基于Simulink的水灭火系统仿真研究

该文提出一种新的基于Visual c＋＋的水灭火系统仿真模型,通过将C＋＋代码转换成C代码植入到仿真模型中,可以大大优化仿真模型的开发,该文中Simulink软件和VSULAL C＋＋软件的优点在仿真模型中得到完整的体现。该文还详细讨论了水灭火仿真系统的开发和实现。     

基于ACTOR模型的并发面向对象语言AC++

ＡＣ＋＋是用ＡＣＴＯＲ模型建造的并发Ｃ＋＋语言．本文介绍ＡＣ＋＋的设计与实现，着重探讨如何在语义级上平滑地结合ＡＣＴＯＲ模型和普通面向对象语言，提出了“扩充的行为抽象”和“异步创建”等新方法，使新语言既能保持面向对象语言的特性，又能支持ＡＣＴＯＲ模型提供的描述并发计算的能力.     

组件对象模型——COM＋的研究

文章阐述了当前主流的组件模型的发展情况,重点介绍了组件对象模型COM＋概念,COM、DCOM、MTS和COM＋的结构关系,还给出了COM＋的目录管理、内存数据库、安全机制、队列组件服务等几大重要特性。     

COM+在钢铁企业经销系统中的应用

对COM＋基本结构及基于COM＋组件的多层应用模型进行了分析，将COM＋组件应用于某钢铁企业“整合型集团经销信息网络管理系统”中．初步实现了基于COM＋组件技术的三层客户端／服务器结构的系统模型．从而提高了钢铁企业经销系统的性能。     

赋值层化占先模型

Ｂｅｚｚａｚｉ,Ｍａｋｉｎｓｏｎ及Ｐｉｎｏ最近系统地研究了一些非Ｈｏｒｎ型推理规则（它们强于ＲＭ规则或者与ＲＭ规则不可比）,给出了Ｐ＋ＲＭ＋ＷＤ与Ｐ＋ＲＭ＋ＲＣ非单调后承的表示定理,并将另两个非单调后承Ｐ＋ＷＤ及Ｐ＋ＲＣ的表示定理作为开问题提出来,文中提出两个新的占先模型类－赋值层化占先模型与ＰＲＣ模型,在有限语言情形下,利用这两个模糊类分别建立了Ｐ＋ＷＤ及Ｐ＋ＲＣ后承的表示定理,并用Ｐ＋ＷＤ的表     

基于OpenGL的雕塑建模与可视化仿真

文章是在OpenGL的虚拟现实技术和VC＋＋2008编程技术以及3DMAX建模技术上进行研究的。3DMAX建模软件对雕塑模型进行创建与绘制。导出aDS格式的文件,在VC＋＋2008支持的OpenGL环境下对雕担模型进行读取与控制。基本实现了雕塑可视化模拟,达到了较逼真的雕塑三维可视化效果。     

一种静态分析C^＋＋异常处理的方法

异常处理是现代程序设计语言提供的用来提高软件健壮性的一种机制。由于在C^＋＋的函数界面中并不要求声明该函数所能传播出的异常的类型，所以要想提高系统的健壮性，必须清楚在程序的执行过程中可能引发的异常、异常的传播路径等。然而在大型系统中，要想确定这些信息是非常困难的。本文针对C^＋＋的异常处理机制，首先提出了一个描述C^＋＋异常结构信息的模型，并把该模型应用于递归函数中。然后，描述了一个基于该模型的分析C^＋＋程序异常结构信息的工具CETool。该工具能提供所有显式引发异常的有关信息，为系统中异常处理结构的改进和程序的结构测试提供有价值的信息。最后给出了该工具的实现方法和应用实例。     

构建基于COM+的Web数据库应用

首先介绍了COM＋技术及基于COM＋的三层结构模型；然后通过一个实例，结合ASP和COM＋技术给出了构建基于COM＋的Web数据库应用系统的解决方案。     

基于UML的图形界面系统对象模型的研究

按照面向对象软件工程的思想,以UML建模语言,以Visio2003为建模工具,研究与建立了小型监控组态软件图形界面系统的对象模型,并且研究和建立了对象模型内部的各子模型,以及各子模型之间的关系。该对象模型已借助面向对象编程语言VisualC＋＋6．0实现。模型的建立过程对于同类软件模型的研究和开发具有参考价值。     

一种基于OpenGL的三维元胞自动机模型

本文以Visual C＋＋为编译平台,运用OpenGL图形函数库建立了一种三维元胞自动机模型。该模型具备了经典元胞自动机的基本特征,因此可以根据需要进行扩展。文中运用该模型进行了简化的枝晶生长模拟,并与二维的模拟结果进行比较,验证了该模型的正确性。     

激光光条中心线提取研究综述

激光光条中心线提取在视觉测量、三维重建等领域具有重要的作用.介绍了不同类型的中心线提取模型,并且回顾了这些模型的转变和创新.具体来说,根据模型采用的核心算法,将中心线提取模型分为传统提取模型和基于深度学习的提取模型;传统中心线提取模型又分为极值模型、灰度重心模型、曲线拟合模型、基于Hessian矩阵的Steger模型和...     

Constrained interactivity for relating multiple representations in science: When virtual is better than real

Virtual models are increasingly used in science education, especially in spatially demanding domains. However, few studies have directly compared the effectiveness of virtual and concrete models, or systematically characterized differences between them. Here, we compared students' accuracy and efficiency using virtual and concrete models to align and produce different representations in the domain of organic chemistry. Naïve undergraduate students learned the conventions of different molecular representations (diagrams and models) and then performed tasks that involved matching models to diagrams and using models to complete diagrams. The results indicated similar levels of accuracy for virtual and concrete models and greater efficiency for virtual models. Students preferred virtual models, but rated the usability of the two model types about equally. The efficiency benefit associated with using virtual models can be explained by their constrained interactivity, which prevented students from making task-irrelevant manipulations and increased the salience of the task-relevant information in the models.     

AR 型非线性时间序列模型的稳定性分析

在工程中,振幅依赖指数自回归模型、门限自回归模型和多项式自回归模型等一类具有ＡＲ型的非线性时间序列模型具有广泛的应用,为此给出了ＡＲ型非线性时间序列模型的稳定性条件及极限环存在条件,并对一些特殊模型进行了讨论。     

信息检索的概率模型

The study of mathematical models on information retrieval is an important area in the Information Retrieval community. Because of the uncertainty characteristic of IR,the probability model based on statistical probability is apromising model from recent to future. Those models can be classified into classical models and probability network models. Several famous models are introduced and their shortcomings are pointed out in this paper. We also clarifythe relationship of these models and introduce a new models based on statistical language model curtly.     

协同多媒体著作工具中演示文档的同步模型

多媒体演示文档的协同著作对文档本身的结构与同步模型提出了一定的要求。为了便于面向对象的实现以及灵活多粒度的共享，提出了一个协同多媒体著作工具中分布交互式多媒体文档的同步模型。在此模型中，文档结构分为三层：页面层、对象组层及单媒体对象层，根据各层的特点，其同步分别采用基于跳转、基于事件及基于时间的策略     

Usability of concrete and virtual models in chemistry instruction

Virtual models are increasingly common in the modern science classroom, however little is known about the relative effectiveness of virtual and concrete models. We developed a virtual modeling system and tested the benefit of haptic cue fidelity, controlling for many other perceptual differences between concrete and virtual models. In two studies we directly compared performance of students using this virtual model and using concrete models for tasks in the domain of organic chemistry. Students used either virtual or concrete models to match diagrams of molecules or compare the structures of molecules represented by models and diagrams. The results indicated similar levels of accuracy and similar ratings of usability for virtual and concrete models but no effect of haptic cue fidelity. Greater efficiency with virtual models was observed when students matched diagrams and models, and this efficiency transferred to later use of concrete models. The efficiency benefit is attributed to interactive constraints of the hand-held interface to the virtual model, which helped students identify task-relevant information in the model and limited them to performing the most task-relevant interactions with the models.     

A bivariate fuzzy time series model to forecast the TAIEX

Fuzzy time series models have been applied to forecast various domain problems and have been shown to forecast better than other models. Neural networks have been very popular in modeling nonlinear data. In addition, the bivariate models are believed to outperform the univariate models. Hence, this study intends to apply neural networks to fuzzy time series forecasting and to propose bivariate models in order to improve forecasting. The stock index and its corresponding index futures are taken as the inputs to forecast the stock index for the next day. Both in-sample estimation and out-of-sample forecasting are conducted. The proposed models are then compared with univariate models as well as other bivariate models. The empirical results show that one of the proposed models outperforms the many other models.     

Dual models for possibilistic regression analysis

Upper and lower regression models (dual possibilistic models) are proposed for data analysis with crisp inputs and interval or fuzzy outputs. Based on the given data, the dual possibilistic models can be derived from upper and lower directions, respectively, where the inclusion relationship between these two models holds. Thus, the inherent uncertainty existing in the given phenomenon can be approximated by the dual models. As a core part of possibilistic regression, firstly possibilistic regression for crisp inputs and interval outputs is considered where the basic dual linear models based on linear programming, dual nonlinear models based on linear programming and dual nonlinear models based on quadratic programming are systematically addressed, and similarities between dual possibilistic regression models and rough sets are analyzed in depth. Then, as a natural extension, dual possibilistic regression models for crisp inputs and fuzzy outputs are addressed.     

力/触觉再现中柔性物体可视化物理形变模型研究进展

力/触觉再现技术的出现,为虚拟现实开辟了全新的应用领域,促使基于物理意义的柔性物体形变建模成为一个研究热点.系统地讨论了近年来基于物理意义的柔性物体形变建模方法,分析了基于直接构建的模型、基于连续介质力学的模型和其他相关模型的基本思想和优缺点.对这些建模方法的性能进行了细致的比较,并探讨了柔性物体物理形变建模的未来发展趋势.     

Web浏览预测的Markov模型综述

Web访问模式挖掘研究的一个重要议题是Web浏览预测,Markov模型是一种经典的Web浏览预测模型.本文首先介绍了基本Markov浏览预测模型,包括基本Markov浏览行为模型,模型的学习训练及其在Web浏览预测问题中的应用;然后重点分析了扩展的Markov浏览预测模型,包括一序组合预测模型、高序模型、混合模型、隐Mark-ov模型、连续时间Markov模型等,综述了各种扩展模型所考虑的浏览预测问题的本质出发点、模型的学习方法及预测方法,最后分析了Markov浏览预测模型有待进一步研究的问题.