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At least 379 records · Page 21

Model-based VQ for image data archival, retrieval and distribution

An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

Manohar, Mareboyana↗

Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework

Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program’s (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States’ largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework’s current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.

54 ENVIRONMENTAL SCIENCES↗

Envision: An interactive system for the management and visualization of large geophysical data sets

Envision is a software project at the University of Illinois and Texas A&M, funded by NASA's Applied Information Systems Research Project. It provides researchers in the geophysical sciences convenient ways to manage, browse, and visualize large observed or model data sets. Envision integrates data management, analysis, and visualization of geophysical data in an interactive environment. It employs commonly used standards in data formats, operating systems, networking, and graphics. It also attempts, wherever possible, to integrate with existing scientific visualization and analysis software. Envision has an easy-to-use graphical interface, distributed process components, and an extensible design. It is a public domain package, freely available to the scientific community.

Searight, K. R.↗

Comprehensive Assessment of Models and Events Using Library Tools (CAMEL) Framework: Time Series Comparisons

The Comprehensive Assessment of Models and Events using Library Tools (CAMEL) framework leverages existing Community Coordinated Modeling Center services: Run on Request post processing tools that generate model time series outputs and the new Community Coordinated Modeling Center Metadata Registry that describes simulation runs using Space Physics Archive Search and Extract metadata. The new CAMEL visualization tool compares the modeled time series with observational data and computes a suite of skill scores such as Prediction Efficiency, Root Mean Square Error, and Symmetric Signed Percentage Bias. Model data pairs used for skill calculations are obtained considering a user selected maximum difference between the time of observation and the nearest model output. The system renders available data for all locations and time periods selected using interactive visualizations that allow the user to zoom, pan, and pick data values along traces. Skill scores are reported for each selected event or aggregated over all events for all participating model runs. Separately, scores are reported for all locations (satellites or stations) and for each location individually. We are building on past experiences with model data comparisons of magnetosphere and ionosphere model outputs from GEM2008, GEMCEDAR Electrodynamics Thermosphere Ionosphere, and the SWPC Operational Space Weather Model challenges. The CAMEL visualization tool is demonstrated using three validation studies: (a) Wang Sheeley Arge heliosphere simulations compared against OMNI solar wind data, (b) ground magnetic perturbations from several magnetosphere and ionosphere electrodynamics models as observed by magnetometers, and (c) electron fluxes from several ring current simulations compared to Radiation Belt Storm Probes Helium Oxygen Proton Electron instrument measurements, integrated over different energy ranges.

Rastätter, Lutz↗

Flow visualization studies of a general research fighter model employing a strake-wing concept at subsonic speeds

A systematic wind tunnel study was conducted in the Langley high-speed 7 by 10 foot tunnel to document, by oil-flow photographs, the surface flow patterns for configurations incorporating strake-wing geometries indicative of current and proposed maneuvering aircraft. The configurations employed combinations of strakes with reflexed planforms having exposed spans of 10 percent, 20 percent, and 30 percent of the reference wing span and wings with trapezoidal planforms having leading-edge sweep angles of approximately 30 deg, 44 deg, and 60 deg. Tests were conducted at Mach numbers of 0.3 and 0.5 and at angles of attack ranging from approximately 5 deg to 30 deg in 5 deg increments at 0 deg sideslip. The configurations incorporating the strake-wing geometries exhibited more organized flow patterns with smaller asymmetries to higher angles of attack than the corresponding configurations incorporating the wing-alone geometries did.

Luckring, J. M.↗

Qualitative Flow Visualization of a 110-N Hydrogen/Oxygen Laboratory Model Thruster

The flow field inside a 110 N gaseous hydrogen/oxygen thruster was investigated using an optically accessible, two-dimensional laboratory test model installed in a high altitude chamber. The injector for this study produced an oxidizer-rich core flow, which was designed to fully mix and react inside a fuel-film sleeve insert before emerging into the main chamber section, where a substantial fuel film cooling layer was added to protect the chamber wall. Techniques used to investigate the flow consisted of spontaneous Raman spectra measurements, visible emission imaging, ultraviolet hydroxyl spectroscopy, and high speed schlieren imaging. Experimental results indicate that the oxygen rich core flow continued to react while emerging from the fuel-film sleeve, suggesting incomplete mixing of the hydrogen in the oxygen rich core flow. Experiments also showed that the fuel film cooling protective layer retained its integrity throughout the straight section of the combustion chamber. In the converging portion of the chamber, however, a turbulent reaction zone near the wall destroyed the integrity of the film layer, a result which implies that a lower contraction angle may improve the fuel film cooling in the converging section and extend the hardware lifetime.

deGroot, Wim A.↗

Accessing, Utilizing and Visualizing NASA Remote Sensing Data for Malaria Modeling and Surveillance

This poster presentation reviews the use of NASA remote sensing data that can be used to extract environmental information for modeling malaria transmission. The authors discuss the remote sensing data from Landsat, Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), Tropical Rainfall Measuring Mission (TRMM), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Earth Observing One (EO-1), Advanced Land Imager (ALI) and Seasonal to Interannual Earth Science Information Partner (SIESIP) dataset.

Kiang, Richard K.↗

Surface flow visualization of separated flows on the forebody of an F-18 aircraft and wind-tunnel model

A method of in-flight surface flow visualization similar to wind-tunnel-model oil flows is described for cases where photo-chase planes or onboard photography are not practical. This method, used on an F-18 aircraft in flight at high angles of attack, clearly showed surface flow streamlines in the fuselage forebody. Vortex separation and reattachment lines were identified with this method and documented using postflight photography. Surface flow angles measured at the 90 and 270 degrees meridians show excellent agreement with the wind tunnel data for a pointed tangent ogive with an aspect ratio of 3.5. The separation and reattachment line locations were qualitatively similar to the F-18 wind-tunnel-model oil flows but neither the laminar separation bubble nor the boundary-layer transition on the wind tunnel model were evident in the flight surface flows. The separation and reattachment line locations were in fair agreement with the wind tunnel data for the 3.5 ogive. The elliptical forebody shape of the F-18 caused the primary separation lines to move toward the leeward meridian. Little effect of angle of attack on the separation locations was noted for the range reported.

Fisher, David F.↗

Predicting rare events using neural networks and short-trajectory data

Estimating the likelihood, timing, and nature of events is a major goal of modeling stochastic dynamical systems. When the event is rare in comparison with the timescales of simulation and/or measurement needed to resolve the elemental dynamics, accurate prediction from direct observations becomes challenging. In such cases a more effective approach is to cast statistics of interest as solutions to Feynman-Kac equations (partial differential equations). Here, we develop an approach to solve Feynman-Kac equations by training neural networks on short-trajectory data. Our approach is based on a Markov approximation but otherwise avoids assumptions about the underlying model and dynamics. This makes it applicable to treating complex computational models and observational data. Additionally, we illustrate the advantages of our method using a low-dimensional model that facilitates visualization, and this analysis motivates an adaptive sampling strategy that allows on-the-fly identification of and addition of data to regions important for predicting the statistics of interest. Finally, we demonstrate that we can compute accurate statistics for a 75-dimensional model of sudden stratospheric warming. This system provides a stringent test bed for our method.

97 MATHEMATICS AND COMPUTING↗

Learning LM Specificity for Ganglion Cells

Unsupervised learning models have been proposed based on experience (Ahumada and Mulligan, 1990;Wachtler, Doi, Lee and Sejnowski, 2007) that allow the cortex to develop units with LM specific color opponent receptive fields like the blob cells reported by Hubel and Wiesel on the basis of visual experience. These models used ganglion cells with LM indiscriminate wiring as inputs to the learning mechanism, which was presumed to occur at the cortical level.

retinal ganglion cells↗

A Spatial Analysis and Modeling System (SAMS) for environment management

This is a proposal to develop a uniform global environmental data gathering and distribution system to support the calibration and validation of remotely sensed data. SAMS is based on an enhanced version of FEMA's Integrated Emergency Management Information Systems and the Department of Defense's Air land Battlefield Environment Software Systems. This system consists of state-of-the-art graphics and visualization techniques, simulation models, database management and expert systems for conducting environmental and disaster preparedness studies. This software package will be integrated into various Landsat and UNEP-GRID stations which are planned to become direct readout stations during the EOS (Earth Observing System) timeframe. This system would be implemented as a pilot program to support the Tropical Rainfall Measuring Mission (TRMM). This will be a joint NASA-FEMA-University-Industry project.

Stetina, Fran↗

Uncertainty quantification of fireball features extracted from nuclear test films using computer vision

Films from the US’s historic nuclear testing era comprise the only extensive collection of imagery depicting high-yield detonations. These films offer unique insights into the characteristics of flows occurring on scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models used to describe nuclear detonations. In recent work, we implemented modern computer vision and machine learning techniques to extract features of the fireball following nuclear detonation. With a training dataset of fireball films, we fine-tuned a You Only Look Once 11 (YOLO11) model to detect and track the fireball. Applied to a video, the outer bounding box produced in each frame by YOLO11 is used as an input prompt to Meta’s Segment Anything Model 2 (SAM2), which is shown to accurately predict the boundary of the fireball over time with high resolution. These state-of-the-art computer vision foundation models exhibit impressive visual accuracy in their results but lack an output of values that robustly quantify uncertainty in scientific applications. In this paper, we develop procedures for uncertainty quantification of extracted fireball features. We outline the application of a parallel attention mechanism to calculate uncertainty ranges that complement and better pose model validation data. This higher quality fireball validation data may serve to improve prognostic models describing nuclear detonations in support of nuclear forensic and emergency response activities.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗

A Spatial Analysis and Modeling System (SAMS) for environment management

This is a proposal to develop a uniform global environmental data gathering and distribution system to support the calibration and validation of remotely sensed data. SAMS is based on an enhanced version of FE MA's Integrated Emergency Management Information Systems and the Department of Defense's Air Land Battlefield Environment Software Systems. This system consists of state-of-the-art graphics and visualization techniques, simulation models, database management and expert systems for conducting environmental and disaster preparedness studies. This software package will be integrated into various Landsat and UNEP-GRID stations which are planned to become direct readout stations during the EOS timeframe. This system would be implemented as a pilot program to support the Tropical Rainfall Measuring Mission (TRMM). This will be a joint NASA-FEMA-University-Industry project.

Vermillion, Charles H.↗

Antarctic Water Masses and Ice Shelves: Visualizing the Physics

High-resolution simulation of global climate physics enables us to model how the climate may change under a variety of future scenarios. Such simulations produce vast amounts of information and dense datasets. If interrogated in tandem, these datasets can provide holistic, vital information on Earth’s many integrated systems by revealing the manifold interrelated properties of the atmosphere, ocean, and polar ice, framed by real-world terrain in three-dimensional space as they vary over time. To accomplish this, climate scientists have joined with computer scientists and an artist to develop techniques enabling scientists to see these relationships. Finally, the impact of ocean water properties on Antarctic ice shelves illustrates the benefit of this analysis in understanding land ice melt rates and thus sea-level rise.

54 ENVIRONMENTAL SCIENCES↗

Fluorescence Visualization of Hypersonic Flow over Rapid Prototype Wind-Tunnel Models

Reentry models for use in hypersonic wind tunnel tests were fabricated using a stereolithography apparatus. These models were produced in one day or less, which is a significant time savings compared to the manufacture of ceramic or metal models. The models were tested in the NASA Langley Research Center 31-Inch Mach 10 Air Tunnel. Most of the models did not survive repeated tests in the tunnel, and several failure modes of the models were identified. Planar laser-induced fluorescence (PLIF) of nitric oxide (NO) was used to visualize the flowfields in the wakes of these models. Pure NO was either seeded through tubes plumbed into the model or via a tube attached to the strut holding the model, which provided localized addition of NO into the model s wake through a porous metal cylinder attached to the end of the tube. Models included several 2-inch diameter Inflatable Reentry Vehicle Experiment (IRVE) models and 5-inch diameter Crew Exploration Vehicle (CEV) models. Various configurations were studied including different sting placements relative to the models, different model orientations and attachment angles, and different NO seeding methods. The angle of attack of the models was also varied and the location of the laser sheet was scanned to provide three-dimensional flowfield information. Virtual Diagnostics Interface technology, developed at NASA Langley, was used to visualize the data sets in post processing. The use of calibration "dotcards" was investigated to correct for camera perspective and lens distortions in the PLIF images. Lessons learned and recommendations for future experiments are discussed.

Alderfer, D. W.↗