PDM电子仓库基于XML的4层分布式模型

在产品生命周期中存在着大量非结构化的产品文档,作为ＣＩＭＳ信息集成主体的ＰＤＭ系统存在着数据粒度过大的问题。ＸＭＬ语言的出现很好地解决了非结构化产品文档表达一致化的问题,提出了的４层分布式系统模型致力于解决ＰＤＭ系统中数据存储和访问 的难题,使ＸＭＬ产品文档在Ｗｅｂ上的浏览在室元素级的水平。     

基于SGML/XML的Internet信息发布

随着Ｉｎｔｅｒｎｅｔ技术的发展与应用的深入,特别是电子商务等深层次应用的迅速崛起,结构化地组织Ｉｎｔｅｒｎｅｔ上的信息,保持信息本身的结构与语义变得越来越重要。文章首先给出一种基于ＳＧＭＬ／ＸＭＬ进行结构化信息组织与Ｉｎｔｅｒｎｅｔ信息发布的模型,并重点讨论了实现该模型的两个关键问题：ＳＧＭＬ／ＸＭＬ信息的获取与信息的Ｉｎｔｅｒｎｅｔ发布。文中讨论的模型与关键问题对基于ＸＭＬ的应用系统具有很好的参     

SUPERBASE：一个CIM环境下面向对象的多数据库集成系统

ＳＵＰＥＲＢＡＳＥ是一个ＣＩＭ环境下面向对象的多数据库集成系统，其目标是有效地集成分布在多个已存在的自治和异构的局部数据库中的信息，以实现各系统间的信息共享。本文首先介绍了ＳＵＰＥＲＢＡＳＥ的体系结构、模式集成机制；然后讨论了全局数据库和局部数据库间的数据副本问题，提出了相应的解决方法；最后给出了集成数据模型ＩＤＭ和集成数据语言ＩＤＬ。     

基于STEP的集成技术研究

文章以８６３／ＣＩＭＳ示范工程的开发为依据,对基于ＳＴＥＰ的集成技术进行了深入研究。文中首先讨论了ＳＴＥＰ的原理及ＳＴＥＰ在集成系统中的作用,随后给出了集成环境中基于ＳＴＥＰ的集成产品信息模型总体结构,并对基于特征的产品模型进行了详细讨论,最后给出了产品信息模型的形式化描述。关键词##4ＳＴＥＰ;;产品模型;;特征;;ＣＩＭＳ     

IPEEE结构化图形支持工具的研究与实现

由于图形信息一目了然，几乎所有科学和工程技术领域都采用了可视化技术。本文首先描述了集成化过程工程环境ＩＰＥＥ的组成及系统结构和可视化过程建模语言ＶＰＭＬ的基本特点，然后详细介绍了该环境的图形支持工具结构化图形编辑器的生成工具ＳＧＥＧ、图形支持库ＧＳＬ和对象管理系统ＯＭＳ     

EUCLID—IS几何模型向MSC／XL的转换方法

本文提出了一种ＥＵＣＬＩＤ－ＩＳ几何模型向ＭＳＣ／ＸＬ的转换方法，通过该方法，用户可方便地利用造型功能相当完善的ＥＵＣＬＩＤ－ＩＳ来构造ＭＳＣ／ＸＬ的几何模型。     

STEP信息集成软件工具的设计和实现

ＳＴＥＰ是国际标准化组织ＩＳＯ正在组织开发的应用于计算机集成制造系统（ＣＩＭＳ）信息集成的产品数据表达与交换标准，ＳＴＥＰ不仅是一种规范，更是一种信息集成技术，本文以ＣＡＤ／ＣＡＰＰ／ＣＡＭ系统集成为背景，提出了ＳＴＥＰ信息集成支持工具ＥｘＴｒａ的设计和实现技术，该软件工具已成功且有效地应用于ＣＡＤ／ＣＡＰＰ／ＣＡＭ系统集成中。     

EUCLID－－IS数据库特点分析

ＥＵＣＬＩＤ－－ＩＳ数据库特点分析海军潜艇学院徐立国李海平一、前言ＥＵＣＬＩＤ－ＩＳ是工作站上的ＣＡＤ／ＣＡＭ系统软件，在我国的许多行业，特别是机械制造业，所采用的工作站上的ＣＡＤ／ＣＡＭ软件很多是ＥＵＣＬＩＤ－ＩＳ。ＥＵＣＬＩＤ－ＩＳ数据库在产品开...     

GHCAD：一个产品模型为基础的CAD／CAM集成系统

ＳＴＥＰ是关于产品数据表达和交换的国际标准，如何将ＳＴＥＰ的方法和规范应用于系统开发是解决计算机集成制造系统（ＣＩＭＳ）开发的关键问题之一。集成化ＣＡＤ／ＣＡＭ系统是ＣＩＭＳ的核心，实现将ＣＡＤ的工程设计功能和ＣＡＭ的制造功能的结合。本文介绍一个产品模型为基础的ＣＡＤ／ＣＡＭ集成系统－ＧＨＣＡＤ。系统采用ＳＴＥＰ的数据交换、建模思想，以产品模型为核心，通过ＳＴＥＰ的标准数据接口ＳＤＡＩ实现了系统的集成。     

自已动手架设UBB讨论区

安装ＡＣＴＩＶＥ ＰＥＲＬ ｌ由于 ＵＬＴＩＭＡＴＥ ＢＨＬＬＥＴＩＮＢＯＡＲＤ ＭＭ．Ｍ＊ｕ ＣＧＩ撰写的讨论区程序,因此如果要在ＷＩＮＤＯＷＳ环境下执行,就必须安装ＰＥＲＬ执行程序。所以首先请到这里下载免费的ＡＣＴＩＶＥＰＥＲＬ程序：ＨＴＴＰ：／／ＷＷＷ．ＡＣＴＩＶＥＳＴＡＴＥ．ＣＯＭ／ＤＯＷＮ－ＬＯＡＤ／ＡＣＴＩＶＥＰＥＲＬ／ＷＩＮＤＯＷＳ／５．６／ＡＣＴＩＶＥＰＥＲＬ－５．６．０．６２３－ＭＳＷＩＮ３２－Ｘ８６－ＭＵＬＴＩ—ＴＨＲＥＡＤ．ＭＳＩ。 下载完后,请直接执行ＡＣＴＩＶＥＰＥＲＬ－５．…     

A simple and effective method for filling gaps in Landsat ETM+ SLC-off images

The scan-line corrector (SLC) of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor failed in 2003, resulting in about 22% of the pixels per scene not being scanned. The SLC failure has seriously limited the scientific applications of ETM+ data. While there have been a number of methods developed to fill in the data gaps, each method has shortcomings, especially for heterogeneous landscapes. Based on the assumption that the same-class neighboring pixels around the un-scanned pixels have similar spectral characteristics, and that these neighboring and un-scanned pixels exhibit similar patterns of spectral differences between dates, we developed a simple and effective method to interpolate the values of the pixels within the gaps. We refer to this method as the Neighborhood Similar Pixel Interpolator (NSPI). Simulated and actual SLC-off ETM+ images were used to assess the performance of the NSPI. Results indicate that NSPI can restore the value of un-scanned pixels very accurately, and that it works especially well in heterogeneous regions. In addition, it can work well even if there is a relatively long time interval or significant spectral changes between the input and target image. The filled images appear reasonably spatially continuous without obvious striping patterns. Supervised classification using the maximum likelihood algorithm was done on both gap-filled simulated SLC-off data and the original “gap free” data set, and it was found that classification results, including accuracies, were very comparable. This indicates that gap-filled products generated by NSPI will have relevance to the user community for various land cover applications. In addition, the simple principle and high computational efficiency of NSPI will enable processing large volumes of SLC-off ETM+ data.     

ONTO-PDM: Product-driven ONTOlogy for Product Data Management interoperability within manufacturing process environment

This paper proposes an approach for facilitating systems interoperability in a manufacturing environment. It is based on the postulate that an ontological model of a product may be considered as a facilitator for interoperating all application software that share information during the physical product lifecycle. The number of applications involved in manufacturing enterprises may in fact refer to the knowledge that must be embedded in it, appropriately storing all its technical data based on a common model. Standardisation initiatives (ISO and IEC) try to answer the problem of managing heterogeneous information scattered within organizations, by formalising the knowledge related to product technical data. The matter of this approach is to formalise all those technical data and concepts contributing to the definition of a Product Ontology, embedded into the product itself and making it interoperable with applications, thus minimising loss of semantics.     

基于CORBA／Web技术的企业级信息系统集成

以制造企业产品远程协同设计制造为背景，基于分布式对象CORBA集成平台，在分布式异构网络环境下，研究基于Web的企业信息系统分布式应用互操作层次体系结构、异构信息数据资源及应用系统与Internet／Intranet的无缝接入方法。针对异地信息资源的远程访问与应用互操作的实现模型、实现方法与支撑机制进行论述，提出了企业级信息系统集成的分布式应用互操作体系结构模型与实现模型。     

基CORBA/Web技术的企业级信息系统集成

以制造企业产品远程协同设计制造为背景,基于分布式对象CORBA集成平台,在分布式异构网络环境下,研究基于Web的企业信息系统分布式应用互操作层次体系结构、异构信息数据资源及应用系统与Internet/In-tranet的无缝接入方法。针对异地信息资源的远程访问与应用互操作的实现模型、实现方法与支撑机制进行论述,提出了企业级信息系统集成的分布式应用互操作体系结构模型与实现模型。     

基于中性文件机制的异构PDM系统集成方法

异构PDM系统之间产品设计信息的集成是实现企业间集成的必要条件。文中提出了一种基于中性文件机制实现异构PDM系统产品设计信息交换的模式,建立了支持该模式的共享信息模型,并给出了基于共享信息模型开发异构PDM系统信息交换接口的方法。所提出的模型和解决方案,对实现异构PDM系统中各种信息的交换具有普遍意义。     

Enhanced default risk models with SVM+

Default risk models have lately raised a great interest due to the recent world economic crisis. In spite of many advanced techniques that have extensively been proposed, no comprehensive method incorporating a holistic perspective has hitherto been considered. Thus, the existing models for bankruptcy prediction lack the whole coverage of contextual knowledge which may prevent the decision makers such as investors and financial analysts to take the right decisions. Recently, SVM+ provides a formal way to incorporate additional information (not only training data) onto the learning models improving generalization. In financial settings examples of such non-financial (though relevant) information are marketing reports, competitors landscape, economic environment, customers screening, industry trends, etc. By exploiting additional information able to improve classical inductive learning we propose a prediction model where data is naturally separated into several structured groups clustered by the size and annual turnover of the firms. Experimental results in the setting of a heterogeneous data set of French companies demonstrated that the proposed default risk model showed better predictability performance than the baseline SVM and multi-task learning with SVM.     

Developing distributed applications for integrated product and process design

A heterogeneous computing environment characterizes today's manufacturing situation. This is a stumbling block for the efficient implementation of manufacturing concepts such as integrated product and process design (IPPD). A computing environment for IPPD would require the seamless integration of the various product and process design software systems. The exchange of information between these systems should be efficient, compatible and synchronous. This article presents an approach for developing distributed manufacturing applications that are compatible and synchronized and thus, able to support IPPD. The approach involves the use of a common manufacturing application ‘middleware’, which is distributed between a central geometric modelling server and application clients. The portability of the middleware is ensured through the use of Java for code portability and XML for data portability. The compatible product model problem is solved through the use of common data structures developed using reusable application client classes. Efficient transfer of product data is proposed using compressed model information embedded in a product data XML schema. Synchronization of design changes among all applications is achieved through the creation of relationships on an Application Relationship Manager.     

一种适合VRML应用的平面三角剖分快速算法

产品数据向Web使能数据的格式转换是实现异地,异构环境下产品信息共享的一条有效途径,VRML作为三维场景的描述语言得到了广泛应用,成为产品数据Web使能的载体,为了满足VRML应用的需要,提出了一种改进的从平面多连通域到单连通域的快速切分归并方法,介绍了一种任意平面通域的三角剖分算法,并对生成的三角面面片进行合并,整个算法具有速度快,生成三角面片较少的优点。     

Hermes: Data Web search on a pay-as-you-go integration infrastructure

The Web as a global information space is developing from a Web of documents to a Web of data. This development opens new ways for addressing complex information needs. Search is no longer limited to matching keywords against documents, but instead complex information needs can be expressed in a structured way, with precise answers as results. In this paper, we present Hermes, an infrastructure for data Web search that addresses a number of challenges involved in realizing search on the data Web. To provide an end-user oriented interface, we support expressive user information needs by translating keywords into structured queries. We integrate heterogeneous Web data sources with automatically computed mappings. Schema-level mappings are exploited in constructing structured queries against the integrated schema. These structured queries are decomposed into queries against the local Web data sources, which are then processed in a distributed way. Finally, heterogeneous result sets are combined using an algorithm called map join, making use of data-level mappings. In evaluation experiments with real life data sets from the data Web, we show the practicability and scalability of the Hermes infrastructure.     

Heterogeneous representation learning with separable structured sparsity regularization

Motivated by real applications, heterogeneous learning has emerged as an important research area, which aims to model the coexistence of multiple types of heterogeneity. In this paper, we propose a heterogeneous representation learning model with structured sparsity regularization (HERES) to learn from multiple types of heterogeneity. It aims to leverage the rich correlations (e.g., task relatedness, view consistency, and label correlation) and the prior knowledge (e.g., the soft-clustering of tasks) of heterogeneous data to improve learning performance. To this end, HERES integrates multi-task, multi-view, and multi-label learning into a principled framework based on representation learning to model the complex correlations and employs the structured sparsity to encode the prior knowledge of data. The objective is to simultaneously minimize the reconstruction loss of using the factor matrices to recover the heterogeneous data, and the structured sparsity imposed on the model. The resulting optimization problem is challenging due to the non-smoothness and non-separability of structured sparsity. We reformulate the problem by using the auxiliary function and prove that the reformulation is separable, which leads to an efficient algorithm family for solving structured sparsity penalized problems. Furthermore, we propose various HERES models based on different loss functions and subsume them into the weighted HERES, which is able to handle missing data. The experimental results in comparison with state-of-the-art methods demonstrate the effectiveness of the proposed approach.