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This paper describes how onboard data summarization will be used as part of an overall knowledge management approach for long duration JPL missions.
Hyperspectral imagers produce very large images, with each pixel recorded at hundreds or thousands of different wavelengths. The ability to automatically generate summaries of these data sets enables several important applications, such as quickly browsing through a large image repository or determining the best use of a limited bandwidth link (e.g., determining which images are most critical for full transmission). Clustering algorithms can be used to generate these summaries, but traditional clustering methods make decisions based only on the information contained in the data set. In contrast, we present a new method that additionally leverages existing spectral libraries to identify materials that are likely to be present in the image target area. We find that this approach simultaneously reduces runtime and produces summaries that are more relevant to science goals.
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The goal of the Astronaut Science Advisor (ASA) project is to improve the scientific return of experiments performed in space by providing astronaut experimenters with an 'intelligent assistant' that encapsulates much of the domain- and experiment-related knowledge commanded by the Principal Investigator (PI) on the ground. By using expert systems technology and the availability of flight-qualified personal computers, it is possible to encode the requisite knowledge and make it available to astronauts as they perform experiments in space. The system performs four major functions: diagnosis and troubleshooting of experiment apparatus, data collection, protocol management, and detection of interesting data. The experiment used for development of the system measures human adaptation to weightlessness in the context of the neurovestibular system. This so-called 'Rotating Dome' experiment was flown on the recent Spacelab Life Sciences One (SLS-1) Mission. This mission was used as an opportunity to test some of the system's functionality. Experiment data was downlinked from the orbiter, and the system then captured the data and analyzed it in real time. The system kept track of the time being used by the experiment, recognized occurrences of interesting data, summarized data statistically and generated potential new protocols that could be used to optimize the course of the experiment.
Summarized performance data are presented for the following major subsystems of the thematic mapper: the focal plane assembly, the radiative cooler, the radiative cooler door assembly, the top optical assembly, and the telescope assembly. Reference lists of the configurations status and of nonconforming material reports, failure reports, and requests for deviation/waiver are included.
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The interplanetary propagation aspects of the first X-class solar flare and coronal mass ejection are discussed. The solar data relevant to this event are summarized. Data from WIND and charge element and isotope analysis system (CELIAS) show solar wind plasma and interplanetary magnetic field disturbances early on 12 July 1996. It was observed that the extrapolation of the coronal mass ejection back to the flare time suggests a close association between them. Moreover, the coronal mass ejection speed is similar to the type two shock's speed. The results suggest that the coronal mass ejection is intimately related to the shock itself.
At the Goddard Distributed Active Archive Center, we have recently added a 35-Year record of output data from the North American Land Assimilation System (NLDAS) to the Giovanni web-based analysis and visualization tool. Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) offers a variety of data summarization and visualization to users that operate at the data center, obviating the need for users to download and read the data themselves for exploratory data analysis. However, the NLDAS data has proven surprisingly resistant to application of the summarization algorithms. Algorithms that were perfectly happy analyzing 15 years of daily satellite data encountered limitations both at the algorithm and system level for 35 years of hourly data. Failures arose, sometimes unexpectedly, from command line overflows, memory overflows, internal buffer overflows, and time-outs, among others. These serve as an early warning sign for the problems likely to be encountered by the general user community as they try to scale up to Big Data analytics. Indeed, it is likely that more users will seek to perform remote web-based analysis precisely to avoid the issues, or the need to reprogram around them. We will discuss approaches to mitigating the limitations and the implications for data systems serving the user communities that try to scale up their current techniques to analyze Big Data.
The data summarized describe single event upset (bit-flips) for 60 device types having data storage elements. The data are from 15 acceleration tests with both protons and heavier ions. Tables are included summarizing the upset threshold data and listing the devices tested for heavy ion induced bit-flip and the devices tested with protons. With regard to the proton data, it is noted that the data are often limited to one proton energy, since the tests were usually motivated by the engineering requirement of comparing similar candidate devices for a system. It is noted that many of the devices exhibited no upset for the given test conditions (the maximum fluence and the maximum proton energy Ep are given for these cases). It is believed, however, that some possibility of upset usually exists because there is a slight chance that the recoil atom may receive up to 10 to 20 MeV of recoil energy (with more energy at higher Ep).
Data from Argentine balloon flights made to investigate gamma ray emission from the galactic center are summarized. Data are also summarized from a Palestine, Texas balloon flight to measure gamma rays from NP 0532 and Crab Nebulae.
This paper summarizes data and findings from the first Aeroelastic Prediction Workshop (AePW) held in April, 2012. The workshop has been designed as a series of technical interchange meetings to assess the state of the art of computational methods for predicting unsteady flowfields and static and dynamic aeroelastic response. The goals are to provide an impartial forum to evaluate the effectiveness of existing computer codes and modeling techniques to simulate aeroelastic problems, and to identify computational and experimental areas needing additional research and development. For this initial workshop, three subject configurations have been chosen from existing wind tunnel data sets where there is pertinent experimental data available for comparison. Participant researchers analyzed one or more of the subject configurations and results from all of these computations were compared at the workshop. Keywords: Unsteady Aerodynamics, Aeroelasticity, Computational Fluid Dynamics, Transonic Flow, Separated Flow.
Ongoing efforts to define and model external magnetic field activities are summarized. Data were obtained and plotted for the five international quiet days of each month Magsat was in orbit. The values of the magnetic field at midnight were also plotted for each of the quiet days. Results show that the zero level of the field fluctuates over the time interval considered. Statistical studies were made for the Kp and Ap indices and more sunspot numbers were obtained for the Magsat period. Satellite data are being thinned and reformatted to make them more amenable to testing the Dst and Sq corrections. The software for processing Magsat tapes is being tested with intermediate attitude data.
The scientific and technological results obtained by an energetic particle spectrometer are summarized. Data on energetic electrons trapped in the Earth's radiation belt near synchronous altitude and on solar particles penetrating to this altitude are discussed.
The ISEE ULEWAT FLUX tapes contain ULEWAT and ISEE pool tape data summarized over relatively long time intervals (1hr) in order to compact the data set into an easily usable size. (Roughly 3 years of data fit onto one 1600 BPI 9-track magnetic tape). In making the tapes, corrections were made to the ULEWAT basic data tapes in order to, remove rate spikes and account for changes in instrument response so that to a large extent instrument fluxes can be calculated easily from the FLUX tapes without further consideration of instrument performance.
This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/ deviation so that further analysis can be directed and corrective actions followed.
This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/deviation so that further analysis can be directed and corrective actions followed.
This viewgraph presentation provides an overview of flight tests conducted on an aircraft turbulence detection radar system. Topics covered include: flight operations summary, radar data collection, baseline algorithm methodology, radar hazard tables and proposed alert criteria. Flight tests results are presented and summarized. Data analysis from these flight tests are also included.
The relationship between surface properties and echo characteristics, as determined by radar technology, is discussed; echo enhancement to reduce measurement uncertainty was included. Feasibility data, suggested baseline functional descriptions of various types of active microwave sensors, and examples of existing radar techniques are summarized. Data manage and measurement processes are also covered.