Web-based simulating system for modeling earthquake seismic wavefields on the grid

We have developed the SYNSEIS (SYNthetic SEISmogram) tool within the GEON (GEOscience Network) project to enable efficient computations of synthetic seismic waveforms for research and education. SYNSEIS is built as a distributed system to support the calculation of synthetic seismograms in 2D/3D media. The underlying simulation software is a finite difference code, E3D, developed by LLNL (S. Larsen). This code is embedded within the SYNSEIS environment and used by our SYNSEIS tool to simulate seismic waveforms of either earthquakes or explosions at regional distances (<1000 km). The SYNSEIS architecture is based around a Web service model. Especially, the computing Web services seamlessly access Grid computing resources by hiding the complexity of grid technologies. Even though the Grid computing is well-established in many computing communities, its use among domain scientists still is not trivial because of multiple levels of complexities encountered. We have also developed the grid-enabling E3D application code which takes our own dialect XML inputs that include geological models that are accessible through standard Web services. Also, the XML inputs for this application code contain structural geometries, source parameters, seismic velocity, density, attenuation values, number of time steps to compute, and number of stations.In this paper, we emphasize the development of a state-of-the-art web-based scientific computational environment. Our system can be used to promote an efficient and effective modeling environment to help scientists as well as educators in their daily activities and speed up the scientific discovery process.     

Deliberate Individual Change Framework for Understanding Programming Practices in four Oceanography Groups

Computing affects how scientific knowledge is constructed, verified, and validated. Rapid changes in hardware capability, and software flexibility, are coupled with a volatile tool and skill set, particularly in the interdisciplinary scientific contexts of oceanography. Existing research considers the role of scientists as both users and producers of code. We focus on how an intentional, individually-initiated but socially-situated, process of uptake influences code written by scientists. We present an 18-month interview and observation study of four oceanography teams, with a focus on ethnographic shadowing of individuals undertaking code work. Through qualitative analysis, we developed a framework of deliberate individual change, which builds upon prior work on programming practices in science through the lens of sociotechnical infrastructures. We use qualitative vignettes to illustrate how our theoretical framework helps to understand changing programming practices. Our findings suggest that scientists use and produce software in a way that deliberately mitigates the potential pitfalls of their programming practice. In particular, the object and method of visualization is subject to restraint intended to prevent accidental misuse.     

Testing scientific software: A systematic literature review

ContextScientific software plays an important role in critical decision making, for example making weather predictions based on climate models, and computation of evidence for research publications. Recently, scientists have had to retract publications due to errors caused by software faults. Systematic testing can identify such faults in code.ObjectiveThis study aims to identify specific challenges, proposed solutions, and unsolved problems faced when testing scientific software.MethodWe conducted a systematic literature survey to identify and analyze relevant literature. We identified 62 studies that provided relevant information about testing scientific software.ResultsWe found that challenges faced when testing scientific software fall into two main categories: (1) testing challenges that occur due to characteristics of scientific software such as oracle problems and (2) testing challenges that occur due to cultural differences between scientists and the software engineering community such as viewing the code and the model that it implements as inseparable entities. In addition, we identified methods to potentially overcome these challenges and their limitations. Finally we describe unsolved challenges and how software engineering researchers and practitioners can help to overcome them.ConclusionsScientific software presents special challenges for testing. Specifically, cultural differences between scientist developers and software engineers, along with the characteristics of the scientific software make testing more difficult. Existing techniques such as code clone detection can help to improve the testing process. Software engineers should consider special challenges posed by scientific software such as oracle problems when developing testing techniques.     

A new library to combine artificial neural networks and support vector machines with statistics and a database engine for application in environmental modeling

SADATO (SAMT DAta TOol) is an open source software library presenting new possibilities in modeling based on artificial neural networks and support vector machines. The main advantage of SADATO is its central data management based on Sqlite3 or MySQL and the statistical functions inherited from the APOPHENIA software. SADATO can be used for modeling as well as in large simulations. Modeling is demonstrated with two examples of artificial neural networks and support vector machines. The use of SADATO in simulation is supported by its very high computation speed. The highly aggregated functions in SADATO keep the software simple and easy to maintain. This allows the scientist experienced in software development easy access to all methods provided by SADATO. Additionally, an easy-to-use graphical user interface was developed to support scientists in developing models without any special knowledge in computer science.     

A scientific data processing framework for time series NetCDF data

The Atmospheric Radiation Measurement (ARM) Data Integrator (ADI) is a framework designed to streamline the development of scientific algorithms that analyze, and models that use time-series NetCDF data. ADI automates the process of retrieving and preparing data for analysis, provides a modular, flexible framework that simplifies software development, and supports a data integration workflow. Algorithm and model input data, preprocessing, and output data specifications are defined through a graphical interface. ADI includes a library of software modules to support the workflow, and a source code generator that produces C, IDL^®, and Python™ templates to jump start development. While developed for processing climate data, ADI can be applied to any time-series data. This paper discusses the ADI framework, and how ADI's capabilities can decrease the time and cost of implementing scientific algorithms allowing modelers and scientists to focus their efforts on their research rather than preparing and packaging data.     

Knowledge and software modeling using UML

Ontology can be considered as a comprehensive knowledge model which enables the developer to practice knowledge, instead of code, reuse. In the development of knowledge-based systems, different modeling languages are employed at different stages of the development process. By using a common modeling language for the knowledge and software models, knowledge instead of software reuse can be achieved. We illustrate the process by first presenting an ontology developed for an industrial domain and then investigate Unified Modeling Language (UML) as an ontology modeling tool. Since any model expressed in UML can be translated into a software model, the transition from the knowledge model to system implementation is better supported with the proposed approach. The industrial domain of selecting a remediation technique for petroleum contaminated sites is adopted for the illustration case study.     

Design and evaluation of a decision support system in a water balance application

Visualization has become a vital tool for representing the results of scientific models in decision support applications. Both the raw data and the models from which these visualizations are derived usually have considerable uncertainty associated with them. Decision-makers are typically presented with results from these models with little or no insight as to the reliability of the information shown. For effective decisions to be made, a decision support system should allow collaborative participation from scientists and decision-makers, and it should display the locations, magnitudes, and sources of uncertainty in the results. This research work discusses a software application for visualizing the results of a water balance model and its associated uncertainty. The effectiveness of the application and its visual presentation methods were incrementally tested and improved through usability engineering principles.     

Documenting,storing, and executing models in Ecology: A conceptual framework and real implementation in a global change monitoring program

Many of the best practices concerning the development of ecological models or analytic techniques published in the scientific literature are not fully available to modelers but rather are stored in scientists' digital or biological memories. We propose that it is time to address the problem of storing, documenting, and executing ecological models and analytical procedures. In this paper, we propose a conceptual framework to design and implement a web application that will help to meet this challenge. This tool will foster cooperation among scientists, enhancing the creation of relevant knowledge that could be transferred to environmental managers. We have implemented this conceptual framework in a tool called ModeleR. This is being used to document, share, and execute more than 200 models and analytical processes associated with a global change monitoring program that is being undertaken in the Sierra Nevada Mountains (south Spain). ModeleR uses the concept of scientific workflow to connect and execute different types of models and analytical processes. Finally, we have envisioned the creation of a federation of model repositories where models documented within a local repository could be linked and even executed by other researchers.     

A Software Tool for Constructing Traditional Chinese Medical Expert Systems

It is an urgent task to hnplemeut a lot of expert systems to capture the valuable expertise ofexperienced doctors of traditional Chinese medicine.In order to meet the needs,a software tool isdeveloped.It features a unified diagnosis model,a specially designed knowledge representationlanguage and an efficient but effective inference engine.To implement an expert system,it isonly necessary to input the expert's knowledge expressed in knowledge representation languagewithout the design of any additional software.The time and effort required for implementing anexpert system are thus greatly saved.The software is very compact and can run onmicrocomputers e.g.IBM-PC/XT.Two traditional Chinese medical expert systems have beensuccessfully implemented with the tool.     

Automatically building customized circuit-based simulation models using symbolic computing

Nowadays, most scientists and engineers rely on computer simulations to analyze, design, and prototype complex systems. Scientific and engineering system models are implemented in a variety of simulation environments; however, limited model libraries are often provided to users who are compelled to create their own customized models. Developing customized simulation models is a time-consuming and error-prone task which requires software developer skills. The difficulty of creating customized models presents the need for user-friendly tools that assist users in their code development process. This paper describes a tool named RCMAG that automatically builds customized models for the Virtual Test Bed (VTB) [http://vtb.engr.sc.edu/, The Virtual Test Bed Overview, Architecture, and Downloads] simulation environment. VTB is an interactive software system that provides a problem-solving environment (PSE) for simulation, prototyping, and advanced visualization of large-scale multi-disciplinary systems. VTB complies with a simulation standard named VHDL-AMS to enforce natural (circuit), signal, and data coupling between entities from diverse disciplines. The PSE tool RCMAG automatically builds naturally coupled or circuit-based VTB entities from input data provided by the user. RCMAG accepts both numeric and symbolic input data from the user, manages it to create code, and releases the compiled model object, which is ready to be added to the VTB model library and be used in a simulation.     

Building a Virtual Ecosystem Dynamic Model for Root Research

Understanding the fundamental mechanistic processes within large environmental models has great implications in model interpretation and future improvement. However, obtaining a good understanding of these processes can be challenging due to the complexities in model structures and software configurations. This paper introduces a functional test framework - with unique approaches to tackling software complexities in large environmental models – to facilitate process-based model exploration and validation. A Virtual Ecosystem Dynamic Model is developed as a case study to better understand and validate root-related processes in the Community Land Model (CLM). The proposed framework could help empiricists better access the inner workings of large environmental models, and facilitate integrative collaborations among broad scientific communities including field scientists, environmental system modelers, and computer scientists.     

An interactive environment for the modeling and discovery of scientific knowledge

Existing tools for scientific modeling offer little support for improving models in response to data, whereas computational methods for scientific knowledge discovery provide few opportunities for user input. In this paper, we present a language for stating process models and background knowledge in terms familiar to scientists, along with an interactive environment for knowledge discovery that lets the user construct, edit, and visualize scientific models, use them to make predictions, and revise them to better fit available data. We report initial studies in three domains that illustrate the operation of this environment and the results of a user study carried out with domain scientists. Finally, we discuss related efforts on model formalisms and revision and suggest priorities for additional research.     

A methodology for transparent knowledge specification in a dynamic tuning environment

The increasing use of parallel/distributed applications demands a continuous support to take significant advantages from parallel power. This includes the evolution of performance analysis and tuning tools which automatically allows for obtaining a better behavior of the applications. Different approaches and tools have been proposed and they are continuously evolving to cover the requirements and expectations of users. One such tool is MATE (Monitoring Analysis and Tuning Environment), which provides automatic and dynamic tuning for parallel/distributed applications. The knowledge used by MATE to analyze and take decisions is based on performance models which include a set of performance parameters and a set of mathematical expressions modeling the solution of the performance problem. These elements are used by the tuning environment to conduct the monitoring and analysis steps, respectively. The tuning phase depends on the results of the performance analysis. This paper presents a methodology to specify performance models. Each performance model specification can be automatically and transparently translated into a piece of software code encapsulating the knowledge to be straightforwardly included in MATE. Applying this methodology, the user does not have to be involved in the implementation details of MATE, which makes the usage of the tool more transparent. Copyright © 2011 John Wiley & Sons, Ltd.     

导弹总体方案设计软件系统设计与实现

针对提高导弹研制效率,研究了支持导弹总体方案设计软件构造的建模方法和软件实现技术,开发了相应软件系统。针对多方案设计过程中任务组织和数据交互动态变化的特点,采用一种通用的建模方法,以5类模型表达基本设计活动及数据结构,可使层次式模型管理策略实现全局组织和调度。依据此建模方法和多方案设计需求,设计了面向对象的模型数据结构和知识库接口方案,解决了软件实现关键问题。在VS.net环境下发展了一套战术导弹设计软件MCDesign,初步应用表明,提出的建模方法和软件设计思想可较好地支持战术导弹的多方案选型。     

CLIPS 在黑河水文水资源决策支持系统中的集成研究

传统的决策支持系统使用数学模型和数值计算方法来辅助决策, 因此决策者必须对某领域的模型和数据有一定的了解。黑河水文水资源决策支持系统集成了SWAT、TopModel、水文系统模型、时间序列模型等一系列模型。这些模型的结构和参数都比较复杂, 决策者难以掌握。在黑河水文水资源决策支持系统中, 加入专家知识支持, 使得决策者更容易的使用该系统是很有必要的。研究中, 采用美国航空航天局(NASA ) 开发的通用专家系统开发工具CLIPS 来实现专家知识支持,使用嵌入式方式将CL IPS 的核心推理机集成到黑河水文水资源决策支持系统中。CLIPS 专家系统在黑河水文水资源决策支持系统中的作用有3 点: ①辅助决策者进行模型的选择; ②辅助决策者进行模型参数的输入; ③辅助决策者分析模型运行的结果。     

基于ontology技术构建科学效应知识库*

为了使科学效应知识更好地支持创新性概念设计,分析了科学效应知识支持原理设计的过程,提出了基于本体的科学效应知识库系统模型。构建了科学效应知识本体,利用本体中的对象属性建立了功能、科学效应、特征流属性和设计实例间的联系;依据系统模型开发了科学效应知识库原型系统,系统支持对本体的推理查询,提供了相关知识表格和用户添加科学效应知识等功能,提高了知识搜索效率及查全率,方便了知识更新和维护,实现了科学效应知识对创新性概念设计的支持。     

An R-package to boost fitness and life expectancy of environmental models

Ordinary differential equations (ODE) are at the center of many environmental models. The R software is increasingly used to implement ODE-based models boosted by add-on packages providing numerical solvers. This paper introduces an R package called rodeo to facilitate the implementation of ODE-based models. It addresses a standardized model notation and documentation as well as the automatic generation of efficient, solver-compliant Fortran or R source code. The package has the potential to make a multitude of environmental models, more comprehensible, reusable, and exchangeable.     

How accurate is scientific software?

This paper describes some results of what, to the authors' knowledge, is the largest N-version programming experiment ever performed. The object of this ongoing four-year study is to attempt to determine just how consistent the results of scientific computation really are, and, from this, to estimate accuracy. The experiment is being carried out in a branch of the earth sciences known as seismic data processing, where 15 or so independently developed large commercial packages that implement mathematical algorithms from the same or similar published specifications in the same programming language (Fortran) have been developed over the last 20 years. The results of processing the same input dataset, using the same user-specified parameters, for nine of these packages is reported in this paper. Finally, feedback of obvious flaws was attempted to reduce the overall disagreement. The results are deeply disturbing. Whereas scientists like to think that their code is accurate to the precision of the arithmetic used, in this study, numerical disagreement grows at around the rate of 1% in average absolute difference per 4000 fines of implemented code, and, even worse, the nature of the disagreement is nonrandom. Furthermore, the seismic data processing industry has better than average quality standards for its software development with both identifiable quality assurance functions and substantial test datasets     

Retargetability and Extensibility in a Parallel Debugger

This paper describes the design and implementation ofPanorama, a parallel debugger for MIMD message-passing computers. Programmers can readily adapt Panorama to new parallel platforms and extended it to include their ownviewsof a target program. The system comes with three built-in graphical program views, and it also includes a software tool to help programmers design and implement new views. Panorama avoids detailed dependence on target architectures by using thebase debuggersupplied by each hardware vendor to carry out low-level debugging tasks such as setting breakpoints and examining data. Since the interfaces and capabilities of base debuggers vary, we have developed a strategy that models interactions between Panorama and base debuggers. The model separates general-purpose code from the special-case functions that handle specific debugger characteristics. The resulting system is easy to adapt and free from the clutter of conditionally-executed, special-case code.