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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

A dual-task investigation of automaticity in visual word processing

An analysis of activation models of visual word processing suggests that frequency-sensitive forms of lexical processing should proceed normally while unattended. This hypothesis was tested by having participants perform a speeded pitch discrimination task followed by lexical decisions or word naming. As the stimulus onset asynchrony between the tasks was reduced, lexical-decision and naming latencies increased dramatically. Word-frequency effects were additive with the increase, indicating that frequency-sensitive processing was subject to postponement while attention was devoted to the other task. Either (a) the same neural hardware shares responsibility for lexical processing and central stages of choice reaction time task processing and cannot perform both computations simultaneously, or (b) lexical processing is blocked in order to optimize performance on the pitch discrimination task. Either way, word processing is not as automatic as activation models suggest.

Attention↗
NASA NTRS2005

Modeling uncertainty in requirements engineering decision support

One inherent characteristic of requrements engineering is a lack of certainty during this early phase of a project. Nevertheless, decisions about requirements must be made in spite of this uncertainty. Here we describe the context in which we are exploring this, and some initial work to support elicitation of uncertain requirements, and to deal with the combination of such information from multiple stakeholders.

risk analysis↗
NASA NTRS2006

Content Integration Networks: Turning Search Upside Down

The slide presentation examines information management and retrieval among NASA centers and with outside sources. It provides an overview and problem statement, vision and high level technologies, strategies, knowledge management benefits, and a summary and challenge.

taxonomy↗
NASA NTRS2008

NASA Engineering Network (NEN)

This slide presentation reviews the NASA Engineering Network (NEN). NEN is designed to search documents over multiple repositories, submit and browse NASA Lessons Learned, collaborate and share ideas with other engineers via communities of practice, access resources from one portal, and find subject matter experts via the People, Organizations, Projects, Skills (POPS) locator.

NASA Engineering Network↗
NASA NTRSDate not supplied

The Radiation Biology Ontology: A New Tool Supporting FAIR Principles Across Radiation Biology Facilitating Data Discovery and Integration

Development of the Radiation Biology Ontology (RBO) was motivated by the need for a comprehensive, well-structured ontology for encoding radiation biology metadata. The primary use-cases were archiving data in the STORE database (https://www.storedb.org/), the repository for the RadoNorm Project, and in GeneLab (https://genelab.nasa.gov), NASA’s ‘omics database. The scope of radiobiology research ranges from physics to radiation oncology to socio-legal studies; no existing ontology has the necessary breadth or depth. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR radiation biology data.

ontology↗
DOE OSTI2012

Integrating Data Management and Collaborative Sharing with Computational Science Processes

Structured Scientific Data Management - the management of storage, access, usage, lifecycle, content and meaning for scientific data - is not as commonly employed in computational science as it is in other fields of scientific endeavor. However, where it has been co-developed and integrated with the computational science research it has had a transformational influence on the scientific work. These infrastructures enabled not only new research previously impossible, but also helped to speed up the research process and improved the quality of the research output. Good data management systems are capable of facilitating effective scientific collaborations on a group, institutional, national or international level, through the easy sharing of resources and results. Today as computational science is becoming more data rich and collaborative, integrated scientific data management is becoming an essential tool for every computational science research and production environment. This chapter will describe the fundamental principles and components of a good data management system, provide real world examples of successful implementations and provides an outlook on future developments. We conclude with a short section on how to get started for those whose interest has been peaked by this chapter

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