飞机火警系统智能测试设备的设计

火警系统是飞机上关系飞行安全的极其重要的设备之一,由于设计和使用环境等各方面的原因,火警系统可靠性差,尤其是虚警率较高,因此研制了飞机火警系统测试设备,它是一套数字采集式多参数智能综合测试系统;该设备以嵌入式工控机为核心,采用单元积木式结构,软件采用C语言编程,以Windows NT作为操作平台,用来管理整个系统的软、硬件资源;该智能综合测试设备具有可靠性高、通用性好,使用、操作简便直观,测试过程程序化、自动化,对测试环境的适应能力强等优点;经使用,该设备功能齐全,技术先进,性能优越,对保证飞行安全具有十分重要的意义。     

A -based layout design for gratings allocation

In the design process of gratings, the grating layout design is the most important activity influencing manufacturing cost. In the grating layout design, the key to saving manufacturing cost is to find a design with a minimal number of cutting operations. This paper presents an application of the A^* algorithm in grating layout design. The design problem is represented as the space search problem of design alternatives. A^* explores the feasible alternatives within the space, until an optimal solution is obtained.     

基于ADE7758芯片的同步发电机智能数据采集系统设计

介绍了一种基于ADE7758的同步发电机智能数据采集系统的设计,在简要描述ADE7758基本特性的基础上,重点阐述了系统的硬件设计和软件设计.系统采集数据丰富,工作稳定可靠,测量精度高,凸显了智能性.     

网络时代的人工智能

五十多年来,人工智能在模式识别、知识工程、机器人等领域已经取得重大成就,但是离真正的人类智能还相差甚远。本文强调 在当今的网络时代,作为信息技术的先导,人工智能科学有着非常值得关注的研究方向,要在学科交叉研究中实现人工智能的发展与创新。要关注认知科学、脑科学、生物智能、物理学、复杂网络、计算机科学与人工智能之间的交叉渗透,尤其是重视认知物理学的研究;自然语言是人类思维活动的载体,是人工智能研究知识表示无法回避的直接对象,要对语言中的概念建立起能够定量表示的不确定性转换模型,发展不确定性人工智能;要利用现实生活中复杂网络的小世界模型和无尺度特性,把网络拓扑作为知识表示的一种新方法,研究网络拓扑的演化与网络动力学行为,研究网络化了的智能,从而适应信息时代数据挖掘的普遍要求,迎接人工智能科学与应用新的辉煌。     

基于派生文法的日—蒙动词短语机器翻译研究

本文探索了源语为日语,目标语为蒙古语的动词短语机器翻译系统的实现方式。基于主张日语不活用的派生文法,重新分析日语附加成分。将日语的词干和附加成分转换到蒙古语的词干和附加成分之后,运用蒙古语的语音规则来处理并生成动词短语。在此基础上试做了日—蒙动词短语机器翻译系统。对30篇日文报道的403个动词短语进行测试,取得了95.78% 的正确率。     

Building brains for bodies

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We are building an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to think by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.     

An application of artificial intelligence to the choreography of dance

This paper describes an experimental computer program that applies the techniques of artificial intelligence to the creation of dance. Specifically, a user expresses a set of dance rules (in a special English-like rule language) which describes some of the dynamic aspects of a dance. These rules are applied nondeterministically by a rule driver program. The rules themselves are similar to those that form the knowledge base of expert systems. The rule driver embodies a heuristic algorithm of the type found in many artificial intelligence programs.James H. Bradford is an Associate Professor of Computer Science at Brock University. He is an active researcher in the area of Human/Computer Interaction with particular interests in the analysis of speech and the representation of dance.Paulette Côté-Laurence is an Associate Professor of Physical Education at Brock University. Her research interests are in the areas of motor control and the acquisition of dance skills, psychology of rhythm, and dance technology.     

Hownot to demarcate cognitive science and folk psychology: A response to Pickering and Chater

Pickering and Chater (P&C) maintain that folk psychology and cognitive science should neither compete nor cooperate. Each is an independent enterprise, with a distinct subject matter and characteristic modes of explanation. P&C's case depends upon their characterizations of cognitive science and folk psychology. We question the basis for their characterizations, challenge both the coherence and the individual adequacy of their contrasts between the two, and show that they waver in their views about the scope of each. We conclude that P&C do not so muchdiscover ascreate the gap they find between folk psychology and cognitive science. It is an artifact of their implausible and unmotivated attempt to demarcate the two areas, and of the excessively narrow accounts they give of each.     

Analytics of learning tactics and strategies in an online learnersourcing environment

Background

The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored.

Objectives

To contribute to filling this gap, this study explores how students engage with learnersourcing tasks across a range of course and assessment designs.

Methods

We conducted an exploratory study on trace data of 1279 students across three courses, originating from the use of a learnersourcing environment under different assessment designs. We employed a new methodology from the learning analytics (LA) field that aims to represent students' behaviour through two theoretically-derived latent constructs: learning tactics and the learning strategies built upon them.

Results

The study's results demonstrate students use different tactics and strategies, highlight the association of learnersourcing contexts with the identified learning tactics and strategies, indicate a significant association between the strategies and performance and contribute to the employed method's generalisability by applying it to a new context.

Implications

This study provides an example of how learning analytics methods can be employed towards the development of effective learnersourcing systems and, more broadly, technological educational solutions that support learner-centred and data-driven learning at scale. Findings should inform best practices for integrating learnersourcing activities into course design and shed light on the relevance of tactics and strategies to support teachers in making informed pedagogical decisions.     

生物视觉系统的神经网络编码模型综述

生物视觉系统的研究一直是计算机视觉算法的重要灵感来源。有许多计算机视觉算法与生物视觉研究具有不同程度的对应关系,包括从纯粹的功能启发到用于解释生物观察的物理模型的方法。从视觉神经科学向计算机视觉界传达的经典观点是视觉皮层分层层次处理的结构。而人工神经网络设计的灵感来源正是视觉系统中的分层结构设计。深度神经网络在计算机视觉和机器学习等领域都占据主导地位。许多神经科学领域的学者也开始将深度神经网络应用在生物视觉系统的计算建模中。深度神经网络多层的结构设计加上误差的反向传播训练,使得它可以拟合绝大多数函数。因此,深度神经网络在学习视觉刺激与神经元响应的映射关系并取得目前性能最好的模型同时,网络内部的单元甚至学习出生物视觉系统子单元的表达。本文将从视网膜等初级视觉皮层和高级视觉皮层(如,视觉皮层第4区(visual area 4,V4)和下颞叶皮层(inferior temporal,IT))分别介绍基于神经网络的视觉系统编码模型。主要内容包括:1)有关视觉系统模型的概念与定义;2)初级视觉系统的神经网络预测模型;3)任务驱动的高级视觉皮层编码模型。最后本文还将介绍最新有关无监督学习的神经编码...