Artificial neural networks for coordination and control: The portability of experiential representations

It is time to locate connectionist representation theory in the new wave of robotics research. The utility of representations developed in artificial neural networks (ANNs) during learning has been demonstrated in cognitive science research since the 1980s. The research reported here puts learned representations to work in a decentered control task, the disembodied arm problem, in which a mobile robot operates an arm fixed to a table to pick up objects. There is no physical linkage between the arm and the robot and so the robot's point of view must be decentered. This is done by developing a modular Artificial Neural Net system in three stages: (i) a classifier net is trained with laser scan data to output transformationally invariant position classes; (ii) an arm net is trained for picking up objects; (iii) an inter net is trained to communicate and coordinate the sensing and acting. The completed system is shown to create new nonsymbolic transformationally invariant representations in order to perform the effective generalization of decentered viewpoints.     

Two-level optimal output feedback stabilizer design

The paper addresses the design of two-level power system stabilizers using an optimal reduced order model whose state variables are torque angles and speeds. The reduced order model retains their physical meaning and is used to design a two-level linear feedback controller that takes into account the realities and constraints of electrical power systems. The two-level control strategy is used, and a global control signal is generated from the output variables to minimize the effect of interactions. The effectiveness of this controller is evaluated and a multimachine system is given as an example to illustrate the advantages of the proposed method. Responses of the system with a two-level scheme and an optimal reduced order scheme are included for comparative analysis.     

Integrating scheduling and control functions in computer integrated manufacturing using artificial intelligence

Proper integration of scheduling and control in Flexible Manufacturing Systems will make available the required level of decision-making capacity to provide a flexibly-automated, efficient, and quality manufacturing process. To achieve this level of integration, the developments in computer technology and sophisticated techniques of artificial intelligence (AI) should be applied to such FMS functions as scheduling. In this paper, we present an Intelligent Scheduling System for FMS under development that makes use of the integration of two AI technologies. These two AI technologies — Neural Networks and Expert Systems — provide the intelligence that the scheduling function requires in order to generate goodschedules within the restrictions imposed by real-time problems. Because the system has the ability to plan ahead and learn, it has a higher probability of success than conventional approaches. The adaptive behavior that will be achieved contribute to the integration of scheduling and control in FMS.     

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.     

Security concepts for the dynamics of autonomous vehicle networks

The secure operation of autonomous vehicle networks in the presence of adversarial observation is examined, in the context of a canonical double-integrator-network (DIN) model. Specifically, we study the ability of a sentient adversary to estimate the full network’s state, from noisy local measurements of vehicle motions. Algebraic, spectral, and graphical characterizations are provided, which indicate the critical role of the inter-vehicle communication topology and control scheme in achieving security.     

基于TCN的地铁列车控制方案的研究

本文针对地铁车厢内控制设备分散的问题,设计了基于TCNRTP的地铁列车控制网络系统。采用NS2网络模拟软件构建的虚拟网络环境,编写消息数据传输层协议,通过测试列控网络的通信效率,得出了影响通信效率的因素;通过配置列控通信设备的基本功能和设定装置运行参数达到配置网络化通信的目的。     

大学英语读写课堂教师提问的逻辑性调查分析

教师提问、学生回答是语言课堂中的一个逻辑过程。教师的提的问题和课堂模式具有逻辑艺术,与学生产生思维共振,教与学才能统一。通过对大学英语读、写、译课堂观摩调查结果的分析,提出重视课堂提问的逻辑性,让学习者开动脑筋把注意力从学什么转移到怎样学和怎样思考的问题上,从而提高语言学习者的学习能力、理解能力和表达能力。     

互文性视角下的杨译《红楼梦》典故的翻译策略

《红楼梦》中有大量的典故,充满着丰富的互文性。翻译过程中的互文指涉蕴含着深厚的历史文化沉淀。从互文性角度探讨杨宪益、戴乃迭夫妇所译《红楼梦》中典故翻译。认为译者充分发挥了主体性,把保留原语互文关系和文化特色放在首位,这对提高翻译质量和更好地传递典故的文化内涵有着重要的作用。