AND TREE computer data structures for supervisory control of manipulation
Supervisory controlled manipulation system for complex manipulation tasks on unmanned space vehicles using AND TREE computer data structure
Hardin, P. A.↗
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1235 Preparing for TEMPO: A Review of Planned Metadata, Data Structure, and Distribution by NASA’s Atmospheric Science Data Center
The Atmospheric Science Data Center (ASDC) is in the Science Directorate located at the NASA Langley Research Center (LaRC), in Hampton, Virginia. The ASDC is one of NASA’s Distributed Active Archive Centers (DAAC) and supports over 60 projects and provides access to more than 1,000 archived collections. These datasets were created from satellite measurements, field experiments, and modeled data products. ASDC projects focus on the following Earth science disciplines: Radiation Budget, Clouds, Aerosols, and Tropospheric Composition. The ASDC is the official Distributed Active Archive Center (DAAC) of record for the upcoming Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument.. The instrument will share a ride on a commercial satellite as a hosted payload and will be launched to an orbit about 22,000 miles above Earth's equator. The investigation will, for the first time, use a space-based instrument to make accurate observations of tropospheric pollution concentrations of ozone, nitrogen dioxide, formaldehyde, and aerosols with high resolution and frequency over the U.S, Canada, and Mexico.
Ashlee Autore↗
1235 Preparing for TEMPO: A Review of Planned Metadata, Data Structure, and Distribution by NASA’s Atmospheric Science Data Center
The Atmospheric Science Data Center (ASDC) is in the Science Directorate located at the NASA Langley Research Center (LaRC), in Hampton, Virginia. The ASDC is one of NASA’s Distributed Active Archive Centers (DAAC) and supports over 60 projects and provides access to more than 1,000 archived collections. These datasets were created from satellite measurements, field experiments, and modeled data products. ASDC projects focus on the following Earth science disciplines: Radiation Budget, Clouds, Aerosols, and Tropospheric Composition. The ASDC is the official Distributed Active Archive Center (DAAC) of record for the upcoming Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument.. The instrument will share a ride on a commercial satellite as a hosted payload and will be launched to an orbit about 22,000 miles above Earth's equator. The investigation will, for the first time, use a space-based instrument to make accurate observations of tropospheric pollution concentrations of ozone, nitrogen dioxide, formaldehyde, and aerosols with high resolution and frequency over the U.S, Canada, and Mexico.
Ashlee Autore↗
Generating a 2D Representation of a Complex Data Structure
A computer program, designed to assist in the development and debugging of other software, generates a two-dimensional (2D) representation of a possibly complex n-dimensional (where n is an integer >2) data structure or abstract rank-n object in that other software. The nature of the 2D representation is such that it can be displayed on a non-graphical output device and distributed by non-graphical means.
James, Mark↗
A data structure and algorithm for fault diagnosis
Results of preliminary research on the design of a knowledge based fault diagnosis system for use with on-orbit spacecraft such as the Hubble Space Telescope are presented. A candidate data structure and associated search algorithm from which the knowledge based system can evolve is discussed. This algorithmic approach will then be examined in view of its inability to diagnose certain common faults. From that critique, a design for the corresponding knowledge based system will be given.
Bosworth, Edward L., Jr.↗
Six-degree-of-freedom aircraft simulation with mixed-data structure using the applied dynamics simulation language, ADSIM
A realistic simulation of an aircraft in the flight using the AD 100 digital computer is presented. The implementation of three model features is specifically discussed: (1) a large aerodynamic data base (130,00 function values) which is evaluated using function interpolation to obtain the aerodynamic coefficients; (2) an option to trim the aircraft in longitudinal flight; and (3) a flight control system which includes a digital controller. Since the model includes a digital controller the simulation implements not only continuous time equations but also discrete time equations, thus the model has a mixed-data structure.
Savaglio, Clare↗
The growth of density perturbations in the last ~10 billion years from tomographic large-scale structure data
In order to investigate the origin of the ongoing tension between the amplitude of matter fluctuations measured by weak lensing experiments at low redshifts and the value inferred from the cosmic microwave background anisotropies, we reconstruct the evolution of this amplitude from z ~ 2 using existing large-scale structure data. To do so, we decouple the linear growth of density inhomogeneities from the background expansion, and constrain its redshift dependence making use of a combination of 6 different data sets, including cosmic shear, galaxy clustering and CMB lensing. We analyze these data under a consistent harmonic-space angular power spectrum-based pipeline. We show that current data constrain the amplitude of fluctuations mostly in the range 0.2 < z < 0.7, where it is lower than predicted by . This difference is mostly driven by current cosmic shear data, although the growth histories reconstructed from different data combinations are consistent with each other, and we find no evidence of systematic deviations in any particular experiment. In spite of the tension with , the data are well-described by the model, albeit with a lower value of S 8 ≡ σ 8 (Ω m /0.3) 0.5 . As part of our analysis, we find constraints on this parameter of S 8 = 0.7781 ± 0.0094 (68% confidence level), reaching almost percent-level errors comparable with CMB measurements, and 3.4σ away from the value found by .
79 ASTRONOMY AND ASTROPHYSICS↗
DGEN Aeropropulsion Research Turbofan Source-Diagnostic Test: Experimental Setup and Acoustic-Data Structure
The experimental setup of, and available data from a recent core/combustor-noise source-diagnostic test utilizing a small turbofan engine are described. The 2019 test campaign continued the investigation of the core/combustor-noise component of aircraft-propulsor noise begun in an earlier baseline test, but with a more extensive acoustic-instrumentation layout. The purpose of both tests was to better understand the impact on civilian-transport airport-community noise from turbofan-combustor sources and thereby to lay the foundation for improved noise-prediction methods and noise-mitigation techniques. Simultaneous high-data-rate acoustic measurements were obtained using a circumferential sensor array at the core nozzle exit in conjunction with sideline and farfield microphone arrays. The test matrix contained engine operational points from engine idle to maximum power and was repeated for different circumferential and sideline array configurations, as well as for redundancy. The extensive data set (up to 93 channels of data and various configurations) allows the application of advanced source-separation and phased-array methods to elucidate not only the core-noise structure, but also the propagation characteristics of other propulsion noise sources. The present report provides a detailed description of the different test points, their associated instrumentation layouts, and the structure of the acquired data set. Results from various data analyses are reported separately.
Aeroacoustics↗
Thematic Mapper Spectral Dimensionality and Data Structure
A simulated LANDSAT 4 TM and MSS data set, representing three crops over three growing seasons and a wide variety of soil types, was used to evaluate the structure of TM data and to compare its characteristics to those of MSS data. TM bands 2, 3, and 4, transformed to tasseled cap-like coordinates, provide an equivalent data space to MSS tasseled cap data, with greater dynamic range and no apparent loss of information resulting from the exclusion of the 0.9 to 1.1 micron region. Data from the six reflective TM bands (excluding the thermal band) primarily occupy two planes and a transition zone between them. The plane of vegetation is comparable to the MSS tasseled cap plane, while the plane of soils and transition zone provide a new dimension of information unavailable from the MSS. This added dimension offers promise of improved ability to determine the relative mix of vegetation and soil in the sensor field of view and to estimate soil moisture status. The improvement in spectral characteristics of the TM over the MSS, not to mention the greater spatial resolution, have resulted in a significant increase in the information content of the data.
Crist, E. P.↗
Enriched immersed finite element and isogeometric analysis: algorithms and data structures
Immersed finite element methods provide a convenient analysis framework for problems involving geometrically complex domains, such as those found in topology optimization and microstructures for engineered materials. However, their implementation remains a major challenge due to, among other things, the need to apply nontrivial stabilization schemes and generate custom quadrature rules. This article introduces the robust and computationally efficient algorithms and data structures comprising an immersed finite element preprocessing framework. The input to the preprocessor consists of a background mesh and one or more geometries defined on its domain. The output is structured into groups of elements with custom quadrature rules formatted such that common finite element assembly routines may be used without or with only minimal modifications. The key to the preprocessing framework is the construction of material topology information, concurrently with the generation of a quadrature rule, which is then used to perform enrichment and generate stabilization rules. While the algorithmic framework applies to a wide range of immersed finite element methods using different types of meshes, integration, and stabilization schemes, the preprocessor is presented within the context of the extended isogeometric analysis. This method utilizes a structured B-spline mesh, a generalized Heaviside enrichment strategy considering the material layout within individual basis functions’ supports, and face-oriented ghost stabilization. Using a set of examples, the effectiveness of the enrichment and stabilization strategies is demonstrated alongside the preprocessor’s robustness in geometric edge cases. Additionally, the performance and parallel scalability of the implementation are evaluated.
Computer implementation↗
cuTS: Scaling Subgraph Isomorphism on Distributed Multi-GPUSystems Using Trie Based Data Structure
Subgraph isomorphism is a pattern-matching algorithm widely used in many domains such as chem-informatics, bioinformatics, databases, and social network analysis. It is computationally expensive and is a proven NP-hard problem. The massive parallelism offered by the GPU hardware is well suited for solving the subgraph isomorphism. However, current GPU implementations are far from the achievable performance. Moreover, the enormous memory requirement of current approaches limits the problem size that can be handled. This work analyzes the fundamental challenges associated with processing the subgraph isomorphism on GPUs and develops an efficient GPU hardware-aware implementation. We also develop a new GPU-friendly trie-based data structure to drastically reduce the intermediate storage space requirement. Hence, our approach runs larger benchmarks than the competitors. We also develop the first distributed sub-graph isomorphism algorithm for GPUs. Our experimental evaluation section demonstrates the efficacy of our approach by comparing the execution time and number of cases that we can handle against the state-of-the-art GPU implementations.
Xiang, Lizhi↗
Comparison of two matrix data structures for advanced CSM testbed applications
The first section describes data storage schemes presently used by the Computational Structural Mechanics (CSM) testbed sparse matrix facilities and similar skyline (profile) matrix facilities. The second section contains a discussion of certain features required for the implementation of particular advanced CSM algorithms, and how these features might be incorporated into the data storage schemes described previously. The third section presents recommendations, based on the discussions of the prior sections, for directing future CSM testbed development to provide necessary matrix facilities for advanced algorithm implementation and use. The objective is to lend insight into the matrix structures discussed and to help explain the process of evaluating alternative matrix data structures and utilities for subsequent use in the CSM testbed.
Regelbrugge, M. E.↗
RCSB Protein Data Bank: Architectural Advances Towards Integrated Searching and Efficient Access to Macromolecular Structure Data from the PDB Archive
Not Available
59 BASIC BIOLOGICAL SCIENCES↗
Mapping Boreal Forest Spruce Beetle Health Status at the Individual Crown Scale Using Fused Spectral and Structural Data
The frequency and severity of spruce bark beetle outbreaks are increasing in boreal forests leading to widespread tree mortality and fuel conditions promoting extreme wildfire. Detection of beetle infestation is a forest health monitoring (FHM) priority but is hampered by the challenges of detecting early stage (“green”) attack from the air. There is indication that green stage might be detected from vertical gradients of spectral data or from shortwave infrared information distributed within a single crown. To evaluate the efficacy of discriminating “non-infested”, “green”, and “dead” health statuses at the landscape scale in Alaska, USA, this study conducted spectral and structural fusion of data from: (1) Unoccupied aerial vehicle (UAV) multispectral (6 cm) + structure from motion point clouds (~700 pts per sq. m); and (2) Goddard Lidar Hyperspectral Thermal (G-LiHT) hyperspectral (400 to 1000 nm, 0.5 m) + SWIR-band lidar (~32 pts per sq.m). We achieved 78% accuracy for all three health statuses using spectral + structural fusion from either UAV or G-LiHT and 97% accuracy for non-infested/dead using G-LiHT. We confirm that UAV 3D spectral (e.g., greenness above versus below median height in crown) and lidar apparent reflectance metrics (e.g., mean reflectance at 99th percentile height in crown), are of high value, perhaps capturing the vertical gradient of needle degradation. In most classification exercises, UAV accuracy was lower than G-LiHT indicating that collecting ultra-high spatial resolution data might be less important than high spectral resolution information. While the value of passive optical spectral information was largely confined to the discrimination of non-infested versus dead crowns, G-LiHT hyperspectral band selection (~400, 675, 755, and 940 nm) could inform future FHM mission planning regarding optimal wavelengths for this task. Interestingly, the selected regions mostly did not align with the band designations for our UAV multispectral data but do correspond to, e.g., Sentinel-2 red edge bands, suggesting a path forward for moderate scale bark beetle detection when paired with suitable structural data.
Janice Cessna↗
What's the gap? A possible strategy for advancing theory, and an appeal for experimental structure data to drive that advance
Strong correlation between electronic structure and geometry might be capitalized upon to tune the DFT functional.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Design and data structure - FORMAC organization in retrospect
Investigating interaction between FORMAC data organization and algorithm design
Marks, P.↗
Universally Accessible Structural Data on Macromolecular Conformation, Assembly, and Dynamics by Small Angle X-Ray Scattering for DNA Repair Insights.
Structures provide a critical breakthrough step for biological analyses, and small angle X-ray scattering (SAXS) is a powerful structural technique to study dynamic DNA repair proteins. As toxic and mutagenic repair intermediates need to be prevented from inadvertently harming the cell, DNA repair proteins often chaperone these intermediates through dynamic conformations, coordinated assemblies, and allosteric regulation. By measuring structural conformations in solution for both proteins, DNA, RNA, and their complexes, SAXS provides insight into initial DNA damage recognition, mechanisms for validation of their substrate, and pathway regulation. Here, we describe exemplary SAXS analyses of a DNA damage response protein spanning from what can be derived directly from the data to obtaining super resolution through the use of SAXS selection of atomic models. We outline strategies and tactics for practical SAXS data collection and analysis. Making these structural experiments in reach of any basic and clinical researchers who have protein, SAXS data can readily be collected at government-funded synchrotrons, typically at no cost for academic researchers. In addition to discussing how SAXS complements and enhances cryo-electron microscopy, X-ray crystallography, NMR, and computational modeling, we furthermore discuss taking advantage of recent advances in protein structure prediction in combination with SAXS analysis.
Chinnam, Naga Babu↗
Temperature Uncertainty Modeling with Proxy Structural Data as Geostatistical Constraints for Well Siting: An Example Applied to Granite Springs Valley, NV, USA
Utilizing existing temperature and structural information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aim of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations . The data used to support the modeling are measured temperatures and structural proxies from 3D geologic modeling, the latter considered "secondary" data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally likely temperature models (i.e., realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: Vprior and entropy. Vprior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e., linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g., dilation versus distance to fault termination) should be used given the specific geothermal system. In general, Vprior from local varying mean results identify locations that are close to high values for the structural proxies: areas with highe r probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comp arison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.
3D temperature modeling↗