ACTIVATE Cloud Data From in-Situ Instruments - Overview and First Results
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Simon Kirschler↗
SEARCH · Engineering Papers
Results for “active data”
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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Observations on Cost Modeling and Performance Measurement of Long Term Archives
This paper describes a prototype suite of Excel-based tools that could be used for estimating lifecycle costs for newly planned or modified long-term archival facilities. These tools may also prove valuable for monitoring the long-term performance of such facilities once operational. Cost estimation is by analogy, using statistical curve-fitting techniques across a database of comparable data activities. The database currently includes 29 operational data centers ranging from small (2 FTEs) to large (66 FTEs), and is readily expandable to include additional activities specifically involving data preservation and added value. Each comparable data center is described in terms of its staffing, throughput workload, archival and distribution requirements, levels of user service, overall complexity, degree of automation, and other data, comprising 94 distinct descriptors in all. The descriptors were developed by normalizing heterogeneous data from the various centers and mapping them into an Excel framework consistent with the OAIS reference model. A user-friendly tool is provided for generating input to and updating the comparables database. This tool can also be used to benchmark the performance (in terms of cost versus throughput) of an operational data center, and to update the staffing, cost and workload data on a periodic basis. The comparables database could thus provide a history of staffing and throughput over time, as a means of performance monitoring and providing feedback for continuous improvement. Ancillary tools are also provided for performing "what-if' cost exercises for planning purposes, and for graphical display of data and results. We provide a high-level description of the tools; present our experiences and observations on gathering the information and maintaining the database; and discuss how this tool set might be applied to long term archives.
Fontaine, Kathy↗
Assessment of Uncertainty in the Determination of Activation Energy for Polymeric Materials
An assessment of the experimental uncertainty in obtaining the kinetic activation energy from thermogravimetric analysis (TGA) data is presented. A neat phenolic resin, Borden SC1O08, was heated at three heating rates to obtain weight loss vs temperature data. Activation energy was calculated by two methods: the traditional Flynn and Wall method based on the slope of log(q) versus 1/T, and a modification of this method where the ordinate and abscissa are reversed in the linear regression. The modified method produced a more accurate curve fit of the data, was more sensitive to data nonlinearity, and gave a value of activation energy 75 percent greater than the original method. An uncertainty analysis using the modified method yielded a 60 percent uncertainty in the average activation energy. Based on this result, the activation energy for a carbon-phenolic material was doubled and used to calculate the ablation rate In a typical solid rocket environment. Doubling the activation energy increased surface recession by 3 percent. Current TGA data reduction techniques that use the traditional Flynn and Wall approach to calculate activation energy should be changed to the modified method.
Darby, Stephania P.↗
NASA’s Commercial Smallsat Data Acquisition (CSDA) Program Data System
The National Aeronautic and Space Administration (NASA) Commercial Smallsat Data Acquisition (CSDA) Program was established to identify, evaluate, and acquire data from commercial satellite companies that support and complement NASA’s Earth sciences missions and research goals. Since becoming a sustained program in 2020, CSDA has been developing a data system to provide scalable, efficient, continuous, and repeatable data management processes for all commercial data acquired by NASA. This includes providing access to commercial data to approved science investigators through NASA developed and vendor operated interfaces. As the commercial data user community and volume of data acquired by CSDA has grown, the team managing these data has adapted technologies and services to better address the data and information search, discovery, and access needs of the science user community. This presentation will provide an overview of CSDA Program data system activities including data availability, development of CSDA user interfaces, challenges in managing large-volume diverse datasets, and long-term data preservation activities to retain data for scientific reproducibility.
data management↗
Metabolic cost of extravehicular activities
The Skylab zero-g extravehicular activity data is of particular interest when it is considered in combination with the Apollo and Gemini data. The energy cost of extravehicular activity from Gemini through Skylab is discussed.
Waligora, J. M.↗
On developing the local research environment of the 1990s - The Space Station era
A requirements analysis for the Space Station's polar platform data system has been performed. Based upon this analysis, a cluster, layered cluster, and layered-modular implementation of one specific module within the Eos Data and Information System (EosDIS), an active data base for satellite remote sensing research has been developed. It is found that a distributed system based on a layered-modular architecture and employing current generation work station technologies has the requisite attributes ascribed by the remote sensing research community. Although, based on benchmark testing, probabilistic analysis, failure analysis and user-survey technique analysis, it is found that this architecture presents some operational shortcomings that will not be alleviated with new hardware or software developments. Consequently, the potential of a fully-modular layered architectural design for meeting the needs of Eos researchers has also been evaluated, concluding that it would be well suited to the evolving requirements of this multidisciplinary research community.
Chase, Robert↗
MODIS Validation, Data Merger and Other Activities Accomplished by the SIMBIOS Project: 2002-2003
The purpose of this technical report is to provide current documentation of the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities, satellite data processing, and data product validation. This documentation is necessary to ensure that critical information is related to the scientific community and NASA management. This critical information includes the technical difficulties and challenges of validating and combining ocean color data from an array of independent satellite systems to form consistent and accurate global bio-optical time series products. This technical report focuses on the SIMBIOS Project s efforts in support of the Moderate-Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra platform (similar evaluations of MODIS/Aqua are underway). This technical report is not meant as a substitute for scientific literature. Instead, it will provide a ready and responsive vehicle for the multitude of technical reports issued by an operational project.
Fargion, Giulietta S.↗
[New Retrieval Algorithms for Geophysical Products from GLI and MODIS Data]
Below is the 1st year progress report for NAG5-13435 "New Retrieval Algorithms for Geophysical Products from GLI and MODIS Data". Activity on this project has been coordinated with our NASA DB project NAG5-9604. For your convenience, this report has six sections and an Appendix. Sections I - III discuss specific activities undertaken during the past year to analyze/use MODIS data. Section IV formally states our intention to no longer pursue any research using JAXA's (formerly NASDA's) GLI instrument which catastrophically failed very early after launch (also see the Appendix). Section V provides some indications of directions for second year activities based on our January 2004 telephone discussions and email exchanges. A brief summary is given in Section VI.
Dodge, James C.↗
Data management study. Appendix N - Contractor data requirements site activation for launch /AL/ Final report
Contractor data requirements for site activation for Voyager spacecraft launch
VOYAGER PROJECT↗
ERTS image data compression technique evaluation
The author has identified the following significant results. Tapes of compressed ERTS data were obtained to permit later reconstruction and to prove that in general four ERTS MSS tapes can be put onto a single compressed tape. A compressed tape was reconstructed and imagery made. The data were compressed using the essentially information preserving SSDIAM algorithm, with mappings of from 1 to 3 levels and imagery was made of the result. This imagery shows that no visual degradation results from the one level mapping while compression is significantly increased. Mappings of up to three levels shows negligible deterioration in areas of moderate to high data activity, but contouring is noticeable in areas of uniform data such as the plains region.
Spencer, D. J.↗
Application of ML/AI for Identifying Earth Science Datasets in Research Publications
NASA Data Active Archive Centers, or DAACs, ingest, store and distribute data acquired from satellites, ground systems as well as modelling data. These data are organized by the datasets, each presenting collection of files usually associated with the certain mission, instrument, processing level, parameter(s), algorithm and/or model. The number of datasets offered by a single DAAC to the public varies. GES DISC, for example, currently offers for public use approximately ~1,300 datasets. While each publicly offered dataset comes with supporting documentation, it is challenging for novice and even experienced scientists to navigate among the datasets that offer similar parameters to find the datasets for their particular research application. Supplying dataset documentation with the scientific paper citations that refer to that dataset provides means for the dataset users to educate themselves with the application research that dataset is being used in. Collecting citations of the papers that use the datasets for their research yield valuable insights into application areas of those datasets, information about usage of the dataset groups for specific applications and those application topics. It also gives insights into the “deep metrics” of the dataset usage, as opposed to the common metrics of the dataset usage such as number of users who downloaded the dataset files and volumes of downloaded data. Association of a certain scientific paper with the dataset(s) presents a challenge because most of the paper authors do not properly cite the datasets, datasets usually have cryptic names and Digital Object Identifiers (DOIs) that are used for dataset identification were assigned to the datasets only few years ago. Simple Google or online library search do not provide even meaningful fraction of the results when performed by the dataset name or DOI, however they provide too many results when the search is done by more broader terms such as mission and instrument names. Attempts to create an AI system capable to identify dataset in the scientific papers have already been made using neural networks classifiers on the basis of the dataset mission, instrument and variable name. This method was applied to NASA SEDAC, which has 41 datasets in total. In GES DISC there can be as many as ~100 datasets per mission/instrument with some of the datasets consisting of multiple variables so there is a need for more differentiating parameters for dataset identification in the paper. The approach we are currently investigating is creating AI classifiers that are based on multiple dataset features, or keywords, extracted from the NASA Earthdata Common Dataset Repository (CMR). The features are weighted based on how precisely they can identify a dataset. The classifier uses preprocessed paper text as input and searches for the CMR datasets whose feature sets are the closest to the feature sets contained in the paper. The challenges of dataset identification include variety of ways the paper authors describe the datasets in their papers and incomplete tagging of the CMR dataset description (DIFs).
Irina Gerasimov↗
Thermal metamorphism of primitive meteorites. XI - The enstatite meteorites: Origin and evolution of a parent body
The neutron activation data for Ag, As, Bi, Cd, Co, Cs, Cu, Ga, In, Rb, Se, Te, Tl, and Zn were obtained in samples of Abee heated to 1000-1400 C at low pressures. In addition, these elements were reported in nine enstatite achondrites and in the silicate part of the Mt. Egerton stony-iron. The data show trace element losses above 1000 C by diffusion-controlled processes with apparent activation energies of 8 to 55 kcal/mol; these data together with abundances of aubrites, Mt. Egerton, and E4-6 chondrites, and isotopic results link all enstatite meteorites to a common parent body. The data also indicate that aubrites and the Mt. Egerton material reflect fractional crystallization of a magma produced from enstatite chondrite-like parent material (E6) and the late introduction of chalcophiles and mobile elements transported by an FeS-Fe eutectic from an E4-6 region undergoing open-system metamorphism.
Biswas, S.↗
Visual Inference Programming
The goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.
Wheeler, Kevin↗
Characterization of Forested Landscapes From Remotely Sensed Data Using Fractals and Spatial Autocorrelation
The characterization of forested areas is frequently required in resource management practice. Passive remotely sensed data, which are much more accessible and cost effective than are active data, have rarely, if ever, been used to characterize forest structure directly, but rather they usually focus on the estimation of indirect measurement of biomass or canopy coverage. In this study, some spatial analysis techniques are presented that might be employed with Landsat TM data to analyze forest structure characteristics. A case study is presented wherein fractal dimensions, along with a simple spatial autocorrelation technique (Moran s I), were related to stand density parameters of the Oakmulgee National Forest located in the southeastern United States (Alabama). The results of the case study presented herein have shown that as the percentage of smaller diameter trees becomes greater, and particularly if it exceeds 50%, then the canopy image obtained from Landsat TM data becomes sufficiently homogeneous so that the spatial indices reach their lower limits and thus are no longer determinative. It also appears, at least for the Oakmulgee forest, that the relationships between the spatial indices and forest class percentages within the boundaries can reasonably be considered linear. The linear relationship is much more pronounced in the sawtimber and saplings cases than in samples dominated by medium sized trees (poletimber). In addition, it also appears that, at least for the Oakmulgee forest, the relationships between the spatial indices and forest species groups (Hardwood and Softwood) percentages can reasonably be considered linear. The linear relationship is more pronounced in the forest species groups cases than in the forest classes cases. These results appear to indicate that both fractal dimensions and spatial autocorrelation indices hold promise as means of estimating forest stand characteristics from remotely sensed images. However, additional work is needed to confirm that the boundaries identified for Oakmulgee forest and the linear nature of the relationship between image complexity indices and forest characteristics are generally evident in other forests. In addition, the effects of other parameters such ,as topographic relief and image distortion due to sun angle and cloud cover, for example, need to be examined.
Al-Hamdan, Mohammad Z.↗
Glucose metabolism in different regions of the rat brain under hypokinetic stress influence
Glucose metabolism in rats kept under long term hypokinetic stress was studied in 7 brain regions. Determination was made of the regional levels of glucose, lactate, glutamate, glutamine, aspartate, gamma-aminobutyrate and the incorporation of C-14 from plasma glucose into these metabolites, in glycogen and protein. From the content and activity data the regional glucose flux was approximated quantitatively. Under normal conditions the activity gradient cortex and frontal pole cerebellum, thalamus and mesencephalon, hypothalamus and pons and medulla is identical with that of the regional blood supply (measured with I131 serum albumin as the blood marker). Within the first days of immobilization a functional hypoxia occurred in all brain regions and the utilization of cycle amino acids for protein synthesis was strongly diminished. After the first week of stress the capillary volumes of all regions increased, aerobic glucose metabolism was enhanced (factors 1.3 - 2.0) and the incorporation of glucose C-14 via cycle amino acids into protein was considerably potentiated. The metabolic parameters normalized between the 7th and 11th week of stress. Blood supply and metabolic rate increased most in the hypothalamus.
Konitzer, K.↗
MEASURE: An integrated data-analysis and model identification facility
The first phase of the development of MEASURE, an integrated data analysis and model identification facility is described. The facility takes system activity data as input and produces as output representative behavioral models of the system in near real time. In addition a wide range of statistical characteristics of the measured system are also available. The usage of the system is illustrated on data collected via software instrumentation of a network of SUN workstations at the University of Illinois. Initially, statistical clustering is used to identify high density regions of resource-usage in a given environment. The identified regions form the states for building a state-transition model to evaluate system and program performance in real time. The model is then solved to obtain useful parameters such as the response-time distribution and the mean waiting time in each state. A graphical interface which displays the identified models and their characteristics (with real time updates) was also developed. The results provide an understanding of the resource-usage in the system under various workload conditions. This work is targeted for a testbed of UNIX workstations with the initial phase ported to SUN workstations on the NASA, Ames Research Center Advanced Automation Testbed.
Singh, Jaidip↗
Description of data base management activities
ARC's current and future data processing needs have been identified and defined. Requirements for improved data processing capabilities are listed: (1) Centralized control of system data files. Establish a DBA/data base administrator position with responsibility for management of the Centers numerous data bases; (2) Programmer tools to improve efficiency of performance; (3) Direct and timely access to information. Presently, the user submits query requests to the data processing department where they are prioritized with other queries and then batch processed using a report generator; (4) On line data entry. With the merger of the Dryden facility with ARC on line data entry, edit and updates have become mandatory for timely operation and reporting. A DBMS software package was purchased to meet the above requirements.
Source record↗
High altitude aircraft remote sensing during the 1988 Yellowstone National Park wildfires
An overview is presented of the effects of the wildfires that occurred in the Yellowstone National Park during 1988 and the techniques employed to combat these fires with the use of remote sensing. The fire management team utilized King-Air and Merlin aircraft flying night missions with a thermal IR line-scanning system. NASA-Ames Research Center assisted with an ER-2 high altitude aircraft with the ability to down-link active data from the aircraft via a teledetection system. The ER-2 was equipped with a multispectral Thematic Mapper Simulator scanner and the resultant map data and video imagery was provided to the fire command personnel for field evaluation and fire suppression activities. This type of information proved very valuable to the fire control management personnel and to the continuing ecological research goals of NASA-Ames scientists analyzing the effects of burn type and severity on ecosystem recovery and development.
Ambrosia, Vincent G.↗