U盘实时监控系统的研究与开发

该文主要介绍如何用VB实现U盘实时监控系统,并给出了实现的关键代码。     

森林火灾无线监测预警系统的设计与实现

针对传统森林火灾监测措施实时性差、实际应用受限的问题,利用无线传感网络技术,构建了基于ZigBee和GPRS的森林火灾监测预警系统.介绍了系统的结构,给出了主要功能模块的硬件设计方法和ZigBee无线传感网络中各功能节点的软件设计.同时,对传统的无线传感网的自组网方案进行了改进,并在分布式组网方案基础上实现了ZigBee无线传感网络节点的分簇置放.实践证明,该系统实现了森林火灾监测和预警的功能,提高了系统中数据传输的实时性、可靠性以及系统的可扩展性.     

涉密文档违规处理系统在保密部门的应用

计算机网络技术的高速发展大幅提高了人们的工作效率和信息获取量,但是提供便利的同时也隐藏着安全隐患。各地保密部门始终高度重视涉密文件、机密数据及个人隐私的安全防护,以防患于未然。因此针对堵截涉密信息泄露扩散的最佳时机研制出监测涉密文档监控系统。系统可通过安装在外网客户端上的监控程序,对客户机上文档的编辑工作进行监控,将编辑的文档标题自动发送给监视控制台或保密局等主管单位,并对编辑的文档自动进行涉密分析,一旦发现该文档可能包含有涉密信息,即刻屏蔽该机的网络连接,并立即报警。     

基于DDE的组态王6．0与MATLAB数据通信在过程控制中的应用

为了充分发挥组态王6．0可视化界面功能与MATLAB强大的数值分析和图形绘制功能的各自优势,利用DDE技术,实现了组态王6．0与MATLAB的通信,开发了一种过程控制实验装置的实时监控系统。该监控系统具有实时监测、控制系统分析、控制系统设计等功能。应用实践表明,该实时监控系统运行可靠,操作方便,而且使得实时监控功能更加强大和灵活。     

GNSS系统接收机自主完好性监测算法

提出一种适用于多星座情况的接收机自主完好性监测算法——基于完好性指标动态分配的完好性监测算法。该算法比传统算法更能适应多星座情况下不同星座观测量属性的差异,其可用性比传统算法提高2％～3％。在多星座和双频情况下,利用该算法分析完好性监测的性能,结果表明,该算法在LPV-200完好性要求下是适用的。     

基于消息顺序图和Petri网的移动应用监测平台建模分析

随着移动互联网的迅猛发展,移动应用的数量呈现井喷式的爆发,对其性能、故障和短板进行实时、有效的监测与分析是保证系统正常运行的关键。统一建模语言(Unified Modeling Language,UML)作为一种功能较强的面向对象的图形建模工具,可以对移动应用监测平台进行建模分析,但在其过程描述中缺乏严格的语义。Petri网作为一种离散事件动态系统的建模和分析方法,提供了在逻辑时序下研究系统特性和性能的有效手段,并具有图形方法的直观性和逻辑方法的概括性。通过将基于UML消息顺序图和Petri网的建模方法应用到移动应用监测平台的分析过程中,针对用户下发的监测任务构建系统的消息顺序图和Petri网模型,利用消息顺序图对平台各对象之间在时间顺序上的交互关系进行了验证,并利用Petri网化简规则和状态方程对该模型进行了结构上的正确性验证和可达性分析。     

Reconfiguring existing pollutant monitoring stations by increasing the value of the gathered information

The objective of this study is to provide a framework for relocating or reconfiguring existing pollution monitoring station networks by using feature selection and data mining techniques. This methodology enables a partial redesign based on the maximization of the available information that is gathered by the pollution networks by the optimal data mining technique. It also considers requirements of the decision makers, like potential target places, etc.Since this methodology is based on the quality of forecasting, it can also be useful for auditing and forecasting. A case study is included in this paper. In light of the prediction results, a new way to relocate the existing monitoring station is proposed.     

Repeated detection of conjunctive predicates in distributed executions

Given a conjunctive predicate ? over a distributed execution, this paper gives an algorithm to detect all interval sets, each interval set containing one interval per process, in which the local values satisfy the Definitely(?) modality. The time complexity of the algorithm is O(n³p), where n is the number of processes and p is the bound on the number of times a local predicate becomes true at any process. The paper also proves that unlike the Possibly(?) modality which admits O(pn) solution interval sets, the Definitely(?) modality admits O(np) solution interval sets. The paper also gives an on-line test to determine whether all solution interval sets can be detected in polynomial time under arbitrary fine-grained causality-based modality specifications.     

Mapping wildfire and clearcut harvest disturbances in boreal forests with Landsat time series data

Information regarding the extent, timing and magnitude of forest disturbance are key inputs required for accurate estimation of the terrestrial carbon balance. Equally important for studying carbon dynamics is the ability to distinguish the cause or type of forest disturbance occurring on the landscape. Wildfire and timber harvesting are common disturbances occurring in boreal forests, with each having differing carbon consequences (i.e., biomass removed, recovery rates). Development of methods to not only map, but distinguish these types of disturbance with satellite data will depend upon an improved understanding of their distinctive spectral properties. In this study, we mapped wildfires and clearcut harvests occurring in a Landsat time series (LTS) acquired in the boreal plains of Saskatchewan, Canada. This highly accurate reference map (kappa = 0.91) depicting the year and cause of historical disturbances was used to determine the spectral and temporal properties needed to accurately classify fire and clearcut disturbances. The results showed that spectral data from the short-wave infrared (SWIR; e.g., Landsat band 5) portion of the electromagnetic spectrum was most effective at separating fires and clearcut harvests possibly due to differences in structure, shadowing, and amounts of exposed soil left behind by the two disturbance types. Although SWIR data acquired 1 year after disturbance enabled the most accurate discrimination of fires and clearcut harvests, good separation (e.g., kappa ≥ 0.80) could still be achieved with Landsat band 5 and other SWIR-based indices 3 to 4 years after disturbance. Conversely, minimal disturbance responses in near infrared-based indices associated with green leaf area (e.g., NDVI) led to unreliably low classification accuracies regardless of time since disturbance. In addition to exploring the spectral and temporal manifestation of forest disturbance types, we also demonstrate how Landsat change maps which attribute cause of disturbance can be used to help elucidate the social, ecological and carbon consequences associated with wildfire and clearcut harvesting in Canadian boreal forests.     

基于免疫网络的异态电磁信号监测模型

针对人工免疫系统运用于信号密度适中的日常异态信号监测时,系统对检测器数量要求过高的问题,本文对现有的模型进行了改进,提出了基于免疫网络的异态电磁信号监测模型。模型引入数据正向压缩和检测器相互抑制的机制,使得系统对检测器数量的要求明显降低。本文采用实际无线电监测数据对模型进行了检验,并与基于阴性选择的模型进行对比,验证了该模型在信号密度适中的日常监测中可大幅减少对检测器数量的要求,提高了监测效率。