Rapid calculation of the periodic steady state for electronicallyswitched, time varying power system loads

The periodic steady state of power distribution system loads is studied for electronically switched, time varying cases. Many loads of this type appear on contemporary power systems as energy saving and controllable demands. Several alternative methods of calculating the periodic steady state are discussed and a new method is proposed based on the frequency modulation property of the discrete Fourier transform. The new method is termed the gain-shift formula (GSF) because the format of the technique entails adding frequency shifted terms which represent the parameter to be calculated. An example of a triac-switched load on the distribution system is given. The main advantages of the GSF are: rapid calculation of the periodic steady state; and efficient calculation of the frequency spectrum of voltages and currents in the periodic steady state     

Stability analysis and antiwindup design of uncertain discrete-time switched linear systems subject to actuator saturation

This paper investigates the stability analysis and antiwindup design problem for a class of discrete-time switched linear systems with time-varying norm-bounded uncertainties and saturating actuators by using the switched Lyapunov function approach.Supposing that a set of linear dynamic output controllers have been designed to stabilize the switched system without considering its input saturation,we design antiwindup compensation gains in order to enlarge the domain of attraction of the closed-loop system in the presence of saturation.Then,in terms of a sector condition,the antiwindup compensation gains which aim to maximize the estimation of domain of attraction of the closed-loop system are presented by solving a convex optimization problem with linear matrix inequality(LMI)constraints.A numerical example is given to demonstrate the effectiveness of the proposed design method.     

入侵检测在存储区域网中的应用

从SAN(存储区域网)的安全隐患出发,分析了SAN在应用环境中受到的三种典型威胁。结合现行的入侵检测技术给出一个可行的解决方案。     

基于模型修正技术的模拟集成电路几何规划优化方法

为了兼顾模拟集成电路设计优化的求解精度和计算效率,提出一种基于正项式模型修正技术的几何规划优化方法.首先将模拟集成电路的设计目标与约束简化为正项式模型,然后在采用几何规划方法迭代优化的过程中利用晶体管级SPICE仿真不断修正这一正项式模型.实例表明,与传统基于公式的优化方法和基于仿真的优化方法相比,该方法能够在尽量保证计算效率和全局最优解的前提下使优化精度满足晶体管级SPICE仿真的要求.     

磁悬浮列车传感器信号传输系统分析

磁悬浮列车传感器系统采用屏蔽双绞线传输数字传感器信号;磁悬浮列车传感器信号传输系统具有典型的传输线系统特点;研究了系统始端内阻抗与终端阻抗对信号传输的影响;分析了在终端为网络变压器时,传输线对信号传输的影响;提出了在有限负载阻抗条件下,阻抗匹配的设计要求;实验证明在有限阻抗负载条件下,并联终端匹配比始端串联匹配具有明显优势。     

无线传感器网络中一种基于移动Sink的数据收集算法

针对移动无线传感器网络设计一种不依赖于节点地理位置的基于移动汇聚节点(Sink)的数据收集算法(Mobile Sink-based Data Gathering,MSDG)。该算法解决了无线传感器网络中多跳路由通信时出现能量空洞的"热点"问题。Sink沿途以最近的固定节点作为根节点动态构建路由树。簇内移动节点感知的数据经簇头进行数据融合计算,然后将融合后的数据沿路由树反向逐跳转发给Sink。仿真结果表明,MSDG在节点的平均能耗和网络生存时间等方面的性能远超过LEACH、ACE-L等数据收集协议。     

HAR-sEMG: A Dataset for Human Activity Recognition on Lower-Limb sEMG

Knowledge and Information Systems - In the past decade, human activity recognition (HAR) has grown in popularity due to its applications in security and entertainment. As recent years have...     

Influence of content and creator characteristics on sharing disaster-related information on social media

Identifying the key factors of the disaster-related information propagation process can provide decision support for disaster management. This study characterizes the effects of content types, location, and social capital of social media users on the virality of disaster-related information. We found through the Weibo dataset of the Yiliang earthquake that the virality of different types of information can vary on the basis of the social capital of users who post the information. This study fills the current research gaps by examining the individual and joint effects of the content and creator characteristics on the virality of disaster-related information.     

GRU-based capsule network with an improved loss for personnel performance prediction

Applied Intelligence - Personnel performance is a key factor to maintain core competitive advantages. Thus, predicting personnel future performance is a significant research domain in human...