一种基于Java的ODS与Excel数据交换方法

Microsoft Excel文档是ODS(Operational Data Store,操作型数据仓)的重要数据来源,同时ODS中的数据也需要按照Excel文件格式输出,而Excel的专有文件格式使其与ODS进行数据交换时存在一定困难.在分析Excel文件结构和Jakarta POI-HSSF (Poor Obfuscation Implementation ＆ Horrible Spread Sheet Format)功能基础上,详细描述了基于Java的Excel文档与ODS之间进行数据交换的方法,并介绍了实际实现过程中应注意的事项.     

基于VC＋＋6．0的浮选泡沫图像识别系统

浮选生产过程涉及许多变量以及存在严重的非线性,很难建立精确的数学模型,它的监控一直是困扰控制技术人员的难题。文中设计开发了一个用于选厂自动控制的浮选泡沫图像识别系统，并给出该系统VisualC 6．0的部分实现。利用该系统可以计算浮选泡沫图像的一些物理参数，通过这些物理参数以及浮选泡沫图像识别实验可以建立一定的数学模型，再通过这些数学模型可以精确预测浮选过程的工艺技术指标,从而为选厂过程的在线控制提供可靠数据依据。     

Validating and Scaling the MicroGrid: A Scientific Instrument for Grid Dynamics

Large-scale Grids that aggregate and share resources over wide-area networks present major challenges in understanding dynamic application and resource behavior for performance, stability, and reliability. Accurate study of the dynamic behavior of applications, middleware, resources, and networks depends on coordinated and accurate modeling of all four of these elements simultaneously. We have designed and implemented a tool called the MicroGrid which enables accurate and comprehensive study of the dynamic interaction of applications, middleware, resource, and networks. The MicroGrid creates a virtual Grid environment – accurately modeling networks, resources, the information services (resource and network metadata) transparently. Thus, the MicroGrid enables users, Grid researchers, or Grid operators to study arbitrary collections of resources and networks. The MicroGrid includes the MaSSF online network simulator which provides packet-level accurate, but scalable network modeling. We present experimental results with applications which validate the implementation of the MicroGrid, showing that it not only runs real Grid applications and middleware, but that it accurately models both their and underlying resource and network behavior. We also study a range of techniques for scaling a critical part of the online network simulator to the simulation of large networks. These techniques employ a sophisticated graph partitioner, and a range of edge and node weighting schemes exploiting a range of static network and dynamic application information. The best of these, profile-driven placement, scales well to online simulation of large networks of 6,000 nodes using 24 simulation engine nodes.     

Sampling period scheduling of networked control systems with multiple-control loops

This paper addresses the sampling period scheduling of Networked Control Systems (NCSs) with multiple control loops. The generalized exponential function is employed to describe Integral Absolute Error (IAE) performance versus sampling period by Truetime toolbox under Matlab environment, and the sampling periods are scheduled to obtain the optimal integrated performance based on Kuhn–Tucker Theorem, which are subject to the stability of every control loop and the bandwidth on available network resource. Numerical examples are given to show the effectiveness of our method.     

Adaptive finite‐time control for nonlinear teleoperation systems with asymmetric time‐varying delays

This paper addresses the adaptive finite‐time control problem of nonlinear teleoperation system in the presence of asymmetric time‐varying delays. To achieve the finite‐time position tracking, a novel adaptive finite‐time coordination algorithm based on subsystem decomposition is developed. By introducing a switching‐technique‐based error filtering into our design framework, the complete closed‐loop master (slave) teleoperation system is modeled as a special class of switched system, which is composed of two subsystems. To analyze such system, a finite‐time state‐independent input‐to‐output stability criterion is first developed for some normal switched nonlinear delayed systems. Then based on the classical Lyapunov–Krasovskii method, the stability of complete closed‐loop systems is obtained. It is shown that the proposed scheme can make the position errors converge into a deterministic domain in finite time when the robots continuously contact with human operator and/or the environment in the presence of asymmetric time‐varying delays. Finally, the simulation results are given to demonstrate the effectiveness. Copyright © 2015 John Wiley & Sons, Ltd.     

一个半监督的中文事件抽取方法

半监督或无监督的事件抽取方法在目前依旧是一个具有挑战性的课题。针对中文本身在表述中存在的固有特点,该文提出一种基于双视图的事件抽取自举学习方法。该方法以少量种子为基础,从文档相关度与语义相似度两个视图出发,进行交互过滤筛选,不断抽取新的有效事件模板,为事件抽取服务。在ACE2005中文语料上的测试表明,和现有方法相比,该方法可以有效地提高中文信息事件抽取系统的性能。     

基于形态学属性剖面的高光谱影像集成分类

传统高光谱遥感影像逐像素分类方法未考虑像元之间的空间关联性且泛化性能较低。形态学属性剖面是表征影像空间结构的有效方法,同时集成学习可显著提升分类算法的泛化能力。为了在高光谱影像分类中充分利用影像的空间信息并提高分类的稳定性,提出一种基于形态学属性剖面高光谱遥感影像集成学习分类方法。首先,用主成分分析和最小噪声变换进行特征提取,并借助形态学属性剖面获取影像的多重空间特征;然后用极限学习和支持向量机的方法进行分类;最后将多个分类结果以多数投票的方式集成。区别于已有集成学习方法,综合考虑了不同特征提取和不同分类方法的联合集成,并将形态学属性剖面引入其中以充分利用影像的空间信息。采用AVIRIS和ROSIS两组高光谱数据检验该方法的分类性能,实验结果表明该方法可获得高精度和高稳定性的分类结果,总体精度分别达到83.41%和95.14%。     

基于TTCN的测试序列选择技术研究

测试序列选择技术一直是协议测试领域中一个研究热点,本文对此技术进行了深入地探讨,建立了测试集动态关系模型,并以此为基础邮综合静态选择和动态选择的一种实现方案。     

参数化设计中的对象约束模型及反向约束的研究

应用图论方法,建立了基于有向超图的对象约束模型,提出了压缩十字链表形式的网状存储结构,能够完整,准确地记录设计者的设计意图,实现尺寸及参数驱动图形的功能清晰地表示约束间的双向约束关系,有效地实现了约束的传播与救解,其完备的表不方式可方便地实现反向约束求解。同时利用面向对象技术,高效地实现了实体及约束建模,采用相应的类层次结构,充分发挥对象的封装性和扩展性,提出了一种方便灵活的参数化设计方法。     

突现（emergence）———系统研究的新观念

当系统科学的研究重点从系统的物质结构转变到有关系统的信息特征和功能特征的探讨以后,“突现”这种新观念就成了系统科学研究的中心课题。在复杂性科学的推动下,这种观念给一些领域带来巨大变化。大型计算机的出现与利用为这种研究提供了最恰当的工具和新的实验性,但在以解决实际问题为出发点和目标的开放的复杂巨系统的研究中,还需要新的方法论“从定性到定量的综合集成法”的补充和扩展,人机结合的大成智慧是这类研究的有效