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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Recent advancements in information extraction methodology and hardware for earth resources survey systems

The present work discusses some recent developments in preprocessing and extractive processing techniques and hardware and in user applications model development for earth resources survey systems. The Multivariate Interactive Digital Analysis System (MIDAS) is currently being developed, and is an attempt to solve the problem of real time multispectral data processing in an operational system. The main features and design philosophy of this system are described. Examples of wetlands mapping and land resource inventory are presented. A user model developed for predicting the yearly production of mallard ducks from remote sensing and ancillary data is described.

Erickson, J. D.↗
NASA NTRS1975

Image enhancement and advanced information extraction techniques for ERTS-1 data

The author has identified the following significant results. It was demonstrated and concluded that: (1) the atmosphere has significant effects on ERTS MSS data which can seriously degrade recognition performance; (2) the application of selected signature extension techniques serve to reduce the deleterious effects of both the atmosphere and changing ground conditions on recognition performance; and (3) a proportion estimation algorithm for overcoming problems in acreage estimation accuracy resulting from the coarse spatial resolution of the ERTS MSS, was able to significantly improve acreage estimation accuracy over that achievable by conventional techniques, especially for high contrast targets such as lakes and ponds.

Malila, W. A.↗
NASA NTRS1982

Analysis of geologic terrain models for determination of optimum SAR sensor configuration and optimum information extraction for exploration of global non-renewable resources. Pilot study: Arkansas Remote Sensing Laboratory, part 1, part 2, and part 3

Computer-generated radar simulations and mathematical geologic terrain models were used to establish the optimum radar sensor operating parameters for geologic research. An initial set of mathematical geologic terrain models was created for three basic landforms and families of simulated radar images were prepared from these models for numerous interacting sensor, platform, and terrain variables. The tradeoffs between the various sensor parameters and the quantity and quality of the extractable geologic data were investigated as well as the development of automated techniques of digital SAR image analysis. Initial work on a texture analysis of SEASAT SAR imagery is reported. Computer-generated radar simulations are shown for combinations of two geologic models and three SAR angles of incidence.

Kaupp, V. H.↗
NASA NTRS1983

Information extraction from thematic mapper data

The improvements introduced in spectral, spatial, and ratiometric capabilities through installation of the thematic mapper (TM) on the Landsat-4 spacecraft are described. The TM optical sensors scan in the visible (0.45-0.52, 0.52-0.60, and 0.63-0.69 micron), near-IR (0.76-0.90 micron), middle-IR (1.55-1.75 micron), and thermal IR (10.4-12.5 microns). The reflectances of vegetation and the differences in chlorophyll absorption by various plants are discerned more accurately than with the MSS, while the effects of land surface obscuration by water vapor are reduced. The blue-green band upgrades water measurements for bathymetry, reef, and atoll mapping, and the middle-IR increases sensitivity to leaf water content. The field-of-view is a 30 x 30 m square, one-fifth that of the MSS. Results from sample surveys of forested wetlands in Tennessee and agricultural land use patterns are presented.

Tilton, E. L., III↗
NASA NTRS1985

Performance comparisons between information extraction techniques using variable spatial resolution data

The decreased instantaneous field of view (IFOV) is one of the principal advances noted for the Thematic Mapper (TM) sensor. The 42.5 microradian IFOV of TM and the 710 km nominal orbit altitude result in a 30 m nominal spatial resolution at the earth surface. This is a considerable decrease in the projected pixel area when compared to the 79 m nominal spatial resolution of the Landsat Multispectral Scanner (MSS). An experiment was conducted which allowed a rigorous test of the influence of classifier design, with data spatial resolution of TM (30 m) and approximately that of the Landsat MSS (90 m), on classification performance for a particular TM scene. The experiment involved evaluation of the results for the per-point Gaussian maximum likelihood (GML) classifier and the supervised ECHO (Extraction and Classification of Homogeneous Objects) classifier.

Latty, R. S.↗
NASA NTRS1986

Information extraction from multivariate images

An overview of several multivariate image processing techniques is presented, with emphasis on techniques based upon the principal component transformation (PCT). Multiimages in various formats have a multivariate pixel value, associated with each pixel location, which has been scaled and quantized into a gray level vector, and the bivariate of the extent to which two images are correlated. The PCT of a multiimage decorrelates the multiimage to reduce its dimensionality and reveal its intercomponent dependencies if some off-diagonal elements are not small, and for the purposes of display the principal component images must be postprocessed into multiimage format. The principal component analysis of a multiimage is a statistical analysis based upon the PCT whose primary application is to determine the intrinsic component dimensionality of the multiimage. Computational considerations are also discussed.

Park, S. K.↗
NASA NTRS1986

Intelligent information extraction from reflectance spectra Absorption band positions

A multiple high-order derivative analysis algorithm has been developed which can automatically extract absorption band positions from low-quality reflectance spectra with little degredation of accuracy. Overlapping bands with comparable widths and intensities can be resolved whose centers are as close as 0.3-0.5 W, with safer resolution limits of 0.6-1.0 W band center separations suggested for overlapping bands that are dissimilar. The segment length for smoothing is continually adjusted to about 0.5 W to minimize signal distortion, and a spectral pattern recognition algorithm predicts the signal spectrum and calculates approximate W across the spectrum using its second derivative. A single-pass cubic spline is applied to the smoothed data, and a sliding segment sixth-order polynomial is fit to the spectrum, with the length of the segment being continuously locally adjusted to 1.0 W across the spectrum. Good reliability and consistency of the algorithm is demonstrated with application to laboratory and earth-based telescope spectra.

Huguenin, R. L.↗
NASA NTRS1994

Spacecraft On-Board Information Extraction Computer (SOBIEC)

The Jet Propulsion Laboratory is the Technical Monitor on an SBIR Program issued for Irvine Sensors Corporation to develop a highly compact, dual use massively parallel processing node known as SOBIEC. SOBIEC couples 3D memory stacking technology provided by nCUBE. The node contains sufficient network Input/Output to implement up to an order-13 binary hypercube. The benefit of this network, is that it scales linearly as more processors are added, and it is a superset of other commonly used interconnect topologies such as: meshes, rings, toroids, and trees. In this manner, a distributed processing network can be easily devised and supported. The SOBIEC node has sufficient memory for most multi-computer applications, and also supports external memory expansion and DMA interfaces. The SOBIEC node is supported by a mature set of software development tools from nCUBE. The nCUBE operating system (OS) provides configuration and operational support for up to 8000 SOBIEC processors in an order-13 binary hypercube or any subset or partition(s) thereof. The OS is UNIX (USL SVR4) compatible, with C, C++, and FORTRAN compilers readily available. A stand-alone development system is also available to support SOBIEC test and integration.

Eisenman, David↗
NASA NTRS1995

Software Helps Extract Information From Astronomical Images

PAC Skyview 2.0 is interactive program for display and analysis of astronomical images. Includes large set of functions for display, analysis and manipulation of images. "Man" pages with descriptions of functions and examples of usage included. Skyview used interactively or in "server" mode, in which another program calls Skyview and executes commands itself. Skyview capable of reading image data files of four types, including those in FITS, S, IRAF, and Z formats. Written in C.

Hartley, Booth↗
NASA NTRSDate not supplied

Towards a program of record of inland water quality: Exploiting present and heritage multispectral sensors for maximum information extraction

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This research exploits recent advancements in bio-optical modeling, cloud computing, and machine learning to enhance our capacity to leverage present and heritage satellite data. Recent research suggests that sensors with low spectral resolution, such as Sentinel 2 and Landsat missions, contain enough hidden spectral variation which can be exploited using data-driven approaches. The availability of three decades of archival imagery will open doors to discover global trends of eutrophication and increased cyanobacteria dominance and provide valuable insight to the development of predictive methodologies. Preliminary efforts in synthetic emulation of global natural inland waters will be discussed and contextualized against satellite radiometric measurement uncertainty, satellite data product uncertainties and causal signal ambiguity over the visible wavelength range, supported by high quality field and image data for selected inland aquatic sites. Insights on water quality estimation via data-driven machine learning models versus matrix inversions will be discussed, and how we can exploit spectral-spatial relationships in high spatial resolution data. A cross-sensor synergistic approach with detailed uncertainty analysis based on optical water types, will allow for unprecedented global snapshots of fine scale ecological dynamics of inland waters.

Inland↗
DOE OSTI2024

Path-BigBird: An AI-Driven Transformer Approach to Classification of Cancer Pathology Reports

PURPOSE Surgical pathology reports are critical for cancer diagnosis and management. To accurately extract information about tumor characteristics from pathology reports in near real time, we explore the impact of using domain-specific transformer models that understand cancer pathology reports. METHODS We built a pathology transformer model, Path-BigBird, by using 2.7 million pathology reports from six SEER cancer registries. We then compare different variations of Path-BigBird with two less computationally intensive methods: Hierarchical Self-Attention Network (HiSAN) classification model and an offthe-shelf clinical transformer model (Clinical BigBird). We use five pathology information extraction tasks for evaluation: site, subsite, laterality, histology, and behavior. Model performance is evaluated by using macro and micro F 1 scores. RESULTS We found that Path-BigBird and Clinical BigBird outperformed the HiSAN in all tasks. Clinical BigBird performed better on the site and laterality tasks. Versions of the Path-BigBird model performed best on the two most difficult tasks: subsite (micro F 1 score of 72.53, macro F 1 score of 35.76) and histology (micro F 1 score of 80.96, macro F 1 score of 37.94). The largest performance gains over the HiSAN model were for histology, for which a Path-BigBird model increased the micro F 1 score by 1.44 points and the macro F 1 score by 3.55 points. Overall, the results suggest that a Path-BigBird model with a vocabulary derived from wellcurated and deidentified data is the best-performing model. CONCLUSION The Path-BigBird pathology transformer model improves automated information extraction from pathology reports. Although Path-BigBird outperforms Clinical BigBird and HiSAN, these less computationally expensive models still have utility when resources are constrained.

60 APPLIED LIFE SCIENCES↗