Reusable abstractions for modeling languages

Model-driven engineering proposes the use of models to describe the relevant aspects of the system to be built and synthesize the final application from them. Models are normally described using Domain-Specific Modeling Languages (DSMLs), which provide primitives and constructs of the domain. Still, the increasing complexity of systems has raised the need for abstraction techniques able to produce simpler versions of the models while retaining some properties of interest. The problem is that developing such abstractions for each DSML from scratch is time and resource consuming.     

Parameter identification and global sensitivity analysis of Xin’anjiang model using meta-modeling approach

Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1) a screening method (Morris) for qualitative ranking of parameters, and (2) a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol). First, the Morris screening method was used to qualitatively identify the parameters’ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM) were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.     

一种Java语言图形编程工具的设计与实现

提出一种用于Java语言的图形编程工具的设计方法.它基于元建模机制设计图形编程语言,采用模型-视图-控制器(MVC)构架模式实现图形编辑器,并设计代码转换器完成从图形代码到对应文本代码的等价转换.通过在机器人编程游戏中的实际使用,证明其满足实际需要,大大提高图形编程语言的设计效率,增强了图形编辑器的可维护性与可复用性.这种设计方法也可以用来设计其他语言的图形编程工具.     

基于可拓元模型架构的产品资源全性能模型

为满足产品全生命周期业务过程中对产品资源的动态需求,以元对象机制和可拓论为基础,提出了产品资源全性能模型.该模型由服务需求、服务行为和产品资源等要素组成.在元模型架构的基础上,将可拓论的物元形式化描述引入面向对象技术,定义各组成要素,并对已经规范化的组成要素进行不同粒度的事物元封装,使其成为可重用的集成单元,以集成并提升产品资源的表达能力,快速搜索能力和服务封装能力,突出产品资源的全性能性.最后,通过实例验证了所提模型的实用性和有效性.     

云制造环境下支持演化的制造云服务元建模

针对制造云服务运行环境的高度动态开放性,在分析了制造云服务建模需求的基础上,提出了支持演化的云服务元建模框架,着重研究了框架的语义表示层中的云服务元模型架构。在云服务元元模型层,给出了云服务元元模型的形式化定义及云服务的概念模型。在云服务元模型层,阐述了云服务业务主对象、业务元对象和业务元数据的模型结构及演化操作对象、演化日志对象的模型结构。在云服务模型层,基于Web本体描述语言建立了云服务本体。在此基础上,提出了云服务的演化过程模型。开发了一个面向模具行业的制造云服务管理平台原型,通过实际案例验证了该云服务建模方法的可行性和有效性。     

基于SHML的CPS行为建模及仿真

信息物理融合系统（cyber-physical systems，简称CPS）是深度融合了计算进程和物理进程的统一体，是集计算、通信与控制于一体的下一代智能系统，具有广阔的应用前景.CPS的行为具有混成性、随机性等特征，建模及仿真CPS的动态行为对于开发高质量的CPS系统至关重要.但是目前缺乏面向CPS的领域建模方法及建模CPS的领域建模语言，也迫切需要支持仿真CPS领域模型的仿真工具.针对以上问题，提出一种面向CPS领域的随机混成建模语言（stochastic hybrid modeling language，简称SHML）以支持建模CPS系统的行为.首先，根据CPS的领域特征定义了SHML的元模型作为其抽象语法，并定义了SHML的具体语法和操作语义；其次，基于GEMOC框架实现了SHML的可视化建模工具.此外，集成GEMOC的序列化执行引擎和Scilab的连续行为仿真引擎，实现仿真CPS的混成行为.提出了一种面向CPS领域的建模及仿真方法，设计并实现了一个集成的面向CPS行为的建模与仿真平台，为CPS的建模及仿真提供了一种有效的方法及工具支撑.     

一个支持模型驱动开发的元建模平台的研制

由于当今软件系统的复杂性,模型驱动的软件开发中需要的建模语言和转换定义语言往往是多种多样的.本文阐述了对一个可满足这种需要的元建模平台的研制.其中着重论述了对建模语言的元模型和表示法进行建模的技术,建模语言质量保证机制,以及针对所建立的建模语言和转换定义语言提供自动生成相应工具的设施.     

Modeling age-related memory deficits: A two-parameter solution.

Recent research and meta-analytic reviews suggest that 1 observed pattern of impaired and intact memory performance with advancing age is a deficit in measures of episodic but not semantic memory. The authors used computational modeling to explore a number of age-related parameters to account for this pattern. A 2-parameter solution based on lifelong experience successfully fit the pattern of results in 5 published studies of the word-frequency mirror effect and paired-associate recognition. Lifelong experience increases the strength (resting level of activation) of concepts in the network but also saturates the network with an increasing number of episodic associations to each concept. More episodic associations to each concept mean that activation spreads more diffusely, making retrieval of any newly established memory trace less likely; however, the greater strength of a concept makes recognition based on familiarity more likely. The simulations provide good quantitative fits to the extant age-related memory literature and support the plausibility of this mechanistic account. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于语义的Web服务注册联邦的研究

元模型互操作框架是一套元对象和元模型结构的集合．用于信息注册和信息资源库开发中元模型的建立．将元模型互操作框架MMFI与联邦信息管理技术结合．运用表体元建模方法，建立Web服务注册联邦的体系结构，以实现异构自治的Web服务注册问可扩展的语义互操作．提出表体对象建模理论和方法，指导Web服务注册联邦系统的开发设计，简化设计开发过程．介绍了一个依据上述方法建立的软构件注册平台的原型系统．     

UML元模型图实例自动生成算法

UML元模型建模与实例生成是软件自动生成技术的重要环节之一,相关理论和技术在领域建模语言DSL中得到广泛应用.元模型自动生成实例技术不仅可以降低软件开发难度和成本,还可以提高软件开发效率.在已有元模型实例生成图语法理论的基础上,提出相应的元模型图实例自动生成算法,证明了该算法与图语法的等价性.并且在可视化UML建模平台中实现了这一算法,得到了从UML元模型自动生成大量实例的预期结果.