基于DMT的1553B带宽扩展研究

由于传统的MIL-STD-1553B总线难以满足高速数据传输需求且更换现有总线代价过高,因此迫切需要在不影响现有基带通信的条件下升级1553B系统以提供高速通信接口。本文分析1553B的信道特性并据此选择频谱利用率高、抗频率选择性衰落的离散多音调制(DMT)作为扩展带宽的技术,基于离散多音调制,提出一个与现有通信相互兼容的扩展方案以显著提高传输速率,并对该方案涉及的关键技术进行介绍。     

基于JMX的MuleESB管理控制台

给出了一个符合JMx规范的MuleESB管理控制台的设计和实现方案。借助了该控制台可以远程管理MuleESB．查看MuleEsB服务器信息、MuleEsB及其服务的运行时状态和运行日志,也可以远程调用部署在MuleESB＆服务方法。该控制台弥补了MuleESB不提供远程管理的开源实现的不足。实验证实,该控制台运行稳定可靠。     

岩石高边坡稳定性并行计算及其应用

在高地震烈度区的岩石高边坡抗震安全评价需要大规模数值计算,而现有商业软件无法有效解决这类复杂的工程问题,因此,本文开发了解决岩石高边坡接触稳定性问题的对等架构并行计算程序,并应用于泰山公司抽水蓄能电站上水库左岸边坡的静力和动力稳定性评价。在数值建模过程中,将岩石边坡滑块体、地质结构面、库水作用以及近场地基作为岩石高边坡动力接触系统。在稳定性安全评价中结合了有限元法、极限平衡法和接触算法,考虑影响高边坡稳定性的多种复杂因素,通过计算特定滑动面的安全系数或安全系数时程,基于现行水电工程水工建筑物抗震设计规范,完成了岩石高边坡稳定性评价,回避了求解复杂岩体材料非线性的问题。计算结果显示,所开发的程序具有较高的并行计算效率,对解决复杂岩石高边坡稳定问题具有显著的优势。     

信息安全在物联网时代面临的挑战

物联网安全研究主要集中在物联网安全体系、物联网个体隐私保护模式、物联网安全相关法律的制定等方面。首先举例说明物联网在智能电网等生产生活领域的应用,然后讨论了物联网安全技术架构。最后根据物联网的安全架构分析了物联网安全面临的挑战。由此警示我们应提早应对物联网发展带来的信息安全等挑战。     

数字证书在环保行业的应用分析

目前国家环保部正在开展的国家环境信息与统计能力建设项目中,采用数字证书为业务系统提供强身份认证服务。详细论述了数字证书在环保部的应用模式,指出了今后的工作方向,同时也指出了现有应用模式的不足之处。     

EMAP: An efficient mutual authentication protocol for passive RFID tags

Radio frequency identification (RFID) system is a contactless automatic identification system, which uses small and low cost RFID tags. The primary problem of current security and privacy preserving schemes is that, in order to identify only one single tag, these schemes require a linear computational complexity on the server side. We propose an efficient mutual authentication protocol for passive RFID tags that provides confidentiality, untraceability, mutual authentication, and efficiency. The proposed protocol shifts the heavy burden of asymmetric encryption and decryption operations on the more powerful server side and only leaves lightweight hash operation on tag side. It is also efficient in terms of time complexity, space complexity, and communication cost, which are very important for practical large-scale RFID applications.     

Robust stability and stabilization of discrete singular systems with interval time-varying delay and linear fractional uncertainty

The robust stability and robust stabilization problems for discrete singular systems with interval time-varying delay and linear fractional uncertainty are discussed. A new delay-dependent criterion is established for the nominal discrete singular delay systems to be regular, causal and stable by employing the linear matrix inequality (LMI) approach. It is shown that the newly proposed criterion can provide less conservative results than some existing ones. Then, with this criterion, the problems of robust stability and robust stabilization for uncertain discrete singular delay systems are solved, and the delay-dependent LMI conditions are obtained. Finally, numerical examples are given to illustrate the e?ectiveness of the proposed approach.     

Handling multiple objectives with biogeography-based optimization

Biogeography-based optimization (BBO) is a new evolutionary optimization method inspired by biogeography. In this paper, BBO is extended to a multi-objective optimization, and a biogeography-based multi-objective optimization (BBMO) is introduced, which uses the cluster attribute of islands to naturally decompose the problem. The proposed algorithm makes use of nondominated sorting approach to improve the convergence ability effciently. It also combines the crowding distance to guarantee the diversity of Pareto optimal solutions. We compare the BBMO with two representative state-of-the-art evolutionary multi-objective optimization methods, non-dominated sorting genetic algorithm-II (NSGA-II) and archive-based micro genetic algorithm (AMGA) in terms of three metrics. Simulation results indicate that in most cases, the proposed BBMO is able to find much better spread of solutions and converge faster to true Pareto optimal fronts than NSGA-II and AMGA do.     

Design of robotic visual servo control based on neural network and genetic algorithm

A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation (BP) neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP algorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.     

Semantic analysis in XTRA,an English — Chinese machine translation system

This paper concerns the resolution of lexical ambiguity in a machine translation environment. We describe the integration of principles of selection restrictions. Preference Semantics, and intelligent relaxation of constraints in handling lexical ambiguity. The approach differs from many previous MT systems in that it is more powerful than brute force systems, while more realistic than systems that assume a large degree of coded encyclopedia information for full understanding.