基于XPath的新闻信息抽取系统设计与实现

随着互联网技术的迅猛发展,因特网成为目前新闻信息最丰富最主要的来源。本文在分析新闻网页的基础上,分析了目前现有的信息抽取技术和XML技术,提出了一个基于XML技术的Web新闻抽取系统。本文主要是充分运用XML中的XPath技术在数据定位方面的优势,并提出一种基于DOM树的XPath生成算法,使用XSLT语言用于描述抽取规则,并使用路径表达式XPath定位待抽取的信息点。     

Generation of GHZ states with invariant-based shortcuts

A scheme is proposed to generate three-atom GHZ states by applying the inversely engineered control method on the basis of Lewis–Riesenfeld invariants. In the proposal, three atoms that have different configurations are trapped in a bimodal cavity. Numerical simulations indicate that our protocol has an obvious improvement of speed for the generation of GHZ states. Moreover, the present scheme is robust against both parameter fluctuations and dissipation.     

IaaSMon: Monitoring Architecture for Public Cloud Computing Data Centers

Monitoring of cloud computing infrastructures is an imperative necessity for cloud providers and administrators to analyze, optimize and discover what is happening in their own infrastructures. Current monitoring solutions do not fit well for this purpose mainly due to the incredible set of new requirements imposed by the particular requirements associated to cloud infrastructures. This paper describes in detail the main reasons why current monitoring solutions do not work well. Also, it provides an innovative monitoring architecture that enables the monitoring of the physical and virtual machines available within a cloud infrastructure in a non-invasive and transparent way making it suitable not only for private cloud computing but also for public cloud computing infrastructures. This architecture has been validated by means of a prototype integrating an existing enterprise-class monitoring solution, Nagios, with the control and data planes of OpenStack, a well-known stack for cloud infrastructures. As a result, our new monitoring architecture is able to extend the exiting Nagios functionalities to fit in the monitoring of cloud infrastructures. The proposed architecture has been designed, implemented and released as open source to the scientific community. The proposal has also been empirically validated in a production-level cloud computing infrastructure running a test bed with up to 128 VMs where overhead and responsiveness has been carefully analyzed.     

基于B/S结构的考勤系统设计

在分析考勤系统需求的基础上,结合实际学生考勤信息录入与汇总的特点,设计了基于B/S结构的课堂考勤系统。应用该系统可方便地进行学生考勤信息的录入、修改与管理,并可进行考勤信息的自动汇总。系统依据权限实现了角色分类,可按角色登录及查询具体的考勤信息,并可进行学生考勤信息的汇总和导出,提高了工作效率。     

卷扬式启闭机闸门闭落困难对策分析

水工闸门主要是用来泄水和挡水的,所以,需要经常开启和关闭闸门。对于螺杆式启闭机,严格按照规范操作正常操作闸门是不会出现问题的;对于卷扬式启闭机,虽然绳索可以传递拉力,但是,对压力完全没有影响。针对卷扬式启闭机闸门闭落困难的问题,积极采取有效的对策,确保卷扬式启闭机闸门可以正常闭落。简要分析了卷扬式启闭机闸门闭落困难的情况,阐述了相关的解决对策。     

Real time motion estimation using a neural architecture implemented on GPUs

This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of global and local motion and the representation of deformable objects. This architecture also avoids the problem of finding corresponding features while tracking moving objects. Due to the parallel nature of neural networks, the architecture has been implemented on GPUs that allows the system to meet a set of requirements such as: time constraints management, robustness, high processing speed and re-configurability. Experiments are presented that demonstrate the validity of our architecture to solve problems of mobile agents tracking and motion analysis.     

基于拉普拉斯分值和超球支持向量机的轴承故障诊断方法设计

针对轴承振动信号中的故障信息往往很微弱,同时振动样本数据分布不平衡即故障样本占总样本数的比例低,从而导致故障诊断模型训练不精确而影响诊断精度的问题,提出了一种基于拉普拉斯分值和超球大间隔支持向量机的故障诊断方法;首先,采用有标签的训练样本数据和拉普拉斯分值法提取原始振动信号中的微弱故障信息,并降低其数据维数,从而得到用于故障诊断的特征向量,然后设计了一种改进的超球大间隔支持向量机的故障诊断模型,通过最小化超球体积和最大化超球边界和故障样本之间的间隔来实现故障诊断,以解决样本的不均衡问题,最终通过将测试样本数据代入决策方程并通过投票机制确定其故障类别;在Matlab环境下对轴承故障诊断进行实验,实验结果证明了文中方法能有效解决样本的不均衡情况下的故障诊断,且相对其它方法,具有诊断精度高和收敛速度快的优点.     

Optimizing content placement in a peer-assisted VoD architecture

Recently, a new peer-assisted architecture to build content delivery systems has been presented. This architecture is based on the use of the storage capacity of end-users’ set-top boxes (STBs), connected in a peer-to-peer (P2P) manner in order to help the content servers in the delivery process. In these systems, the contents are usually split into a set of smaller pieces, called sub-streams, which are randomly injected at the STBs. The present paper is focused on Video on Demand (VoD) streaming and it is assumed that the STB-based content delivery system is deployed over the global Internet, where the clients are distributed over different ISP networks. In this scenario, three different strategies are studied for increasing the percentage of data uploaded by peers, in order to offload the content servers as much as possible. First of all, a new mechanism is presented which determines which sub-stream has to be placed at which STB by a Non-Linear Programming (NLP) formulation. A different strategy for reducing the content server load is to take advantage of the available bandwidth in the different ISP networks. In this sense, two new mechanisms for forwarding the VoD requests to different ISP networks are presented. Finally, the present paper also shows that in some situations the available uplink bandwidth is associated with STBs that do not have the required sub-streams. Regarding this concern, a new mechanism has been designed that dynamically re-allocates some streams, which are being transmitted from specific STBs, to different STBs, in order to find the necessary resources to start new streaming sessions.