基于VRML的航天模拟训练系统

使用虚拟现实建模语言（VRML）建立一个航天地面设备仿真实验和导弹弹体虚拟装配的模拟训练系统，操作者可使用浏览器通过网络进行交互式的虚拟实验和弹体装配，实现航天工程中部分高成本，高代价的实物操作训练功能，该系统具有较好的真实效果，显示了虚拟现实技术在航天工程中的广阔应用前景。     

数字波束形成技术在雷达中的应用

由于电磁工作环境的恶化和大量射频干扰的存在,在极低的信干噪比(SINR)条件下进行目标检测和信息提取十分困难.对于阵列系统,往往采用自适应数字波束形成(ADBF)技术,来抑制强干扰和方向性干扰对有用信号的影响.给出了数字波束形成器的基本原理及其工程实现.     

无线电陆空通话英语交际能力模型研究

民航无线电陆空通话语言是以英语为载体的一种空地交流的特殊语言。本文在应用语言学的研究成果之上,提出了该语言的交际能力模型,该模型包括语言能力、策略能力、背景知识和心理生理机制四个部分。笔者结合民航陆空通话实际,对模型各个部分进行了分析,重点解析了策略能力在模型中的核心功能。     

基于Matlab语言的系统可靠性仿真

Matlab是一种高性能数值计算语言 ,本文用Matlab语言编制系统可靠性仿真程序 ,并给出了具体实例。此方法比其他方法简单有效 ,可适用于复杂系统。     

基于实测数据的海杂波时空相关性分析

海杂波的相关特性分为时间相关性和空间相关性,二者均与雷达系统参数、环境条件等多种因素有关。文章利用X波段雷达实测海杂波数据,重点研究了不同极化条件下海杂波的时间相关性、高低典型海况和不同入射余角条件下的海杂波距离向和方位向空间相关性。经大量实测数据验证表明,极化方式对海杂波强时间相关性影响较小,海杂波距离向空间相关性受海况影响较大、方位向相邻分辨单元空间相关性较弱,这些结论对于海杂波中目标检测方法优化设计具有重要意义。     

航电系统安全性分析工具设计与研究

随着航电系统综合化程度的不断提高,传统的安全性分析方法过于依赖工程经验,难以保证失效模式的完备性。同时在系统迭代设计的过程中,由于系统的复杂性,会导致安全性分析工作量过大,增加了时间及经济成本。针对上述问题,设计了一种自动化安全性分析工具,基于Sys ML描述语言建立安全性数据模型,采用路径追溯的方法完成故障树自动建模,并对生成的故障树进行共模分析和区域安全性分析。以某系统为例的实验结果表明,该工具能够实现故障树自动建模与分析,提高了安全性分析的效率和完备性。     

Mining Spatial Associations with Limited Sensory Information

Abstract

Human navigation in an unknown environment requires an understanding of the spatial relationships of the terrain. For example, a soldier who is on a reconnaissance mission in a new city needs to “know” the spatial layout of the surroundings with high confidence. Oftentimes, this understanding must be acquired within a very short amount of time and with limited sensory inputs. The soldier would benefit from a digital avatar that draws inferences about the spatial layout of the city based on an initial set of observations and guides the soldier either in further exploring the environment or in making decisions based on these inferences. In this paper, we present and evaluate an inductive approach to learning spatial associations using sensory data that is available from the simulation environment of a computer game, Unreal Tournament. We study two kinds of spatial relationships between nodes on a level of a game map: nodes that are placed near each other to satisfy some spatial requirement and nodes that are placed near each other to satisfy the design preferences of a level architect. We show that we can infer both kinds of relationships using an association rule mining algorithm. Furthermore, we show how to use an ontology to distinguish between these relationships in order to discover different types of spatial arrangements on a specific map. We discuss how the inferred associations can be used to control an avatar that makes recommendations for navigating unexplored areas on a map. We conclude with some thoughts on the applicability of our methods to scenarios in the real world, beyond the simulation environment of a game, and on how the learned associations can be represented and queried by a simple question-answer type system.     

The Space within Fisherman's Folly: Playing with a Puzzle in Mereotopology

Abstract

In this paper we propose a spatial ontology for reasoning about holes, rigid objects and a string, taking a classical puzzle as a motivating example. In this ontology the domain is composed of spatial regions whereby a theory about holes is defined over a mereotopological basis. Within this theory we define a data structure, named chain, that facilitates a clear and efficient representation of the puzzle states and its solution.     

Spatio-Temporal Ontologies and Attention

ABSTRACT

This paper presents a new proposal for the design of spatio-temporal ontologies which has its origin in cognitively motivated spatial semantics. It is shown that selective attention not only plays a central role in the characterization of spatial relations but that the representation of attentional aspects also leads to the possibility of defining an ontological upper structure which systematically covers both the spatial and the temporal domain.     

Expert Algorithmic and Imagistic Problem Solving Strategies in Advanced Chemistry

Abstract

Visualization and imagistic reasoning appear central to expert practice in science; however, expert use of these strategies on authentic tasks has not been examined in detail. This study documents how science experts use both algorithms and imagistic reasoning to solve problems. Using protocol analysis, we report expert chemists' preferential use of algorithms for solving spatial problems and imagistic reasoning for deducing spatial transformations. We observed experts employ algorithms to solve the majority of spatial tasks while reserving imagistic strategies to solve a class of tasks that required translating between representations. Strategy used varied widely among experts and tasks.