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NASA NTRS1975

MITNYS-II - A digital program for on-line analysis of nystagmus

A digital computer program, MITNYS-II, has been developed for on-line analysis of nystagmus which results from visual, vestibular or caloric stimulation. The program accepts sampled records of eye position and yields cumulative slow phase position, slow phase velocity, instantaneous fast phase frequency and other parameters in 25 ms. In this paper the algorithms by which fast phases are detected, and by which slow phase cumulative eye position is extrapolated across the fast phase interval are described. Extensive tests with vestibular, optokinetic and caloric nystagmus yield reliability figures of the order of 2% for false identification of fast phases and missed fast phases. MITNYS-II has been successfully employed to interpret clinical EOG records, examples of which are presented.

Allum, J. H. J.↗

DOE OSTI2026

Pushing the Limits of Pulse Shape Discrimination in a Large Liquid Xenon Detector

The LUX-ZEPLIN (LZ) experiment is a direct-detection dark matter experiment, optimized to search for weakly interacting massive particles (WIMPs) through WIMP-nucleon interactions. The main challenge in dark matter detection is differentiating between WIMP signals and background events. In LZ, the ratio of ionization to scintillation signals (charge-to-light) is the primary method for rejecting electronic recoil (ER) background. Pulse shape discrimination (PSD) offers a method for additional ER backgrounds rejection in liquid xenon detectors. In this paper, the discrimination power of PSD with the LZ experiment is discussed. To precisely characterize the scintillation pulse shape, an analysis framework is developed to reconstruct the detection time of individual photons. Using LZ calibration data, the photon-timing prompt fraction discriminator is optimized and achieves ER leakage as low as $15\%$. For specific background processes such as $^{124}$Xe double electron capture, the leakage is reduced further to about $5\%$. PSD is combined with charge-to-light to form two-factor discrimination (TFD). The optimized TFD performance is compared with the performance of the charge-to-light method, with the corresponding false positive rate reduced by up to a factor of two for large scintillation pulses. Finally, PSD and TFD are applied to data from LZ's WS2024 run and their performance is summarized.

Akerib, D. S. [SLAC; KIPAC, Menlo Park]↗

NASA NTRS2011

Lightning Initiation Forecasting: An Operational Dual-Polarimetric Radar Technique

The objective of this NASA MSFC and NOAA CSTAR funded study is to develop and test operational forecast algorithms for the prediction of lightning initiation utilizing the C-band dual-polarimetric radar, UAHuntsville's Advanced Radar for Meteorological and Operational Research (ARMOR). Although there is a rich research history of radar signatures associated with lightning initiation, few studies have utilized dual-polarimetric radar signatures (e.g., Z(sub dr) columns) and capabilities (e.g., fuzzy-logic particle identification [PID] of precipitation ice) in an operational algorithm for first flash forecasting. The specific goal of this study is to develop and test polarimetric techniques that enhance the performance of current operational radar reflectivity based first flash algorithms. Improving lightning watch and warning performance will positively impact personnel safety in both work and leisure environments. Advanced warnings can provide space shuttle launch managers time to respond appropriately to secure equipment and personnel, while they can also provide appropriate warnings for spectators and players of leisure sporting events to seek safe shelter. Through the analysis of eight case dates, consisting of 35 pulse-type thunderstorms and 20 non-thunderstorm case studies, lightning initiation forecast techniques were developed and tested. The hypothesis is that the additional dual-polarimetric information could potentially reduce false alarms while maintaining high probability of detection and increasing lead-time for the prediction of the first lightning flash relative to reflectivity-only based techniques. To test the hypothesis, various physically-based techniques using polarimetric variables and/or PID categories, which are strongly correlated to initial storm electrification (e.g., large precipitation ice production via drop freezing), were benchmarked against the operational reflectivity-only based approaches to find the best compromise between forecast skill and lead-time. Forecast skill is determined by statistical analysis of probability of detection (POD), false alarm ratio (FAR), Operational Utility Index (OUI), and critical success index (CSI).

Woodard, Crystal J.↗

DOE OSTI2026

Pushing the limits of pulse shape discrimination in a large liquid xenon detector

Abstract The LUX-ZEPLIN (LZ) experiment is a direct-detection dark matter experiment, optimized to search for weakly interacting massive particles (WIMPs) through WIMP-nucleon interactions. The main challenge in dark matter detection is differentiating between WIMP signals and background events. In LZ, the ratio of ionization to scintillation signals (charge-to-light) is the primary method for rejecting electronic recoil (ER) background. Pulse shape discrimination (PSD) offers a method for additional ER backgrounds rejection in liquid xenon detectors. In this paper, the discrimination power of PSD with the LZ experiment is discussed. To precisely characterize the scintillation pulse shape, an analysis framework is developed to reconstruct the detection time of individual photons. Using LZ calibration data, the photon-timing tail fraction discriminator is optimized and achieves ER leakage as low as $$15\%$$ 15 % . For specific background processes such as $$^{124}$$ 124 Xe double electron capture, the leakage is reduced further to about $$5\%$$ 5 % . PSD is combined with charge-to-light to form two-factor discrimination (TFD). The optimized TFD performance is compared with the performance of the charge-to-light method, with the corresponding false positive rate reduced by up to a factor of two for large scintillation pulses. Finally, PSD and TFD are applied to data from LZ’s WS2024 run and their performance is summarized.

Akerib, D. S. [SLAC National Accelerator Laborator↗

DOE OSTI2024

Inferring precocial Chinook Salmon production through single‐parentage assignments

Abstract Objective Parentage analysis is a routine methodology in fisheries research, but study systems exist where it is impractical to sample both parents. The ability to reliably assign offspring to a single parent is beneficial in these situations. We applied single‐parentage assignments to a naturally spawning population of Chinook Salmon Oncorhynchus tshawytscha to quantify production of anadromous returns by unsampled precocial males. Methods We used an approach that focused on two important aspects of parentage analyses: (1) addressing the presence of family structure within the set of sampled parents and (2) controlling for false‐positive and false‐negative assignments. Result Results indicated that 30% of reproductively successful males were precocial males, which produced 20% of the returning anadromous offspring. Conclusion This study provides a framework for applying single‐parent assignments in a salmonid study system while explicitly addressing sources of assignment errors.

Steele, Craig A.↗

NASA NTRS2012

Multi-Parameter Observation and Detection of Pre-Earthquake Signals in Seismically Active Areas

The recent large earthquakes (M9.0 Tohoku, 03/2011; M7.0 Haiti, 01/2010; M6.7 L Aquila, 04/2008; and M7.9 Wenchuan 05/2008) have renewed interest in pre-anomalous seismic signals associated with them. Recent workshops (DEMETER 2006, 2011 and VESTO 2009 ) have shown that there were precursory atmospheric /ionospheric signals observed in space prior to these events. Our initial results indicate that no single pre-earthquake observation (seismic, magnetic field, electric field, thermal infrared [TIR], or GPS/TEC) can provide a consistent and successful global scale early warning. This is most likely due to complexity and chaotic nature of earthquakes and the limitation in existing ground (temporal/spatial) and global satellite observations. In this study we analyze preseismic temporal and spatial variations (gas/radon counting rate, atmospheric temperature and humidity change, long-wave radiation transitions and ionospheric electron density/plasma variations) which we propose occur before the onset of major earthquakes:. We propose an Integrated Space -- Terrestrial Framework (ISTF), as a different approach for revealing pre-earthquake phenomena in seismically active areas. ISTF is a sensor web of a coordinated observation infrastructure employing multiple sensors that are distributed on one or more platforms; data from satellite sensors (Terra, Aqua, POES, DEMETER and others) and ground observations, e.g., Global Positioning System, Total Electron Content (GPS/TEC). As a theoretical guide we use the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) model to explain the generation of multiple earthquake precursors. Using our methodology, we evaluated retrospectively the signals preceding the most devastated earthquakes during 2005-2011. We observed a correlation between both atmospheric and ionospheric anomalies preceding most of these earthquakes. The second phase of our validation include systematic retrospective analysis for more than 100 major earthquakes (M>5.9) in Taiwan and Japan. We have found anomalous behavior before all of these events with no false negatives. Calculated false alarm ratio for the for the same month over the entire period of analysis (2003-2009) is less than 10% and was d as the earthquakes. The commonalities in detecting atmospheric/ionospheric anomalies show that they may exist over both land and sea in regions of maximum stress (i.e., along plate boundaries) Our results indicate that the ISTF model could provide a capability to observe pre-earthquake atmospheric/ionospheric signals by combining this information into a common framework.

Ouzounov, D.↗

DOE OSTI2025

Characterisation and comparative analysis of mitochondrial genomes of false, yellow, black and blushing morels provide insights on their structure and evolution

Morchella species have considerable significance in terrestrial ecosystems, exhibiting a range of ecological lifestyles along the saprotrophism-to-symbiosis continuum. However, the mitochondrial genomes of these ascomycetous fungi have not been thoroughly studied, thereby impeding a comprehensive understanding of their genetic makeup and ecological role. In this study, we analysed the mitogenomes of 30 Morchellaceae species, including yellow, black, blushing and false morels. These mitogenomes are either circular or linear DNA molecules with lengths ranging from 217 to 565 kbp and GC content ranging from 38% to 48%. Fifteen core protein-coding genes, 28–37 tRNA genes and 3–8 rRNA genes were identified in these Morchellaceae mitogenomes. The gene order demonstrated a high level of conservation, with the cox1 gene consistently positioned adjacent to the rnS gene and cob gene flanked by apt genes. Some exceptions were observed, such as the rearrangement of atp6 and rps3 in Morchella importuna and the reversed order of atp6 and atp8 in certain morel mitogenomes. However, the arrangement of the tRNA genes remains conserved. We additionally investigated the distribution and phylogeny of homing endonuclease genes (HEGs) of the LAGLIDADG (LAGs) and GIY-YIG (GIYs) families. A total of 925 LAG and GIY sequences were detected, with individual species containing 19–48HEGs. These HEGs were primarily located in the cox1, cob, cox2 and nad5 introns and their presence and distribution displayed significant diversity amongst morel species. These elements significantly contribute to shaping their mitogenome diversity. Overall, this study provides novel insights into the phylogeny and evolution of the Morchellaceae.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Archetype-based Redshift Estimation for the Dark Energy Spectroscopic Instrument Survey

We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral classifier using a linear combination of principal component analysis–derived templates, which is very efficient in processing large volumes of DESI spectra within a short time frame. However, this method occasionally yields unphysical model fits for galaxies and fails to adequately absorb calibration errors that may still be occasionally visible in the reduced spectra. Our proposed approach improves upon this existing method by refitting the spectra with carefully generated physical galaxy archetypes combined with additional terms designed to absorb data reduction defects and provide more physical models to the DESI spectra. We test our method on an extensive data set derived from the survey validation (SV) and Year 1 (Y1) data of DESI. Our findings indicate that the new method delivers marginally better redshift success for SV tiles while reducing catastrophic redshift failure by 10%–30%. At the same time, results from millions of targets from the main survey show that our model has relatively higher redshift success and purity rates (0.5%–0.8% higher) for galaxy targets while having similar success for QSOs. These improvements also demonstrate that the main DESI redshift pipeline is generally robust. Additionally, it reduces the false-positive redshift estimation by 5%–40% for sky fibers. We also discuss the generic nature of our method and how it can be extended to other large spectroscopic surveys, along with possible future improvements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1994

Climatic, eustatic, and tectnoic controls on Quarternary deposits and landforms, Red Sea coast, Egypt

The degree to which local climatic variations, eustatic sea level fluctuations, and tectonic uplift have influenced the development of Quaternary marine and fluvial landforms and deposits along the Red Sea coast, Eastern Desert, was investigated using a combination of remote sensing and field data, age determinations of corals, and numerical simulations. False color composites generated from Landsat Thematic Mapper and SPOT image data, digital elevation models derived from sterophotogrammetric analysis of SPOT data, and field observations document that a approximately 10-km wide swath inland from the coast is covered in many places with coalescing alluvial fans of Quaternary age. Wadis cutting through the fans exhibit several pairs of fluvial terraces, and wadi walls expose alluvium interbedded with corraline limestone deposits Further, three distinct coral terraces are evident along the coatline. Climatic, eustatic, and tectonic uplift controls on the overall system were simulated using a cellular automata algorithm with the following characteristics: (1) uplift as a function of position and time, as defined by the elevations and ages of corals; (2) climatic variations driven by insolation changes associated with Milankovitch cycles; (3) sea level fluctuations based on U/Th ages of coral terraces and eustatic data; and (4) parametrized fluvial erosion and deposition. Results imply that the fans and coralline limestones were generated in a setting in which the tectonic uplift rate decreased over the Quarternary to negligible values at present. Coralline limestones formed furing eustatic highstands when alluvium was trapped uspstream and wadis filled with debris. During lowstands, wadis cut into sedimentary deposits; coupled with continuing uplift, fans were dissected, leaving remnant surfaces, and wadi-related terraces were generated by down cutting. Only landforms from the past three to four eustatic sea level cycles (i.e., approximately 300 to 400 kyr) are likely to have survived erosion and deposition associated with fluvial processes.

Arvidson, Raymond↗

NASA NTRS2013

Semi-Supervised Eigenbasis Novelty Detection

Recent discoveries in high-time-resolution radio astronomy data have focused attention on a new class of events. Fast transients are rare pulses of radio frequency energy lasting from microseconds to seconds that might be produced by a variety of exotic astrophysical phenomena. For example, X-ray bursts, neutron stars, and active galactic nuclei are all possible sources of short-duration, transient radio signals. It is difficult to anticipate where such signals might appear, and they are most commonly discovered through analysis of high-time- resolution data that had been collected for other purposes. Transients are often faint and difficult to detect, so improved detection algorithms can directly benefit the science yield of all such commensal monitoring. A new detection algorithm learns a low-dimensional linear manifold for describing the normal data. High reconstruction error indicates a novel signal that does not match the patterns of normal data. One unsupervised portion of the manifold model adapts its representation in response to recent data. A second supervised portion of the model is made of a basis trained in advance using labeled examples of RFI; this prevents false positives due to these events. For a linear model, an orthonormalization operation is used to combine these bases prior to the anomaly detection decision. Another novel aspect of the approach lies in combining basis vectors learned in an unsupervised, online fashion from the data stream with supervised basis vectors learned in advance from known examples of false alarms. Adaptive, data-driven detection is achieved that is also informed by existing domain knowledge about signals that may be statistically anomalous, but are not interesting and should therefore be ignored. The method was evaluated using data from the Parkes Multibeam Survey. This data set was originally collected to search for pulsars, which are astronomical sources that emit radio pulses at regular periods. However, several non-pulsar anomalies have recently been discovered in this dataset, making it a compelling test case. By explicitly filtering known false alarm patterns, the approach yields significantly better performance than current transient detection methods.

Wagstaff, Kiri L.↗

NASA NTRS2012

In-Situ Wire Damage Detection System

An In-Situ Wire Damage Detection System (ISWDDS) has been developed that is capable of detecting damage to a wire insulation, or a wire conductor, or to both. The system will allow for realtime, continuous monitoring of wiring health/integrity and reduce the number of false negatives and false positives while being smaller, lighter in weight, and more robust than current systems. The technology allows for improved safety and significant reduction in maintenance hours for aircraft, space vehicles, satellites, and other critical high-performance wiring systems for industries such as energy production and mining. The integrated ISWDDS is comprised of two main components: (1) a wire with an innermost core conductor, an inner insulation film, a conductive layer or inherently conductive polymer (ICP) covering the inner insulation film, an outermost insulation jacket; and (2) smart connectors and electronics capable of producing and detecting electronic signals, and a central processing unit (CPU) for data collection and analysis. The wire is constructed by applying the inner insulation films to the conductor, followed by the outer insulation jacket. The conductive layer or ICP is on the outer surface of the inner insulation film. One or more wires are connected to the CPU using the smart connectors, and up to 64 wires can be monitored in real-time. The ISWDDS uses time domain reflectometry for damage detection. A fast-risetime pulse is injected into either the core conductor or conductive layer and referenced against the other conductor, producing transmission line behavior. If either conductor is damaged, then the signal is reflected. By knowing the speed of propagation of the pulse, and the time it takes to reflect, one can calculate the distance to and location of the damage.

Williams, Martha↗

DOE OSTI2024

Predictive analytics of selections of russet potatoes

We explore the application of machine learning algorithms specifically to enhance the selection process of Russet potato (Solanum tuberosum L.) clones in breeding trials by predicting their suitability for advancement. This study addresses the challenge of efficiently identifying high-yield, disease-resistant, and climate-resilient potato varieties that meet processing industry standards. Leveraging manually collected data from trials in the state of Oregon, we investigate the potential of a wide variety of state-of-the-art binary classification models. The dataset includes 1086 clones, with data on 38 attributes recorded for each clone, focusing on yield, size, appearance, and frying characteristics, with several control varieties planted consistently across four Oregon regions from 2013 to 2021. We conduct a comprehensive analysis of the dataset that includes preprocessing, feature engineering, and imputation to address missing values. We focus on several key metrics such as accuracy, F1-score, and Matthews correlation coefficient (MCC) for model evaluation. The top-performing models, namely a feedforward neural network classifier (Neural Net), a histogram-based gradient boosting classifier (HGBC), and a support vector machine classifier (SVM), demonstrate consistent and significant results. To further validate our findings, we conducted a simulation study using the aims, data-generating mechanisms, estimands, methods, and performance measures (ADEMP) framework, simulating different data-generating scenarios to assess model robustness and performance through true positive, true negative, false positive, and false negative distributions, area under the receiver operating characteristic curve (AUC-ROC) and MCC. The simulation results highlight that non-linear models like SVM and HGBC consistently show higher AUC-ROC and MCC than logistic regression, thus outperforming the traditional linear model across various distributions, and emphasizing the importance of model selection and tuning in agricultural trials. Variable selection further enhances model performance and identifies influential features in predicting trial outcomes. The findings emphasize the potential of machine learning in streamlining the selection process for potato varieties, offering benefits such as increased efficiency, substantial cost savings, and judicious resource utilization. Our study contributes insights into precision agriculture and showcases the relevance of advanced technologies for informed decision-making in breeding programs.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2001

Facility Concepts for Mars Returned Sample Handling

Samples returned from Mars must be held in quarantine until their biological safety has been determined. A significant challenge, unique to NASA's needs, is how to contain the samples (to protect the blaspheme) while simultaneously protecting their pristine nature. This paper presents a comparative analysis of several quarantine facility concepts for handling and analyzing these samples. The considerations in this design analysis include: modes of manipulation; capability for destructive as well as non-destructive testing; avoidance of cross-contamination; linear versus recursive processing; and sample storage and retrieval within a closed system. The ability to rigorously contain biologically hazardous materials has been amply demonstrated by facilities that meet the specifications of the Center for Disease Control Biosafety Level 4. The newly defined Planetary Protection Level Alpha must provide comparable containment while assuring that the samples remain pristine; the latter requirement is based on the need to avoid compromising science analyses by instrumentation of the highest possible sensitivity (among other things this will assure that there is no false positive detection of organisms or organic molecules - a situation that would delay or prevent the release of the samples from quarantine). Protection of the samples against contamination by terrestrial organisms and organic molecules makes a considerable impact upon the sample handling facility. The use of glove boxes appears to be impractical because of their tendency to leak and to surges. As a result, a returned sample quarantine facility must consider the use of automation and remote manipulation to carry out the various functions of sample handling and transfer within the system. The problem of maintaining sensitive and bulky instrumentation under the constraints of simultaneous sample containment and contamination protection also places demands on the architectural configuration of the facility that houses it.

Cohen, Marc M.↗

NASA NTRS2000

Aircraft Conflict Analysis and Real-Time Conflict Probing Using Probabilistic Trajectory Modeling

Methods for maintaining separation between aircraft in the current airspace system have been built from a foundation of structured routes and evolved procedures. However, as the airspace becomes more congested and the chance of failures or operational error become more problematic, automated conflict alerting systems have been proposed to help provide decision support and to serve as traffic monitoring aids. The problem of conflict detection and resolution has been tackled from a number of different ways, but in this thesis, it is recast as a problem of prediction in the presence of uncertainties. Much of the focus is concentrated on the errors and uncertainties from the working trajectory model used to estimate future aircraft positions. The more accurate the prediction, the more likely an ideal (no false alarms, no missed detections) alerting system can be designed. Additional insights into the problem were brought forth by a review of current operational and developmental approaches found in the literature. An iterative, trial and error approach to threshold design was identified. When examined from a probabilistic perspective, the threshold parameters were found to be a surrogate to probabilistic performance measures. To overcome the limitations in the current iterative design method, a new direct approach is presented where the performance measures are directly computed and used to perform the alerting decisions. The methodology is shown to handle complex encounter situations (3-D, multi-aircraft, multi-intent, with uncertainties) with relative ease. Utilizing a Monte Carlo approach, a method was devised to perform the probabilistic computations in near realtime. Not only does this greatly increase the method's potential as an analytical tool, but it also opens up the possibility for use as a real-time conflict alerting probe. A prototype alerting logic was developed and has been utilized in several NASA Ames Research Center experimental studies.

Yang, Lee C.↗

NASA NTRS2010

Kepler Planet Detection Mission: Introduction and First Results

The Kepler Mission is designed to determine the frequency of Earth-size and rocky planets in and near the habitable zone (HZ) of solar-like stars. The HZ is defined to be the region of space where a rocky planet could maintain liquid water on its surface. Kepler is the 10th competitively-selected Discovery Mission and was launched on March 6, 2009. Since completing its commissioning, Kepler has observed over 156,000 stars simultaneously and near continuously to search for planets that periodically pass in front of their host star (transit). The photometric precision is approximately 23 ppm for 50% of the 12th magnitude dwarf stars for an integration period of 6.5 hours. During the first 3 months of operation the photometer detected transit-like signatures from more than 200 stars. Careful examination shows that many of these events are false-positives such as small stars orbiting large stars or blends of target stars with eclipsing binary stars. Ground-based follow-up observations confirm the discovery of five new exoplanets with sizes between 0.37 andl.6 Jupiter radii (R(sub J)) and orbital periods ranging from 3.2 to 4.9 days. Ground-based observations with the Keck 1, Hobby-Ebberly, Hale, WIYN, MMT, Tillinghast, Shane, and Nordic Optical Telescopes are used to vet the planetary candidates and measure the masses of the putative planets. Observations of occultations and phase variations of hot, short-period planets such as HT-P-7b provide a probe of atmospheric properties. Asteroseismic analysis already shows the presence of p-mode oscillations in several stars. Such observations will be used to measure the mean stellar density and infer the stellar size and age. For stars too dim to permit asteroseismology, observations of the centroid motion of target stars will be used to measure the parallax and be combined with photometric measurements to estimate stellar sizes. Four open clusters are being observed to determine stellar rotation rates as a function of age and spectral type. Many different types of stellar variability are observed with unprecedented precision and over a wide range of time scales. Solar-like photometric variability of thousands of field stars is being studied to determine how photometric variability and the stellar rotation rates change with stellar age and metallicity. A wide variety of other astrophysical phenomena have also been observed. The data are being analyzed at the Ames Research Center and archived at the MAST at STScI. The Kepler Mission also supports a vigorous Guest Observer Program.

Borucki, William↗

NASA NTRS2000

Real Time Intelligent Target Detection and Analysis with Machine Vision

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

Howard, Ayanna↗

NASA NTRS2007

NASA Tech Briefs, December 2007

Topics include: Ka-Band TWT High-Efficiency Power Combiner for High-Rate Data Transmission; Reusable, Extensible High-Level Data-Distribution Concept; Processing Satellite Imagery To Detect Waste Tire Piles; Monitoring by Use of Clusters of Sensor-Data Vectors; Circuit and Method for Communication Over DC Power Line; Switched Band-Pass Filters for Adaptive Transceivers; Noncoherent DTTLs for Symbol Synchronization; High-Voltage Power Supply With Fast Rise and Fall Times; Waveguide Calibrator for Multi-Element Probe Calibration; Four-Way Ka-Band Power Combiner; Loss-of-Control-Inhibitor Systems for Aircraft; Improved Underwater Excitation-Emission Matrix Fluorometer; Metrology Camera System Using Two-Color Interferometry; Design and Fabrication of High-Efficiency CMOS/CCD Imagers; Foam Core Shielding for Spacecraft CHEM-Based Self-Deploying Planetary Storage Tanks Sequestration of Single-Walled Carbon Nanotubes in a Polymer PPC750 Performance Monitor Application-Program-Installer Builder Using Visual Odometry to Estimate Position and Attitude Design and Data Management System Simple, Script-Based Science Processing Archive Automated Rocket Propulsion Test Management Online Remote Sensing Interface Fusing Image Data for Calculating Position of an Object Implementation of a Point Algorithm for Real-Time Convex Optimization Handling Input and Output for COAMPS Modeling and Grid Generation of Iced Airfoils Automated Identification of Nucleotide Sequences Balloon Design Software Rocket Science 101 Interactive Educational Program Creep Forming of Carbon-Reinforced Ceramic-Matrix Composites Dog-Bone Horns for Piezoelectric Ultrasonic/Sonic Actuators Benchtop Detection of Proteins Recombinant Collagenlike Proteins Remote Sensing of Parasitic Nematodes in Plants Direct Coupling From WGM Resonator Disks to Photodetectors Using Digital Radiography To Image Liquid Nitrogen in Voids Multiple-Parameter, Low-False-Alarm Fire-Detection Systems Mosaic-Detector-Based Fluorescence Spectral Imager Plasmoid Thruster for High Specific-Impulse Propulsion Analysis Method for Quantifying Vehicle Design Goals Improved Tracking of Targets by Cameras on a Mars Rover Sample Caching Subsystem Multistage Passive Cooler for Spaceborne Instruments GVIPS Models and Software Stowable Energy-Absorbing Rocker-Bogie Suspensions

Source record↗

NASA NTRS1973

Census cities experiment in urban change detection

The author has identified the following significant results. Work continues on mapping of 1970 urban land use from 1970 census contemporaneous aircraft photography. In addition, change detection analysis from 1972 aircraft photography is underway for several urban test sites. Land use maps, mosaics, and census overlays for the two largest urban test sites are nearing publication readiness. Preliminary examinations of ERTS-1 imagery of San Francisco Bay have been conducted which show that tracts of land of more than 10 acres in size which are undergoing development in an urban setting can be identified. In addition, each spectral band is being evaluated as to its utility for urban analyses. It has been found that MSS infrared band 7 helps to differentiate intra-urban land use details not found in other MSS bands or in the RBV coverage of the same scene. Good quality false CIR composites have been generated from 9 x 9 inch positive MSS bands using the Diazo process.

Wray, J. R.↗