Windows平台下补丁管理系统的设计与实现

计算机系统的补丁管理已经成为计算机系统安全的一个重要组成部分.在现有技术下,如何完整、规范地为需要严格与Intemet隔离的内联网计算机用户分发和安装补丁是一个较为突出的问题.文章在微软免费的WSUS(Windows Server Update Services)服务基础上,开发出一套基于Windows平台的内联网补丁管理系统,弥补了WSUS系统的不足,提出了一种解决该问题的方案,并已经在中国人民银行浙江省范围内的分支机构中使用,具有很好的效果.     

基于struts框架的林政加工厂管理系统的开发

随着Internet及全球信息网应用的快速发展,WEB应用已逐步走向企业办公自动化,极大的方便了现代企业处理日常事务,B/S模式的方便性以及安全性越来越受到人们的青睐.本林政加工厂管理系统采用B/S模式,利用Struts框架和Hibernate技术的结合来开发.相对于使用JDBC和SQL来手工操作数据库,Hibernate可以大大减少操作数据库的工作量.     

别让键盘“谋杀”汉字

首先我们先来"赞美"一下我们每天所使用的文字--汉字.它是我们华夏民族几千年文化的瑰宝,也是我们终身的良师益友,每个人的精神家园.人生几十年,一切身外之物都发生了许多次变异.新陈代谢,过时的淘汰了,破损的废弃了,家用电器不多久就要换代,人们都习以为常,毫不为怪.天地万物,只有语言文字是永远存在的.     

虚拟现实及其应用进展

虚拟现实是一种多通道的新型人机交互接口,它提供了具有沉浸感的智能虚拟环境并允许用户和该环境进行交互.计算机技术、交互技术和人工智能等相关技术的快速发展促进了虚拟现实技术的巨大进步,以此为基础的实际应用也得到了很快的发展和提高.描述了虚拟现实的涵义及其本质特征,归纳了适合使用虚拟现实技术的场合,并介绍了虚拟现实技术在教育、医疗、科学可视化和工程制造等方面的最新应用,最后对虚拟现实未来的应用做出了展望.     

Java中双向控件的使用、制作及布局*

介绍了一种国际化控件--双向控件的使用、制作和布局方法,并介绍了如何设置控件的方向,设计控件的结构和布局控件的原理,以及在此过程中可能遇到的问题和解决方法.     

中华卫士DNA构筑中小企业安全链

在目前的安全市场里,活跃着这样一批硬件芯片级防火墙,它们正是卫士通信息产业股份有限公司新近推出的——中华卫士VPN防火墙低端系列产品,由于专门服务于中小企业以及远程分支机构,所以它们都普遍具有高性价比、功能齐备和使用     

中国可信计算技术:TCM带动IT安全新革命

创新点:传统的防御方式主要通过防火墙、病毒检测、VPN及加密锁等安全体系,都是以被动防御为主,大有兵来将挡、水来土掩之势,结果不仅各种防御措施花样层出,而且防火墙也越砌越高、入侵检测越做越复杂、恶意代码库越做越大,但是信息安全仍然得不到有效保障。如今,最简单的方法,就是建立起中国自主可信计算的技术架构,让我们的计算机像人类的免疫系统那样可以识别计算状态、防泄漏、防木马、防病毒。可信计算平台让我们看到了IT安全新革命的曙光,这也将是未来安全免疫计算的重要基础。     

上海大学自强队征战RoboCup伊朗公开赛获小型组冠军

在RoboCup机器人大赛开展10周年之际,RoboCup机器人伊朗公开赛(IranOpen2007)于2007年4月3日-7日在伊朗首都德黑兰举行,本次大赛分为senior与junior组,参赛队伍有东道主伊朗、德国、巴西、日本、葡萄牙、中国等共400多支代表队,比赛项目包括了除RoboCup2D组以外的RoboCup其它组全部项目.     

PTC的梦想

2004年11月16日,PTC在北京召开了2004年PTC用户大会,这是全球巡展(北美、印度、欧洲以及日本)的其中一站,来自总部的8位专家,为了更好地了解用户的需求,与参会的1000多名企业代表进行了面对面交流.人数规模之大给记者留下了深刻印象,也给竞争对手施加了压力.目前PTC在全球已为35000多家用户提供了PLM解决方案,在中国市场,自2003年Pro/ENGINEER野火版投放以来,约52%的老客户已开始采用,Windchill 7.0推出仅6个月,用户数量即扩大了15%.环顾我们身边,航天、船舶、汽车、电脑、甚至牙刷等等,越来越多的产品留下了PTC的痕迹,他在幕后默默地帮助企业实现一个又一个梦想的同时也在一步步实现着自己的梦想.     

稳步发展的HP CAE

随着市场需求的不断扩大,世界巨头开始纷纷入住中国.在街头、商场、办公室,越来越多中国制造的名牌映入眼帘.不过,几年前很多厂商都是看中中国低廉的劳动力,采取国外元件,中国组装的方式进行生产.市场永远是最终的引导者,中国人群的消费水平、审美水准在潜移默化地提高,洋品牌不得不开始考虑中国人的生活习惯、东方人的审美思想,中国制造也开始了转变.曾经属于研究院所"专有名词"的CAE开始作为产品设计研发的重要一环,被越来越多的企业所应用,其需求在稳步增长.     

Control allocation-based adaptive control for greenhouse climate

This paper presents an adaptive approach to greenhouse climate control, as part of an integrated control and management system for greenhouse production. In this approach, an adaptive control algorithm is first derived to guarantee the asymptotic convergence of the closed system with uncertainty, then using that control algorithm, a controller is designed to satisfy the demands for heat and mass fluxes to maintain inside temperature, humidity and CO₂ concentration at their desired values. Instead of applying the original adaptive control inputs directly, second, a control allocation technique is applied to distribute the demands of the heat and mass fluxes to the actuators by minimising tracking errors and energy consumption. To find an energy-saving solution, both single-objective optimisation (SOO) and multiobjective optimisation (MOO) in the control allocation structure are considered. The advantage of the proposed approach is that it does not require any a priori knowledge of the uncertainty bounds, and the simulation results illustrate the effectiveness of the proposed control scheme. It also indicates that MOO saves more energy in the control process.     

Nonlinear MPC based on a Volterra series model for greenhouse temperature control using natural ventilation

Suitable environmental conditions are a fundamental issue in greenhouse crop growth and can be achieved by advanced climate control strategies. In different climatic zones, natural ventilation is used to regulate both the greenhouse temperature and humidity. In mild climates, the greatest problem faced by far in greenhouse climate control is cooling, which, for dynamical reasons, leads to natural ventilation as a standard tool. This work addresses the design of a nonlinear model predictive control (NMPC) strategy for greenhouse temperature control using natural ventilation. The NMPC strategy is based on a second-order Volterra series model identified from experimental input/output data of a greenhouse. These models, representing the simple and logical extension of convolution models, can be used to approximate the nonlinear dynamic effect of the ventilation and other environmental conditions on the greenhouse temperature. The developed NMPC is applied to a greenhouse and the control performance of the proposed strategy will be illustrated by means of experimental results.     

物联网技术在高效农业种植中的应用研究

我国是一个农业大国,以温室大棚为主体的高效农业种植是目前非常关注的问题。论文设计了一种基于物联网技术的温室智能监控系统,该系统采用n RF2401组建无线传感网络,实现对温室内多个环境因子的实时监测与控制。经测试,该系统运行稳定,达到智能监控的效果。     

基于局部合作的RoboCup多智能体Q-学习

针对多智能体Q-学习中存在的联合动作指数级增长问题,采用-种局部合作的Q-学习方法,在智能体之间有协作时才考察联合动作,否则只进行简单的个体智能体的Q-学习,从而减少学习时所要考察的状态-动作对值。在机器人足球仿真2D平台上进行的实验表明,该方法比常用多智能体强化学习技术具有更高的效率。     

Greenhouse climate fuzzy adaptive control considering energy saving

This paper proposes a fuzzy adaptive control approach to solve greenhouse climate control problem. The aim is to ensure the controlled environmental variables to track their desired trajectories so as to create a favorable environment for crop growth. In this method, a feedback linearization technique is first introduced to derive the control laws of heating, fogging and CO2 injection, then to compensate for the saturation of the actuators, a fuzzy logic system (FLS) is used to approximate the differences between controller outputs and actuator outputs due to actuator constraints. A robust control term is introduced to eliminate the impact of external disturbances and model uncertainty, and finally, Lyapunov stability analysis is performed to guarantee the convergence of the closed-loop system. Taking into account the fact that the crop is usually insensitive to the change of the environment inside the greenhouse during a short time interval, a certain amount of tracking error of the environmental variables is usually acceptable, which means that the environmental variables need only be driven into the corresponding target intervals. In this case, an energy-saving management mechanism is designed to reduce the energy consumption as much as possible. The simulation results illustrate the effectiveness of the proposed control scheme.

     

Model-Free control performance improvement using virtual reference feedback tuning and reinforcement Q-learning

This paper proposes the combination of two model-free controller tuning techniques, namely linear virtual reference feedback tuning (VRFT) and nonlinear state-feedback Q-learning, referred to as a new mixed VRFT-Q learning approach. VRFT is first used to find stabilising feedback controller using input-output experimental data from the process in a model reference tracking setting. Reinforcement Q-learning is next applied in the same setting using input-state experimental data collected under perturbed VRFT to ensure good exploration. The Q-learning controller learned with a batch fitted Q iteration algorithm uses two neural networks, one for the Q-function estimator and one for the controller, respectively. The VRFT-Q learning approach is validated on position control of a two-degrees-of-motion open-loop stable multi input-multi output (MIMO) aerodynamic system (AS). Extensive simulations for the two independent control channels of the MIMO AS show that the Q-learning controllers clearly improve performance over the VRFT controllers.     

基于多智能体增强学习的公交驻站控制方法

车辆驻站是减少串车现象和改善公交服务可靠性的常用且有效控制策略,其执行过程需要在随机交互的系统环境中进行动态决策。考虑实时公交运营信息的可获得性,研究智能体完全合作环境下公交车辆驻站增强学习控制问题,建立基于多智能体系统的单线公交控制概念模型,描述学习框架下包括智能体状态、动作集、收益函数、协调机制等主要元素,采用hysteretic Q-learning算法求解问题。仿真实验结果表明该方法能有效防止串车现象并保持单线公交服务系统车头时距的均衡性。     

基于Q学习的单路口交通信号协调控制

Q学习通过与外部环境的交互来进行单路口的交通信号自适应控制。在城市交通愈加拥堵的时代背景下,为了缓解交通拥堵,提出一种结合SCOOT系统对绿信比优化方法的Q学习算法。本文将SCOOT系统中对绿信比优化的方法与Q学习相结合,即通过结合车均延误率以及停车次数等时间因素以及经济因素2方面,建立新的数学模型来作为本算法的成本函数并建立一种连续的奖惩函数,在此基础上详细介绍Q学习算法在单路口上的运行过程并且通过与Webster延误率和基于最小车均延误率的Q学习进行横向对比,验证了此算法优于定时控制以及基于车均延误的Q学习算法。相对于这2种算法,本文提出的算法更加适合单路口的绿信比优化。     

Q-learning of complex behaviours on a six-legged walking machine

We present work on a six-legged walking machine that uses a hierarchical version of [C.J.C.H. Watkins, Learning with delayed rewards, Ph.D. Thesis, Psychology Department, Cambridge University, 1989] Q-learning (HQL) to learn both: the elementary swing and stance movements of individual legs as well as the overall coordination scheme to perform forward movements. The architecture consists of a hierarchy of local controllers implemented in layers. The lowest layer consists of control modules performing elementary actions, like moving a leg up, down, left or right to achieve the elementary swing and stance motions for individual legs. The next level consists of controllers that learn to perform more complex tasks like forward movement by using the previously learned, lower level modules. The work is related to similar, although simulation based, work [L.J. Lin, Reinforcement learning for robots using neural networks, Ph.D. Thesis, Carnegie Mellon University, 1993] on hierarchical reinforcement-learning and [S.P. Singh, learning to solve Markovian decision problems, Ph.D. Thesis, Department of Computer Science at the University of Massachusetts, 1994] on compositional Q-learning. We report on the HQL architecture as well as on its implementation on the walking machine Sir Arthur. Results from experiments carried out on the real robot are reported to show the applicability of the HQL approach to real world robot problems.     

基于Q-learning的离散时间多智能体系统一致性

针对模型未知的一类离散时间多智能体系统,本文提出了一种Q-learning方法实现多智能体系统的一致性控制.该方法不依赖于系统模型,能够利用系统数据迭代求解出可使给定目标函数最小的控制律,使所有智能体的状态实现一致.通过各个智能体所产生的系统数据,采用策略迭代的方法实时更新求解得到多智能体系统的控制律,并对所提Q-learning方法进行了收敛性和稳定性分析.最后,论文给出了计算机仿真验证了所提方法的有效性.