基于凌动处理器ATOM-510的车载信息终端设计

随着人们对汽车安全性、舒适性要求的不断提高,汽车电子控制功能逐渐增多,针对使用传统单片机控制方法功能单一、灵活性差等缺点,提出基于intel凌动处理器ATOM-510平台和嵌入式操作系统ubuntu的车载信息终端解决方案;实现了GPS(全球卫星定位系统)定位信息采集与解析、GPRS(通用无线分组业务)数据传输以及多媒体娱乐等功能,并基于嵌入式GUI(图形用户界面)Qt设计了良好的人机交互界面;应用结果表明,该方案运行稳定可靠、功能丰富、操作简便、易于扩展。     

模糊自适应卡尔曼滤波算法在航位推算系统中的应用

针对实际的应用中车载航位推算系统的模型参数、噪声的统计特性不确定性,影响估计效果,提出了车载航位推算的模糊自适应卡尔曼滤波模型及其滤波算法;该方法通过监视理论残差与实际残差的比值是否接近1,应用模糊推理系统不断地调整量测噪声协方差的加权,对自适应卡尔曼滤波的量测噪声协方差进行递推修正,通过该算法来抑制噪声对精度的影响,进而提高系统的导航精度;仿真结果表明,这种算法能够有效地提高系统的精度,是一种比较理想的车载DR导航滤波方法。     

基于能量强度的簇区分路由方法研究

传感器节点体积微小,通常携带能量十分有限的电池。由于传感器节点个数多,成本要求低廉,分布区域广,而且部署区域环境复杂,有些区域甚至是人员不能到达的,所以传感器节点通过更换电池的方式来补充能量是不现实的。如何高效使用能量来最大化网路的生命周期是无线传感器网络面临的首要挑战。为了提高网络的寿命,目前人们已经提出了很多基于网络层的路由协议。比较研究了传感器网络现有的路由协议,参考LEACH分簇算法和MTP协议,提出了一种在MTP协议基础上将LEACH分簇思想引入进来的改进方法,即在基于能量强度将网络节点分层后,再在各层上进行簇区分,均衡各传感器节点的能量来提高网络的寿命。实验表明该路由算法可提高网络寿命。     

STM32F103的汽车远程防盗系统设计

设计了以STM32F103R6T6单片机为核心的汽车远程防盗系统。应用WT588D语音模块,增加了后视镜折叠和展开功能,使防盗更加智能化。结合STM32F103R6T6的内部结构,设计了系统的硬件电路,详细介绍了系统的软件设计方法。实验结果表明,系统能够实时有效地处理检测到的异常情况,驱动语音模块进行正确的语音提醒。     

基于语义的网售护肤品消费者调查算法

本文针对电子商务网售护肤品消费者调查困难的问题,结合语义路由的思想,在物联网环境下提出基于语义的网售护肤品消费者调查算法,可统计消费者对商品的喜爱程度和使用习惯。仿真结果表明,算法具有冗余数据少、能耗小、响应快速、实现简单等特点。     

基于Ad Hoc的虫洞攻击与防御研究综述

本文在分析无线Ad Hoc网络路由协议研究现状的基础上,指出无线Ad Hoc网络路由协议存在的脆弱性及针对协议漏洞所发起的几种主要攻击形式。重点分析虫洞攻击的基本原理及其当前的防御方法和不足,为今后更进一步研究安全路由协议打下基础。     

Routing with multiple quality-of-services constraints: An approximation perspective

Finding a path that satisfies multiple Quality-of-Service (QoS) constraints is vital to the deployment of current emerged services. However, existing algorithms are not very efficient and effective at finding such a path. Moreover, few works focus on three or more QoS constraints. In this paper, we present an enhanced version of fully polynomial time approximation scheme (EFPTAS) for multiconstrainted path optimal (MCOP) problem. Specifically, we make four major contributions. We first allow the proposed algorithm to construct an auxiliary graph, through which the QoS parameters on each of the finding path can be guaranteed not to exceed the given constraints. Then we adopt a concept, called nonlinear definition of path constraints in EFPTAS for reducing both time and space complexity. Also, we enable EFPTAS to run iteratively to facilitate a progressive refinement of the finding result. In addition to these, we identify some “deployment” issues for proposed algorithm, the essential steps that how and when the EFPTAS takes place are presented. By analyzing the proposed algorithm theoretically, we find that the presented EFPTAS can find a (1+ε)-approximation path in the network with time complexity O(|E||V|/ε) (where |E| is the number of edges and |V| is the number of nodes), which outperforms the previous best-known algorithm for MCOP. We conduct an extensive comparison between the algorithm presented in this paper and previous best-known study experimentally, our results indicate that EFPTAS can find a path with low complexity and preferable quality.     

A comparative study between dynamic adapted PSO and VNS for the vehicle routing problem with dynamic requests

Combinatorial optimization problems are usually modeled in a static fashion. In this kind of problems, all data are known in advance, i.e. before the optimization process has started. However, in practice, many problems are dynamic, and change while the optimization is in progress. For example, in the dynamic vehicle routing problem (DVRP), new orders arrive when the working day plan is in progress. In this case, routes must be reconfigured dynamically while executing the current simulation. The DVRP is an extension of a conventional routing problem, its main interest being the connection to many real word applications (repair services, courier mail services, dial-a-ride services, etc.). In this article, a DVRP is examined, and solving methods based on particle swarm optimization and variable neighborhood search paradigms are proposed. The performance of both approaches is evaluated using a new set of benchmarks that we introduce here as well as existing benchmarks in the literature. Finally, we measure the behavior of both methods in terms of dynamic adaptation.     

机动车车牌识别中SVM的应用

支持向量机是一类新型机器学习方法,成功应用于各个领域,算法在分类性能上优于其它学习算法。该文在字符特征提取基础上,将支持向量机理论应用于车牌识别系统,提高识别率和识别速度,具有很好的推广价值。     

A preliminary study of a diagonal channel-routing model

The layout of two-terminal nets in a VLSI channel is realized in a new diagonal channel-routing model (DCRM), where the tracks are segments respectively displayed at +45 ° and –45 ° on the two layers of the channel. A new definition of channel density is introduced, and a lower bound to the channel width is derived by the application of an algorithm, whose complexity is evaluated as a function of the channel density, and other parameters of the problem.A simple linear-time algorithm is proposed, which produces an optimal layout (i.e., it requires a channel of minimum width) if the length of the longest net equals the lower bound for the channel width. In any case, the number of vias is at most one for each net. Some particular solutions are proposed for problems with long nets.Specific problems are much easier in DCRM than in the classical Manhattan model. For example, any shift-by-i can be realized in DCRM in a channel of widthi.This work has been supported by Consiglio Nazionale delle Ricerche of Italy under a research grant.