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Data concerning a multidisciplinary and multi-organizational effort to implement multispectral data analysis algorithms on a revolutionary computer, the Illiac 4, are reported. The effectiveness and efficiency of implementing the digital multispectral data analysis techniques for producing useful land use classifications from satellite collected data were demonstrated.
Data were obtained on the trace- and major-element compositions of 16 Antarctic abnormal eucrites, many of which exhibiting positive (but sometimes negative) Ce anomalies, positive Eu anomalies, and low abundances of the remainder of the REEs. The results of data analysis suggest that the unusual REE patterns of abnormal Antarctic eucrites arise from weathering effects generated in or on the Antarctic ice. The suggested scenario involves the formation of melt water and its equilibration with the atmosphere, promoting the dissolution of REE-rich phosphates and the oxidation of Ce. As a result, tetravalent Ce is fractionated from the trivalent REE in solution.
Data are presented showing that calc-alkaline high-K ignimbrites from the Altiplano-Puna Volcanic Complex of the Central Volcanic Zone of the Andes, showing a variety of compositional zonations. The characteristics of the juvenile material from the zoned and heterogenous ignimbrites suggest that crystallization of the observed phenocrysts occurred in prezoned magma chambers consisting of two or more layers. It is suggested that the width/height ratio of a magma chamber plays a critical role in the control of the style of zonation that may develop in a closed magma chamber.
Data from the TIMAS ion mass spectrometer on the Polar satellite, covering 15 ev/e to 33 keV/e in energy and essentially 4(pi) in view angles, are used to investigate the properties of earthward (sunward) field-aligned flows of ions, especially protons, in the plasma sheet-lobe transition region near local midnight. A total of 142 crossings of this region are analyzed at 12-sec time resolution, all in the northern hemisphere, at R(SM) approx. 4 - 7 R(sub E), and most (106) in the poleward (sunward) direction. Earthward proton flows are prominent in this transition region (greater than 50% of the time), typically appearing as sudden "blasts" with the most energetic protons (approx. 33 keV) arriving first with weak flux, followed by protons of decreasing energy and increasing flux until either: (1) a new "blast" appears, (2) the flux ends at a sharp boundary, or (3) the flux fades away within a few minutes as the mean energy drops to a few keV. Frequent step-like changes (less than 12 sec) of the flux suggest that perpendicular gradients on the scale of proton gyroradii are common. Peak flux is similar to central plasma sheet proton flux (10(exp 5) - 10(exp 6)/[cq cm sr sec keV/e] and usually occurs at E approx. 4 - 12 keV. Only the initial phase of each "blast" (approx. 1 min) displays pronounced field-alignment of the proton velocity distribution, consistent with the time-of-flight separation of a more or less isotropic source distribution with df/d(nu) less than 0. The dispersive signatures are often consistent with a source at R(SM) less than or equal to 30 R(sub E). No systematic latitudinal velocity dispersion is found, implying that the equatorial plasma source is itself convecting. In short, the proton "blasts" appear as sudden local expansions of central plasma sheet particles along reconfigured ("dipolarized") magnetic field lines.
Comparison of FPS-16 and GMD-1 radar tracking and radiosonde measurements and methods for processing wind data - time variability of atmospheric parameters
A transmission X-ray microscope (TXM) can investigate morphological and chemical information of a tens to hundred micrometre-thick specimen on a length scale of tens to hundreds of nanometres. It has broad applications in material sciences and battery research. TXM data processing is composed of multiple steps. A workflow software has been developed that integrates all the tools required for general TXM data processing and visualization. The software is written in Python and has a graphic user interface in Jupyter Notebook . Users have access to the intermediate analysis results within Jupyter Notebook and have options to insert extra data processing steps in addition to those that are integrated in the software. The software seamlessly integrates ImageJ as its primary image viewer, providing rich image visualization and processing routines. As a guide for users, several TXM specific data analysis issues and examples are also presented.
A telemetry data processing system was defined of the Data Reduction. Data reduction activities in support of the developmental flights of the Space Shuttle were used as references against which requirements are assessed in general terms. A conceptual system design believed to offer significant throughput for the anticipated types of data reduction activities is presented. The design identifies the use of a large, intermediate data store as a key element in a complex of high speed, single purpose processors, each of which performs predesignated, repetitive operations on either raw or partially processed data. The recommended approach to implement the design concept is to adopt an established interface standard and rely heavily on mature or promising technologies which are considered main stream of the integrated circuit industry. The design system concept, is believed to be implementable without reliance on exotic devices and/or operational procedures. Numerical methods were employed to examine the feasibility of digital discrimination of FDM composite signals, and of eliminating line frequency noises in data measurements.
The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges.
Many distributed applications implement complex data flows and need a flexible mechanism for routing data between producers and consumers. Recent advances in programmable network interface cards, or SmartNICs, represent an opportunity to offload data-flow tasks into the network fabric, thereby freeing the hosts to perform other work. System architects in this space face multiple questions about the best way to leverage SmartNICs as processing elements in data flows. In this paper, we advocate the use of Apache Arrow as a foundation for implementing data-flow tasks on SmartNICs. We report on our experiences adapting a partitioning algorithm for particle data to Apache Arrow and measure the on-card processing performance for the BlueField-2 SmartNIC. Our experiments confirm that the BlueField-2’s (de)compression hardware can have a significant impact on in-transit workflows where data must be unpacked, processed, and repacked.
Edge computing aims to address the challenges associated with communicating and transferring large amounts of data generated remotely to a data center in a timely and efficient manner. A central pillar of edge computing is local (i.e., at- or near-source) data processing capability so that data transfer to a data center for processing can be minimized. Data compression at the edge is therefore a natural component of edge workflows. Here we present a survey of data compression algorithms with a focus on edge computing. Not all compression algorithms can accommodate the data type heterogeneity, tight processing and communication time constraints, or energy efficiency requirement characteristics of edge computing. We discuss specific examples of compression algorithms that are being explored in the context of edge computing. We end our review with a brief survey of emerging quantum compression techniques that are of importance in quantum information processing, including the proposed concept of quantum edge computing.
SpaceCube is a family of Field Programmable Gate Array (FPGA) based on-board science data processing systems developed at the NASA Goddard Space Flight Center (GSFC). The goal of the SpaceCube program is to provide 10x to 100x improvements in on-board computing power while lowering relative power consumption and cost. SpaceCube is based on the Xilinx Virtex family of FPGAs, which include processor, FPGA logic and digital signal processing (DSP) resources. These processing elements are leveraged to produce a hybrid science data processing platform that accelerates the execution of algorithms by distributing computational functions to the most suitable elements. This approach enables the implementation of complex on-board functions that were previously limited to ground based systems, such as on-board product generation, data reduction, calibration, classification, eventfeature detection, data mining and real-time autonomous operations. The system is fully reconfigurable in flight, including data parameters, software and FPGA logic, through either ground commanding or autonomously in response to detected eventsfeatures in the instrument data stream.
Recent advances in image processing and new applications are presented to the user community to stimulate the development and transfer of this technology to industrial and commercial applications. The Proceedings contains 37 papers and abstracts, including many illustrations (some in color) and provides a single reference source for the user community regarding the ordering and obtaining of NASA-developed image-processing software and science data.
The Continuous Stellar Tracking Attitude Reference (CSTAR) system is an in-house project for Space Station to provide high accuracy, drift free attitude and angular rate information for the GN&C system. The outputs of the solid state star trackers are processed to provide attitude information; rate data is then derived from the attitude. Rate derivation is based on discrete time polynomial approximation techniques. This gives simple algorithms which allow for interpolation by other users. Attitude rate is modeled as a constant with low amplitude, low frequency sinusoids superimposed. The rate processor is parameterized to account for the effects of random errors, sample rate, data processing rate and perturbation frequency. The baseline system may be characterized as follows: the three sigma attitude accuracy is 0.01 degrees, the three sigma rate accuracy is 0.0001 degrees per second, the sample rate is 100 Hertz, the sampled signal is bandlimited to 0.5 Hertz, and the data processing rate is 10 Hertz. The above system requires a differentiator of length 127. This will track rate perturbations of frequencies less than 0.01 Hertz with low systematic errors.
Background information and exercises are provided to: (1) establish or expand understanding of the concepts, methods, and terminology of computer processing of image producing data; (2) develop insight into the advantages of computer based image processing compared with the photointerpretation approach for processing, classifying, interpreting, and applying remote sensing data; (3) foster a broad perspective on the principal of the main techniques for image enhancement, pattern recognition, and thematic classification; (4) appreciate the pros and cons of batch and interactive modes of image analysis; (5) examine and evaluate some specific computer generated products for subscenes in Pennsylvania and New Jersey; and (6) interrelate these particular examples of output with more theoretical explanations of computer processing strategies and procedures.
We present DEIMoS: Data Extraction for Integrated Multidimensional Spectrometry, a Python application programming interface and command-line tool for high-dimensional mass spectrometry data analysis workflows, offering ease of development and access to efficient algorithmic implementations. Functionality includes feature detection, feature alignment, collision cross section calibration, isotope detection, and MS/MS spectral deconvolution, with the output comprising detected features aligned across study samples and characterized by mass, CCS, tandem mass spectra, and isotopic signature. Notably, DEIMoS operates on N-dimensional data, largely agnostic to acquisition instrumentation: algorithm implementations utilize all dimensions simultaneously to (i) offer greater separation between features, improving detection sensitivity, (ii) increase alignment/feature matching confidence among datasets, and (iii) mitigate convolution artifacts in tandem mass spectra. We demonstrate DEIMoS with LC-IMS-MS/MS data, demonstrating the advantages of a multidimensional approach in each data processing step.
Techniques are described for preprocessing raw return waveform data from the GEOS-3 radar altimeter. Topics discussed include: (1) general altimeter data preprocessing to be done at the GEOS-3 Data Processing Center to correct altimeter waveform data for temperature calibrations, to convert between engineering and final data units and to convert telemetered parameter quantities to more appropriate final data distribution values: (2) time "tagging" of altimeter return waveform data quantities to compensate for various delays, misalignments and calculational intervals; (3) data processing procedures for use in estimating spacecraft attitude from altimeter waveform sampling gates; and (4) feasibility of use of a ground-based reflector or transponder to obtain in-flight calibration information on GEOS-3 altimeter performance.
Procedures used to map residential land cover on the Orlando, Florida, Urban fringe zone are detailed. The NASA Bureau of the Census Applications Systems Verification and Transfer project and the test site are described as well as the LANDSAT data used as the land cover information sources. Both single-date LANDSAT data processing and multitemporal principal components LANDSAT data processing are described. A summary of significant findings is included.
Computer programming, data processing, and a correlation study that employed data collected in the first phase test were used to demonstrate that standard test procedures and equipment could be used to collect a significant number of transfer functions from tests of the Lunar Module test article LTA-11. The testing consisted of suspending the vehicle from the apex fittings of the outrigger trusses through a set of air springs to simulate the free-free state. Impulsive loadings were delivered, one at a time, at each of the landing gear's attachment points, in three mutually perpendicular directions; thus a total of 36 impulses were applied to the vehicle. Time histories of each pulse were recorded on magnetic tape along with 40 channels of strain gage response and 28 channels of accelerometer response. Since an automated data processing system was not available, oscillograph playbacks were made of all 2400 time histories as a check on the validity of the data taken. In addition, one channel of instrumentation was processed to determine its response to a set of forcing functions from a prior LTA-11 drop test. This prediction was compared with drop test results as a first measure of accuracy.