一种高方向灵敏度光纤F-P超声传感系统设计研究

针对光纤F-P超声传感器工作点易偏离问题,设计了基于双波长稳定技术的低细度光纤F-P传感系统,建立了双波长光纤F-P传感系统的DE算法数学模型,优化设计了一高正交精度光纤F-P传感系统,建立基于该传感器的激光超声检测系统,实验研究了该传感器探测超声信号的有效性和方向灵敏度。结果表明,该传感器可以有效检测试样中激发出的超声表面波信号。激发源与传感器轴向夹角为0°时,表面波幅值最大。随着激发源与传感器轴向夹角增大,表面波幅值降低。激发源与传感器轴线垂直时,幅值下降达80%,说明该传感器有很强的方向性。     

一种改进小波阈值函数的光纤光栅传感信号去噪方法

光纤布拉格光栅( FBG)传感信号中存在的噪声严重影响了其中心波长的检测精度,因此必须进行去噪处理。本文针对传统的小波软、硬阈值函数去噪的不足,提出了一种改进的对数阈值函数,并确定了最优的小波基和分解尺度。仿真表明,本文提出的改进阈值函数去噪后信噪比( SNR)较大,均方根误差( RMSE)较小,其中信噪比比传统的软、硬阈值方法提高了1.5 dB~4 dB。最后通过实验验证了本文方法的去噪效果。     

The governance strategies for public emergencies on social media and their effects: a case study based on the microblog data

Since the 1980s, the development of information and communication technologies (ICTs) has greatly changed people’s modes of production and lifestyle, and it has also had a significant influence on traditional social structures. Microblogs – a type of social media application such as Twitter or Weibo – have served as an important platform for network governance in some local governments in China. This study makes an attempt to answer the following questions: What types of strategies should governments implement on social media platforms during public emergencies? What are the effects of these strategies? Based on the case of the Shifang Incident, which was a large-scale environmental protest that occurred in Shifang, China in 2012, we analyze all the messages posted during the incident on the official microblog of the Shifang government and examine the public feedback by using an online big data analysis tool. In line with the time sequence and the extent of the conflict, we divide the Shifang Incident into three phases: the fermentation period, the confrontation period, and the digestion period. In addition, we classify government strategies on social media into five categories: introducing, appealing, explaining, rumor-refuting, and decision-making. The analysis results show that different government strategies are applied to different phases of the incident and that the responses of the public also vary during different periods.     

Determining Geographic Vulnerabilities Using a Novel Impact Based Resilience Metric

Various natural and man-made disasters as well as major political events (like riots) have increased the importance of understanding geographic failures and how correlated failures impact networks. Since mission critical networks are overlaid as virtual networks over a physical network infrastructure forming multilayer networks, there is an increasing need for methods to analyze multilayer networks for geographic vulnerabilities. In this paper, we present a novel impact-based resilience metric. Our new metric uses ideas borrowed from performability to combine network impact with state probability to calculate a new metric called Network Impact Resilience. The idea is that the highest impact to the mission of a network should drive its resilience metric. Furthermore, we present a state space analysis method that analyzes multilayer networks for geographic vulnerabilities. To demonstrate the methods, the inability to provision a given number of upper layer services is used as the criteria for network failure. Mapping techniques for multilayer network states are presented. Simplifying geographic state mapping techniques to reduce enumeration costs are also presented and tested. Finally, these techniques are tested on networks of varying sizes.     

Exact and approximate flexible aggregate similarity search

Aggregate similarity search, also known as aggregate nearest-neighbor (Ann) query, finds many useful applications in spatial and multimedia databases. Given a group Q of M query objects, it retrieves from a database the objects most similar to Q, where the similarity is an aggregation (e.g., \({{\mathrm{sum}}}\), \(\max \)) of the distances between each retrieved object p and all the objects in Q. In this paper, we propose an added flexibility to the query definition, where the similarity is an aggregation over the distances between p and any subset of \(\phi M\) objects in Q for some support \(0< \phi \le 1\). We call this new definition flexible aggregate similarity search and accordingly refer to a query as a flexible aggregate nearest-neighbor ( Fann ) query. We present algorithms for answering Fann queries exactly and approximately. Our approximation algorithms are especially appealing, which are simple, highly efficient, and work well in both low and high dimensions. They also return near-optimal answers with guaranteed constant-factor approximations in any dimensions. Extensive experiments on large real and synthetic datasets from 2 to 74 dimensions have demonstrated their superior efficiency and high quality.     

Two general integral inequalities and their applications to stability analysis for systems with time‐varying delay

Integral inequalities have been widely used in stability analysis for systems with time‐varying delay because they directly produce bounds for integral terms with respect to quadratic functions. This paper presents two general integral inequalities from which almost all of the existing integral inequalities can be obtained, such as Jensen inequality, the Wirtinger‐based inequality, the Bessel–Legendre inequality, the Wirtinger‐based double integral inequality, and the auxiliary function‐based integral inequalities. Based on orthogonal polynomials defined in different inner spaces, various concrete single/multiple integral inequalities are obtained. They can produce more accurate bounds with more orthogonal polynomials considered. To show the effectiveness of the new inequalities, their applications to stability analysis for systems with time‐varying delay are demonstrated with two numerical examples. Copyright © 2016 John Wiley & Sons, Ltd.     

Controller design and analysis for singularly perturbed switched systems with actuator saturation

This paper investigates the problems of controller design and stability analysis for singularly perturbed switched systems subject to actuator saturation. A set of well‐defined sufficient conditions for the existence of state feedback controllers is proposed, under which the closed‐loop system is locally asymptotically stable for arbitrary switching law as long as the singular perturbation parameter is sufficiently small. With the obtained controller, the estimation problem of stability bound and basin of attraction of the closed‐loop system is reduced to solving a convex optimization problem. A numerical example and a hydraulic servo position system are used to illustrate the obtained results. Copyright © 2016 John Wiley & Sons, Ltd.     

Hopf Bifurcation Analysis of a Reaction-Diffusion Neural Network with Time Delay in Leakage Terms and Distributed Delays

In this paper, a reaction-diffusion neural network with time delay in leakage terms and distributed synaptic transmission delays under homogeneous Neumann boundary conditions is investigated. By analyzing the corresponding characteristic equation, the local stability of the trivial uniform steady state and the existence of Hopf bifurcation are established. By using the normal form theory and the center manifold reduction of partial functional differential equations, explicit formulae are obtained to determine the direction of bifurcations and the stability of bifurcating periodic solutions. Numerical simulations are carried out to illustrate the main results.     

Scheduling evacuation operations

In this paper, we consider a large-scale evacuation problem after a major disaster. The evacuation is assumed to occur by means of a fleet of buses, thus leading to scheduling the evacuation operations by buses [(bus evacuation problem (BEP)]. We propose time-indexed formulations as well as heuristic algorithms such as greedy algorithms and a matheuristic. This matheuristic uses the former formulation to improve the best solution obtained by the greedy heuristics. In computational experiments, we analyze and evaluate the efficiency of the proposed solution algorithms.