应用于UHF RFID标签的低功耗真随机数发生器

设计了一种基于振荡采样法的真随机数发生器.针对UHF RFID标签芯片功耗低、面积小的特点,利用简单有效的电路结构增强发生器的随机性.采用频率受控的被采样数据振荡器与采样时钟异或后形成初步随机数,并增加异或链输出负反馈结构,有效提高了输出序列中"0""1"分布的均匀性,降低了序列的自相关性.标签采用SMIC 0.18μm RF CMOS工艺设计并流片,采样时钟为2MHz,总工作电流少于2μA.     

“模拟电子电路”课程教学改革思考

本文就＂模拟电子电路＂课程教学中计算机辅助教学、授课安排以及实验教学三个方面的问题进行分析。我们提出使用3D电路图的方法增强学生对电路的感性认识,在授课安排中穿插介绍电子元器件基本知识以及使用范围,提升学生的工程意识;我们在＂模拟电子电路＂课程实验环节引入＂虚拟公司＂形式,以强调真实环境和真实压力,以问题为向导和任务为导向的方法有效地提高学生在电路设计中的自学意识、成本意识和在工作中的协同能力。     

结构健康监测无线传感网络同步采集研究

无线传感网络时间同步和同步采集预同步后,采用物理初始化相对(Physical time,Initialize time,Relative time,PIR)时间分离法,以及时间戳和数据包序号相结合的数据包结构,并对时间信息建立柔性优化模型。该同步采集方法可获取准确的时间信息,具有适用高频采集和低功耗的特点,保障了结构健康监测中同步采集时间信息和场域诊断的可靠性。     

基于虚拟仿真技术的航空发动机油封模拟系统

我军航空发动机油封工作中存在的问题阻碍了航空发动机油封技术的训练。为解决该问题,开发了一套航空发动机油封模拟系统。它利用虚拟仿真技术模拟航空发动机油封操作过程,是一种集油封虚拟训练和考核评价于一体、经济实用的现代化教学手段。根据航空发动机油封操作规程,系统功能设计包括引导提示、油封仿真、考核评价三个模块,油封仿真是核心,它包括视景仿真、运动仿真、音响仿真、操作仿真四个子功能,能够提供等同于实操,甚至更好的训练效果,具有重大的经济效益和军事效益。     

一种门式起重机安全监测传感器布设方法

近年来,起重机事故频发,对起重机进行长期、实时安全监测已是大势所趋,设计合理的传感器布设点是保证整个监测系统可靠性的关键所在。提出了基于虚拟仿真技术的传感器布设点选取方法,并以1台L型门式起重机为例系统的阐述了其实现过程。建立虚拟样机,利用有限元分析考察其在典型工况下应力分布,确定应力较大点为传感器的布点位置。通过应变测试进行验证,仿真结果与实际测试结果吻合,证明了此方法是可行的。     

半导体混合加工制程的虚拟量测方法

为提高经济效应,半导体加工制程变得越来越复杂,生产线上同时有不同规格的产品在混合加工,能够同时预测这些规格晶圆的最终品质对提高晶圆的生产良率有着重要的意义。本文针对这种混合制程,提出一种虚拟量测算法,在统计回归的基础上,找出影响制程的关键变量,考虑不同规格晶圆的产品效应,利用共变异数分析算法辨识出虚拟量测模型,线上测试结果表明,本文算法不仅可以精确的预测待加工晶圆的线宽,而且可以用于半导体加工制程晶圆的故障侦测。     

虚拟光栅的可视化生成软件设计

基于结构光照明的主动三维测量技术由于具有快速、非接触、高精度、易于实现自动化等测量特点,日益受到人们的重视。文中依据正弦光栅、Ronchi光栅的物理模型,在计算机可视化软件平台上实现对光栅的图像仿真及功能变换,包括光栅类型的选择、光栅密度的设定、对比度的设定、占空比的设定、红绿双频显示、相位移动、正交光栅、混合光栅的生成以及在光栅上添加标记。该软件交互性强,结果直观,操作简单,可应用于日常教学及三维测量技术中虚拟光栅的生成,从而取代实际光栅的使用不便。     

Autocorrelation of two Legendre-Sidelnikov sequences

Sequences with nice pseudo-randomness play an important role in not only communication system but also cryptography system. Based on the Legendre-Sidelnikov sequence, a modified Legendre-Sidelnikov sequence was introduced. The exact value of the autocorrelation function was derived by strict computation. According to the values of the autocorrelation functions of the two Legendre-Sidelnikov sequences, it is proven that both of them have perfect pseudo-randomness. Furthermore, a detailed comparison between autocorrelation functions of the two Legendre-Sidelnikov sequences was deduced. It indicates that no matter which parameters are chosen, the modified sequence has pseudo-randomness as good as the primitive sequence, which is of great significance for applications.     

Framework for distributed autonomic self‐healing in fixed IPv6 networks

A main requirement for the Future Internet is to enable self‐management behaviors facilitating the network to adapt to changing conditions and self‐heal in the face of erroneous states. On the basis of Autonomic Fault‐Management principles, this paper proposes a framework consisting of a set of components operating inside the network elements and allowing the devices to collaboratively realize self‐healing. In that context, Autonomic Fault‐Management is intuitively constituted by the detection of the presence of faulty conditions, followed in turn by the self‐diagnosis and identification of the corresponding root causes, and completed consequently by the removal of the identified root causes and their effects. The proposed framework implements a distributed control loop that interacts with the network operations personnel in case the current erroneous state is not resolvable by means of Autonomic Fault‐Management. We argue that there are a number of mutual benefits between our proposed framework and the IPv6 protocol suite. This is demonstrated by a case study that illustrates these benefits and shows how the capabilities of IPv6 can be enhanced through the self‐healing mechanisms of the proposed framework. Finally, the prototype implementation used for the case study is analyzed in terms of scalability and overhead produced in the network nodes. Copyright © 2013 John Wiley & Sons, Ltd.     

Symbiotic Dynamic Memory Balancing for Virtual Machines in Smart TV Systems

Smart TV is expected to bring cloud services based on virtualization technologies to the home environment with hardware and software support. Although most physical resources can be shared among virtual machines (VMs) using a time sharing approach, allocating the proper amount of memory to VMs is still challenging. In this paper, we propose a novel mechanism to dynamically balance the memory allocation among VMs in virtualized Smart TV systems. In contrast to previous studies, where a virtual machine monitor (VMM) is solely responsible for estimating the working set size, our mechanism is symbiotic. Each VM periodically reports its memory usage pattern to the VMM. The VMM then predicts the future memory demand of each VM and rebalances the memory allocation among the VMs when necessary. Experimental results show that our mechanism improves performance by up to 18.28 times and reduces expensive memory swapping by up to 99.73% with negligible overheads (0.05% on average).