Optimal Terminal Iterative Learning Control for the Automatic Train Stop System

The train stop control is a typical set‐point control task, where only the final state (i.e., the terminal train stop position) is of concern and specified. For such a control problem, an optimal terminal iterative learning control (TILC) approach is presented in this paper, where the stopping position and initial braking speed are chosen as the terminal system output and the control input, respectively. The controller design only depends on the measured input/output (I/O) data without requiring any modeling information of the train operation system, and the learning gain is updated by the system I/O data iteratively to accommodate the system uncertainties. The monotonic convergence of the terminal tracking error is guaranteed by rigorous mathematical analysis. Extensive simulation results are provided to show the applicability and effectiveness of the proposed approach.     

嵌入式Web的远程数据交互式设计

随着物联网的发展,越来越多的嵌入式系统与网络相结合。要实现设备与网络之间数据互联互通,必须解决嵌入式系统与Web之间数据交互的问题。本文基于CGI/SSI和XMLHTTPRequest两种方式,实现了嵌入式Web与浏览器之间的动态数据交换。通过实际运行测试,性能稳定可靠。     

CNGI青海湖系统建设中的若干技术问题

CNGI 青海湖系统支撑青海湖区域的生态保护和多学科交叉融合的科研协作。针对青海湖基础设施种类众多的特点,我们发展了 IPv6 相关关键技术,应用于基础网络环境建设、数据传输、设备管理与状态监控等多个层面,并充分考虑了由此带来的安全隐患,制定了相应安全策略。这些技术可以支持多种传感器构成的 IPv6 网络,并支持 IPv6 的相关应用软件研发,促进大规模、跨领域复杂科学问题研究工作。     

Concurrence for infinite-dimensional quantum systems

Concurrence is an important entanglement measure for states in finite-dimensional quantum systems that was explored intensively in the last decade. In this paper, we extend the concept of concurrence to infinite-dimensional bipartite systems and show that it is continuous and does not increase under local operation and classical communication.     

IDC信息安全管理系统建设方案探讨

根据工业和信息化部对电信企业IDC／ISP信息安全的管控要求,本文通过分析中国移动已建的IDC运营管理平台、网站备案管理系统、某内容监测系统、IDC流量流向分析控制系统、上网日志留存等多个涉及IDC信息安全系统的现状,在对上述系统进行梳理整合的基础上,补充完善相关功能,以实现对中国移动IDC系统的静态信息、实时动态流量信息进行全方位的覆盖监、管、控立体化管理。对IDC信息安全管理系统建设方案中的关键问题进行分析及总结,包括系统的主要功能、系统架构、建设原则、建设方案、安全要求等内容。     

基于MQP模型的电离图参数反演解析算法研究

针对现今普遍采用的偏导迭代电离图反演算法存在的求解依赖于初值选择的不足,给出了一种初值选择准则,保证了该算法的收敛性。同时,利用该准则,以及在对电离图虚高表达式进行合理近似的基础上,提出了一种新的电离图参数反演算法,该方法实现电离图参数反演的解析计算,较偏导迭代法计算量大大减少,更好满足工程实时性要求。     

面向微博平台的产品市场分析模型研究

通过对面向微博平台的产品市场分析过程进行抽象,提出了3层分析模型。第一层实现了数据准备模块,为兴趣分析提供规范化的数据。第二层通过情感分析提取微博平台上与产品相关的用户兴趣。第三层利用用户兴趣信息计算产品的满意度和关注度来表现产品市场形势。整个模型提供了面向微博平台搭建产品市场分析系统的快速解决方案。     

基于任务驱动的《计算机文化基础》教学

<计算机文化基础>是非计算机专业学生掌握计算机技术的入门课程,授课的对象广,且已经具有一定的计算机基础操作能力.如何在有限的课时中,让学生掌握计算机基础知识并灵活运用于本专业的学习过程,是一个有待研究的问题.本文探讨了如何采用基于任务驱动的方法进行<计算机文化基础>的教学,提高学生主动学习意识以及灵活运用知识的能力.     

New insights on survivability in multi-domain optical networks

With the development of intelligent optical networks and the general multi-protocol label switching (GMPLS) technique, the seamless convergence between IP network and optical network is no longer be a dream but a practical reality. Similar to the Internet, current optical networks have been divided into multiple domains each of which has its own network provider and management policy. Therefore, the development of multi-domain optical networks will be the trend of new-generation intelligent optical networks, and GMPLS-based survivability for multi-domain optical networks will become a hot topic of research in the future. This paper provides a comprehensive review of the existing survivable schemes in multi-domain optical networks and analyzes the shortcomings of current research. Based on previous studies, we present possible challenges and propose new ideas to design efficient survivable schemes to guide the future work of researchers in multi-domain optical networks.     

An integrated multi-objective immune algorithm for optimizing the wire bonding process of integrated circuits

Optimization of the wire bonding process of an integrated circuit (IC) is a multi-objective optimization problem (MOOP). In this research, an integrated multi-objective immune algorithm (MOIA) that combines an artificial immune algorithm (IA) with an artificial neural network (ANN) and a generalized Pareto-based scale-independent fitness function (GPSIFF) is developed to find the optimal process parameters for the first bond of an IC wire bonding. The back-propagation ANN is used to establish the nonlinear multivariate relationships between the wire boning parameters and the multi-responses, and is applied to generate the multiple response values for each antibody generated by the IA. The GPSIFF is then used to evaluate the affinity for each antibody and to find the non-dominated solutions. The “Error Ratio” is then applied to measure the convergence of the integrated approach. The “Spread Metric” is used to measure the diversity of the proposed approach. Implementation results show that the integrated MOIA approach does generate the Pareto-optimal solutions for the decision maker, and the Pareto-optimal solutions have good convergence and diversity performance.