基于多元智能理论的大学英语视听说自主学习模式研究

以多元智能理论为基础,介绍了沈阳建筑大学开展视听说自主学习模式试点教学的实践过程,并通过问卷和访谈调查了学习者对视听说自主学习的总体评价以及自主学习过程中存在的问题。研究表明,大部分学习者能够适应网络自主学习模式,并比较认可网络自主学习对英语学习的作用,但是视听说自主学习模式在教材、教学软件设计、学生之间、师生之间的交流与互动等方面还存在一些不足,学习者的积极性也有待提高。针对这些发现,本文提出了相应的教学建议。     

飞行员素质与飞行安全的探讨

＂安全第一＂是民航永恒的主题。飞行员是飞行活动的执行者,研究飞行员与飞行安全意义重大。飞行活动具有特殊性,分析飞行员的自身因素（健康状况、文化素质、专业知识技能、技术处置能力、非智力因素等）是如何影响飞行安全的。并对飞行员安全飞行作出了方向性的提示,为安全飞行提供借鉴。     

高校文学课程中的问题探求与知识建构

面对文学类课程教学所面临的内外双重困境,在教学中以自主学习为课程目标,以问题与知识构建为重要突破口,使学生的课内学习与课外探求互为联动,从而不断提高文学类课程的教学效果,使文学类课程从"无用"走向隐性与显性的双重"有用",从而处理好问题探求与知识建构之间良性互动的关系。     

自主移动机器人局部优化导航算法研究

自主移动机器人在未知环境下需要依靠自身装配的传感器不间断地获得周围环境信息,辨别出障碍物的位置,进行计算和自主决策.现有导航算法在面临U型等复杂环境时容易在僵死路径上产生反复,导致导航不能继续.文中提出了一种基于模糊逻辑的局部优化导航算法,采用"辨识-记忆"策略来处理传感器信息.在路径规划中保留最近走过路径的位置和角度特征等相关资源,形成"记忆".当前规划路径形成死区并反复运行时,会形成"辨识"并重新规划路径和导航决策以避免障碍物碰撞.在Webots Pro和Matlab下设计仿真实验,结果表明移动机器人在模糊规则指导下能有效避障和避免死区现象,实现较好的自主导航.     

悬停状态下旋翼飞行机器人自适应鲁棒控制

针对加装二自由度绳驱动机械臂的旋翼飞行机器人在悬停条件下的抗干扰控制,提出了一种自适应终端滑模控制策略.将系统分成四旋翼飞行器和机械臂两个子系统,分别采用拉格朗日法与牛顿-欧拉法获得各自的动力学模型.在Lyapunov稳定性框架下设计了旋翼飞行器人的抗干扰轨迹跟踪控制器,并引人自适应策略来估计扰动上界.通过3个仿真算例验证了所设计控制器的有效性,结果表明,与其他控制器相比,本控制器具有较高的跟踪精度、较强的鲁棒性以及较好的抗干扰能力;机械臂质量的变化主要影响x通道和y通道的控制性能;本控制器基本能满足旋翼飞行机器人悬停作业的工作需求,具有一定的工程参考意义.     

国外TOFD检测标准分析和比较

概述了超声波衍射时差法（TOFD），对目前世界上主要的七个TOFD检测标准或规范进行了分析和比较，归纳了其中十二个方面的异同点。为我国TOFD检测标准的制订和TOFD技术的发展提供参考。     

Implementation and performance evaluation of a scheduling algorithm for divisible load parallel applications in a cloud computing environment

Cloud computing is an emerging technology in which information technology resources are virtualized to users in a set of computing resources on a pay‐per‐use basis. It is seen as an effective infrastructure for high performance applications. Divisible load applications occur in many scientific and engineering applications. However, dividing an application and deploying it in a cloud computing environment face challenges to obtain an optimal performance due to the overheads introduced by the cloud virtualization and the supporting cloud middleware. Therefore, we provide results of series of extensive experiments in scheduling divisible load application in a Cloud environment to decrease the overall application execution time considering the cloud networking and computing capacities presented to the application's user. We experiment with real applications within the Amazon cloud computing environment. Our extensive experiments analyze the reasons of the discrepancies between a theoretical model and the reality and propose adequate solutions. These discrepancies are due to three factors: the network behavior, the application behavior and the cloud computing virtualization. Our results show that applying the algorithm result in a maximum ratio of 1.41 of the measured normalized makespan versus the ideal makespan for application in which the communication to computation ratio is big. They show that the algorithm is effective for those applications in a heterogeneous setting reaching a ratio of 1.28 for large data sets. For application following the ensemble clustering model in which the computation to communication ratio is big and variable, we obtained a maximum ratio of 4.7 for large data set and a ratio of 2.11 for small data set. Applying the algorithm also results in an important speedup. These results are revealing for the type of applications we consider under experiments. The experiments also reveal the impact of the choice of the platforms provided by Amazon on the performance of the applications under study. Considering the emergence of cloud computing for high performance applications, the results in this paper can be widely adopted by cloud computing developers. Copyright © 2014 John Wiley & Sons, Ltd.     

Flight control of tethered kites in autonomous pumping cycles for airborne wind energy

Energy harvesting based on tethered kites benefits from exploiting higher wind speeds at higher altitudes. The setup considered in this paper is based on a pumping cycle. It generates energy by winching out at high tether forces, driving an electrical generator while flying crosswind. Then it winches in at a stationary neutral position, thus leaving a net amount of generated energy.The focus of this paper is put on the flight control design, which implements an accurate direction control towards target points and allows for a flight with an eight-down pattern. An extended overview on the control system approach, as well as details of each element of the flight controller, is presented. The control architecture is motivated by a simple, yet comprehensive model for the kite dynamics.In addition, winch strategies based on an optimization scheme are presented. In order to demonstrate the real world functionality of the presented algorithms, flight data from a fully automated pumping-cycle operation of a small-scale prototype are given. The setup is based on a 30 m² kite linked to a ground-based 50 kW electrical motor/generator by a single line.     

旋翼飞行机器人研究进展

旋翼飞行机器人是面向空中自主作业需求,将旋翼飞行器与多自由度机械臂相结合所提出的新型机器人.该机器人作业过程中旋翼飞行器、机械臂与作业目标之间的动态相对运动以及与作业目标接触过程中未建模外力、力矩扰动使自主控制受到极大挑战.本文将针对旋翼飞行机器人的结构演变及关键技术、作业机构集成技术进行综述.从动力学建模及动力学特性分析、动态运动约束/力约束下的协调规划、非结构环境下的运动和作业控制、面向任务动态操作的环境感知、面向任务的实验系统构建与实验验证五个方面初步构建了旋翼飞行机器人自主作业理论体系.     

水上无人机自主着水控制系统设计

针对水上无人机在高海况下的着水问题,本文在分析了不同着水阶段特性的基础上,提出了一种自主着水控制系统设计方案.该方案将整个系统分为速度控制子系统和姿态控制子系统.速度控制子系统包含速度动态逆控制器和油门切换模块,姿态控制子系统包含海浪滤波器俯仰角反步控制器、高度PID控制器、俯仰角切换模块和T-S模糊推理模块.其中,海浪滤波器能有效滤除受扰姿态角中的海浪高频扰动,避免了着水之后舵面的频繁抖动;俯仰角反步控制器采用指令滤波的反步法设计,有效缓解了高海况下的舵面饱和问题.最后,在不同海况条件下进行了仿真.仿真结果表明所设计的控制系统具有良好的控制性能.