变精度下近似算子与程度上近似算子的逻辑与运算模型

基于精度与程度的逻辑与需求,提出了变精度下近似算子与程度上近似算子的逻辑与运算模型。在该模型中,得到了变精度下近似算子与程度上近似算子的逻辑与运算的精确描述与基本性质,提出了宏观算法与微观算法,进行了算法分析与比较,得到了微观算法更具空间优势的结论。最后用医疗实例对模型与算法进行了说明。变精度下近似算子与程度上近似算子的逻辑与运算模型,部分拓展了变精度粗糙集模型、程度粗糙集模型和经典粗糙集模型,并在这些模型中得到了近似算子的相应性质。     

统一资源库的研究与实现

在分析了资源与资源库建设的现状后,提出了统一资源库的概念以简化资源的交换、共享与访问,研究了其实现的技术途径,并设计与实现了其原型系统一URMS,验证了统一资源库的可行性与效率。     

计算机技术与虚拟技术的协同发展

计算机技术的实现与迅速发展,带动了诸多领域的信息技术变革,拓宽了虚拟技术在社会领域的应用。文章从计算机技术与虚拟技术的实践化应用角度出发,简要概述了计算机技术与虚拟技术的相关概念,分析了虚拟技术工作原理,研究了计算机技术与虚拟技术协同发展的特点,并在此基础上探讨了计算机技术与虚拟技术的应用现状与基于虚拟技术的多台计算机协同发展。计算机技术作为一种技术手段,在与虚拟技术有机融合并协同发展的过程中,必将为人们的生产与生活带来了极大的便利。     

基于LonWorks的高校校区智能安防与管理系统的研究

该文简单分析了LonWorks技术的特点,分析了高校校区安防与管理系统的需求与实现,研究了高校校区安防与管理系统.     

基于目标实现的MAS群体模型

本文研究了基于目标或工作实现的MAS群体中协同与冲突的分析与计算。首先建立了相应的数学模型,然后应用Rough集方法讨论了模型系统中的协同与冲突度量,最后研究了系统中不参与协同与冲突的Agent对于系统状态的作用与影响。     

基于联邦式作战仿真的高层体系结构及其应用

本文详细阐述了美军HLA的系统结构及其建模与仿真的环境与原理,介绍了我国在借鉴HLA的思想与经验基础上对分布式交互仿真技术的开发与应用,最后给出了研究与开发中要注意的问题。     

机器意识研究综述

意识问题是尚未解决的重大哲学问题与科学问题.机器意识是人工智能最前沿的研究领域之一.研发意识机器人对于人工智能与机器人学的发展具有重要科学意义与应用价值.本文首先介绍了意识与感受性的相关概念和理论;然后,详细讨论了机器意识的概念与研究分类、实现方法与计算模型,重点论述了实现机器意识的量子方法;最后,总结了机器意识目前面临的困境与未来可能的发展,并给出了一套机器意识总体实现框架.     

浅析计算机技术与信息技术

本文分析了计算机与信息技术的定义、本质与特征,提出了文化教育模式,讨论了计算机文化教育与教育信息化、科技教育、素质教育的关系。     

基于PDM的EDA集成关键技术研究与实现*

提出了产品数据管理(PDM)与电子设计辅助(EDA)集成的主要框架;阐述了PDM与EDA集成的主要内容,并对数据存储、BOM文件处理以及安全管理等关键技术进行了深入研究;总结了PDM与EDA集成的主要实现步骤;通过实例描述了PDM与EDA集成的整个过程.     

计算机学院学科建设与专业建设的探讨

阐述了高等院校的学科与专业、学科建设与专业建设的内涵及其相互关系,论述了学科建设与专业建设的基本要素,指出了计算机学院在还没有本科专业的情况下提出学科建设的原因及其必要性,探讨了计算机学院的学科建设与专业建设,提出了加强学科建设与专业建设方法和思路。     

POS-MIS系统应用实例分析

通过一个实际企业的POS-MIS系统具体实例,描述了该系统所需的软硬件环境,介绍其中采用的常用技术,并进一步考虑新产品的出现给POS-MIS系统添入新的活力。希望企业在实际应用中能从自身实际出发,对应用软件系统的使用及其关键技术能有个透彻的理解,能最大限度发挥信息系统的作用,能在激烈市场竞争中以最小的投入获得最大的回报。     

Principal Angles Separate Subject Illumination Spaces in YDB and CMU-PIE

The theory of illumination subspaces is well developed and has been tested extensively on the Yale Face Database B (YDB) and CMU-PIE (PIE) data sets. This paper shows that if face recognition under varying illumination is cast as a problem of matching sets of images to sets of images, then the minimal principal angle between subspaces is sufficient to perfectly separate matching pairs of image sets from nonmatching pairs of image sets sampled from YDB and PIE. This is true even for subspaces estimated from as few as six images and when one of the subspaces is estimated from as few as three images if the second subspace is estimated from a larger set (10 or more). This suggests that variation under illumination may be thought of as useful discriminating information rather than unwanted noise.     

Cost-effective solution to synchronised audio-visual data capture using multiple sensors

Applications such as surveillance and human behaviour analysis require high-bandwidth recording from multiple cameras, as well as from other sensors. In turn, sensor fusion has increased the required accuracy of synchronisation between sensors. Using commercial off-the-shelf components may compromise quality and accuracy due to several challenges, such as dealing with the combined data rate from multiple sensors; unknown offset and rate discrepancies between independent hardware clocks; the absence of trigger inputs or -outputs in the hardware; as well as the different methods for time-stamping the recorded data. To achieve accurate synchronisation, we centralise the synchronisation task by recording all trigger- or timestamp signals with a multi-channel audio interface. For sensors that don't have an external trigger signal, we let the computer that captures the sensor data periodically generate timestamp signals from its serial port output. These signals can also be used as a common time base to synchronise multiple asynchronous audio interfaces. Furthermore, we show that a consumer PC can currently capture 8-bit video data with 1024 × 1024 spatial- and 59.1 Hz temporal resolution, from at least 14 cameras, together with 8 channels of 24-bit audio at 96 kHz. We thus improve the quality/cost ratio of multi-sensor systems data capture systems.     

Visual Foxpro教学中研究性学习的探索与实践

本文从研究性学习的特点入手,从学习目标、学习内容、课题的实施以及学习的最终评价等方面探讨了研究性学习在Visualfoxpro程序设计课程教学中的应用进行的一点探索,以及实践过程的简要描述。     

Solving discretized optimization problems by partially reduced SQP methods

The solution of discretized optimization problems is a major task in many application areas from engineering and science. These optimization problems present various challenges which result from the high number of variables involved as well as from the properties of the underlying process to be optimized. They also provide several strucures which have to be exploited by efficient numerical solution approaches. In this paper we focus on partially reduced SQP methods which are shown to be particularly well suited for this problem class. In practical applications the efficiency of this approach is demonstrated for optimization problems resulting from discretized DAE as well as from discretized PDE. The practically important issues of inexact solution of linearized subproblems and of working range validation are tackled as well. Received: 17 April 1997 / Accepted: 2 September 1997     

DS/CDMA系统中多址干扰的消除

在直接序列扩频/码分多址(DS/CDMA)系统中由于各用户之间的影响而使其容量受到很大限制。通常这种用户之间的影响是作为噪声来处理的。本文讨论了多址干扰问题,从另一不同的角度出发,即把用户之间的影响作为有用信息,对多个用户的数据信息进行联合判决,提出了提高判决准确性的方案。     

基于辛空间的具有仲裁的认证码的构造

具有仲裁的认证码既要防止敌手的欺骗,又要防止收方和发方的互相欺骗。该文给出一种由辛几何构造具有仲裁的认证码的方法,并计算了有关参数,分析了各种攻击成功的概率。     

Visual Foxpro教学中研究性学习的探索与实践

本文从研究性学习的特点入手,从学习目标、学习内容、课题的实施以及学习的最终评价等方面探讨了研究性学习在Visualfoxpro程序设计课程教学中的应用进行的一点探索,以及实践过程的简要描述。     

What artificial experts can and cannot do

One's model of skill determines what one expects from neural network modelling and how one proposes to go about enhancing expertise. We view skill acquisition as a progression from acting on the basis of a rough theory of a domain in terms of facts and rules to being able to respond appropriately to the current situation on the basis of neuron connections changed by the results of responses to the relevant aspects of many past situations. Viewing skill acquisition in this ways suggests how one can avoid the problem currently facing AI of how to train a network to make human-like generalizations. In training a network one must progress, as the human learner does, from rules and facts to wholistic responses. As to future work, from our perspective one should not try to enhance expertise as in traditional AI by attempting to construct improved theories of a domain, but rather by improving the learner's access to the relevant aspects of a domain so as to facilitate learning from experience.     

Urban scene understanding from aerial and ground LIDAR data

We present a framework to segment cultural and natural features, given 3D aerial scans of a large urban area, and (optionally) registered ground level scans of the same area. This system provides a primary step to achieve the ultimate goal of detecting every object from a large number of varied categories, from antenna to power plants. Our framework first identifies local patches of the ground surface and roofs of buildings. This is accomplished by tensor voting that infers surface orientation from neighboring regions as well as local 3D points. We then group adjacent planar surfaces with consistent pose to find surface segments and classify them as either the terrain or roofs of buildings. The same approach is also applied to delineate vertical faces of buildings, as well as free-standing vertical structures such as fences. The inferred large structures are then used as geometric context to segment linear structures, such as power lines, and structures attached to walls and roofs from remaining unclassified 3D points in the scene. We demonstrate our system on real LIDAR datasets acquired from typical urban regions with areas of a few square kilometers each, and provide a quantitative analysis of performance using externally provided ground truth.