CAL delivery selection criteria and authoring systems

Abstract  In the past, authoring systems have been used to generate computer-assisted learning materials that have often followed the rather restrictive programmed learning format. A number of innovative ways of using recently developed systems to develop CAL packages that include a wider range of learning activities (access to data bases, simulations, interactive video, etc.) are described. Analogous to the concept of a media selection model, a computer delivery mode selection model is presented as an aid to decision making for designers. This increase in flexibility should broaden the applicability of computerassisted learning (CAL) to a wider range of educational objectives and raise the level of the cognitive emphasis in learning packages, as well as facilitate the implementation of visually appealing materials. The paper also implies a standard of acceptability for authoring systems.     

底板翻面机及其液压系统设计

本文介绍了底板翻面机及其液压系统的工作原理和设计特点。该机结构紧凑、运行平稳、工作可靠、能耗低，其成功的设计经验对同类设备的设计改造具有一定的参考价值     

KNOWLEDGE-BASED FEATURE DISCOVERY FOR EVALUATION FUNCTIONS

Since Samuel's work on checkers over thirty years ago, much effort has been devoted to learning evaluation functions. However, all such methods are sensitive to the feature set chosen to represent the examples. If the features do not capture aspects of the examples significant for problem solving, the learned evaluation function may be inaccurate or inconsistent. Typically, good feature sets are carefully handcrafted and a great deal of time and effort goes into refining and tuning them. This paper presents an automatic knowledge-based method for generating features for evaluation functions. The feature set is developed iteratively: features are generated, then evaluated, and this information is used to develop new features in turn. Both the contribution of a feature and its computational expense are considered in determining whether and how to develop it further.
This method has been applied to two problem-solving domains: the Othello board game and the domain of telecommunications network management. Empirical results show that the method is able to generate many known features and several novel features and to improve concept accuracy in both domains.     

Deterministic learning of completely resonant nonlinear wave systems with Dirichlet boundary conditions

In this paper, we investigate the approximation of completely resonant nonlinear wave systems via deterministic learning. The plants are distributed parameter systems (DPS) describing homogeneous and isotropic elastic vibrating strings with fixed endpoints. The purpose of the paper is to approximate the infinite-dimensional dynamics, rather than the parameters of the wave systems. To solve the problem, the wave systems are first transformed into finite-dimensional dynamical systems described by ordinary differential equation (ODE). The properties of the finite-dimensional systems, including the convergence of the solution, as well as the dominance of partial system dynamics according to point-wise measurements, are analyzed. Based on the properties, second, by using the deterministic learning algorithm, an approximately accurate neural network (NN) approximation of the the finite-dimensional system dynamics is achieved in a local region along the recurrent trajectories. Simulation studies are included to demonstrate the effectiveness of the proposed approach.     

Adaptive control of permanent magnet synchronous machines with disturbance estimation

In this paper,an adaptive control scheme is introduced for permanent magnet synchronous machines (PMSMs)as an alternative to classical control techniques.The adaptive control strategy capitalizes on the machine’s inverse dynamics to achieve accurate tracking by using an observer to approximate disturbance in the form of friction and load torque.The controller’s output is then fed to a space vector pulse width modulation(SVPWM)algorithm to produce duty cycles for the inverter.The control scheme is validated through a set of simulations on an experimentally validated PMSM model.Results for different situations highlight its high speed tracking accuracy and high performance in compensating for friction and load disturbances of various magnitudes.     

网络对抗训练混合虚拟化平台设计研究

讨论了虚拟化技术实现原理及其在网络对抗教学中的应用上,分析了各类虚拟化技术的优缺点和构建网络对抗训练环境存在的问题。提出了一种混合虚拟化平台设计,该平台利用Libvirt虚拟化的应用程序编程接口（API）调用两种虚拟化技术同时运行在同一物理主机上。并详细叙述了混合虚拟化平台的实现过程和方法,并在多个虚拟机内同时运行测试基准,分析其可扩展性。多种虚拟化技术在同一物理机上的混合,实现了复杂实验环境的创建,对构建大规模的网络实验平台具有一定的参考价值。     

大型立式玻璃磨边机整机动态特性分析

大型立式玻璃磨边机的动态特性影响玻璃磨边质量和磨边效率。利用Solidworks软件建立某大型立式玻璃磨边机三维实体模型,导入ANSYS软件中,对整机结构有限元动力学分析,得到该磨边机前六阶模态参数,分析了各阶振型对磨边机动态特性的影响,为磨边机结构的改进设计提供了理论依据。     

无线ILC系统测控信号延时效应补偿方法

针对通过无线信道进行测控信号传输的远程迭代学习控制( ILC)系统,研究信号传输延时对控制系统性能的影响.分析了测控信号延时情况下ILC系统的收敛性问题,通过引入预控制向量,提出了ILC系统信道延时效应补偿的向量更新方法.数值仿真结果表明了所提方法的有效性.     

制丝线FT651型叶片垂直分片机控制系统的改进方案

针对叶片垂直分片机使用过程中出现的劈坏烟箱、纵向移动刀架失控和系统无报警功能等问题,分析故障产生的原因,并对其控制系统进行改进。     

视觉技术在YP19装封箱机中的设计与应用

介绍视觉技术在YP19装封箱机的装箱过程中的应用,简述视觉技术系统的基本组成、工作原理及软件设计。