Transformation of a thin-walled solid model into a surface model via solid deflation

A simplified geometric model with lower dimensionality, such as a mid-surface model, is often preferred over a detailed solid model for the analysis process, if the analysis results are not seriously impacted. In order to derive a mid-surface model from a thin-walled solid model, in this paper, we propose a novel approach called the solid deflation method. In this method, a solid model is assumed to be created by using air to inflate a shell that comprises the surface of the solid model. First, the model is simplified by the removal of any detailed features whose absence would not alter its overall shape. Next, the solid model itself can be converted into a degenerate solid model with zero thickness. Finally, a surface model is generated by splitting large faces paired in the thinned solid model, selecting one face per pair for creating a sheet model, and sewing the selected faces. Using this method, a more practical and usable mid-surface model can be very efficiently generated from a solid model because it can circumvent not only the tedious trimming and extension processes of the medial axis transformation method but also the time-consuming patch joining process of the mid-surface abstraction approach.     

细粒度的基于角色的访问控制模型

RBAC模型是一种被广泛应用的访问控制模型。但是,RBAC模型是在角色级管理和控制权限,不能满足用户获得角色的部分权限和角色权限的部分继承等安全需求。针对这个问题,在RBAC模型中增加权限的重要程度要素,提出了FGRBAC模型（Fine-Grained Role-Based Access Control Model--细粒度的基于角色的访问控制模型）,并给出了在FGRBAC模型中求用户权限和角色权限的算法。FGRBAC模型不仅可以使用户获得角色的部分权限、父角色可以继承子角色的部分权限,而且RBAC模型可被看成是FGRBAC模型的一种特例。因此,FGRBAC模型不仅具有RBAC模型的所有优点,而且比RBAC模型具有更好的灵活性和实用性。     

基于认知理论和随机开放性测试的动态学生建模研究

论文从认知理论出发,提出了一种实用的学生建模方法,即以信息模型和学习模型的组合形式进行学生建模,并采用认知模型、覆盖模型和测试模型对学习模型进行描述。该学生模型可以很好地实现学生模型的动态修改以及教学策略的自适应调整。文中对基于随机算法的开放性测试进行了研究,给出了它的实现算法,并进一步讨论了基于此算法的学生模型修改策略。最后,讨论了基于认知理论与随机开放性测试的动态学生模型在ICAI中的实践,建立了一个ICAI集成教学系统。     

On models of information retrieval processes

A model called the binary independence model is presented as a generalization of a few models which have applied to the analyses of a clustered search process, some indexing strategies and a relevance feedback process. This model, together with the Swets model, the linked-2-Poisson model, the 2-Poisson model, the binary limited-dependence model, the tree dependence model, the binary dependence model and the non-binary independent model are compared and contrasted. Despite the fact that these models are intended for different applications, three aspects of modelling are identified, based on which, these models are compared. The three aspects are the class concept, the distribution of similarities and the relation between a matching function and its retrieval effectiveness. As results of the comparison between the models, more insight into the models is gained and a set of guidelines are suggested to help a system designer to choose a model.     

Assessment of structural simulation models by estimating uncertainties due to model selection and model simplification

In this paper several methods for model assessment considering uncertainties are discussed. Sensitivity analysis is performed to quantify the influence of the individual model input parameters. In addition to the well-known analysis of a single model, a new procedure for quantifying the influence of the model choice on the uncertainty of the model prediction is proposed. Furthermore, a procedure is presented which can be used to estimate the model framework uncertainty and which enables the selection of the optimal model with the best compromise between model input and framework uncertainty. Finally Bayesian methods for model selection are extended for model assessment without measurements using model averaging as reference.     

数据仓库概念模型的设计

要设计一个能够正确反映用户的需求，又能够使用户易于理解的数据仓库概念模型是一项不同于传统事务处理系统概念模式设计的重要工作，文章提出了一个类似于传统事务的ER模型的DWER模型，给出了对DWER模型的评价，并与其它相关的模型进行了比较，最后给出了模型的描述方法。     

面向对象数据库的安全模型及其应用

近年来,数据库安全模型一直是数据库方面研究的热点。由于关系数据模型是建立在良好的数学模型的基础上,因而成熟的关系数据安全模型已经被提出。而面向对象数据模型本身尚未找到坚实的数学基础,针对面向对象数据库的安全模型研究不多,文章在这方面做了一些尝试,它提出了一种基于视图的面向对象数据库的信息过滤模型。该模型以多级数据模型为基础,综合了视图模型和信息过滤模型的优点;然后给出该模型的评价及其应用。     

基于泛关系模型表示的层次化模型管理框架

针对常见模型表示方法缺少对多阶段建模过程支持,造成不同建模阶段模型难以统一管理、共享和重用的问题,提出基于泛关系模型表示的层次化模型管理框架。分析现有模型表示方法特点和多阶段建模过程中模型表示及管理需求,采用泛关系模型表示建立概念模型和数学模型表示方法之间映射关系,建立一体化模型表示方法和层次化模型管理框架; 研究层次化模型管理框架中概念层模型和泛关系层模型的模型库设计逻辑,并基于泛关系理论,研究了物理层模型的动态生成方法,实现了不同建模阶段模型的一体化表示和统一管理。     

C4ISR系统仿真中的模型标准化和运行技术研究

C4ISR是一个十分复杂的大系统,在仿真中所涉及的模型种类繁多,类别不一。为了有效地模型实行管理、组合和调度,模型规范化是一个迫切需要解决的问题,在对各类模型进行分析和归纳的基础上,提出了一种模型规范化实现方案,并给出了其格式描述。文中还探讨了模型的封装结构和模型的运行调度机制,最后给出了一个仿真模型标准化的实例。     

基于演化建模的图像配准模型

传统的多项式配准模型原理直观,计算简单,但由于采用多项式建立模型,往往带有局限性,对于复杂的配准可能无效;传统的物理配准模型虽然配准精度较高,但对成像的各种因素需要精确掌握,实际操作难度较大。演化建模只需要根据问题的特征来确定模型结构的一些基本组成单元,就可以自动建立较为精确的模型。针对以上传统图像配准模型的不足,并考虑到演化建模具有智能挖掘模型的优点,提出了一种基于演化建模的图像配准模型。最后给出了该方法在图像配准中的实验,实验结果表明该方法有较高配准精度,适用于图像配准。     

基于三层植物模型的大规模植物模拟方法*

针对在大规模植物模拟中基于三维几何网格模型的植物模拟方法内存消耗大,以及基于二维平面模型的植物模拟方法近视点模糊缺陷问题,提出了一种基于三层植物模型的大规模植物模拟方法。该方法将大规模植物分为三层：精度高的几何网格模型层、精度适中的Impostor模型层和精度低的Billboard模型层。根据植物到视点的距离,动态加载相应层中的模型,即当植物距视点较近时,加载精度高的几何网格模型层中的模型;当植物距视点较远时,加载精度适中的Impostor模型层中的模型;当植物距视点很远时,加载精度低的Billboard模型层中的模型。最后,利用Ogre图形引擎对三种植物模拟方法进行了渲染效果对比实验。由实验结果可知,该方法可以在低内存消耗情况下,取得与基于三维几何网格模型的植物模拟方法一样的逼真感,取得与基于二维平面模型的植物模拟方法相近的渲染速度。     

Layered animation of captured data

normal volume of a triangle to convert individual triangles to a volumetric representation. A layered model is constructed to animate the reconstructed high-resolution surface. The model consists of 3 layers: a skeleton for animation from key-frame or motion capture; a low-resolution control model for real-time mesh deformation; and a high-resolution model to represent the captured surface detail. Initially the skeleton model is manually placed inside the low-resolution control model and high-resolution scanned data. Automatic techniques are introduced to map both the control model and captured data into a single layered model. The high-resolution captured data is mapped onto the low-resolution control model using the normal volume. The resulting model enables efficient, seamless animation by manipulation of the skeleton while maintaining the captured high-resolution surface detail. The animation of high-resolution captured data based on a low-resolution generic model of the object opens up the possibility of rapid capture and animation of new objects based on libraries of generic models. Published online: 2 October 2001     

Mapping feature models onto domain models: ensuring consistency of configured domain models

We present an approach to model-driven software product line engineering which is based on feature models and domain models. A feature model describes both common and varying properties of the instances of a software product line. The domain model is composed of a structural model (package and class diagrams) and a behavioral model (story diagrams). Features are mapped onto the domain model by annotating elements of the domain model with features. An element of a domain model is specific to the features included in its feature annotation. An instance of the product line is defined by a set of selected features (a feature configuration). A configuration of the domain model is built by excluding all elements whose feature set is not included in the feature configuration. To ensure consistency of the configured domain model, we define constraints on the annotations of inter-dependent domain model elements. These constraints guarantee that a model element may be selected only when the model elements are also included on which it depends. Violations of dependency constraints may be removed automatically with the help of an error repair tool which propagates features to dependent model elements.     

原子数据模型

一个柔性的信息系统要求它的业务模型是可变的,满足企业业务需求多变性。然而,业务模型是以数据模型为支撑的,这就要求数据模型也是可变的、可扩展的。出于这个目的,讨论了普遍的数据建模方法中存在的问题,并提出一种改进的数据模型,称之为原子数据模型。     

Modeling, identification, and control of a class of nonlinearsystems

In this paper, we propose a new fuzzy hyperbolic model for a class of complex systems, which is difficult to model. The fuzzy hyperbolic model is a nonlinear model in nature and can be easily derived from a set of fuzzy rules. It can also be seen as a feedforward neural network model and so we can identify the model parameters by BP-algorithm. We prove that the stable controller can be designed based on linear system theory. Two methods of designing the controller for the fuzzy hyperbolic model are proposed. The results of simulation support the effectiveness of the model and the control scheme     

Static, Dynamic, and Hybrid Neural Networks in Forecasting Inflation

The back-propagation neural network (BPN) model has been the most popular form of artificial neural network model used for forecasting, particularly in economics and finance. It is a static (feed-forward) model which has a learning process in both hidden and output layers. In this paper we compare the performance of the BPN model with that of two other neural network models, viz., the radial basis function network (RBFN) model and the recurrent neural network (RNN) model, in the context of forecasting inflation. The RBFN model is a hybrid model with a learning process that is much faster than the BPN model and that is able to generate almost the same results as the BPN model. The RNN model is a dynamic model which allows feedback from other layers to the input layer, enabling it to capture the dynamic behavior of the series. The results of the ANN models are also compared with those of the econometric time series models.     

A complete approach for CIM modelling and model formalising

ContextComputation Independent Model (CIM) as a business model describes the requirements and environment of a business system and instructs the designing and development; it is a key to influencing software success. Although many studies currently focus on model driven development (MDD); those researches, to a large extent, study the PIM-level and PSM-level model, and few have dealt with CIM-level modelling for case in which the requirements are unclear or incomplete.ObjectiveThis paper proposes a CIM-level modelling approach, which applies a stepwise refinement approach to modelling the CIM-level model starting from a high-level goal model to a lower-level business process model. A key advantage of our approach is the combination of the requirement model with the business model, which helps software engineers to define business models exactly for cases in which the requirements are unclear or incomplete.MethodThis paper, based on the model driven approach, proposes a set of models at the CIM-level and model transformations to connect these models. Accordingly, the formalisation approach of this paper involves formalising the goal model using the category theory and the scenario model and business process model using Petri nets.ResultsWe have defined a set of metamodels and transformation rules making it possible to obtain automatically a scenario model from the goal model and a business process model from the scenario model. At the same time, we have defined a mapping rule to formalise these models. Our proposed CIM modelling approach and formalisation approach are implemented with an MDA tool, and it has been empirically validated by a travel agency case study.ConclusionThis study shows how a CIM modelling approach helps to build a complete and consistent model at the CIM level for cases in which the requirements are unclear or incomplete in advance.     

医院数据仓库数据模型设计

数据模型设计是数据仓库建设的核心,提出一种医院数据仓库数据模型的设计方法。以某一三甲医院的HIS数据为背景,采用数据驱动的手段,结合医院的需求,提出了医院数据仓库的三层数据模型,概念模型、逻辑模型、物理模型,并完整地给出了每个模型的具体的设计和主要内容。设计并实现了医院数据仓库的数据模型,并结合医院具体的数据给出了相应的实例。此医院数据仓库的三层数据模型易于理解和实现,为医院数据仓库设计最终完成提供了基础。     

A hybrid model formulation for a distillation column and the on-line optimisation study

Wavelet-based neural networks are employed to simplify the model of a distillation column. The idea is to use a simplified hybrid model of the column for the purpose of on-line optimisation of the unit. The hybrid model consists of a neural network part plus a mechanistic model part. This highly simplifies the model while preserving the accuracy of the model together with the availability of the required internal variables of the model. The employed wavelet-based neural networks (i.e. wave-nets) are briefly explained. Then, results of the approximation capability of the wave-net model and the on-line optimisation of the column with the aid of the hybrid model are presented.     

工作流模型的扩展及其形式化描述

工作流是一类能够部分或全部由计算机支持或自动处理的业务过程,工作流模型是对工作流的抽象表示,也就是对业务过程的抽象表示。论文以过程工程理论建立的企业模型作为工作流模型的扩展思想,归纳出了工作流模型设计原则,并对现有的扩展方法进行了分析;最后提出了一种工作流模型,该模型由过程模型、活动模型、组织模型、资源模型和信息模型五个子模型组成,并给出了各子模型的形式化描述。