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NASA NTRS1978

Multispectral data acquisition and classification - Statistical models for system design

In this paper we relate the statistical processes that are involved in multispectral data acquisition and classification to a simple radiometric model of the earth surface and atmosphere. If generalized, these formulations could provide an analytical link between the steadily improving models of our environment and the performance characteristics of rapidly advancing device technology. This link is needed to bring system analysis tools to the task of optimizing remote sensing and (real-time) signal processing systems as a function of target and atmospheric properties, remote sensor spectral bands and system topology (e.g., image-plane processing), radiometric sensitivity and calibration accuracy, compensation for imaging conditions (e.g., atmospheric effects), and classification rates and errors.

Huck, F. O.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-12973-DND

CFD methods are employing semi-empirical models used in analysis of hypersonic airbreathing engine flow paths. RANS (or Favre averaged) codes have models for turbulent stresses, mass and energy transport; turbulence chemistry interactions. LES methods have models for subgrid scale turbulence. Models depend upon experimental data for validation. Information on mean flow and statistics of the turbulent fluctuation in flow properties is useful. Data requirements: simple well defined supersonic combustion flows with well-known boundary conditions, time and spatially resolved, good instrument precision, and converged statistics. Approach: dual-pump CARS and planar laser-induced fluorescence imaging of OH radical (PLIF).

Andrew Cutler↗

DOE OSTI2022

Different CT slice thickness and contrast‐enhancement phase in radiomics models on the differential performance of lung adenocarcinoma

Abstract Background To investigate the effects of computed tomography (CT) reconstruction slice thickness and contrast‐enhancement phase on the differential diagnosis performance of radiomic signature in lung adenocarcinoma. Methods A total of 187 patients who had been pathologically confirmed with lung adenocarcinoma and nonadenocarcinoma were divided into a training cohort ( n = 149) and validation cohort ( n = 38). All the patients underwent contrast‐enhanced CT and the images were reconstructed with different slice thickness. The radiomic features were extracted from different slice thickness and scan phase. The logistic regression (LR) algorithm was used to build a machine learning model for each group. The area under the curve (AUC) obtained from the receiver operating characteristic (ROC) curve and DeLong test was used to evaluate its discriminating performance. Results Finally, 34 image features and five semantic features were selected to establish a radiomics model. Based on the three contrast‐enhanced CT phases and four reconstruction slice thickness, 12 groups of radiomics models showed good discrimination ability with the AUCs range from 0.9287 to 0.9631, sensitivity range from 0.8349 to 0.9083, specificity range from 0.825 to 0.925 in the training group. Similar results were observed in the validation group. However, there was no statistical significance between the different CT scan phase groups and different slice thickness ( p > 0.05). Conclusions The radiomic analysis of contrast‐enhanced CT can be used for the differential diagnosis of lung adenocarcinoma. Moreover, different slice thickness and contrast‐enhanced scan phase did not affect the discriminating ability in the radiomics models.

Wang, Yang↗

NASA NTRS2011

Global CALIPSO Observations of Aerosol Changes Near Clouds

Several recent studies have found that clouds are surrounded by a transition zone of rapidly changing aerosol optical properties and particle size. Characterizing this transition zone is important for better understanding aerosol-cloud interactions and aerosol radiative effects, and also for improving satellite retrievals of aerosol properties. This letter presents a statistical analysis of a monthlong global data set of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar observations over oceans. The results show that the transition zone is ubiquitous over all oceans and extends up to 15 km away from clouds. They also show that near-cloud enhancements in backscatter and particle size are strongest at low altitudes, slightly below the top of the nearest clouds. Also, the enhancements are similar near illuminated and shadowy cloud sides, which confirms that the asymmetry of Moderate Resolution Imaging Spectroradiometer reflectances found in an earlier study comes from 3-D radiative processes and not from differences in aerosol properties. Finally, the effects of CALIPSO aerosol detection and cloud identification uncertainties are discussed. The findings underline the importance of accounting for the transition zone to avoid potential biases in studies of satellite aerosol products, aerosol-cloud interactions, and aerosol direct radiative effects.

Varnai, Tamas↗

NASA NTRS2017

Advances in Medical Analytics Solutions for Autonomous Medical Operations on Long-Duration Missions

A review will be presented on the progress made under STMDGame Changing Development Program Funding towards the development of a Medical Decision Support System for augmenting crew capabilities during long-duration missions, such as Mars Transit. To create an MDSS, initial work requires acquiring images and developing models that analyze and assess the features in such medical biosensor images that support medical assessment of pathologies. For FY17, the project has focused on ultrasound images towards cardiac pathologies: namely, evaluation and assessment of pericardial effusion identification and discrimination from related pneumothorax and even bladder-induced infections that cause inflammation around the heart. This identification is substantially changed due to uncertainty due to conditions of fluid behavior under space-microgravity. This talk will present and discuss the work-to-date in this Project, recognizing conditions under which various machine learning technologies, deep-learning via convolutional neural nets, and statistical learning methods for feature identification and classification can be employed and conditioned to graphical format in preparation for attachment to an inference engine that eventually creates decision support recommendations to remote crew in a triage setting.

Medical Decision Support Systems↗

NASA NTRS1995

Measurement of high-degree solar oscillation frequencies

We present m-averaged solar p- and f-mode oscillation frequencies over the frequency range nu greater than 1.8 and less than 5.0 mHz and the spherical harmonic degree range l greater than or equal to 100 and less than or equal to 1200 from full-disk, 1000 x 1024 pixel, Ca II intensity images collected 1993 June 22-25 with a temporal cadence of 60 s. We itemize the sources and magnitudes of statistical and systematic uncertainties and of small frequency corrections, and we show that our frequencies represent an improvement in accuracy and coverage over previous measurements. Our frequencies agree at the 2 micro Hz level with Mount Wilson frequencies determined for l less than or equal to 600 from full-disk images, and we find systematic offsets of 10-20 micro Hz with respect to frequencies measured from Big Bear and La Palma observations. We give evidence that these latter offsets are indicative of spatial scaling uncertainties associated with the analysis of partial-disk images. In comparison with theory, our p-mode frequencies agree within 10 micro Hz of frequencies predicted by the Los Alamos model but are as much as 100 micro Hz smaller than frequencies predicted by the Denmark and Yale models at degrees near 1000. We also find systematic differences between our n = 0 frequencies and the frequencies closely agreed upon by all three models.

Bachmann, K. T.↗

NASA NTRS1985

The missing bulge globular clusters in M31 - New optical candidates

A new method to attack the question of the 'missing' globular clusters in the bulge of M31 is used. Image-processing techniques were used on 13 videocamera fields to obtain an accurate photometric census of stellar objects in M31's bulge down to a limiting B magnitude of 21. This luminosity distribution is compared with the Bahcall-Soneira model of galactic foreground stars. A statistically significant excess of bright images in the luminosity range of globular clusters at M31's distance is found. If the optical candidates considered prove to be globular clusters, they would double the number of known globular clusters in the surveyed region. The colors of a subsample of the candidates are the same as those of the known globular clusters. It is concluded that the previously observed flattening away from a de Vaucouleurs law in the radial distribution of M31 may be an observational selection effect. As an offshoot of this analysis, no evidence is found for very luminous stars in the inner bulge of M31. The lack of such stars indicates that there has not been active star formation (with a normal IMF) in the recent past. Coupled with the existence of many planetary nebulae in the bulge, this may strengthen the case for a galactic wind in M31's bulge.

Wirth, A.↗

NASA NTRS2000

Computational Analysis for Rocket-Based Combined-Cycle Systems During Rocket-Only Operation

A series of Reynolds-averaged Navier-Stokes calculations were employed to study the performance of rocket-based combined-cycle systems operating in an all-rocket mode. This parametric series of calculations were executed within a statistical framework, commonly known as design of experiments. The parametric design space included four geometric and two flowfield variables set at three levels each, for a total of 729 possible combinations. A D-optimal design strategy was selected. It required that only 36 separate computational fluid dynamics (CFD) solutions be performed to develop a full response surface model, which quantified the linear, bilinear, and curvilinear effects of the six experimental variables. The axisymmetric, Reynolds-averaged Navier-Stokes simulations were executed with the NPARC v3.0 code. The response used in the statistical analysis was created from Isp efficiency data integrated from the 36 CFD simulations. The influence of turbulence modeling was analyzed by using both one- and two-equation models. Careful attention was also given to quantify the influence of mesh dependence, iterative convergence, and artificial viscosity upon the resulting statistical model. Thirteen statistically significant effects were observed to have an influence on rocket-based combined-cycle nozzle performance. It was apparent that the free-expansion process, directly downstream of the rocket nozzle, can influence the Isp efficiency. Numerical schlieren images and particle traces have been used to further understand the physical phenomena behind several of the statistically significant results.

Steffen, C. J., Jr.↗

NASA NTRS2003

Search for 1-10 Hz Modulations in Coronal Emission with SECIS During the August 11, 1999 Eclipse

Results of the search of the periodic changes of the 530.3 nm line intensity emitted by selected structures of the solar corona in the frequency range 1-10 Hz are presented. A set of 12728 images of the section of the solar corona extending from near the north pole to the south-west were taken simultaneously in the 530.3 nm ('green') line and white-light with the Solar Eclipse Coronal Imaging System (SECIS) during the 143-seconds-long totality of the 1999 August 11 solar eclipse observed in Shabla, Bulgaria. The time resolution of the collected data is better than 0.05-s and the pixel size is approximately 4 arcsecs. Using classical Fourier spectral analysis tools, we investigated temporal changes of the local 530.3 nm coronal line brightness in the frequency range 1-10 Hz of thousands of points within the field of view. The various photometric and instrumental effects have been extensively considered. We did not find any indisputable, statistically significant evidence of periodicities in any of the investigated points (at significance level alpha = 0.05 or better).

Rudawy, P.↗

NASA NTRS2012

FERMI/GLAST Integrated Trending and Plotting System Release 5.0

An Integrated Trending and Plotting System (ITPS) is a trending, analysis, and plotting system used by space missions to determine performance and status of spacecraft and its instruments. ITPS supports several NASA mission operational control centers providing engineers, ground controllers, and scientists with access to the entire spacecraft telemetry data archive for the life of the mission, and includes a secure Web component for remote access. FERMI/GLAST ITPS Release 5.0 features include the option to display dates (yyyy/ddd) instead of orbit numbers along orbital Long-Term Trend (LTT) plot axis, the ability to save statistics from daily production plots as image files, and removal of redundant edit/create Input Definition File (IDF) screens. Other features are a fix to address invalid packet lengths, a change in naming convention of image files in order to use in script, the ability to save all ITPS plot images (from Windows or the Web) as GIF or PNG format, the ability to specify ymin and ymax on plots where previously only the desired range could be specified, Web interface capability to plot IDFs that contain out-oforder page and plot numbers, and a fix to change all default file names to show yyyydddhhmmss time stamps instead of hhmmssdddyyyy. A Web interface capability sorts files based on modification date (with newest one at top), and the statistics block can be displayed via a Web interface. Via the Web, users can graphically view the volume of telemetry data from each day contained in the ITPS archive in the Web digest. The ITPS could be also used in nonspace fields that need to plot data or trend data, including financial and banking systems, aviation and transportation systems, healthcare and educational systems, sales and marketing, and housing and construction.

Ritter, Sheila↗

DOE OSTI2025

Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. In preparation for VENUS, the neutron imaging beamline to be located at beam port 10, we have performed a series of experiments focused on wavelength-dependent radiography and computed tomography for a broad range of applications, from materials science to biological tissues.One of the time-of-flight (TOF) techniques that is of interest to the scientific community is the 2-dimensional mapping of phases and average crystalline plane orientation in samples both ex-situ and during applied stresses such as tensile loading and heating. This technique is known as Bragg edgeimaging and relies on the identification of changes of transmission values, fitting of the edge to measure its displacement, and thus identify the shift in lattice parameter due to stresses. One of the challenges of TOF imaging measurements is the amount of data and the inability to observe Bragg edge shifts in real time during an experiment. Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the

Bilheux, JeanChristophe [Oak Ridge National Labora↗

NASA NTRS2022

Midwest Water Resources II: Evaluating Evapotranspiration with NASA Earth Observations and In Situ Observations to Understand Water Balance in Midwest Agriculture

Seasonal water variability in the midwestern United States extensively affects the agricultural community, as it impacts irrigation schedules, growing seasons, and overall ecosystem function. Evapotranspiration (ET) is a critical climatic variable in the water cycle and is used to evaluate spatiotemporal trends in drought and flood conditions. The NASA DEVELOP team partnered with the United States Department of Agriculture (USDA) Midwest Climate Hub, the Minnesota Department of Agriculture, the Illinois State Water Survey, and Michigan State University to compare remotely sensed ET products with in situ observations from January 2001 through December 2020. Remotely sensed actual ET (aET) data were sourced from NASA’s Terra Moderate Resolution Imaging Spectroradiometer (MODIS), and reference ET (refET) data were derived from the Gridded Surface Meteorological (gridMET) dataset. For in situ comparison, aET data were downloaded from the AmeriFlux database while refET data were collected from the Illinois Climate Network and Michigan State University’s Enviro-weather database. For a holistic assessment of ET, this project generated comparisons between remotely sensed and in situ observations, calculated descriptive statistics for validation between refET datasets, and spatially produced statistical validation maps regarding in situ sites. The temporal and spatial gaps of AmeriFlux data limited aET analysis. This comparative assessment of ET products across the Midwest can be used by project partners to assess regional water trends and guide future land management decisions.

Addison Pletcher↗

NASA NTRS2012

Analysis of Fine-Mode Aerosol Retrieval Capabilities by Different Passive Remote Sensing Instrument Designs

Remote sensing of aerosol optical properties is difficult, but multi-angle, multi-spectral, polarimetric instruments have the potential to retrieve sufficient information about aerosols that they can be used to improve global climate models. However, the complexity of these instruments means that it is difficult to intuitively understand the relationship between instrument design and retrieval success. We apply a Bayesian statistical technique that relates instrument characteristics to the information contained in an observation. Using realistic simulations of fine size mode dominated spherical aerosols, we investigate three instrument designs. Two of these represent instruments currently in orbit: the Multiangle Imaging SpectroRadiometer (MISR) and the POLarization and Directionality of the Earths Reflectances (POLDER). The third is the Aerosol Polarimetry Sensor (APS), which failed to reach orbit during recent launch, but represents a viable design for future instruments. The results show fundamental differences between the three, and offer suggestions for future instrument design and the optimal retrieval strategy for current instruments. Generally, our results agree with previous validation efforts of POLDER and airborne prototypes of APS, but show that the MISR aerosol optical thickness uncertainty characterization is possibly underestimated.

Knobelspiesse, Kirk↗

DOE OSTI2026

Two datasets are better than one: method of double moments for 3D reconstruction in cryo-EM

Cryo-electron microscopy is a powerful imaging technique for reconstructing three-dimensional molecular structures from noisy tomographic projection images of randomly oriented particles. We introduce a new data fusion framework, termed the method of double moments, which reconstructs molecular structures from two instances of the second-order moment of projection images obtained under distinct orientation distributions: one uniform, the other non-uniform and unknown. We prove that these moments generically uniquely determine the underlying structure, up to a global rotation and reflection, and we develop a convex-relaxation-based algorithm that achieves accurate recovery using only second-order statistics. Our results demonstrate the advantage of collecting and modeling multiple datasets under different experimental conditions, illustrating that leveraging dataset diversity can substantially enhance reconstruction quality in computational imaging tasks.

Kam’s method↗

NASA NTRS2010

Global Patterns of Lightning Properties Derived by LIS

The Lightning Imaging Sensor LIS aboard the TRMM satellite provides unmatched empirical data of the global lightning distribution (up to approx.35deg S/N) since end of 1997. Climatological flash rate densities derived from LIS are standard references, e.g. for flash rate parameterizations used in GCMs. It is known that flash characteristics are quite variable, and that various quantities (like the flash energy or the NOx production per flash) vary considerably, statistically as well as systematically on regional and seasonal scales. LIS provides information beyond flash counts, in particular radiance and flash footprint. Here we present an analysis of global patterns of various lightning properties derived from LIS, in relation to the number of flashes. These normalized flash characteristics show consistent spatial patterns of regions with "strong" versus regions with "weak" lightning. Most striking is a clear land-ocean contrast, with oceanic flashes being "stronger" than continental flashes. But also over continents, flash strength shows systematic variations. Highest continental values are found over the US, while values over South America and India are quite low. These regional variations cannot be simply parameterized as function of latitude. Information on spatial patterns of mean flash "strength", though rather qualitative up to now, is potentially a valuable input for improving empirical parameterizations based on flash counts (like precipitation or lightning NOx). Further investigation is in progress to come to a more physical and quantitative understanding of the spatial patterns of the different LIS properties. In particular, it has to be checked how far they could be related to established lightning properties (like energy or the fraction of intra-cloud to cloud-to-ground flashes) or to meteorological quantities (like CAPE).

Beirle, S.↗

NASA NTRS2021

Cryovolcanic flooding in Viking Terra on Pluto

A prominent fossa trough (Uncama Fossa) and adjacent 28-km diameter impact crater (Hardie) in Pluto's Viking Terra, as seen in the high-resolution images from the New Horizons spacecraft, show morphological evidence of in-filling with a material of uniform texture and red-brown color. A linear fissure parallel to the trough may be the source of a fountaining event yielding a cryoclastic deposit having the same composition and color properties as is found in the trough and crater. Spectral maps of this region with the New Horizons LEISA instrument reveal the spectral signature of H2O ice in these structures and in distributed patches in the adjacent terrain in Viking Terra. A detailed statistical analysis of the spectral maps shows that the colored H2O ice filling material also carries the 2.2-μm signature of an ammoniated component that may be an ammonia hydrate (NH3·nH2O) or an ammoniated salt. This paper advances the view that the crater and fossa trough have been flooded by a cryolava debouched from Pluto's interior along fault lines in the trough and in the floor of the impact crater. The now frozen cryolava consisted of liquid H2O infused with the red-brown pigment presumed to be a tholin, and one or more ammoniated compounds. Although the abundances of the pigment and ammoniated compounds entrained in, or possibly covering, the H2O ice are unknown, the strong spectral bands of the H2O ice are clearly visible. In consideration of the factors in Pluto's space environment that are known to destroy ammonia and ammonia-water mixtures, the age of the exposure is of order ≤109 years. Ammoniated salts may be more robust, and laboratory investigations of these compounds are needed.

Pluto↗

NASA NTRS2022

Peru Health and Air Quality II: Leveraging Earth Observations and Health Data to Map Outbreak Risk and Inform Public Health Interventions for Zoonotic Disease Prevention

Peru's Madre de Dios region is a hotspot for dengue fever and leishmaniasis due to its tropical Amazonian climate. Though treatable, these zoonotic diseases are debilitating for under-resourced communities whose already close proximity to mosquito and sandfly vectors continues to increase via rapid urbanization and deforestation. Peru’s Ministries of Health (MINSA) and Environment (MINAM) are working to better understand the environmental factors amplifying the risk of dengue fever and leishmaniasis transmission. The first term of this project classified the land use and land cover of Madre de Dios’ 11 districts for 2010, 2015, and 2020 and identified a correlation between both diseases and urbanization. Our team expanded this analysis by creating urban-forest edge maps and incorporating climatic and topographic variables with data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), the Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG), and the Shuttle Radar Topography Mission (SRTM). We determined these variables’ impacts on disease incidence by assessing existing literature and running regression models. Dengue fever correlated with urban-forest edge, urban area, slope, temperature, and precipitation. Leishmaniasis primarily correlated with forest-edge area and elevation, but lacking additional statistical significance prevented further work, a decision supported by the literature. Thus, the risk matrix and risk map which we scripted in R to visualize the risk of disease posed to districts alongside health post locations addresses only dengue fever. The results and products will inform MINSA and MINAM in public health interventions, resource distribution, and policy initiatives.

Jennifer Rogers↗

DOE OSTI2020

Quantitative probing of the fast particle motion during the solidification of battery electrodes

Synchrotron x-ray tomography represents one of the most powerful imaging techniques that can visualize the three-dimensional microstructural complexity with a high spatial resolution. To date, however, the temporal resolution of this technique has been handicapped by the intrinsic limitations in the data acquisition speed and the lack of a suitable data processing method. The present study aims to fundamentally resolve this challenge by implementing a data analysis method that is based on differentiating discrete tomography reconstruction from a continuous scan reconstruction. With this methodological development, we capture and quantify the particle motion during the solidification of battery electrodes and reveal the statistics of the dynamically evolving motion in the drying process, which has been challenging to resolve. We discover that the particle motion exhibits a strong dependence on its geometric location within a drying electrode. Our results also imply that the final electrode quality can be controlled by balancing the solvent evaporation rate and the particle mobility in the region close to the drying surface.

25 ENERGY STORAGE↗