一种改进的RAID后台初始化技术

新创建的RAID系统必须要经过初始化才能使磁盘上的随机数据满足一定的校验关系,从而使RAID系统具有数据恢复能力。文章分析了传统RAID系统初始化方案的优缺点,提出了一种改进的后台初始化方案,试验证明该方案能够有效做到初始化与主机IO读写的并行,并在初始化性能和主机IO读写性能上较传统方案有较大的提高。     

基于Struts框架的Web应用研究与实现

Struts是目前Java Web领域使用最广泛的框架,研究了MVC设计模式以及Struts框架中的主要组件。详细描述了将Struts框架应用到实际项目中的过程。实践表明：利用Struts框架可以提高Web开发效率以及系统的可扩展性和维护性。     

基于Agent技术的交通流仿真研究

基于我国当前的交通问题以及传统交通管理系统的特点,在前人的理论基础上,文中将agent技术应用于智能交通系统,运用系统中各个元素进行agent建模。介绍了KQML语言规范并详细探讨了KQML消息机制在agent通信中的应用,在此基础上选择Java编写agent消息类,构建仿真系统。系统在周期边界条件下进行单车道交通流仿真,真实地再现了流量-平均速度、密度-流量之间的关系。仿真结果表明,基于agent的智能交通仿真能够细致地刻画交通流特性和交通实体的微观行为。     

Robust monitoring and fault reconstruction based on variational inference component analysis

Probabilistic models such as probabilistic principal component analysis (PPCA) have recently caught much attention in the process monitoring area. An important issue of the PPCA method is how to determine the dimensionality of the latent variable space. In the present paper, one of the most popular Bayesian type chemometric methods, Bayesian PCA (BPCA) is introduced for process monitoring purpose, which is based on the recent developed variational inference algorithm. In this monitoring framework, the effectiveness of each extracted latent variable can be well reflected by a hyperparameter, upon which the dimensionality of the latent variable space can be automatically determined. Meanwhile, for practical consideration, the developed BPCA-based monitoring method is robust to missing data and can also give satisfactory performance under limited data samples. Another contribution of this paper is due to the proposal of a new fault reconstruction method under the BPCA model structure. Two case studies are provided to evaluate the performance of the proposed method.     

基于维基百科的未登录词译文挖掘

未登录词(out of vocabulary,OOV)的查询翻译是影响跨语言信息检索(cross-language information retrieval,CLIR)性能的关键因素之一.它根据维基百科(Wikipedia)的数据结构和语言特性,将译文环境划分为目标存在环境和目标缺失环境.针对目标缺失环境下的译文挖掘难点,它采用频度变化信息和邻接信息实现候选单元抽取,并建立基于频度-距离模型、表层匹配模板和摘要得分模型的混合译文挖掘策略.实验将基于搜索引擎的未登录词挖掘技术作为baseline,并采用TOP1进行评测.实验验证基于维基百科的混合译文挖掘方法可达到0.6822的译文正确率,相对baseline取得6.98%的改进.     

基于GL Studio的无人机地面站天线控件设计与实现

为了实现良好的人机交互,并对无人机宽带数据链进行实时直观地监控,搭建了基于GL Studio的无人机地面站天线控件,并详细介绍了其设计开发原理和方法.GL Studio生成的地面站控件不仅具有良好的可移植性,而且还可以与多种软件开发平台实现很好的融合.     

Barrier Lyapunov Functions for the control of output-constrained nonlinear systems

In this paper, we present control designs for single-input single-output (SISO) nonlinear systems in strict feedback form with an output constraint. To prevent constraint violation, we employ a Barrier Lyapunov Function, which grows to infinity when its arguments approach some limits. By ensuring boundedness of the Barrier Lyapunov Function in the closed loop, we ensure that those limits are not transgressed. Besides the nominal case where full knowledge of the plant is available, we also tackle scenarios wherein parametric uncertainties are present. Asymptotic tracking is achieved without violation of the constraint, and all closed loop signals remain bounded, under a mild condition on the initial output. Furthermore, we explore the use of an Asymmetric Barrier Lyapunov Function as a generalized approach that relaxes the requirements on the initial conditions. We also compare our control with one that is based on a Quadratic Lyapunov Function, and we show that our control requires less restrictive initial conditions. A numerical example is provided to illustrate the performance of the proposed control.     

Flow simulations in arbitrarily complex cardiovascular anatomies – An unstructured Cartesian grid approach

Image guided computational fluid dynamics is attracting increasing attention as a tool for refining in vivo flow measurements or predicting the outcome of different surgical scenarios. Sharp interface Cartesian/Immersed-Boundary methods constitute an attractive option for handling complex in vivo geometries but their capability to carry out fine-mesh simulations in the branching, multi-vessel configurations typically encountered in cardiovascular anatomies or pulmonary airways has yet to be demonstrated. A major computational challenge stems from the fact that when such a complex geometry is immersed in a rectangular Cartesian box the excessively large number of grid nodes in the exterior of the flow domain imposes an unnecessary burden on both memory and computational overhead of the Cartesian solver without enhancing the numerical resolution in the region of interest. For many anatomies, this added burden could be large enough to render comprehensive mesh refinement studies impossible. To remedy this situation, we recast the original structured Cartesian formulation of Gilmanov and Sotiropoulos [Gilmanov A, Sotiropoulos F. A hybrid Cartesian/immersed boundary method for simulating flows with 3D, geometrically complex, moving bodies. J Comput Phys 2005;207(2):457–92] into an unstructured Cartesian grid layout. This simple yet powerful approach retains the simplicity and computational efficiency of a Cartesian grid solver, while drastically reducing its memory footprint. The method is applied to carry out systematic mesh refinement studies for several internal flow problems ranging in complexity from flow in a 90° pipe bend to flow in an actual, patient-specific anatomy reconstructed from magnetic resonance images. Finally, we tackle the challenging clinical scenario of a single-ventricle patient with severe arterio-venous malformations, seeking to provide a fluid dynamics prospective on a clinical problem and suggestions for procedure improvements. Results from these simulations demonstrate very complex cardiovascular flow dynamics and underscore the need for high-resolution simulations prior to drawing any clinical recommendations.