Decomposition of first-order hybrid Petri nets for hierarchical control of manufacturing systems

Although hybrid Petri net (HPN) is a popular formalism in modelling hybrid production systems, the HPN model of large scale systems gets substantially complicated for analysis and control due to large dimensionality of such systems. To overcome this problem, a typical approach is to decompose the net into subnets and then control the plant through hierarchical or decentralized structures. Although this concept has been widely discussed in the literature for discrete PNs, there is a lack of research for HPNs. In this paper, a new method of decomposition of first-order hybrid Petri nets (FOHPNs) is proposed first and then the hierarchical control of the subnets through a coordinator is introduced. The advantage of using the proposed approach is validated by an existing example. A sugar milling case study is analysed by using a decomposed FOHPN model and the optimization results are compared against the results of the approaches presented in other papers. Simulation results show not only an improvement in production rate, but also show the ability to control the plant online. In addition, by using the hierarchical control structure for an FOHPN model, it is possible to reduce the cost of communication links, improve the reliability of the system, maintain the plant locally, and partially redesign the system.     

Evolutionary collective behavior decomposition model for time series data mining

In this research, we propose a novel framework referred to as collective game behavior decomposition where complex collective behavior is assumed to be generated by aggregation of several groups of agents following different strategies and complexity emerges from collaboration and competition of individuals. The strategy of an agent is modeled by certain simple game theory models with limited information. Genetic algorithms are used to obtain the optimal collective behavior decomposition based on history data. The trained model can be used for collective behavior prediction. For modeling individual behavior, two simple games, the minority game and mixed game are investigated in experiments on the real-world stock prices and foreign-exchange rate. Experimental results are presented to show the effectiveness of the new proposed model.     

A case-deletion diagnostic for penalized calibration estimators and BLUP under linear mixed models in survey sampling

The penalized calibration technique in survey sampling combines usual calibration and soft calibration by introducing a penalty term. Certain relevant estimates in survey sampling can be considered as penalized calibration estimates obtained as particular cases from an optimization problem with a common basic structure. In this framework, a case deletion diagnostic is proposed for a class of penalized calibration estimators including both design-based and model-based estimators. The diagnostic compares finite population parameter estimates and can be calculated from quantities related to the full data set. The resulting diagnostic is a function of the residual and leverage, as other diagnostics in regression models, and of the calibration weight, a singular feature in survey sampling. Moreover, a particular case, which includes the basic unit level model for small area estimation, is considered. Both a real and an artificial example are included to illustrate the diagnostic proposed. The results obtained clearly show that the proposed diagnostic depends on the calibration and soft-calibration variables, on the penalization term, as well as on the parameter to estimate.     

The implementation of a smartphone-based fall detection system using a high-level fuzzy Petri net

The falling down problem has become one of the very important issues of global public health in an aging society. The specific equipment was adopted as the detection device of falling-down in the early studies, but it is inconvenient for the elderly and difficult for future application. The smart phone more commonly used than the specific fall detection equipment is selected as a mobile device for human fall detection, and a fall detection algorithm is developed for this purpose. What the user has to do is to put the smart phone in his/her thigh pocket for falling down detection. The signals detected by the tri-axial G-sensor are converted into signal vector magnitudes as the basis of detecting a human body in a stalling condition. The Z-axis data sets are captured for identification of human body inclination and the occurrence frequencies at the peak of the area of use are used as the input parameters. A high-level fuzzy Petri net is used for the analysis and the development of identifying human actions, including normal action, exercising, and falling down. The results of this study can be used in the relevant equipments or in the field of home nursing.     

运动会新闻发布系统的设计与实现

针对运动会比赛期间随时需要方便、快捷、高效地更新大量新闻的需求 ,研制和开发一套运动会新闻发布系统。利用微软最新推出的asp .net动态网页开发工具 ,采用web分布式三层设计模型设计实现了一套操作简单、功能完善、具有通用性的运动会新闻发布系统     

基于USB总线的虚拟频谱分析仪设计

文章详细介绍了基于USB总线的虚拟频谱分析仪的设计过程。该仪器使用嵌入式混合处理器MC56F8323来实现动态信号的实时采集、频谱分析和数字滤波等功能。处理结果由USB2．0接口芯片CY7C68013上传至PC机．以完成数据显示、存储、绘制图形等功能。其中，CY7C68013工作于Slave FIFO模式，以实现与MC56F8323间的数据传输。该系统可同时对两路动态信号进行实时谱分析，每路采样频率高选500kHz。     

织金县HFC双向网络设计方案

织金电视台通过对有线电视网络进行双向改造，为Internet宽带接入、数字电视、VOD等多媒体应用提供了运行平台，介绍织金县城区HFC双向网络设计方案。     

协同作战能力简析

协同作战能力(CEC)是一种充分利用网络技术的新型海岸防空技术，给系统的作战能力带来了革命性的交破。本文对协同作战能力的产生、功能、组成以及未来的发展趋势作了详细的介绍，阐述了CEC系统的总体设计思想。在此基础上，将CEC系统与传统的作战系统的性能和设计思想在各方面进行了比较，交出了CEC系统各方面的优越性能。协同作战能力是现代和未来作战系统的发展方向，CEC系统的发展必将成为衡量各国国防科技现代化的重要指标。     

分布式光纤拉曼放大器的增益平坦设计

介绍了在波分复用（WDM）系统中分布式光纤拉曼放大器（FRA）的理论分析模型。在此基础上，对增益平坦设计所需考虑的因素进行了分析；最后通过试验证明了它的有效性。     

网络管理中事件关联检测机制的研究

网络事件的关联检测是网络管理需要解决的一个关键问题,本文根据分布式网络管理的特点,首次明确定义了网络事件的基本关联关系,在此基础上提出了一种基于Petri Net的事件关联检测机制,实现了基于事件内容的细粒度关联检测,并且在事件检测中充分考虑了时间因素,有效地提高了事件关联检测的准确性。