An object-oriented product database using ROSE

A product database for a design and manufacturing enterprise serves as a repository for the data needed to manufacture a product. This paper discusses how an object-oriented persistent object manager named ROSE, under development at Rensselaer, has been used in the Rensselaer CIM program to develop a STEP/PDES-compliant product database for its research test bed. In so doing, it provides an overview of the requirements for a product database system in an integrated design and manufacturing facility, and it discusses how the chosen system meets these requirements.     

Bayes网络与关系模型的集成:概率关系模型

对象关系模型和Bayes网络分别是关系理论和概率理论两个不同领域中最重要的模型，它们首次集成于本文引入的概率关系模型中，作为新型的概率模型，概率关系模型不仅继承了Bayes网络的大部分优点，而且关系特征和对象的概念使它能有效地克服Bayes网络在许多方面的不足，而成为对复杂系统模建的理想工具，是对Bayes网络的重要创新；作为新型的关系模型，概率关系模型也是对传统关系模型的重要创新，具备概率特征的对象关系模型有了处理不确定性问题的能力。概率关系模型的创建对复杂智能信息系统开发研究有有着特别重要的意义，本文首先评述Bayes网络和对象关系模型，然后在此基础上引入概率关系模型。     

Nonlinear filtering structure for image smoothing in mixed-noise environments

This paper introduces a new nonlinear filtering structure for filtering image data that have been corrupted by both impulsive and nonimpulsive additive noise. Like other nonlinear filters, the proposed filtering structure uses order-statistic operations to remove the effects of the impulsive noise. Unlike other filters, however, nonimpulsive noise is smoothed by using a maximum a posteriori estimation criterion. The prior model for the image is a novel Markov random-field model that models image edges so that they are accurately estimated while additive Gaussian noise is smoothed. The Markov random-field-based prior is chosen such that the filter has desirable analytical and computational properties. The estimate of the signal value is obtained at the unique minimum of the a posteriori log likelihood function. This function is convex so that the output of the filter can be easily computed by using either digital or analog computational methods. The effects of the various parameters of the model will be discussed, and the choice of the predetection order statistic filter will also be examined. Example outputs under various noise conditions will be given.     

Combined-Stage Sintering Model

By focusing on the similarities between the three stages of sintering, a single equation is derived that quantifies sintering as a continuous process from beginning to end. The microstructure is characterized by two separate parameters representing geometry and scale. The dimensionless geometry parameter, denoted T, comprises five scaling factors that relate specific microstructural featuers (e.g., surface curvature) to the scale (grain diameter). Calculations of T from experimental data show (a) agreement with computer simulations of initial-stage sintering, (b) the effect of surface diffusion on T, and (c) changes in T with microstructural evolution during sintering. Application of the model to the design of firing schedules and the study of microstructural geometry effects on sintering is discussed.     

3D model retrieval using principal plane analysis and dynamic programming

Three dimensional models play an important role in many applications; the problem is how to select the appropriate models from a 3D database rapidly and accurately. In recent years, a variety of shape representations, statistical methods, and geometric algorithms have been proposed for matching 3D shapes or models. In this paper, we propose a 3D shape representation scheme based on a combination of principal plane analysis and dynamic programming. The proposed 3D shape representation scheme consists of three steps. First, a 3D model is transformed into a 2D image by projecting the vertices of the model onto its principal plane. Second, the convex hall of the 2D shape of the model is further segmented into multiple disjoint triangles using dynamic programming. Finally, for each triangle, a projection score histogram and moments are extracted as the feature vectors for similarity searching. Experimental results showed the robustness of the proposed scheme, which resists translation, rotation, scaling, noise, and destructive attacks. The proposed 3D model retrieval method performs fairly well in retrieving models having similar characteristics from a database of 3D models.