Scientific Application Domains Research Articles

The dynamical study and analysis of diverse bright-dark and breathers wave solutions of nonlinear evolution equations and their applications

In this work, we establish novel solitary wave solutions of three nonlinear evolution dynamical models, namely, Boussinesq model, [Formula: see text]-dimensional generalized shallow water wave (SWW) and [Formula: see text]-dimensional Fokas dynamical models by applying two-variable [Formula: see text]- expansion technique. The SWW equations are usually appropriate when the fluid is in a state where the vertical length scale is significantly smaller than the length of horizontal scale. In computer simulations for ocean engineering, Boussinesq-type models are frequently used to represent water waves in harbors and shallow seas. In order to understand the physical processes of waves inside and on the surface of water, the Fokas dynamical model plays a crucial part in wave theory. Analytical solutions in different forms such as solitons, solitary waves, trigonometric, hyperbolic, rational function solutions, breathers-type waves and more wave solutions are devised through using the proposed method. The exact solutions are also presented in graphical form having applications in engineering and other areas of applied sciences. The obtained results show that the given technique is universal and efficient. In addition, this technique can also be applied on lots of other nonlinear dynamical wave models occurring in many scientific real-world application domains, including engineering sciences, mathematics physics, and many more.

User needs for future Landsat missions

Landsat satellites have been operating since 1972, providing the longest continuous observation record of the Earth's land surface. Over the past half century, the Landsat user community has grown exponentially, encompassing more diverse and evolving scientific research and operational uses. Understanding current and future user needs is crucial to informing the design of Landsat missions beyond Landsat 9. The U.S. Geological Survey (USGS) initiated a user needs collection process to document needs from U.S. Federal civil subject matter experts who rely on moderate-resolution land imaging data across a diverse range of scientific research and application domains. In total, 379 moderate-resolution land imaging user needs were collected through structured interviews. The findings indicate that, at present, users need continuity in Landsat capabilities with free and open data access. Improvements to future Landsat systems should include 10 m spatial resolution and at least weekly cloud-free observation frequency. Spectral enhancements should include the addition of red edge bands, and multiple, narrower visible, near infrared, shortwave infrared, and thermal infrared bands. Ideally, a variety of applications need continuous, full-spectrum coverage in 10 nm-wide bands spanning the visible to shortwave infrared (VSWIR) region (400–2500 nm) and 5 to 8 multispectral thermal infrared bands. Non-Federal (state, local, commercial, academic, and international) sources found similar results, but a more comprehensive comparison across these communities through a broader survey may provide additional insights. USGS-collected moderate-resolution land imaging user needs are an input to the Landsat 10 Architecture Study to develop and assess feasible Landsat 10 mission architectures.

Test-Driven Development in HPC Science: A Case Study

Many scientific software developers have applied software engineering practices in their work in recent years. Agile methods are gaining increased interest from both industry and academia, including scientific application domains. Test-driven development (TDD) and refactoring practices are critical to the success of agile methods. Although many scientific projects employ agile practices, the effect of TDD on scientific software development remains unknown and should thus be investigated. The authors investigated the effects of using TDD to develop scientific software in a high-performance computing environment, finding both advantages and disadvantages. In particular, they observed that developers face problems with writing unit tests and with a lack of experience with software engineering practices.

Parallel and distributed association rule mining in life science: A novel parallel algorithm to mine genomics data

Association rule mining (ARM) is largely employed in several scientific areas and application domains, and many different algorithms for learning association rules from databases have been introduced. Despite the presence of many existing algorithms, there is still room for the introduction of novel approaches tailored for novel kinds of datasets. Because often the efficiency of such algorithms depends on the type of analyzed dataset. For instance, classical ARM algorithms present some drawbacks for biological datasets produced by microarray technologies in particular containing Single Nucleotide Polymorphisms (SNPs). In particular classical algorithms require large execution times also with small datasets. Therefore the possibility to improve the performance of such algorithms by leveraging parallel computing is a growing research area. The main contributions of this paper are: a comparison among different sequential, parallels and distributed ARM techniques, and the presentation of a novel ARM algorithm, named Balanced Parallel Association Rule Extractor from SNPs (BPARES), that employs parallel computing and a novel balancing strategy to improve response time. BPARES improves performance without loosing in accuracy as well as it handles more efficiently the available computational power and reduces the memory consumption.

SASO 2013

IEEE SASO (Self-Adapting and Self-Organizing Systems) is the premier international conference for computer systems and networks that autonomously change some aspect of themselves: code, form, function, shape, structure, components, and so on. Over the past 10 years, it has emerged as a key multidisciplinary event for sharing theoretical insights and technical innovations across the numerous scientific fields and application domains impacted by this research. In 2013, the conference was hosted by Drexel University in Philadelphia, Pennsylvania, and offered an extensive program of high-quality papers. This special issue of ACM TAAS presents selected, revised, and extended best articles, which showcase the rich variety and depth of the SASO scientific community.

Engineering Systems: Best-in-Class/Worst-in-Class

Measurement’s goal is to help assess performance—to determine which methods are productive or counterproductive. Metrics are tools used to identify and implement practices that lower costs, reduce time to market, and improve product quality. But process improvement is not accomplished through measurement or metrics alone. Rather, one must use the data to make conscious decisions that change the way business is done. In fact, one of best ways to make those decisions is by studying the characteristics of best- and worst-in-class software projects. Referencing Quantitative Software Management’s database of 10,000+ completed software projects, this article evaluates the common factors that define the most and least successful engineering projects—drawn from the database’s System Software, Scientific, Telecom, and Command and Control application domains. Presenting a thorough analysis of project staffing, effort, duration, cost, and quality data, this article gives project managers a solid, scientific framewor...

Status of the DIRAC Project

The DIRAC Project was initiated to provide a data processing system for the LHCb Experiment at CERN. It provides all the necessary functionality and performance to satisfy the current and projected future requirements of the LHCb Computing Model. A considerable restructuring of the DIRAC software was undertaken in order to turn it into a general purpose framework for building distributed computing systems that can be used by various user communities in High Energy Physics and other scientific application domains. The CLIC and ILC-SID detector projects started to use DIRAC for their data production system. The Belle Collaboration at KEK, Japan, has adopted the Computing Model based on the DIRAC system for its second phase starting in 2015. The CTA Collaboration uses DIRAC for the data analysis tasks. A large number of other experiments are starting to use DIRAC or are evaluating this solution for their data processing tasks. DIRAC services are included as part of the production infrastructure of the GISELA Latin America grid. Similar services are provided for the users of the France-Grilles and IBERGrid National Grid Initiatives in France and Spain respectively. The new communities using DIRAC started to provide important contributions to its functionality. Among recent additions can be mentioned the support of the Amazon EC2 computing resources as well as other Cloud management systems; a versatile File Replica Catalog with File Metadata capabilities; support for running MPI jobs in the pilot based Workload Management System. Integration with existing application Web Portals, like WS-PGRADE, is demonstrated. In this paper we will describe the current status of the DIRAC Project, recent developments of its framework and functionality as well as the status of the rapidly evolving community of the DIRAC users.

Provenance trails in the Wings/Pegasus system

AbstractOur research focuses on creating and executing large‐scale scientific workflows that often involve thousands of computations over distributed, shared resources. We describe an approach to workflow creation and refinement that uses semantic representations to (1) describe complex scientific applications in a data‐independent manner, (2) automatically generate workflows of computations for given data sets, and (3) map the workflows to available computing resources for efficient execution. Our approach is implemented in the Wings/Pegasus workflow system and has been demonstrated in a variety of scientific application domains. This paper illustrates the application‐level provenance information generated Wings during workflow creation and the refinement provenance by the Pegasus mapping system for execution over grid computing environments. We show how this information is used in answering the queries of the First Provenance Challenge. Copyright © 2007 John Wiley & Sons, Ltd.

File-based replica management

Data replication is one of the best known strategies to achieve high levels of availability and fault tolerance, as well as minimal access times for large, distributed user communities using a world-wide Data Grid. In certain scientific application domains, the data volume can reach the order of several petabytes; in these domains, data replication and access optimization play an important role in the manageability and usability of the Grid. In this paper, we present the design and implementation of a replica management Grid middleware that was developed within the EDG project [European DataGrid Project (EDG), http://www.eu-egee.org] and is designed to be extensible so that user communities can adjust its detailed behavior according to their QoS requirements.