Search NASA⌕ Search

SEARCH · Search NASA

Results for “Information extraction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Multi-aspect techniques in remote sensing

Multi-aspect techniques, which use multispectral scanner information collected from two or more different view angles for each spatial element, are discussed. Empirical recognition results obtained with various combinations of information channels are presented. Theoretical calculations of multi-aspect reflectances of corn fields also are analyzed and compared with empirical data. Also presented is a brief comparison between recognition processing and scene attribute estimation techniques for extracting information from multispectral scanner data. One method for improving information extraction by employing a post-recognition attribute estimation procedure is suggested.

Malila, W. A.↗
NASA NTRS1992

The Quickest, Lowest-cost Lunar Resource Assessment Program: Integrated High-tech Earth-based Astronomy

Science and technology applications for the Moon have not fully kept pace with technical advancements in sensor development and analytical information extraction capabilities. Appropriate unanswered questions for the Moon abound, but until recently there has been little motivation to link sophisticated technical capabilities with specific measurement and analysis projects. Over the last decade enormous technical progress has been made in the development of (1) CCD photometric array detectors; (2) visible to near-infrared imaging spectrometers; (3)infrared spectroscopy; (4) high-resolution dual-polarization radar imaging at 3.5, 12, and 70 cm; and equally important (5) data analysis and information extraction techniques using compact powerful computers. Parts of each of these have been tested separately, but there has been no programmatic effort to develop and optimize instruments to meet lunar science and resource assessment needs (e.g., specific wavelength range, resolution, etc.) nor to coordinate activities so that the symbiotic relation between different kinds of data can be fully realized. No single type of remotely acquired data completely characterizes the lunar environment, but there has been little opportunity for integration of diverse advanced sensor data for the Moon. Two examples of technology concepts for lunar measurements are given. Using VIS/near-IR spectroscopy, the mineral composition of surface material can be derived from visible and near-infrared radiation reflected from the surface. The surface and subsurface scattering properties of the Moon can be analyzed using radar backscattering imaging.

Pieters, Carle M.↗
NASA NTRS1975

On-board data management study for EOPAP

The requirements, implementation techniques, and mission analysis associated with on-board data management for EOPAP were studied. SEASAT-A was used as a baseline, and the storage requirements, data rates, and information extraction requirements were investigated for each of the following proposed SEASAT sensors: a short pulse 13.9 GHz radar, a long pulse 13.9 GHz radar, a synthetic aperture radar, a multispectral passive microwave radiometer facility, and an infrared/visible very high resolution radiometer (VHRR). Rate distortion theory was applied to determine theoretical minimum data rates and compared with the rates required by practical techniques. It was concluded that practical techniques can be used which approach the theoretically optimum based upon an empirically determined source random process model. The results of the preceding investigations were used to recommend an on-board data management system for (1) data compression through information extraction, optimal noiseless coding, source coding with distortion, data buffering, and data selection under command or as a function of data activity, (2) for command handling, (3) for spacecraft operation and control, and (4) for experiment operation and monitoring.

Davisson, L. D.↗
NASA NTRS1977

Multispectral system analysis through modeling and simulation

The design and development of multispectral remote sensor systems and associated information extraction techniques should be optimized under the physical and economic constraints encountered and yet be effective over a wide range of scene and environmental conditions. Direct measurement of the full range of conditions to be encountered can be difficult, time consuming, and costly. Simulation of multispectral data by modeling scene, atmosphere, sensor, and data classifier characteristics is set forth as a viable alternative, particularly when coupled with limited sets of empirical measurements. A multispectral system modeling capability is described. Use of the model is illustrated for several applications - interpretation of remotely sensed data from agricultural and forest scenes, evaluating atmospheric effects in LANDSAT data, examining system design and operational configuration, and development of information extraction techniques.

Malila, W. A.↗
NASA NTRS1977

Multispectral system analysis through modeling and simulation

The design and development of multispectral remote sensor systems and associated information extraction techniques should be optimized under the physical and economic constraints encountered and yet be effective over a wide range of scene and environmental conditions. Direct measurement of the full range of conditions to be encountered can be difficult, time consuming, and costly. Simulation of multispectral data by modeling scene, atmosphere, sensor, and data classifier characteristics is set forth as a viable alternative, particularly when coupled with limited sets of empirical measurements. A multispectral system modeling capability is described. Use of the model is illustrated for several applications - interpretation of remotely sensed data from agricultural and forest scenes, evaluating atmospheric effects in Landsat data, examining system design and operational configuration, and development of information extraction techniques.

Malila, W. A.↗
DOE OSTI2025

Baryon number violation: from nuclear matrix elements to BSM physics

Processes that violate baryon number, most notably proton decay and $n\bar{n}$ transitions, are promising probes of physics beyond the Standard Model (BSM) needed to understand the lack of antimatter in the Universe. To interpret current and forthcoming experimental limits, theory input from nuclear matrix elements to UV complete models enters. Thus, an interplay of experiment, effective field theory, lattice QCD, and BSM model building is required to develop strategies to accurately extract information from current and future data and maximize the impact and sensitivity of next-generation experiments. Here, we briefly summarize the main results and discussions from the workshop ‘INT-25-91W: Baryon Number Violation: From Nuclear Matrix Elements to BSM Physics,’ held at the Institute for Nuclear Theory, University of Washington, Seattle, WA, 13–17 January 2025.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

First-Principles Approach to Extracting Chemical Information from X-ray Absorption Near-Edge Spectra of Ga-Containing Materials

The X-ray absorption near-edge structure (XANES) can provide uniquely detailed information on the coordination environments of important Ga-containing materials with unknown structures, including catalytically active materials. In this work, the Ga K-edge XANES was simulated using first-principles-based methods for seven molecular Ga complexes as well β-Ga 2 O 3 , in order to explore the chemical origins of the experimentally observed features. The theoretical spectra were computed using FEFF, CASTEP, and StoBe, to assess the sensitivity of the results to the computational approach. While the XANES features depend on the Ga coordination environment, they are also sensitive to the electronegativity of the ligands and the symmetry at Ga. The white line position responds to changes in both the core state (due to differential screening) and the valence “p” states (arising from differences in ligand coordination).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1975

Advances in automatic extraction of information from multispectral scanner data

The state-of-the-art of automatic multispectral scanner data analysis and interpretation is reviewed. Sources of system variability which tend to obscure the spectral characteristics of the classes under consideration are discussed, and examples of the application of spatial and temporal discrimination bases are given. Automatic processing functions, techniques and methods, and equipment are described with particular attention to those that are applicable to large land surveys using satellite data. The development and characteristics of the Multivariate Interactive Digital Analysis System (MIDAS) for processing aircraft or satellite multispectral scanning data are discussed in detail. The MIDAS system combines the parallel digital implementation capabilities of a low-cost processor with a general purpose PDP-11/45 minicomputer to provide near-real-time data processing. The preprocessing functions are user-selectable. The input subsystem accepts data stored on high density digital tape, computer compatible tape, and analog tape.

Erickson, J. D.↗
NASA NTRS1981

Extracting spatial information from large aperture exposures of diffuse sources

The spatial properties of large aperture exposures of diffuse emission can be used both to investigate spatial variations in the emission and to filter out camera noise in exposures of weak emission sources. Spatial imaging can be accomplished both parallel and perpendicular to dispersion with a resolution of 5-6 arc sec, and a narrow median filter running perpendicular to dispersion across a diffuse image selectively filters out point source features, such as reseaux marks and fast particle hits. Spatial information derived from observations of solar system objects is presented.

Clarke, J. T.↗
NASA NTRS1985

Extraction of information from major element chemical analyses of lunar basalts

Major element chemical analyses often form the framework within which similarities and differences of analyzed specimens are noted and used to propose or devise models. When percentages are formed the ratios of pairs of components are preserved whereas many familiar statistical and geometrical descriptors are likely to exhibit major changes. This ratio preserving aspect forms the basis for a proposed framework. An analysis of compositional variability within the data set of 42 major element analyses of lunar reference samples was selected to investigate this proposal.

Butler, J. C.↗
NASA NTRS1988

Pulse shaping and extraction of information from ultrasonic reflections in composite materials

The application of ultrasonic inspection to the nondestructive testing of composite materials is examined with reference to specific examples including monitoring of epoxy curing, evaluation of impact damage in a graphite/epoxy laminate, and monitoring of a repaired area in a composite wing plate. Signal processing methods are described which improve time resolution, facilitating identification of discrete echoes corresponding to events in the material.

Kishoni, Doron↗
NASA NTRS1992

A system for verifying models and classification maps by extraction of information from a variety of data sources

Recent updates to a geographical information system (GIS) called VICAR (Video Image Communication and Retrieval)/IBIS are described. The system is designed to handle data from many different formats (vector, raster, tabular) and many different sources (models, radar images, ground truth surveys, optical images). All the data are referenced to a single georeference plane, and average or typical values for parameters defined within a polygonal region are stored in a tabular file, called an info file. The info file format allows tracking of data in time, maintenance of links between component data sets and the georeference image, conversion of pixel values to `actual' values (e.g., radar cross-section, luminance, temperature), graph plotting, data manipulation, generation of training vectors for classification algorithms, and comparison between actual measurements and model predictions (with ground truth data as input).

Norikane, L.↗
DOE OSTI2021

Extract useful information from building permits data to profile a city’s building retrofit history

Building retrofit is one of the key strategies for cities to reduce energy use and GHG emissions. The historical information about changes to buildings is crucial to infer the buildings’ current energy system efficiency levels and to identify candidate buildings for retrofit. In general, a building permit is required before the start of any construction activity of a building, such as changing building structure, remodeling, or installing new equipment. Moreover, many large cities provide public datasets of building permits in history. Therefore, the permits are a potentially good resource for mining information on the city’s retrofit history. In this study, we use the permit dataset from the city of San Francisco as a case study. Location and time information from the dataset is also used to depict the retrofit timeline of each building and the whole building stock. The type of work of the permit is inferred from the descriptive text by a machine learning model. At last, the limitations of the current permit dataset and potential improvements on the permit data management are discussed to better utilize the information in the future.

Zhang, Wanni↗
NASA NTRS2022

Natural Language Understanding and Extraction of Flight Constraints Recorded in Letters of Agreement

This paper presents an automated information extraction and inference technique using natural language processing for extracting flight operational procedures and constraints embedded in heritage air traffic management documents. The extracted flight constraints can be digitized and fit into existing airspace information exchange models such as the Aeronautical Information Exchange Model (AIXM). This approach offers a digitized solution to disseminate airspace operating conditions to diverse air users and stakeholders in the National Airspace System (NAS). Furthermore, the digitized flight procedures can provide operational flexibility for emerging advanced air mobility providers and reduce traffic controller workload while maintaining current safety standards. To demonstrate this process, 1,972 Letters of Agreement (LOAs) have been selected for processing, named entity extraction, constraint identification and extraction. This dataset is derived from a subset of documents related to Air Route Traffic Control Centers (ARTCC) operations. We experimented with various traditional information extraction techniques, state-of-the-art machine learning and deep learning models to perform named entity recognition and pattern recognition on our dataset. We present the results from our experiments and demonstrate 99.0% F-1 score for named entity recognition, and a 96.6% accuracy for our entire workflow up to named entity recognition. We also discuss constraint definitions using generic patterned templates and extensions to this work in applying entity linking to digitally extracting relevant constraints.

Natural Language Processing↗
NASA NTRSDate not supplied

Natural Language Understanding and Extraction of Flight Constraints Recorded in Letters of Agreement

This paper presents an automated information extraction and inference technique using natural language processing for extracting flight operational procedures and constraints embedded in heritage air traffic management documents. The extracted flight constraints can be digitized and fit into existing airspace information exchange models such as the Aeronautical Information Exchange Model (AIXM). This approach offers a digitized solution to disseminate airspace operating conditions to diverse air users and stakeholders in the National Airspace System (NAS). Furthermore, the digitized flight procedures can provide operational flexibility for emerging advanced air mobility providers and reduce traffic controller workload while maintaining current safety standards. To demonstrate this process, 1,972 Letters of Agreement (LOAs) have been selected for processing, named entity extraction, constraint identification and extraction. This dataset is derived from a subset of documents related to Air Route Traffic Control Centers (ARTCC) operations. We experimented with various traditional information extraction techniques, state-of-the-art machine learning and deep learning models to perform named entity recognition and pattern recognition on our dataset. We present the results from our experiments and demonstrate 99.0% F-1 score for named entity recognition, and a 96.6% accuracy for our entire workflow up to named entity recognition. We also discuss constraint definitions using generic patterned templates and extensions to this work in applying entity linking to digitally extracting relevant constraints.

Natural Language Processing↗
DOE OSTI2025

MechBERT: Language Models for Extracting Chemical and Property Relationships about Mechanical Stress and Strain

Language models are transforming materials-aware naturallanguage processing by enabling the extraction of dynamic, context-rich information from unstructured text, thus, moving beyond the limitations of traditional information-extraction methods. Moreover, small language models are on the rise because some of them can perform better than large language models (LLMs) when given domain-specific questionanswer tasks, especially about an application area that relies on a highly specialized vernacular, such as materials science. We therefore present a new class of MechBERT language models for understanding mechanical stress and strain in materials. These employ Bidirectional Encoder Representations for transformer (BERT) architectures. We showcase four MechBERT models, all of which were pretrained on a corpus of documents that are textually rich in chemicals and their stress–strain properties and were fine-tuned on question-answering tasks. We evaluated the level of performance of our models on domain-specific as well as general English-language question-answer tasks and also explored the influence of the size and type of BERT architectures on model performance. We find that our MechBERT models outperform BERT-based models of the same size and maintain relevancy better than much larger BERT-based models when tasked with domain-specific question-answering tasks within the stress–strain engineering sector. These small language models also enable much faster processing and require a much smaller fraction of data to pretrain them, affording them greater operational efficiency and energy sustainability than LLMs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1977

LANDSAT image interpretation aids

In the Large Area Crop Inventory Experiment, image interpretation aids were produced to assist in selecting and/or identifying representative samples of signatures in a given LANDSAT scene. The three methods employed are based on clustering techniques, information extraction, and aggregation of like spectral information on a two dimensional spectral plot.

Abotteen, R. A.↗