一种通用信息系统的研究与开发

论文从提高信息系统的通用性、灵活性和可维护性角度出发，提出了基于数据字典的通用信息系统设计思想，在对数据字典结构进行说明的基础上，介绍了系统实现中的几个基本问题。     

实现异构数据库集成的一种方法——元数据库法

本文提出的元数据库系统ＭＤＢＳ是一个基于知识库的联邦数据库系统，通过集中管理各异构数据库中的元数据，支持多库间的数据共享、交互操作及自治。在整个集成系统中无全局模式，异构数据库模式间的结构和语义冲突，由ＭＤＢＭＳ通过访问元数据库中有关各局部库的模式信息和模式转换规则来解决。ＭＤＢＳ利用知识来描述应用系统的数据流信息和控制信息支持集成应用系统的实现。本文着重论述了ＭＤＢＳ的数据模型、数据库模式和ＭＤＢＳ实现的技术问题。     

并行工程环境中的信息资源字典系统

并行工程（ＣＥ）的信息种类繁多，结构复杂，并且数据量非常大，需要存储在异构分散的数据库中，为方便应用和各种ＣＥ工具的集成，需对它们对行统一管理。信息资源字典系统（ＩＲＤＳ）从广义的概念上支持三模式结构，是ＣＥ信息集成的有效工具。文章介绍一个ＩＲＤＳ系统的开发，它有在并概念，三模式结构及在ＣＥ信息管理中的应用。     

如何在PowerBuilder中实现通用查询

所谓通用查询是指,用户可以任意选择想要查找的对象,再利用已知信息任意设置查询条件及条件的组合,依此来寻找自己想要的信息,灵活性、通用性是其最大的特点。本文就是利用PowerBuilder实现通用查询功能的一个解决方案。     

无线传感器网络信息融合平台设计与实现

针对军用无线传感器网络中存在大量不同种类的传感器节点,其异构性易形成的信息孤岛问题,通过设计构建通用无线传感器网络信息融合决策平台来屏蔽各类传感器信息在数据结构上的异构性,以实现数据的集成、挖掘,达到信息的实时共享的目的。重点研究设计了平台的数据包解析模块和及其信息融合机制,并使用数据字典作为数据包解析的核心。采用了决策级结构作为平台的信息融合机制,实现了军用传感器网络的信息融合决策。     

一个基于DOS的分布式操作系统的设计

本文针对多机并行处理系统ＭＰＳ－１这种通用结构环境，基于ＤＯＳ进行了一个分布式操作系统ＭＤＯＳ的方案设计，阐述了ＭＤＯＳ的系统结构，资源管理，进程控制与文件系统结构，实现了打印机及文件的共享。为ＤＯＳ用户开展分布式应用提供了一个示例，有现实意义。     

一个基于DOS的分布式操作系统的设计

本文针对多机并行处理系统ＭＰＳ—１这种通用结构环境，基于ＤＯＳ进行了一个分布式操作系统ＭＤＯＳ的方案设计。阐述了ＭＤＯＳ的系统结构、资源管理、进程控制与文件系统结构，实现了打印机及文件的共享。为ＤＯＳ用户开展分布式应用提供了一个示例，有现实意义。     

利用Delphi自定义控件类实现通用数据控制程序：基于数据字典的界？…

本文论述了面向对象技术在ＭＩＳ系统开发中的应用及利用Ｄｅｌｐｈｉ提供的功能建立自定义控件类，在程序运行中动态生成与释放控件对象，控件实例数组的使用以及如何在Ｄｅｌｐｈｉ下编写面向数据字典的通用数据编辑和浏览界面。     

DOS环境下一个通用测控软件平台的设计

介绍一个基于ＤＯＳ环境下分布式结构的通用测控软件平台的设计与实现，详细描述了通用界面生成器，多任务调工算法，通信管理函库，测控Ｉ／Ｏ接口模块库和数据自理函数库的设计方法来实现，并给出了采用本软件平台实际构成的一个测控系统的应用实例。     

复杂化工流程的优化及在DOPS上的实现(Ⅱ)通用流程优化系统在DOPS上的实现

论述了在数据驱动的化工流程模拟系统ＤＯＰＳ上实现的通用复杂过程优化系统的结构，该系统结构灵活，易于实现大系统的优化。提出了一个通用优化目标函数，它由有关的物流、能流及单元模块参数线性组合而成，在系统中被自动描述出来。通过考核表明，本系统对生产实际过程的优化操作，创造最佳经济效益具有一定的指导意义。     

A proposal for modelling usability in a holistic MDD method

Holistic methods for Model-Driven Development (MDD) aim to model all the system features in a conceptual model. This conceptual model is the input for a model compiler that can generate software systems by means of automatic transformations. However, in general, MDD methods focus on modelling the structure and functionality of systems, relegating the interaction and usability features to manual implementations at the last steps of the software development process. Some usability features are strongly related to the functionality of the system and their inclusion is not so easy. In order to facilitate the inclusion of functional usability features from the first steps of the development process and bring closer MDD methods to the holistic perspective, we propose a Usability Model. The Usability Model gathers conceptual primitives that represent functional usability features in a sufficiently abstract way so that the model can be used with different holistic MDD methods. This paper defines all the primitives that can be used to represent functional usability features. Moreover, we have defined a process to include the Usability Model in any MDD method without affecting its existing conceptual model. The proposal is based on model-to-model and model-to-code transformations. As proof of concept, we have applied our proposal to an existing MDD method called the OO-method and we have measured its efficiency.     

Preconditioning of the p-version of the finite element method

The p-version finite element method for linear, second-order elliptic equations in an arbitrary, sufficiently smooth (incl. polygonal), bounded domain is studied in the framework of the Domain Decomposition (DD) method. Two types of square reference elements are used with coordinate functions given by the products of the integrated Legendre polynomials. Estimates for the condition numbers and some useful inequalities are given. We consider preconditioning of the problems arising on subdomains and of the Schur complement, as well as the derivation and analysis of the DD preconditioner for the entire system. This is done for a class of curvilinear finite elements. We obtain several DD preconditioners for which the generalized condition numbers vary from ((log p)³) to (1).

This paper is based on [19–21,27]. We have omitted most of the proofs in order to shorten it and have described instead what could be done as well as outlined some additional ideas. The full proofs omitted can in most cases be found in [19,20,27].     

An investigation of critical factors in medical device development through Bayesian networks

In this paper, we investigate the impact of product, company context and regulatory environment factors for their potential impact on medical device development (MDD). The presented work investigates the impact of these factors on the Food and Drug Administration’s (FDA) decision time for submissions that request clearance, or approval to launch a medical device in the market. Our overall goal is to identify critical factors using historical data and rigorous techniques so that an expert system can be built to guide product developers to improve the efficiency of the MDD process, and thereby reduce associated costs. We employ a Bayesian network (BN) approach, a well-known machine learning method, to examine what the critical factors in the MDD context are. This analysis is performed using the data from 2400 FDA approved orthopedic devices that represent products from 474 different companies. Presented inferences are to be used as the backbone of an expert system specific to MDD.     

On thermoelectric materials with memory-dependent derivative and subjected to a moving heat source

We develop a model of generalized thermoelasticity with memory-dependent derivative (MDD) heat conduction law for a thermoelectric half-space. Some urgent theories take after as most remote point cases. The Laplace transform and state-space procedures are utilized to urge the overall account for any arrangement of limit conditions. The general solution acquired is connected to the particular issue of a half-space exposed to a uniform magnetic field, a moving heat source with consistent speed and ramp-type heating. The inverse Laplace transforms are registered numerically. The impacts of various estimations of the figure-of-merit quantity, heat source speed, MDD parameters, the magnetic number and the ramping time parameter are thought about.

     

A queuing network model for minimizing the total makespan of computational grids

This paper offers a mathematical solution based on queuing theory and a generalized stochastic Petri net model to minimize the total makespan of the grid computing environments. A grid manager could minimize the total makespan through cautious distribution of subtasks to the grid resources. Subtask arrival rates depend on the arrival rate of the grid tasks submitted to the grid manager, local tasks directly submitted to the grid resources and the processing speed of the resources. Modeling the grid environment using queuing network, the steady state analysis of the network will result in the mean response time of the resources. Therefore, the total makespan could be minimized by minimizing the longest mean response time of the resources. The accuracy of the values obtained for the subtasks arrival rates at each of the grid resources from solving the corresponding queuing network could be further evaluated by steady state analysis of the generalized stochastic Petri net modeling the same grid environment.     

附网存储系统卷管理模块的性能优化分析

为了提高NAS系统的性能,设计一个良好的卷管理模块是关键。该文首先介绍了卷管理中的功能模块和相应的处理流程。然后针对卷管理模块中与系统性能相关的问题进行探讨和研究,通过理论和实验分析,得出针对不同应用的优化方案。通过在实际中使用表明,优化后的系统性能得到较大提高。     

Mega-modeling of complex,distributed, heterogeneous CPS systems

Model-Driven Design (MDD) has proven to be a powerful technology to address the development of increasingly complex embedded systems. Beyond complexity itself, challenges come from the need to deal with parallelism and heterogeneity. System design must target different execution platforms with different OSs and HW resources, even bare-metal, support local and distributed systems, and integrate on top of these heterogeneous platforms multiple functional component coming from different sources (developed from scratch, legacy code and third-party code), with different behaviors operating under different models of computation and communication. Additionally, system optimization to improve performance, power consumption, cost, etc. requires analyzing huge lists of possible design solutions. Addressing these challenges require flexible design technologies able to support from a single-source model its architectural mapping to different computing resources, of different kind and in different platforms. Traditional MDD methods and tools typically rely on fixed elements, which makes difficult their integration under this variability. For example, it is unlikely to integrate in the same system legacy code with a third-party component. Usually some re-coding is required to enable such interconnection. This paper proposes a UML/MARTE system modeling methodology able to address the challenges mentioned above by improving flexibility and scalability. This approach is illustrated and demonstrated on a flight management system. The model is flexible enough to be adapted to different architectural solutions with a minimal effort by changing its underlying Model of Computation and Communication (MoCC). Being completely platform independent, from the same model it is possible to explore various solutions on different execution platforms.     

Formal requirements modelling with executable use cases and coloured Petri nets

This paper presents executable use cases (EUCs), which constitute a model-based approach to requirements engineering. EUCs may be used as a supplement to model-driven development (MDD) and can describe and link user-level requirements and more technical software specifications. In MDD, user-level requirements are not always explicitly described, since usually it is sufficient that one provides a specification, or platform-independent model, of the software that is to be developed. Therefore, a combination of EUCs and MDD may have potential to cover the path from user-level requirements via specifications to implementations of computer-based systems.     

Model-driven development of mobile applications for Android and iOS supporting role-based app variability

Rapidly increasing numbers of applications and users make the development of mobile applications to one of the most promising fields in software engineering. Due to short time to market, differing platforms, and fast emerging technologies, mobile application development faces typical challenges where model-driven development (MDD) can help. We present a modeling language and an infrastructure for the MDD of native apps in Android and iOS. Our approach allows a flexible app development on different abstraction levels: compact modeling of standard app elements such as standard data management and increasingly detailed modeling of individual elements to cover, for example, specific behavior. Moreover, a kind of variability modeling is supported such that mobile apps with variants can be developed. We demonstrate our MDD approach with several apps including a conference app, a museum guide with augmented reality functionality, and a SmartPlug.