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At least 631 records · Page 35

Remote Adaptive Motor Resistance Training Exercise Apparatus and Method of Use Thereof

The invention comprises a method and/or an apparatus using a computer configured exercise system equipped with an electric motor to provide physical resistance to user motion in conjunction with means for sharing exercise system related data and/or user performance data with a secondary user, such as a medical professional, a physical therapist, a trainer, a computer generated competitor, and/or a human competitor. For example, the exercise system is used with a remote trainer to enhance exercise performance, with a remote medical professional for rehabilitation, and/or with a competitor in a competition, such as in a power/weightlifting competition or in a video game. The exercise system is optionally configured with an intelligent software assistant and knowledge navigator functioning as a personal assistant application.

Reich, Alton↗

NASAs Solar System Exploration Research Virtual Institute- Expanded Goals and More Partners

The NASA Solar System Exploration Research Virtual Institute (SSERVI) has been pursuing international partnerships since its inception as the NASA Lunar Science Institute (NLSI), in order to both leverage the science being done by its domestic member institutions as well as to help lunar science and exploration become a greater global endeavor. The international partners of the Institute have pursued a broad program of lunar science stimulated by scientific partnerships enabled by the SSERVI community. Furthermore, regional partnerships have been formed such as the new pan-European lunar science consortium, which promises both new scientific approaches and mission concepts. International partner membership requires long-term commitment from both the partner and SSERVI, together with tangible and specific plans for scientific interaction that will produce results of mutual benefit to both the institute's U.S. Teams and the international partner. International partners are invited to participate in all aspects of the Institute's activities and programs, on a basis of no exchange of funds. Through these activities, SSERVI researchers and international partners participate in sharing ideas, information, and data arising from their respective research efforts, and contribute to the training of young scientists. This talk will present an overview of the Institute and the international nodes. We will also discuss the various processes to become a SSERVI partner as well as the opportunities available for collaborations with the SSERVI national teams.

SSERVI↗

Science in a Team Environment (AKA, How to Play Nicely with Others)

So you want to do NASA funded research in a spaceflight analog? There are several things about participating in an HRP managed analog that may be different from the way you normally do work in your laboratory. The purpose of this presentation is to highlight those differences and explain some of the unique aspects of doing this research. Participation in an HRP funded analog study complement, even if initially selected for funding, is not automatic and involves numerous actions from ISSMP, HRP, and the PI. There are steps that have to be taken and processes to follow before approval and ISSMP-FA integration. After the proposal and acceptance process the Investigator works closely with the Flight Analog team to ensure full integration of their study requirements into a compliment. A complement is comprised of a group of studies requiring a common platform and/or scenario that are able to be integrated on a non-interference basis for implementation. Full integration into the analog platform can be broken down into three phases: integration, preparation, and implementation. These phases occur in order with some overlap in the integration and preparation phase. The ISSMP-FA team integrates, plans and implements analog study complements. Properly defining your research requirements and getting them documented is one of the most critical components to ensure successful integration and implementation of your study, but is also one of the most likely to be neglected by PIs. Requirements that are not documented, or that are documented poorly are unlikely to get done, no matter how much you push. The process to document requirements is two-fold, consisting of an initial individual requirements integration and then a compliment requirements integration. Understanding the requirements in detail and early ensures that the science is not compromised by outside influences. This step is vital to the integration, preparation, and implementation phases. The individual requirements integration is the first step in ensuring that the research fits into an available analog platform or allows for the Flight Analog team to provide information on structural study changes for participation in the analog. At this early point investigators need to understand exactly what their requirements are to produce relevant data and convey their must have needs to the Flight Analog team. The fluid nature of analog platforms allow for minor alterations to the operational structure. Participation in analog research requires flexibility from the investigator to ensure implementation of their research into a flight like analog platform. The compliment integration requires plasticity; investigators are asked to work closely with one another and the Flight Analog team to combine research studies into a single study plan. This study plan's ultimate goal is to facilitate multiple study participation with minimal scientific impact to each individual study. The Flight Analogs team works to find the best compromise for all parties while protecting the flight like atmosphere of a particular analog. Additional restrictions, limitations and constraints may be required by the analog in order to make all of the science work. Many studies need to be combined into each complement and there are a limited number of hours available for data collection. Through data/sample sharing, we can reduce the burden on the test subject, while usually avoiding significant science impacts. Restrictions on food, exercise, medications and sleep cycle are important to consider for your research.

Platts, S. H.↗

Remote Adaptive Motor Resistance Training Exercise Apparatus and Method of Use Thereof

The invention comprises a method and/or an apparatus using a computer configured exercise system equipped with an electric motor to provide physical resistance to user motion in conjunction with means for sharing exercise system related data and/or user performance data with a secondary user, such as a medical professional, a physical therapist, a trainer, a computer generated competitor, and/or a human competitor. For example, the exercise system is used with a remote trainer to enhance exercise performance, with a remote medical professional for rehabilitation, and/or with a competitor in a competition, such as in a power/weightlifting competition or in a video game. The exercise system is optionally configured with an intelligent software assistant and knowledge navigator functioning as a personal assistant application.

Reich, Alton↗

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When coupled with large scale, distributed hardware and software, STARE-based data access reduces pre-analysis data preparation costs by offering a convenient means to align different datasets spatiotemporally without specialized effort in parallel computing or distributed data management.

Kuo, Kwo-Sen↗

An Innovative Infrastructure with a Universal Geo-Spatiotemporal Data Representation Supporting Cost-Effective Integration of Diverse Earth Science Data

The SpatioTemporal Adaptive Resolution Encoding (STARE) is a unifying scheme encoding geospatial and temporal information for organizing data on scalable computing/storage resources, minimizing expensive data transfers. STARE provides a compact representation that turns set-logic functions into integer operations, e.g. conditional sub-setting, taking into account representative spatiotemporal resolutions of the data in the datasets. STARE geo-spatiotemporally aligns data placements of diverse data on massive parallel resources to maximize performance. Automating important scientific functions (e.g. regridding) and computational functions (e.g. data placement) allows scientists to focus on domain-specific questions instead of expending their efforts and expertise on data processing. With STARE-enabled automation, SciDB (Scientific Database) plus STARE provides a database interface, reducing costly data preparation, increasing the volume and variety of interoperable data, and easing result sharing. Using SciDB plus STARE as part of an integrated analysis infrastructure dramatically eases combining diametrically different datasets.

Rilee, Michael Lee↗

Experimental Design for Pre-Clinical Animal Model Study in Microgravity

The Rodent Research program at NASAs Ames Research Center (ARC) has pioneered a new research capability on the International Space Station in less than four years and has progressed toward translating research to the ISS utilizing commercial rockets, collaborating with academia and science industry, and training crew for research purposes on-orbit. Animal models are the foundation of pre-clinical research to understand human diseases and evaluate new therapeutics. Advancement in alleviating ground diseases such as muscle atrophy and osteoporosis can come from the study of similar conditions that are known to occur as a result of exposure to the spaceflight environment. During the completion of the flight phase of two missions, our practices, hardware and operations evolved from tested to developed standards, which successfully translated the studies from ground to space. Results from these studies contribute to the science community via both the primary investigation and banked samples that are shared in publicly available data repository such as GeneLab. Every completed mission sets a foundation to build and design greater complexity into future research and answer questions about common human diseases on ground and in space. Here, we present methods developed for the translation of a rodent experiment to the ISS including a description of hardware and kits available for investigators and a discussion of operational constraints.

Rodent Research↗

Cognitive Communications and Networking Technology Infusion Study Report

As the envisioned next-generation SCaN Network transitions into an end-to-end “system of systems” with new enabling capabilities, it is anticipated that the introduction of machine learning, artificial intelligence, and other cognitive strategies into the network infrastructure will result in increased mission science return, improved resource efficiencies, and increased autonomy and reliability. This enhanced set of cognitive capabilities will be implemented via a “space cloud” concept to achieve a service-oriented architecture with distributed cognition, de-centralized routing, and shared, on-orbit data processing. The enabling cognitive communications and networking capabilities that may facilitate the desired network enhancements are identified in this document, and the associated enablers of these capabilities, such as technologies and standards, are described in detail.

Knoblock, Eric J.↗

Scalable Traffic Management for Emergency Response Operations (STEReO)

The Scalable Traffic Management for Emergency Response Operations (STEReO) project aims to apply various NASA technologies, such as Unmanned Aircraft System (UAS) Traffic Management (UTM) services, onboard-vehicle autonomy, novel approaches to communications and connectivity, and remote/virtual collaboration interfaces to current-day emergency response efforts to natural disasters. Today's emergency response efforts are based on long-standing procedures that are manaul in nature, and could benefit from modernization. In particular, the use of UAS vehicles is limited, primarily due to concerns surrounding dangerous interactions between manned/unmanned operations. STEReO hopes to introduce data exchanges that improve shared situation awareness, reduce manual coordination procedures, enable scalable and high-density air operations, collectivley bringing a positive impact to the incident response. When successful, STEReO technologies will improve efficiency and timeliness of the response and recovery phases of a disaster, resulting in substantial reductions to community harm, and will also accelerate NASA’s development of high-density resilient operations, benefitting other projects relying on increasing levels of autonomy and connectivity. The prepared material provides an overview of the STEReO project, for presentation at the 2019 Convergent Aeronautics Solution (CAS) Showcase event. The CAS showcase brings together all of the current CAS execution activities, highlighting NASA's high-risk investments in aeronautics research.

Mercer, Joey↗

Lessons Learned From Smallsat Microwave Sounders Data Assimilation in the NASA Goddard Earth Observing System (GEOS)

The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of small satellites carrying state-of-art microwave temperature and humidity sounders with 12 channels between 91 GHz and 205 GHz frequency. Including TROPICS-pathfinder, launched on 30 June 2021, five TROPICS satellites operate and provide temperature and humidity data to NWP and atmospheric retrieval communities. This study evaluates the quality of radiance data from these five satellites. It assesses data impacts on NASA Goddard Earth Observing System (GEOS) global NWP analysis and forecasts while seeking answers to the following key questions: 1. What information do TROPICS satellites bring to NWP analysis? 2. How will TROPICS data assimilation affect NWP forecasts, including tropical cyclone analysis and forecasts? 3. What are the benefits of having multiple TROPICS satellites in NWP forecasts? 4. What are the weaknesses regarding instrument stability, consistency, and data quality of these CubeSats? 5. Can multiple TROPICS make similar impacts as conventional MW sensors such as ATMS or GPM Microwave Imager (GMI)? The sensitivities of each TROPICS channel to temperature, water vapor, cloud, and precipitation are examined in various weather conditions. Results from observing system experiments assimilating TROPICS radiance are used for evaluation metrics, including forecast skills and fit to other observations such as radiosondes and microwave and infrared sounders. Finally, the lessons learned from using these cube satellite radiance data in the GEOS atmospheric data assimilation system are shared.

Min-Jeong Kim↗

Architecture of High-Altitude Operations (HAO) Discovery and Synchronization Service (DSS)

The aviation industry is evolving at an unprecedented pace, necessitating the development of efficient, secure, and interoperable systems to manage increasingly complex air traffic. Moreover, the demand for High-Altitude Operations (HAO) is increasing. Furthermore, air traffic control services are limited in HAO environments. HAO industry participants will need airspace access and flexibility to perform their missions in this airspace that provides provisions for scalability. The Discovery and Synchronization Service (DSS) will be a cornerstone of the HAO ecosystem, enabling the effective sharing of critical airspace data, including operational intent, aircraft trajectories, and airspace usage among various stakeholders and operators. The DSS architecture addresses these challenges with a distributed, decentralized, and interoperable system that facilitates seamless integration across diverse airspaces. It prioritizes secure data exchange while safeguarding data ownership. This white paper presents the vision, architecture, and benefits of the DSS for HAO, underscoring its potential to streamline operations, reduce redundancies, and establish a foundation for safe and efficient airspace management.

HAO↗

ROSAT implementation of a proposed multi-mission x ray data format

Until recently little effort has been made to ensure that data from X-ray telescopes are delivered in a format that reflects the common characteristics that most X-ray datasets share. Instrument-specific data-product design hampers the comparison of X-ray measurements made by different detectors and should be avoided whenever possible. The ROSAT project and the High Energy Astrophysics Science Archive Research Center (HEASARC) have defined a set of X-ray data products ('rationalized files') for ROSAT data that can be used for distribution and archiving of data from other X-ray missions. This set of 'rationalized files' has been defined to isolate instrument-independent and instrument-specific quantities using standards FITS constructs to ensure portability. We discuss the usage of the 'rationalized files' by ROSAT for data distribution and archiving, with particular emphasis on discrimination between instrument-independent and instrument-specific quantities, and discuss application of this format to data from other X-ray missions.

Corcoran, M.↗

Beyond Fair: Engagement, Data Usability, and Open Community Productivity through the NASA Open Science Data Repository

The FAIR principle (findable, accessible, interoperable, and reusable) governs the storage and sharing of NASA space biology and health data[1]. These guiding principles maximize reuse of data and the reproducibility of scientific findings. The NASA Open Science Data Repository (OSDR; an expansion of NASA GeneLab) was built on the FAIR principles and houses over 500 studies and close to 1000 datasets from decades of space life sciences experiments. OSDR embodies the FAIR principles through data governance that includes mediated, embargoed, and fully open access data. The FAIR data governance principles were recently proposed to be expanded to encompass a FAIREST framework for assessing research data repositories (FAIR + Engagement, Social connections, and Trust)[2]. FAIREST emphasizes the importance of data repositories engaging with the scientific community and gaining the trust of researchers regarding data quality. Trust also refers to the TRUST principles developed for assessment of digital repositories: Transparency, Responsibility, User Focus, Sustainability, Technology[3]. We present the “Open Science for Life in Space” Analysis Working Groups (AWGs) as evidence regarding the power of engagement, social connections, and trust which has enhanced OSDR’s capabilities and productivity. AWG members engage in two main activities. One, members provide feedback on OSDR scientific standards for data ingestion, curation, and reuse (study, subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability). Two, AWG members collaborate to mine-reuse OSDR data to conduct scientific analysis. With nearly 800 active members, the AWGs have resulted in 32 publications re-using OSDR data and contributed many papers in two major special issues in Cell (2020) and Nature (2024). AWGs also serve as networking groups, facilitate social connections between researchers at all levels of experience, and also have a social online ‘Forum’ used to keep members informed on projects and opportunities. This community-centric, productive, and trustworthy data culture has resulted in a broader effect with international space agencies, academics, and the commercial space sector wanting to submit their data to OSDR. Ten studies of Inspiration 4 data were recently publicly released by OSDR, as were some JAXA human data. Coming up soon in OSDR are data submissions from the European Space Agency, Virgin Galactic PIs, and SpaceX Polaris Dawn. A major benefit of OSDR is the array of standardized and uniformly formatted data (which was developed through AWG member consensus), from which visualization tools, analysis tools, and machine learning models can be built or trained. This talk will cover the Multi-Study Visualization Tool, the Environmental Data Application, RadLab, and a UCSF-NSF funded knowledge graph biomedical health discovery tool ‘SPOKE’ currently being integrated with OSDR. OSDR also provides training programs in bioinformatics and machine learning to improve the scientific community’s awareness of data availability and to boost their ability to perform data analysis. The increasing engagement of the scientific community and the public with technologies powered by artificial intelligence (AI) heightens the need for data analysis to be transparent. The AI for Life in Space initiative leverages the data products provided in OSDR to train AI models, with an emphasis on explainable and trustworthy AI, which would not be possible without FAIR data and metadata. Overall, here we will demonstrate the importance for NASA life sciences data repositories to adhere to the FAIREST framework, by providing examples and success stories from different aspects of OSDR.

data↗

The Test Analysis Retrieval System (TARS): Meeting the challenges of the network's test processes

The Networks Systems Test Section (GSFC 531.4) is responsible for managing a variety of engineering and operational tests used to assess the status of the Network elements relative to readiness certification for new and ongoing mission support and for performance trending. To conduct analysis of data collected during these tests, to disseminate and share the information, and to catalog and create reports based on the analysis is currently a cumbersome and inefficient task due primarily to the manual handling of paper products and the inability to easily exchange information between the various Networks elements. The Test Analysis and Retrieval System (TARS) is being implemented to promote concise data analysis, intelligible reporting of test results, to minimize test duplication by fostering a broad sharing of test data, and perhaps most importantly, to provide significantly improved response to the Network's internal and external customers. This paper outlines the intended application, architecture, and benefits of the TARS.

Stelmaszek, Robert L.↗

Move to Talk, Talk to Move: Tightly Integrated Communication and Control for Coordinated Swarms of Small Spacecraft

The Move to Talk, Talk to Move: Tightly Integrated Communication and Control for Coordinated Swarms of Small Spacecraft project will build on existing research on collaborative autonomy of multi-agent systems and design techniques that will enable coordinated communication and control of spacecraft. The success of many space exploration and science missions hinges on real-time monitoring of time-varying and/or geographically distributed phenomena. This monitoring can be achieved using a swarm of small spacecraft, which collect data about the environment and share information within the swarm of spacecraft. Current space exploration missions typically issue commands to control each spacecraft individually from Earth, and the data gathered by each spacecraft is also transmitted to Earth separately via X-band communication over the Deep Space Network (DSN). This approach is expensive, slow, and unreliable. Many coordinated tasks amongst a swarm of autonomous agents (or, specifically, small spacecraft) rely on communication. Existing control, estimation, and decision algorithms often assume that mostly reliable communications are available; however, this is often not the case in actual environments and thus is a barrier to operating swarms of small spacecraft.

Qi Han↗

Overview of the Upper Atmosphere Research Satellite: Observations from 1991 to 2002

The Upper Atmosphere Research Satellite (UARS) was launched in September 1991 by the Space Shuttle Discovery. Seven of the original ten instruments aboard the UARS are functional and six instruments regularly take measurements. The UARS is in a stable observing configuration, in spite of experiencing several anomalies which have impacted the data tape storage and power available. Power sharing and "real-time" operations using the Tracking and Data Relay Satellites have reduced the data collection over the past five years. Although the UARS measurements have not been continuous, the UARS instruments HALOE, SUSIM, SOLSTICE, HRDI, WINDII, and PEM have provided important observations over an entire solar cycle. The UARS HALOE instrument measures ozone and other constituents important in understanding ozone variations. The UARS SUSIM and SOLSTICE instruments observe ultraviolet light between 120 and 420 nm, which influence middle atmospheric constituent fluctuations. The UARS HRDI and WINDII instruments measure winds in the stratosphere, mesosphere, and thermosphere, which move constituents among the various atmospheric regions. The UARS PEM instrument provides observations of input precipitating charged particles, including both electrons and protons. This paper will provide an overview about the UARS mission and its relevant atmospheric measurements.

Jackman, Charles H.↗

Generic, Extensible, Configurable Push-Pull Framework for Large-Scale Science Missions

The push-pull framework was developed in hopes that an infrastructure would be created that could literally connect to any given remote site, and (given a set of restrictions) download files from that remote site based on those restrictions. The Cataloging and Archiving Service (CAS) has recently been re-architected and re-factored in its canonical services, including file management, workflow management, and resource management. Additionally, a generic CAS Crawling Framework was built based on motivation from Apache s open-source search engine project called Nutch. Nutch is an Apache effort to provide search engine services (akin to Google), including crawling, parsing, content analysis, and indexing. It has produced several stable software releases, and is currently used in production services at companies such as Yahoo, and at NASA's Planetary Data System. The CAS Crawling Framework supports many of the Nutch Crawler's generic services, including metadata extraction, crawling, and ingestion. However, one service that was not ported over from Nutch is a generic protocol layer service that allows the Nutch crawler to obtain content using protocol plug-ins that download content using implementations of remote protocols, such as HTTP, FTP, WinNT file system, HTTPS, etc. Such a generic protocol layer would greatly aid in the CAS Crawling Framework, as the layer would allow the framework to generically obtain content (i.e., data products) from remote sites using protocols such as FTP and others. Augmented with this capability, the Orbiting Carbon Observatory (OCO) and NPP (NPOESS Preparatory Project) Sounder PEATE (Product Evaluation and Analysis Tools Elements) would be provided with an infrastructure to support generic FTP-based pull access to remote data products, obviating the need for any specialized software outside of the context of their existing process control systems. This extensible configurable framework was created in Java, and allows the use of different underlying communication middleware (at present, both XMLRPC, and RMI). In addition, the framework is entirely suitable in a multi-mission environment and is supporting both NPP Sounder PEATE and the OCO Mission. Both systems involve tasks such as high-throughput job processing, terabyte-scale data management, and science computing facilities. NPP Sounder PEATE is already using the push-pull framework to accept hundreds of gigabytes of IASI (infrared atmospheric sounding interferometer) data, and is in preparation to accept CRIMS (Cross-track Infrared Microwave Sounding Suite) data. OCO will leverage the framework to download MODIS, CloudSat, and other ancillary data products for use in the high-performance Level 2 Science Algorithm. The National Cancer Institute is also evaluating the framework for use in sharing and disseminating cancer research data through its Early Detection Research Network (EDRN).

Foster, Brian M.↗