Random walk based rank aggregation to improving web search

In Web search, with the aid of related query recommendation, Web users can revise their initial queries in several serial rounds in pursuit of finding needed Web pages. In this paper, we address the Web search problem on aggregating search results of related queries to improve the retrieval quality. Given an initial query and the suggested related queries, our search system concurrently processes their search result lists from an existing search engine and then forms a single list aggregated by all the retrieved lists. We specifically propose a generic rank aggregation framework which consists of three steps. First we build a so-called Win/Loss graph of Web pages according to a competition rule, and then apply the random walk mechanism on the Win/Loss graph. Last we sort these Web pages by their ranks using a PageRank-like rank mechanism. The proposed framework considers not only the number of wins that an item won in competitions, but also the quality of its competitor items in calculating the ranking of Web page items. Experimental results show that our search system can clearly improve the retrieval quality in a parallel manner over the traditional search strategy that serially returns result lists. Moreover, we also provide empirical evidences as to demonstrate how different rank aggregation methods affect the retrieval quality.     

Outbound logistics exception monitoring: A multi-perspective ontologies’ approach with intelligent agents

Logistics consists of a complex network of organizations and processes where exception monitoring is critical for the success of logistics service. In order to detect exceptions effectively, exception monitoring requires proper understanding of the possible exceptions. However, the extant exception monitoring approaches or systems still lack sufficient emphasis in exceptions understanding. This paper presents a novel outbound logistics exception monitoring approach by incorporating multi-perspective ontologies and intelligent agents. Specially, the multi-perspective ontologies, involving static ontology, social ontology and dynamic ontology, are firstly employed to develop the taxonomy of the logistics exception, to reflect the situation dependencies of logistics exception and to represent the dynamic nature of business processes. From this point forwards, an outbound exception monitoring system is designed by introducing multi-intelligent agents, which can ensure autonomous, flexible, and collaborative exception monitor in logistics service. Finally, the presented approach and designed system are exhibited through a case study of two ubiquitous logistics exceptions, which indicates that the proposed multi-perspective ontologies provide better understanding of exceptions thereby enabling the designed outbound exception monitoring system to perform well.     

基于免疫算法和反向传播神经元网络的无线网络入侵检测研究

为了能够检测到无线网络系统中已知和未知类型的入侵者,提高无线网络系统的安全性,在对网络数据分析和研究的基础上,提出一种基于免疫算法和反向传播神经元网络的入侵检测方法。首先利用免疫算法对网络数据进行预处理,再运用反向传播神经元网络对处理后的数据(程序)进行识别。实验表明用该方法检测无线网络系统中的新型入侵者是可行、有效的,检测入侵者的准确率可达到97%。     

一种NURBS曲面拟合精度的量化评测算法

曲面重构是逆向工程中的核心技术之一,由于NURBS曲面在光顺性和局部可编辑等方面所具有的优点,使其成为点云数据自由曲面重构的常见形式。目前对NURBS曲面重构技术的研究上取得了一些成果,但各方法在拟合精度和效果上各有参差,因此有必要对NURBS曲面拟合精度评价算法进行研究。在采用NURBS实现曲面拟合的基础上,对拟合精度的量化指标进行研究,设计了一种基于区域划分的搜索迭代算法,可快速地计算得到原始点云与NURBS曲面的偏差。     

面向数据重构算法

关于磁盘阵列在线重构的研究一直以来都是国内外研究热点。提出面向数据重构算法。面向数据重构算法只对正被使用逻辑块上数据进行重构,而不需对整个磁盘进行数据重构。测试结果说明了面向数据重构算法相对于现有重构方法显著改善了磁盘阵列的重构性能。相对于DOR算法(现在最常用且最有效重构算法之一),面向数据重构算法将重构性能提高了1至2.2倍,并且没有降低重构过程中磁盘阵列服务性能。     

基于Web的家庭安保机器人视频传输的研究与实现

针对家庭安保机器人视频传输问题,在综合比较了几种主流方法的基础上,提出了一种新的基于视频流的方案。对图像进行实时编解码,在保证较好的图像质量的基础上,实现了图像的实时同步,并具有良好的扩展性。实验验证了该方法的先进性与有效性。     

基于ZigBee的多机器人通信系统的设计

为解决多机器人协作的问题,设计了可以让机器人之间基于ZigBee网络进行通信的通信方案。机器人硬件系统中引入了ZigBee节点,多个机器人依赖ZigBee形成一个星型网络,每个机器人可以通过中心节点保持通信。实验结果表明,机器人之间可以可靠地进行通信,能够显著提高机器人的工作效率。     

Makespan minimization for two parallel machines scheduling with a periodic availability constraint

A two parallel machines scheduling problem where one machine is periodically unavailable with the objective of minimizing makespan is considered. It is showed that the worst-case ratio of the classical LPT algorithm and the competitive ratio of the LS algorithm are 3/2 and 2, respectively, for the offline version and the online version of the problem.     

Active disturbance rejection control for high pointing accuracy and rotation speed

This paper presents a design method proposed to design an active disturbance rejection control for the antenna pointing control of a large flexible satellite system. A simplified dynamics model is established using Euler-Lagrange and used to analyze the dynamic stability of the antenna system. The capturing strategy of the antenna is configured and the inner and outer loops of the active disturbance rejection control are then designed to improve pointing accuracy and rotation speed. The design of the active disturbance rejection control is verified through numerical simulation. Simulation results indicate that the proposed method can be used to achieve high pointing accuracy and rotation speed.