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At least 1,495 records · Page 83

Correction of thin cirrus effects in AVIRIS images using the sensitive 1.375-micron cirrus detecting channel

Using spectral imaging data acquired with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) from an ER-2 aircraft at 20 km altitude during various field programs, it was found that narrow channels near the center of the strong 1.38-micrometer water vapor band are very effective in detecting think cirrus clouds. Based on this observation from AVIRIS data, Gao and Kaufman proposed to put a channel centered at 1.375 micrometers with a width of 30 nm on the Moderate Resolution Imaging Spectrometer (MODIS) for remote sensing of cirrus clouds from space. The sensitivity of the 1.375-micrometer MODIS channel to detect thin cirrus clouds during the day time is expected to be one to two orders of magnitude better than the current infrared emission techniques. As a result, much larger fraction of the satellite data is expected to be identified as being covered by cirrus clouds, some of them so thin that their obscuration of the surface is very small. In order to make better studies of surface reflectance properties, thin cirrus effects must be removed from satellite images. Therefore, there is a need to study radiative properties of thin cirrus clouds, so that a strategy for correction or removal of the thin cirrus effects, similar to the correction of atmospheric aerosol effect, can be formed. In this extended abstract, we describe an empirical approach for removing/correcting thin cirrus effects in AVIRIS images using channels near 1.375 microns - one step beyond the detection of cirrus clouds using these channels.

Gao, Bo-Cai↗

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. It affects the efficiency of the National Airspace System (NAS) and both surface and airspace operations can benefit from better understanding future runway configurations. In this paper, we present a comprehensive implementation of predictive models for runway configuration estimation from large volumes of historical data. Specifically, operational data from two full years (2018 and 2019) is collected, analyzed, and fused together to build the data product used in this work. The data set differs from prior work in the field in terms of its scope, resolution, and variety of factors collected and considered. Meteorological data is collected from two different sources – current weather conditions from METAR (Meteorological Terminal Aviation Routine Weather Report) and forecast weather conditions from Localized Aviation MOS Program (LAMP). Operational data from the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) related to scheduled and actual number of arrivals and departures, average taxi times, etc. are collected. NASA’s Sherlock Data Warehouse is used to identify critical information such as go-arounds, and other events that might impact RCM decision-making. All data is collected and aggregated over 15-minute intervals throughout the two years. This provides a resolution like the timescales that might be necessary for runway configuration management decision-making. A variety of supervised learning algorithms are tested including Support Vector Machine, Random Forest, Gradient Boosting, etc. including tuning of the model hyperparameters. The modeling process is applied and presented on two representative U.S. airports – Charlotte Douglas International Airport (KCLT) and Denver International Airport (KDEN). The two airports present different levels of complexity in terms of the total number of configurations used and provide a balanced perspective on the generalizability of the developed approach to other airports in the NAS. Initial results are promising (F1 score of 0.91 at KCLT and 0.83 at KDEN) for data in the test set. The final paper will contain a comprehensive comparison between different models and model building strategies as well as further refined results. Most important predictors for each airport will be identified along with a discussion and recommendations on adapting the framework to other scenarios.

Tejas G Puranik↗

Detection of coherent 7.6 Hz oscillations during a burst from Aquila X-1

The results are reported of timing and spectral analysis of the X-ray source Aql X-1 (X1908 + 005) using data obtained with the Einstein SSS and MPC instruments. A classic type I burst was observed from Aql X-1 in both detectors, and a coherent modulation with a period of 131.66 + or - 0.02 (7.6 Hz) and a pulsed fraction of 10 percent was detected in the SSS data (0.64-4.5 keV) during the period of enhanced emission. The signal has a random occurrence probability of less than 5 x 10 to the -5th. The sensitivity of the MPC for high-resolution timing during the burst is greatly reduced because of the low-duty cycle during the burst, and the modulation is not detected. There is no evidence for a loss of coherence during the 80 s or so when it is observable. It is argued that an asymmetrical burst occurring on a neutron star rotating at 7.6 Hz offers a plausible explanation for the oscillation.

Schoelkopf, R. J.↗

Likelihood-based docking of models into cryo-EM maps

Optimized docking of models into cryo-EM maps requires exploiting an understanding of the signal expected in the data to minimize the calculation time while maintaining sufficient signal. The likelihood-based rotation function used in crystallography can be employed to establish plausible orientations in a docking search. A phased likelihood translation function yields scores for the placement and rigid-body refinement of oriented models. Optimized strategies for choices of the resolution of data from the cryo-EM maps to use in the calculations and the size of search volumes are based on expected log-likelihood-gain scores computed in advance of the search calculation. Tests demonstrate that the new procedure is fast, robust and effective at placing models into even challenging cryo-EM maps.

59 BASIC BIOLOGICAL SCIENCES↗

Probing solar system objects at infrared wavelengths

The instruments, techniques, and analysis methods employed in IR observations of solar-system objects are discussed and illustrated with sample data. Particular attention is given to (1) high-resolution (Doppler-limited) spectra of H2O in Comet Halley and Comet Wilson (1986l), obtained with the NASA Kuiper Airborne Observatory in 1985-1986, and (2) scanning observations of Jovian thermal emission, obtained with the NASA IRTF in 1987 and subjected to detailed time-series analysis to investigate atmospheric motion. The data are presented in spectra, energy-level diagrams, maps, and graphs and briefly characterized.

Mumma, M. J.↗

Performance and Characterization of a Modular Superconducting Nanowire Single Photon Detector System for Space-to-Earth Optical Communications Links

Space-to-ground photon-counting optical communication links supporting high data rates over large distances require enhanced ground receiver sensitivity in order to reduce the mass and power burden on the spacecraft transmitter. Superconducting nanowire single-photon detectors (SNSPDs) have been demonstrated to offer superior performance in detection efficiency, timing resolution, and count rates over semiconductor photodetectors, and are a suitable technology for high photon efficiency links. Recently photon detectors based on superconducting nanowires have become commercially available, and we have assessed the characteristics and performance of one such commercial system as a candidate for potential utilization in ground receiver designs. The SNSPD system features independent channels which can be added modularly, and we analyze the scalability of the system to support different data rates, as well as consider coupling concepts and issues as the number of channels increases.

Superconductors↗

Image processing for improved eye-tracking accuracy

Video cameras provide a simple, noninvasive method for monitoring a subject's eye movements. An important concept is that of the resolution of the system, which is the smallest eye movement that can be reliably detected. While hardware systems are available that estimate direction of gaze in real-time from a video image of the pupil, such systems must limit image processing to attain real-time performance and are limited to a resolution of about 10 arc minutes. Two ways to improve resolution are discussed. The first is to improve the image processing algorithms that are used to derive an estimate. Off-line analysis of the data can improve resolution by at least one order of magnitude for images of the pupil. A second avenue by which to improve resolution is to increase the optical gain of the imaging setup (i.e., the amount of image motion produced by a given eye rotation). Ophthalmoscopic imaging of retinal blood vessels provides increased optical gain and improved immunity to small head movements but requires a highly sensitive camera. The large number of images involved in a typical experiment imposes great demands on the storage, handling, and processing of data. A major bottleneck had been the real-time digitization and storage of large amounts of video imagery, but recent developments in video compression hardware have made this problem tractable at a reasonable cost. Images of both the retina and the pupil can be analyzed successfully using a basic toolbox of image-processing routines (filtering, correlation, thresholding, etc.), which are, for the most part, well suited to implementation on vectorizing supercomputers.

NASA Discipline Space Human Factors↗

A high-granularity calorimeter insert based on SiPM-on-tile technology at the future Electron-Ion Collider

Herein we present a design for a high-granularity calorimeter insert for future experiments at the Electron-Ion Collider (EIC). The sampling-calorimeter design uses scintillator tiles read out with silicon photomultipliers. It maximizes coverage close to the beampipe, while solving challenges arising from the beam-crossing angle and mechanical integration. It yields a compensated response that is linear over the energy range of interest for the EIC. Its energy resolution meets the requirements set in the EIC Yellow Report even with a basic reconstruction algorithm. Moreover, this detector will provide 5D shower data (position, energy, and time), which can be exploited with machine-learning techniques. This detector concept has the potential to unleash the power of imaging calorimetry at the EIC to enable measurements at extreme kinematics in electron–proton and electron–nucleus collisions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Defect detection in atomic-resolution images via unsupervised learning with translational invariance

Abstract Crystallographic defects can now be routinely imaged at atomic resolution with aberration-corrected scanning transmission electron microscopy (STEM) at high speed, with the potential for vast volumes of data to be acquired in relatively short times or through autonomous experiments that can continue over very long periods. Automatic detection and classification of defects in the STEM images are needed in order to handle the data in an efficient way. However, like many other tasks related to object detection and identification in artificial intelligence, it is challenging to detect and identify defects from STEM images. Furthermore, it is difficult to deal with crystal structures that have many atoms and low symmetries. Previous methods used for defect detection and classification were based on supervised learning, which requires human-labeled data. In this work, we develop an approach for defect detection with unsupervised machine learning based on a one-class support vector machine (OCSVM). We introduce two schemes of image segmentation and data preprocessing, both of which involve taking the Patterson function of each segment as inputs. We demonstrate that this method can be applied to various defects, such as point and line defects in 2D materials and twin boundaries in 3D nanocrystals.

36 MATERIALS SCIENCE↗

Structural measurement of electron-phonon coupling and electronic thermal transport across a metal-semiconductor interface

Scattering of energetic charge carriers and their coupling to lattice vibrations (phonons) in dielectric materials and semiconductors are crucial processes that determine the functional limits of optoelectronics, photovoltaics, and photocatalysts. The strength of these energy exchanges is often described by the electron-phonon coupling coefficient, which is difficult to measure due to the microscopic time- and length-scales involved. In the present study, we propose an alternate means to quantify the coupling parameter along with thermal boundary resistance and electron conductivity by performing a high angular-resolution time-resolved X-ray diffraction measurement of propagating lattice deformation following laser excitation of a nanoscale, polycrystalline metal film on a semiconductor substrate. Our data present direct experimental evidence for identifying the ballistic and diffusive transport components occurring at the interface, where only the latter participates in thermal diffusion. This approach provides a robust measurement that can be applied to investigate microscopic energy transport in various solid-state materials.

36 MATERIALS SCIENCE↗

Bayesian High-Rank Hankel Matrix Completion for Nonlinear Synchrophasor Data Recovery

Phasor measurement units (PMUs) provide high temporal-resolution synchrophasor measurements for power system monitoring and control. The frequent data quality issues, such as missing and bad data, prevent the incorporation of synchrophasor data in real-time operations. Most existing data-driven data recovery methods assume the power system dynamics can be approximated by a linear dynamical system, and the recovery performance degrades significantly when the power system is experiencing nonlinear dynamics during significant events. Here, this paper proposes a data-driven Bayesian nonlinear synchrophasor data recovery method (Ba-NSDR) that can recover a consecutive time period of simultaneous data losses or errors across all channels, even when the underlying system is highly nonlinear. The idea is to lift the Hankel matrix of the spatial-temporal synchrophasor data to a higher dimension such that the lifted Hankel matrix is low-rank in that space and can be processed with the kernel trick. Our proposed Bayesian method then infers the probabilistic distributions of synchrophasor from the partial observations. Some distinctive features of Ba-NSDR include an uncertainty index to measure the accuracy of the recovery result and the robustness to parameter selections. Our method is verified on both synthetic and recorded event datasets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Genomic variation across Chinook salmon populations reveals effects of a duplication on migration alleles and supports fine scale structure

Abstract The distribution of ecotypic variation in natural populations is influenced by neutral and adaptive evolutionary forces that are challenging to disentangle. This study provides a high‐resolution portrait of genomic variation in Chinook salmon ( Oncorhynchus tshawytscha ) with emphasis on a region of major effect for ecotypic variation in migration timing. With a filtered data set of ~13 million single nucleotide polymorphisms (SNPs) from low‐coverage whole genome resequencing of 53 populations (3566 barcoded individuals), we contrasted patterns of genomic structure within and among major lineages and examined the extent of a selective sweep at a major effect region underlying migration timing (GREB1L/ROCK1). Neutral variation provided support for fine‐scale structure of populations, while allele frequency variation in GREB1L/ROCK1 was highly correlated with mean return timing for early and late migrating populations within each of the lineages ( r 2 = .58–.95; p < .001). However, the extent of selection within the genomic region controlling migration timing was much narrower in one lineage (interior stream‐type) compared to the other two major lineages, which corresponded to the breadth of phenotypic variation in migration timing observed among lineages. Evidence of a duplicated block within GREB1L/ROCK1 may be responsible for reduced recombination in this portion of the genome and contributes to phenotypic variation within and across lineages. Lastly, SNP positions across GREB1L/ROCK1 were assessed for their utility in discriminating migration timing among lineages, and we recommend multiple markers nearest the duplication to provide highest accuracy in conservation applications such as those that aim to protect early migrating Chinook salmon. These results highlight the need to investigate variation throughout the genome and the effects of structural variants on ecologically relevant phenotypic variation in natural species.

Horn, Rebekah L.↗

Fast and Accurate Intersections on a Sphere

We introduce a fast, high-precision algorithm for calculating intersections between great circle arcs and lines of constant latitude on the unit sphere. We first propose a simplified intersection point formula with improved speed and numerical robustness over the ones traditionally implemented in geoscience software. We then show how algorithms based on the concept of error-free transformations (EFT) can be applied to evaluate this formula within a relative error bound that is on the order of machine precision. Here, we demonstrate that, with a vectorized and parallelized implementation, this enhanced accuracy is achieved with no compute time overhead compared to a direct calculation in hardware floating point, making our algorithm suitable for performance-sensitive applications like regridding of high-resolution climate data. In contrast, evaluating our formula using high-precision data types like quadruple precision and arbitrary precision, or using the robust intersection computation routines from the Computational Geometry Algorithms Library, leads to significant computational overhead, especially since these alternatives inhibit vectorization. More generally, our work demonstrates how EFT techniques can be combined and extended to implement nontrivial geometric calculations with high accuracy and speed.

Environmental sciences↗

Extreme Scale Infrasound Inversion and Prediction for Weather Characterization and Acute Event Detection

Accurate and timely weather predictions are critical to many aspects of society with a profound impact on our economy, general well-being, and national security. In particular, our ability to forecast severe weather systems is necessary to avoid injuries and fatalities, but also important to minimize infrastructure damage and maximize mitigation strategies. The weather community has developed a range of sophisticated numerical models that are executed at various spatial and temporal scales in an attempt to issue global, regional, and local forecasts in pseudo real time. The accuracy however depends on the time period of the forecast, the nonlinearities of the dynamics, and the target spatial resolution. Significant uncertainties plague these predictions including errors in initial conditions, material properties, data, and model approximations. To address these shortcomings, a continuous data collection occurs at an effort level that is even larger than the modeling process. It has been demonstrated that the accuracy of the predictions depends on the quality of the data and is independent to a certain extent on the sophistication of the numerical models. Data assimilation has become one of the more critical steps in the overall weather prediction business and consequently substantial improvements in the quality of the data would have transformational benefits. This paper describes the use of infrasound inversion technology, enabled through exascale computing, that could potentially achieve orders of magnitude improvement in data quality and therefore transform weather predictions with significant impact on many aspects of our society.

58 GEOSCIENCES↗

The M.I.T. Ku-band radio interferometer.

The construction of a Ku-band radio interferometer and some preliminary observations are reported. The interferometer was built for the purpose of mapping discrete radio sources like the Crab Nebula, Cassiopeia A, and Cygnus A. It has two 8-ft parabolic antennas operating at 17.128 GHz. The maximum baseline of 100 m corresponds to a resolution of 35 sec of arc. A PDP-8 computer is incorporated in the system and is used for pointing, tracking, delay compensation, and real-time data analysis. The phase stability of the system was better than 10 deg over a period of 2 hours. Consistent fringe components were obtained from the Crab Nebula with a baseline set at 8 m.

Papadopoulos, G. D.↗

Uranian methane abundance, rotational temperature, and effective pressure from the 6800 A band

Measurements of the methane absorption features at 6800 A in two spectrograms of Uranus have been analyzed on the working hypothesis that the features are the R branch of the 5 mu(3) rotation-vibration overtone. Internal and external consistencies in temperature calculations from the measurements give increased confidence that the band identification and rotational-quantum-number assignments to band members are correct. Parametric fitting of synthetic reflecting-layer and homogeneous scattering-layer spectra to the spectrograms is attempted. The best-fit methane abundances, taken with recent estimates of the molecular hydrogen abundance, correspond to an average C:H ratio between 1.5 and 25 times larger than the solar ratio. Even greater enrichment of the C:H ratio may occur below the visible cloud boundary. High spectroscopic resolution of the present data permits direct measurement of the methane line halfwidth in Uranus's spectrum. The halfwidth corresponds to an effective pressure greater than 3 atm, depending on the mixture of atmospheric gases. Pressure in this range, at the methane rotational temperature of between 93 and 100 K, is inconsistent with current Uranus atmosphere models having solar elemental-abundance ratios. It is consistent with models which are considerably enriched in 'heavier' constituents.

Bergstralh, J. T.↗

Laser modulation of optical absorption in ZnSe

The possibility of producing and detecting laser induced modulation of absorption (LIMA) in ZnSe crystals using a moderate laser intensity of about 6 mw output was investigated. The modulation is smaller than that previously obtained with higher laser photon flux, but is not too difficult to detect. Modulation of the order of a few parts in 10 to the 5th power, up to one part in 10 to the 4th power appears typical at the present. LIMA pulse shapes were recorded with varying system resolutions at a half dozen wavelengths in the visible, from 4800 A to 6000 A. Detailed data were taken, particularly at 5000 A, for a range of time intervals following laser pulse turn-on. Quantitative study of the excitation and decay kinetics of these is underway, though analysis is not complete. Major features are discussed with attention centered upon the detailed measurements made most recently at 5000 A.

Major, R. W.↗

Application of image processing techniques to fluid flow data analysis

The application of color coding techniques used in processing remote sensing imagery to analyze and display fluid flow data is discussed. A minicomputer based color film recording and color CRT display system is described. High quality, high resolution images of two-dimensional data are produced on the film recorder. Three dimensional data, in large volume, are used to generate color motion pictures in which time is used to represent the third dimension. Several applications and examples are presented. System hardware and software is described.

Giamati, C. C.↗