一种基于Ajax的爬虫模型的设计与实现

Ajax技术给传统的爬虫带来了巨大的挑战,为了能够提取出在Ajax程序中隐藏的WEB资源,需要解决两大关键问题：JavaScript脚本解析和每一次脚本事件触发后的页面状态信息的保存。提出一种适合Ajax的爬虫模型,在模型中设计了一个嵌入的脚本解析引擎和使用了有向状态图,有效地解决了上述的两个关键问题。实验结果显示该爬虫模型能够有效地提取出Ajax程序中的隐藏资源。     

分布式系统多星故障诊断任务调度结构研究

多星故障诊断任务调度模型是构建多星任务调度系统的基础,提出分布式的多星故障诊断调度模型,将调度功能分为三个模块——监控模块、任务调度模块和服务器模块。将这些模块结合起来,便于实现多星的故障诊断,便于系统扩展、维护。以多星故障诊断任务调度的禁忌搜索算法为例,分析各模块之间的关系,为未来多星故障诊断任务划分提供了有力支撑。     

ECM-based maximum likelihood inference for multivariate linear mixed models with autoregressive errors

For the analysis of longitudinal data with multiple characteristics, we are devoted to providing additional tools for multivariate linear mixed models in which the errors are assumed to be serially correlated according to an autoregressive process. We present a computationally flexible ECM procedure for obtaining the maximum likelihood estimates of model parameters. A score test statistic for testing the existence of autocorrelation among within-subject errors of each characteristic is derived. The techniques for the estimation of random effects and the prediction of further responses given past repeated measures are also investigated. The methodology is illustrated through an application to a set of AIDS data and two small simulation studies.     

Sentiment-oriented contextual advertising

Web advertising (Online advertising), a form of advertising that uses the World Wide Web to attract customers, has become one of the world’s most important marketing channels. This paper addresses the mechanism of Content-based advertising (Contextual advertising), which refers to the assignment of relevant ads to a generic web page, e.g., a blog post. As blogs become a platform for expressing personal opinion, they naturally contain various kinds of expressions, including both facts and comments of both a positive and negative nature. Besides, in line with the major tenet of Web 2.0 (i.e., user-centric), we believe that the web-site owners would be willing to be in charge of the ads which are positively related to their contents. Hence, in this paper, we propose the utilization of sentiment detection to improve Web-based contextual advertising. The proposed sentiment-oriented contextual advertising (SOCA) framework aims to combine contextual advertising matching with sentiment analysis to select ads that are related to the positive (and neutral) aspects of a blog and rank them according to their relevance. We experimentally validate our approach using a set of data that includes both real ads and actual blog pages. The results indicate that our proposed method can effectively identify those ads that are positively correlated with the given blog pages.     

改进的乘积合并接收机部分频带抗干扰性能分析

乘积合并接收机以其简单有效的特性在快速跳频通信系统中得到了广泛关注。对于实际应用中普遍遇到的非最坏部分频带干扰环境,传统乘积合并算法有其自身的不足。针对这种情况,提出了一种改进的乘积合并方法,它保留了传统乘积合并算法的主要特征,通过增加对各跳频信号能量差异的检测信息,改善了传统乘积合并接收机在部分频带干扰下的传输性能,仿真验证了这种改进合并方法的有效性。     

Dynamically modulated intensity interrogation scheme using waveguide coupled surface plasmon resonance sensors

An electro-optically modulated intensity interrogation method based on tunable waveguide coupled surface plasmon resonance sensors has been proposed. It has been theoretically and experimentally demonstrated that the proposed scheme can enable sensitive measurement of measurand variations. By modulating the refractive index in the waveguide layer, this interrogation method yields modulated signal whose amplitude is related to measurand's refractive index. This amplitude modulated signal offers a higher signal to noise ratio and eliminates additive noise in the sensor system. A preliminary investigation using saline buffers with different NaCl concentrations shows a resolution of 2.3 × 10^?6 refractive index unit by our approach. Resolution can be controlled by the amplitude of the applied modulation voltage and can be further enhanced by optimizing the device structure or improving the electro-optical (E-O) coefficient of the E-O material. This approach is simple, stable, and promising for low-cost or multi-channel SPR biosensor applications.     

针对低轮PRESENT的代数攻击

基于MiniSAT 2.0软件,研究对低轮PRESENT的代数攻击问题。提出将S盒表示为单项式个数较少的无冗余等效方程组的方法,将PRESENT的S盒表示为由14个单项式个数均≤6的8元布尔方程构成的等效方程组,并基于不同的已知明文量,利用MiniSAT软件对PRESENT进行代数攻击实验,获得了较好的攻击效果。实验表明,在已知明文条件下可以在121 h内求出80 bit密钥的5轮PRESENT的全部密钥比特,在选择明文条件下可以在203 h内求出6轮PRESENT的全部密钥比特。     

基于优化目标可调控的免疫网络算法的分析与应用

针对目前几种免疫网络模型在数据聚类方面应用的一些不足,在aiNet免疫算法的基础上结合函数优化的思想提出一种基于目标可调控的免疫模型。并在算法中给出目标控制函数,和细胞记忆库的概念。本算法提高了免疫学习质量并从整体上对免疫网络进行优化。     

面向构件接口变异的模型检验技术研究

随着构件技术在软件开发中的广泛应用,人们对构件化软件系统质量的要求也在不断提高。该文运用模型检验技术进行接口变异测试的相关研究工作。该文首先详细介绍了基于模型检验技术的变异测试的基本原理,随后通过对构件集成时接口之间的交互关系进行分析后,提出了通过构造接口函数调用关系模型进行基于模型检验的接口变异测试方法。最后,通过实例进行了对JavaBean构件的接口测试用例的自动生成。     

Robust Feature-Preserving Mesh Denoising Based on Consistent Subneighborhoods

In this paper, we introduce a feature-preserving denoising algorithm. It is built on the premise that the underlying surface of a noisy mesh is piecewise smooth, and a sharp feature lies on the intersection of multiple smooth surface regions. A vertex close to a sharp feature is likely to have a neighborhood that includes distinct smooth segments. By defining the consistent subneighborhood as the segment whose geometry and normal orientation most consistent with those of the vertex, we can completely remove the influence from neighbors lying on other segments during denoising. Our method identifies piecewise smooth subneighborhoods using a robust density-based clustering algorithm based on shared nearest neighbors. In our method, we obtain an initial estimate of vertex normals and curvature tensors by robustly fitting a local quadric model. An anisotropic filter based on optimal estimation theory is further applied to smooth the normal field and the curvature tensor field. This is followed by second-order bilateral filtering, which better preserves curvature details and alleviates volume shrinkage during denoising. The support of these filters is defined by the consistent subneighborhood of a vertex. We have applied this algorithm to both generic and CAD models, and sharp features, such as edges and corners, are very well preserved.