一种网络模型的计算机模拟方法

许多科学技术问题可以抽象成网络模型。而计算机硬件和软件技术的发展，为求解这类模型提供了新方法。在空间上随时间变化的一种场的问题抽象成网络并得到一种线性或非线性方程组形式的数学模型，提出一种预测加速因子的时空耦合的计算机模拟与求解方法。模拟与求解结果证明了模型和求解方法的可靠性。为解决科技中的类似课题提供了方法。     

基于移动代理的协同气候模拟计算环境设计

针对全球气候模拟中多学科交叉合作的特点,采用基于移动Agent的分布式计算技术,构造了一个层次结构的协同气候模拟计算环境。在系统原型中,应用层各通信实体通过软件总线和代理间的通信原语互联,形成一个自治的求解网络,并将用户请求以作业的形式向中间层提交。中间层利用自适应资源调度和负载平衡策略,对任务进行合理的调度,使资源和任务的有机结合,实现问题的分布式求解。同时,该计算环境下的计算代码移动策略,为解决互联网环境下实现大规模的协同科学计算提供了一种有效的途径。     

一种面向生物基因组可变剪接问题的网络并行求解方案

生物基因的可变剪接是调节基因表达和产生蛋白质组多样性的重要机制,具有重要的生物学意义.随着生物数据的快速增长,单机计算环境难以满足可变剪接研究所需要的超大计算能力.为了解决这一问题,提出了一种面向生物基因组可变剪接问题的网络并行求解方案.它充分考虑了可变剪接问题的挑战,设计了面向服务的网络资源虚拟化方案,提供了对网络资源一致的选择、访问、监控接口.通过一组API提供了面向用户的应用层支持,屏蔽了访问网络资源的细节,支持用户快速有效的开发应用程序.     

线性规划的一种并行修正松弛算法

对求解线性规划问题的松弛算法进行了修正 ,在此基础上提出了一种基于 Cluster结构的并行算法 ,分析了算法的性能 ;基于曙光— 30 0 0大规模并行计算机 ,给出了算法用于求解线性规划问题实例的实验结果 .理论分析和实验结果表明 :修正算法改进了松弛算法的实际性能 ,同时具有较好的并行性和稳定性 ,可用于求解此类大规模科学与工程规划问题的高性能计算     

利用遗传算法改善前馈神经网络容错性

针对前馈神经网络的断路故障,将网络容错性的改善转化为一个最小优化问题,并通过遗传算法进化求解来获取容错性好、泛化能力强的网络,该方法不需给网络增加额外冗余,也不需修改网络训练算法,较好地保持了网络结构、训练算法与容错处理的独立性,实验表明,该方法在两个基准测试问题上均取了很好的效果。     

一种普及计算环境中统一传输网络UTN

提出了一种普及计算环境中统一传输网络UTN(Uniform Transport Network),该统一传输网络实现了以DevicelD作为设备的唯一标识的通信地址,DcvicelD的地址到具体的传输地址的映射、多传输协议之间的路由和转换问题、实现进程之间可靠的单播、组播通信。该统一传输网络为普及计算环境中多种设备之间互联到通提供了必要的技术支持。     

Polymath软件在化学工程中非均相催化反应的模拟研究

Polymath软件作为一种科学与工程计算的数学软件包,用它所带的库函数可以高效、便捷地解决化学工程中许多数学问题,从而把人们从复杂的编程与调试中解脱出来.本文以化学工程中的气-固非均相催化反应为例,讨论Polymath在求解非线性微分方程组、插值计算以及图形绘制等方面的应用,结果表明:利用Polymath求解化学工程计算问题稳定性好、方便快捷,是化工设计、计算的好工具.     

科学数据网格中面向天文应用的问题求解环境设计与实现*

通过对虚拟天文台中科学课题的需求分析,提出一种基于数据网格针对天文应用的问题求解环境的框架;以"2MASS巡天星表搜寻OB星协候选体研究银河系的旋臂结构"科学课题为例,在科学数据网格上设计和实现了面向天文应用的问题求解环境,并对实现中的关键技术进行研究.     

基于XML的科学平台实验系统模型

科学平台是一新型集成网络知识载体,其提出是为了解决知识总量和信息总量爆炸性增长所带来的诸多问题。将可扩展标记语言引入科学平台这一高度集成的知识系统中,为科学平台系统建立了一个全新的技术模型,提供了进一步在网络知识库环境下开发科学平台系统的基本依据。     

MATLAB与Java的联合应用研究

科学与工程领域经常涉及网络环境下的工程计算问题。MATLAB具有很强的数值计算能力,Java是目前普遍使用的网络应用开发工具。本文研究了工程计算问题中的MATLAB与Java联合途径,提出二者联合应用的三种方法。研究与应用表明,这些方法能够将MATLAB的运算能力与Java的网络开发功能结合起来,实现二者的优势互补,拓宽应用领域,增强应用程序的处理能力,很好地解决网络环境下的工程计算问题。由于三种方法各有所长,在实际应用中要根据具体问题和要求的不同进行合适的选择。     

A grid-enabled problem solving environment for parallel computational engineering design

This paper describes the development and application of a piece of engineering software that provides a problem solving environment (PSE) capable of launching, and interfacing with, computational jobs executing on remote resources on a computational grid. In particular it is demonstrated how a complex, serial, engineering optimisation code may be efficiently parallelised, grid-enabled and embedded within a PSE. The environment is highly flexible, allowing remote users from different sites to collaborate, and permitting computational tasks to be executed in parallel across multiple grid resources, each of which may be a parallel architecture. A full working prototype has been built and successfully applied to a computationally demanding engineering optimisation problem. This particular problem stems from elastohydrodynamic lubrication and involves optimising the computational model for a lubricant based on the match between simulation results and experimentally observed data.     

The software architecture of a distributed problem‐solving environment

This paper describes the functionality and software architecture of a generic problem‐solving environment (PSE) for collaborative computational science and engineering. A PSE is designed to provide transparent access to heterogeneous distributed computing resources, and is intended to enhance research productivity by making it easier to construct, run, and analyze the results of computer simulations. Although implementation details are not discussed in depth, the role of software technologies such as CORBA, Java, and XML is outlined. An XML‐based component model is presented. The main features of a Visual Component Composition Environment for software development, and an Intelligent Resource Management System for scheduling components, are described. Some prototype implementations of PSE applications are also presented. Copyright © 2000 John Wiley & Sons, Ltd.     

S4W: a problem‐solving environment for wireless system design

This work describes the Site‐Specific System Simulator for Wireless System Design (S⁴W), a problem‐solving environment (PSE) that integrates visualization and computational tools with a high‐level graphical user interface. S⁴W improves the ability of wireless system engineers to design an indoor wireless system by encouraging them to think in terms of designing the system for optimal performance. Issues of computation management, data management, and location of resources are hidden from the user. The complex nature of data sets in the domain of wireless simulations calls for a customized set of visualization tools. Therefore, a number of ad hoc visualizations were developed for S⁴W. A study comparing the integrated system with an earlier, unintegrated version is presented. This helps to demonstrate the productivity gains that a PSE provides. Copyright © 2007 John Wiley & Sons, Ltd.     

Building problem-solving environments with the Arches framework

The computational problems that scientists face are rapidly escalating in size and scope. Moreover, the computer systems used to solve these problems are becoming significantly more complex than the familiar, well-understood sequential model on their desktops. While it is possible to re-train scientists to use emerging high-performance computing (HPC) models, it is much more effective to provide them with a higher-level programming environment that has been specialized to their particular domain. By fostering interaction between HPC specialists and the domain scientists, problem-solving environments (PSEs) provide a collaborative environment. A PSE environment allows scientists to focus on expressing their computational problem while the PSE and associated tools support mapping that domain-specific problem to a high-performance computing system.This article describes Arches, an object-oriented framework for building domain-specific PSEs. The framework was designed to support a wide range of problem domains and to be extensible to support very different high-performance computing targets. To demonstrate this flexibility, two PSEs have been developed from the Arches framework to solve problem in two different domains and target very different computing platforms. The Coven PSE supports parallel applications that require large-scale parallelism found in cost-effective Beowulf clusters. In contrast, RCADE targets FPGA-based reconfigurable computing and was originally designed to aid NASA Earth scientists studying satellite instrument data.     

MEDITOMO: a high performance software package for 3D SPECT imaging

We describe a parallel software library, named MEDITOMO, designed for processing MEDIcal images obtained by SPECT (single photon emission computed tomography) TOMOgraphic systems. MEDITOMO is the core library of the PSE (problem solving environment) MEDIGRID, oriented to medical imaging analysis, which the authors are currently developing. MEDIGRID is employed in a Grid-computing infrastructure involving clinical departments and research institutes. The algorithms of MEDITOMO are the standard ones that are usually applied in the SPECT analysis, i.e. the conjugate gradient and the expectation maximization. The main contribution of this work concerns the introduction of the total variation seminorm as the edge-preserving regularization in both algorithms and the development of the parallel software library. Experiments carried out on synthetic and clinical data are shown.     

网格环境下银河系化学演化研究

许多计算或数据密集型的科学应用要求一种共享和协同使用分布异构资源的机制,作为其复杂的问题求解过程的一部分.网格环境下银河系化学演化研究是中国虚拟天文台应用系统的一个重要部分.详细描述了该演化研究的设计和实现.通过这个范例,提出一种共享和协同使用资源的机制.该机制通过在网格环境中集成网格服务和网格服务工作流,能够有效地支持e-Science应用.该机制对于建模和管理实验研究、数据积累和科研成果的消化吸收这样的科研过程是有益的.     

面向问题求解的集成软件系统的设计研究

问题求解、信息检索和科学计算、通常是由专家系统、数据库管理系统和科学计算语言系统独立完成的。但许多工程应用的实际问题需要三者有机地结合在一起互相合作。本文结合一个具体的集成软件环境的设计，提出了一个集问题求解，信息检索和科学计算于一体的软件模型，研究了数据库、知识库和科学计算模型库的耦合问题，给出了提高耦合系统运行效率的若干方法。     

Factors of problem-solving competency in a virtual chemistry environment: The role of metacognitive knowledge about strategies

The ability to solve complex scientific problems is regarded as one of the key competencies in science education. Until now, research on problem solving focused on the relationship between analytical and complex problem solving, but rarely took into account the structure of problem-solving processes and metacognitive aspects. This paper, therefore, presents a theoretical framework, which describes the relationship between the components of problem solving and strategy knowledge.In order to assess the constructs, we developed a virtual environment which allows students to solve interactive and static problems. 162 students of grade 10 and the upper secondary level completed the tests within a cross-sectional survey. In order to investigate the structure of problem-solving competency, we established measurement models representing different theoretical assumptions, and evaluated model fit statistics by using confirmatory factor analyses.Results show that problem-solving competency in virtual environments comprises to three correlated abilities: achieving a goal state, systematical handling of variables, and solving analytical tasks. Furthermore, our study provides empirical evidence on the distinction between analytical and complex problem solving.Additionally, we found significant differences between students of grades 10 and 12 within the problem-solving subscales, which could be explained by gaming experience and prior knowledge. These findings are discussed from a measurement perspective. Implications for assessing complex problem solving are given.     

基于语义的网格工作流复合技术及实现

作为网格环境的基本服务,网格工作流的大规模共享和重用是使网格成为问题求解的智能化集成环境的一项核心技术。工作流复合技术能够通过已存在的解决方法的重用简化复杂的科学应用问题,而基于语义的工作流复合降低了需要了解工作流语法细节才能重用网格工作流带来的复杂性。首先运用知识表达技术提出一个基于目标概念的网格工作流语义模板,其次介绍了一个实现基于语义的工作流复合的工作流管理原型系统,其中详细阐述了工作流建模过程中基于语义的工作流复合的实现。