A FORMAL REPRESENTATION FOR FEATURE-BASED DESIGN

从三个方面研究了基于特征设计的形式化描述方法：基于特征设计的基本定义、设计过程模型及设计算法。文中给出了特征分类、特征操作、特征模型验证和特征映射策略及其形式化描述方式，建立了兼顾并行工程和顺序工程设计方式的基于特征设计过程形式化描述模型，提出了基于特征的设计算法，为解决基于特征设计系统开发和运行缺乏统一方法学这一课题作了有益的尝试。     

微结构的拓扑表达模型及自由排布阵列加工方法

制造过程中需要微结构阵列的数学模型从而进行图纸设计、刀具补偿计算、切深数据生成等.本文从拓扑原理出发,结合方向关系与距离关系,得到微结构阵列空间关系的统一表达模型.搭建快刀伺服加工实验平台,利用统一表达模型,并以具体样例加工了微透镜阵列,实现了自由排布的微结构加工.     

可靠性及可靠性灵敏度分析的改进点估计方法

针对低维高度非线性问题,提出了一种可靠 性及可靠性灵敏度分析的改进的点估计方法。基本思想是首先由空间分割来降低局部子空间 中功能函数的非线性程度,然后用低精度的稀疏网格积分探索子空间中功能函数的概率响应 特性,最后组合子空间中的信息来得到所需的可靠性及其灵敏度分析结果。方法的优点 是适用于低维高度非线性功能函数的失效概率和可靠性灵敏度分析,由于无需求解功能函数 的梯度函数,因此适用于复杂的隐式功能函数。另外,由于方法利用少量均匀抽样来估计对 失效概率贡献最大的点,并依据其进行子空间的划分,从而使得子空间的划分更有利于提高 可靠性及可靠性灵敏度分析的效率。用算例对所提方法进行了验证,结果表明：在低维高度 非线性条件下,所提算法的精度和效率比类似的三点估计、直接稀疏网格积分方法有明显优 势。     

红外与可见光图像融合的空间碎片识别方法

针对暗弱空间环境中空间碎片的识别问题,提出了一种光照不均匀环境中的空间碎片识别方法。不同于现有识别方案,该方法从光照不均匀导致空间碎片图像源细节丢失造成识别性能下降的角度出发,首先将空间碎片的红外和可见光图像进行深度融合,并建立空间碎片融合图像数据库,然后基于训练样本采用深度学习技术训练得到空间碎片识别模型。算法分析表明,该图像融合方案具有高度的细节保留能力,识别模型具有在暗弱环境中高精度目标识别能力。最后进行了仿真实验,实验结果表明,该识别方案在姿态变化、图像源亮度变化等干扰条件下都具有较好的鲁棒性。     

飞机结构有限元模型化的智能化方法应用研究

针对飞机结构的复杂性,提出了适用于飞机结构有限元模型化各阶段的整体式知识表达模型,并在此基础上,以 NASTRAN软件为依托,构造了基于推理和算法任务调度的有限元模型化过程求解模型,侧重剖析了模型化各阶段的具体分解任务内容。通过应用实例,说明其有效性。     

Bottom-Up Saliency Estimation Based on Redundancy Reduction and Global Contrast

A new algorithm for bottom-up saliency estimation is proposed. Based on the sparse coding model, a power spectral filter is proposed to eliminate the second-order residual correlation, which suppresses the global repeated items effectively. In addition, aiming at modeling the mechanism of the human retina prior response to high-contrast stimuli, the effect of color context is considered. Experiments on the three publicly available databases and some psychophysical images show that the proposed model is comparable with the state-of-the-art saliency models, which not only highlights the salient objects in a complex environment but also pops up them uniformly.     

Object-based representations of spatial images

Object based representations of image data enable new content-related functionalities while facilitating management of large image databases. Developing such representations for multi-date and multi-spectral images is one of the objectives of the second phase of the Alexandria Digital Library (ADL) project at UCSB. Image segmentation and image registration are two of the main issues that are to be addressed in creating localized image representations. We present in this paper some of the recent and current work by the ADL's image processing group on robust image segmentation, registration, and the use of image texture for content representation. Built upon these technologies are techniques for managing large repositories of data. A texture thesaurus assists in creating a semantic classification of image regions. An object-based representation is proposed to facilitate data storage, retrieval, analysis, and navigation.     

Space,Language and Ontology: A Response to Davis

Abstract

Ernest Davis' article “Qualititative Spatial Reasoning in Interpreting Text and Narrative” discusses challenges that the interpretation of natural language appears to raise for the formalization of commonsense spatial reasoning. Davis finds these to be of “surprising logical complexity,” but also “erratic” in that they do not show a logical structuring of the problem space that could guide productive research. In this response I argue that much of the apparent lack of structure Davis laments is due to the very style of formal modeling he pursues. By augmenting logical considerations with substantial input from other disciplines and by adopting a heterogeneous and modular approach to formalization, I suggest that the problem space is by no means as ill-structured as Davis presents it.