实现多数据源集成与互操作的扩展视图方法

文中针对多数据源集成与互操作提出了一种扩展视图方法．其基本思想是：以扩展对象模型（ＥＯＭ）为理论基础，通过扩展视图方法实现对多种数据源中的数据（对象）进行多层抽象与封装，以此满足分布环境下不同层次的应用集成需求．文中还讨论了扩展对象模型（ＥＯＭ）、基于扩展视图方法的集成机制，并结合具体的实例给出了扩展视图方法的形式化描述。

一种基于立体视觉的多视点建模方法

论述了一种基于立体视觉的建模方法。该方法利用立体视觉系统在不同视点对景物观测所获得的局部三维几何模型，通过空间特征点匹配和坐标变换将局部模型融合，从而建立景物的完整描述。文章重点介绍了一种基于空间向量的坐标变换求解方法。

基于神经网络的三维物体姿态测定

利用单幅图象中物体的三条边与模型中的三条对应边,可求出三维物体姿态,但解不唯一,通过将这些可能姿态所产生的图象与实际图象匹配,可求出唯一正确姿态.二维图象特征对应问题是个NP完全问题,存在组合爆炸的困难,为此,我们把特征对应问题看作一个组合优化问题,利用Hopfield网络成功解决这一组合优化问题.该算法通用性强,而且适合于并行实现。文中给出了在Ⅵ-COM图象处理系统上对人造图象和实际图象进行的实验结果。

企业经营系统的对象模型──资金流模型

本文阐述了大型工业企业综合自动化系统体系结构中经营管理层的对象模型（资金流模型）。首先论述了该模型在自动化体系结构中的地位和作用，然后分析了企业生产经营过程中发生的资金流，提出用借贷流程图方法表达资金流模型，并将这一方法与国际通用的借贷记帐法相联系，从而揭示了资金流模型与会计核算的内在联系．本文还对企业生产与经营活动的几个主要过程用借贷流程图进行了细化描述。

Absolute measurement of roughness and lateral-correlation length of random surfaces by use of the simplified model of image-speckle contrast

We present a method of image-speckle contrast for the nonprecalibration measurement of the root-mean-square roughness and the lateral-correlation length of random surfaces with Gaussian correlation. We use the simplified model of the speckle fields produced by the weak scattering object in the theoretical analysis. The explicit mathematical relation shows that the saturation value of the image-speckle contrast at a large aperture radius determines the roughness, while the variation of the contrast with the aperture radius determines the lateral-correlation length. In the experimental performance, we specially fabricate the random surface samples with Gaussian correlation. The square of the image-speckle contrast is measured versus the radius of the aperture in the 4f system, and the roughness and the lateral-correlation length are extracted by fitting the theoretical result to the experimental data. Comparison of the measurement with that by an atomic force microscope shows our method has a satisfying accuracy. (C) 2002 Optical Society of America.

The Effects of Visual Object Size in The Depth Perception in KM Mouse

Whether mice perceive the depth of space dependent on the visual size of object targets was explored when visual cues such as perspective and partial occlusion in space were excluded. A mouse was placed on a platform the height of which is adjustable. The platform located inside a box in which all other walls were dark exception its bottom through that light was projected as a sole visual cue. The visual object cue was composed of 4x4 grids to allow a mouse estimating the distance of the platform relative to the grids. Three sizes of grids reduced in a proportion of 2/3 and seven distances with an equal interval between the platform and the grids at the bottom were applied in the experiments. The duration of a mouse staying on the platform at each height was recorded when the different sizes of the grids were presented randomly to test whether the Judgment of the mouse for the depth of the platform from the bottom was affected by the size information of the visual target. The results from all conditions of three object sizes show that time of mice staying on the platform became longer with the increase in height. In distance of 20 similar to 30 cm, the mice did not use the size information of a target to judge the depth, while mainly used the information of binocular disparity. In distance less than 20 cm or more than 30 cm, however, especially in much higher distance 50 cm, 60 cm and 70 cm, the mice were able to use the size information to do so in order to compensate the lack of binocular disparity information from both eyes. Because the mice have only 1/3 of the visual field that is binocular. This behavioral paradigm established in the current study is a useful model and can be applied to the experiments using transgenic mouse as an animal model to investigate the relationships between behaviors and gene functions.

The application of DBF neural networks for object recognition

On the basis of DBF nets proposed by Wang Shoujue, the model and properties of DBF neural network were discussed in this paper. When applied in pattern recognition, the algorithm and implement on hardware were presented respectively. We did experiments on recognition of omnidirectionally oriented rigid objects on the same level, using direction basis function neural networks, which acts by the method of covering the high dimensional geometrical distribution of the sample set in the feature space. Many animal and vehicle models (even with rather similar shapes) were recognized omnidirectionally thousands of times. For total 8800 tests, the correct recognition rate is 98.75%, the error rate and the rejection rate are 0.5% and 1.25% respectively. (C) 2003 Elsevier Inc. All rights reserved.

基于MDA的TRISO-Model模型管理方法及应用

TRISO-Model(tridimensional integrated software development model)是为处理软件开发的复杂性和动态性而提出的三维集成软件开发方法学,其中,多维模型之间的语义一致性维护以及对模型应用中公共操作部分的重用,提出了基于一致语义进行模型管理的需求.给出了基于MDA(model driven architecture)进行模型管理的方法MDA-MMMethod(MDA based model management method),应用MDA的4层模型管理结构,基于MDA核心标准MOF(meta object facility)所提供的公共语义基础管理模型和元模型,MDA-MMMethod支持各种MDA模型操作标准实现在TRSIO-model应用中的重用.开发了相应的支持系统MDA-MMSystem(MDA based model management system),应用于SoftPM的项目实践中.与传统方法相比,模型应用的开发效率得到了显著提高,同时降低了开发成本.最后,给出了模型融合的应用实例介绍.

Elliptic Object Detection Based on Shape Preserving and Active Contour

本文通过形状约束方程(组)与一般主动轮廓模型结合,将目标形状与主动轮廓模型融合到统一能量泛函模型中,提出了一种形状保持主动轮廓模型即曲线在演化过程中保持为某一类特定形状。模型通过参数化水平集函数的零水平集控制演化曲线形状,不仅达到了分割即目标的目的,而且能够给出特定目标的定量描述。根据形状保持主动轮廓模型,建立了一个用于椭圆状目标检测的统一能量泛函模型,导出了相应的Euler-Lagrange常微分方程并用水平集方法实现了椭圆状目标检测。此模型可以应用于眼底乳头分割,虹膜检测及相机标定。实验结果表明,此模型不仅能够准确的检测出给定图像中的椭圆状目标,而且有很强的抗噪、抗变形及遮挡性能。

Resolution deterioration in emission electron microscopy due to object roughness

In the present paper a general analytic expression has been obtained and confirmed by a computer simulation which links the surface roughness of an object under study in an emission electron microscope and it's resolution. A quantitative derivation was made for the model case when there is a step on the object surface. It was shown that the resolution is deteriorated asymmetrically relative to the step. The effect sets a practical limit to the ultimate lateral resolution obtainable in an emission electron microscope.