技术和神经网络集成应用于泥石流危险性评价中,发挥GIS强大的空间信息可视化管理和分析功能以及神经网络的非线性描述和分析功能,实现泥石流危险性评价的可视化管理,为工程决策者和管理人员提供一种强有力的决策支持方案。     

基于多种视频特征的镜头边界检测算法

针对固定场景的视频,提出一种基于时空分割的视频分割算法.该算法在时域中利用Tophat形态学滤波得到视频对象的精确位置,在空域中采用基于t混合模型和贪婪EM的聚类算法进行单帧图像分割.将时域定位和空域分割结果结合,可以准确地将视频序列中感兴趣的运动目标分割出来.实验表明,该算法能够得到完整的视频对象,有一定的理论意义和实用性.     

组件式仿真系统中基于Web的管理控制方法

介绍组件式仿真系统的结构和特点,提出基于Web的组件资源管理方法和组件式仿真系统管理方法。描述组件资源库的结构和仿真管理方法的工作原理,阐述仿真过程控制服务的设计思路和管控Web服务器的结构。分析结果表明,该方法能用于可扩展建模与仿真框架。     

基于节点性能估算的应用层组播算法

提出一种基于节点性能估算的应用层组播树构建和维护算法(PPE)。综合考虑节点的性能及其在组播树中的位置,尽可能使高性能的节点接近源节点,使低性能的节点接近叶子节点,以此来提高组播树的效率,降低端到端的延迟,减小链路压力和控制开销。仿真结果表明,PPE在大规模节点环境中能有效改善组播树的性能。     

基于本体的概念语义相似度度量

针对概念语义相似度度量问题,提出结合基于图理论和信息量2种方法的语义相似度度量算法。计算2个概念在概念图中连接的路径长度、局部密度以及在连接2个概念之间的路径上连接关系的连接力度,结合连结路径权重和信息量来度量概念之间的语义相似度。实验结果表明,该算法能取得较好的度量效果。     

基于调和映射的三维医学图像增强系统

医学成像仪器产生12位的体数据,然而普通显示器只支持8位的灰度图。如果使用普通显示器来显示医学图像,显卡会自动将这些12位数据转化成8位数据,这就造成了数据动态范围被压缩。解决这一问题,在2D领域通常使用昂贵的医学专用灰阶显示器。在3D领域却限制了医生使用三维可视化软件。尝试将一些在2D图像处理中使用的图像增强技术如加权平均模板,不同程度曝光等来实现色调映射算法等应用到三维体数据的显示当中,通过种种复杂的数据变换,使得在普通显示器上显示的8位灰度图呈现出更高的动态范围,得到更为生动、更加丰富的显示效果。这种技术也可以实现任意位数的转化,使得12位显示器的显示效果也可以得到增强。