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At least 163 records · Page 9

Earth resources data analysis program, phase 2

The efforts and findings of the Earth Resources Data Analysis Program are summarized. Results of a detailed study of the needs of EOD with respect to an applications development system (ADS) for the analysis of remotely sensed data, including an evaluation of four existing systems with respect to these needs are described. Recommendations as to possible courses for EOD to follow to obtain a viable ADS are presented. Algorithmic development comprised of several subtasks is discussed. These subtasks include the following: (1) two algorithms for multivariate density estimation; (2) a data smoothing algorithm; (3) a method for optimally estimating prior probabilities of unclassified data; and (4) further applications of the modified Cholesky decomposition in various calculations. Little effort was expended on task 3, however, two reports were reviewed.

Source record↗

Examining the Trends in Financial Support Given to Science Teams for Data Analysis in Mission Proposals

Introduction: The goal of this summer internship research project was to analyze trends in financial support proposed for the science teams of planetary missions. The analysis focuses on the funding for Co-Investigators (Co-Is) to conduct research and/or data analysis needed to achieve the science objectives of the mission. The operational portion of the missions after launch (i.e., Phase E, including cruise and prime operations at the final destination) were examined since that is when the bulk of research is funded and conducted. The objectives of the project were to determine the average level of support for Co-Investigators, identify variation between mission competitions and over time, and determine the relationship between mission type and the amount of support requested. Methodology: This project was conducted using data from 90 proposals submitted to six mission competitions in the Discovery and New Frontiers programs. The level of support for Co-Is was determined by examining Work Breakdown Structure (WBS) 4 (Science Analysis) for Phase E, which was further subdivided into cruise and prime operations. This data represents a proxy rather than the actual funding Co-Is receive to perform research and data analysis because not every dollar in WBS 4 is spent on this activity. Therefore, the proxy obtained in this research represents an overestimate of the funds allocated to Co-Is for research and data analysis. Findings: Analysis shows that on average a Co-I receives approximately four full years of support spread across the entirety of Phase E for science analysis. The variation among proposed missions is less than expected given the variety of factors that are expected to drive this metric (length of mission, mission type, etc.). Additionally, the level of requested support for Co-Is has been remarkably consistent across every variable considered (by competition, over time, by mission type) over the six competitions and nearly 20 years spanned by this project. This remains true for cruise, primary operations, and all of Phase E. Conclusions: A remarkable amount of science is accomplished by the science teams of planetary missions. However, a surprisingly small amount of funding is requested to support the science analysis driving this productivity, both in terms of absolute magnitude of funding and as a portion of total mission cost. This suggests improvements are needed to refine the estimates of Co-I support and/or that Co-Is rely on other funding sources to conduct their research. Better estimates can be determined by engaging directly with Co-Is and NASA centers to obtain data as well as finding other data sources. Additionally, NASA could consider mandating improved reporting of requested funding levels in mission competitions.

E Murray↗

LinkWinds: An Approach to Visual Data Analysis

The Linked Windows Interactive Data System (LinkWinds) is a prototype visual data exploration and analysis system resulting from a NASA/JPL program of research into graphical methods for rapidly accessing, displaying and analyzing large multivariate multidisciplinary datasets. It is an integrated multi-application execution environment allowing the dynamic interconnection of multiple windows containing visual displays and/or controls through a data-linking paradigm. This paradigm, which results in a system much like a graphical spreadsheet, is not only a powerful method for organizing large amounts of data for analysis, but provides a highly intuitive, easy to learn user interface on top of the traditional graphical user interface.

Jacobson, Allan S.↗

Phase 1 of the earth resources data analysis program

Research completed in the Earth Resources Data Analysis Program is discussed along with recommendations for future study. Projects discussed include use of the Cholesky decomposition in feature selection and classification algorithms; optimal feature selection and extraction, probability density estimation and nonparametric classifiers; use of spatial information in classification; and model for crop row reflectance. The installation of LARSYS on the ICSA's IBM 370/155 is discussed, and a list of technical reports is included.

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Hierarchical neural networks for autonomous data analysis and decision making

A neural network based data analysis and decision making system to increase the autonomy of a planetary rover or similar exploratory vehicle is presented. A hierarchical series of neural networks for real time analysis of scientific images is used. The system under development emphasizes analysis of multispectral images by classifier and feature detector neural networks, to provide information on the mineral composition of a scene. A hierarchy of alternating analysis and decision making networks is being developed to allow increasingly fine scale analysis in regions of the image that are potentially important. It is noted that this system will facilitate both the selection of high priorty scientific information for transmission to earth, and the autonomous collection of rocks and soil for sample return.

Eberlein, Susan↗

SEPAC data analysis in support of the environmental interaction program

Data analyses of the Space Experiments with Particle Accelerators (SEPAC) data and computer modeling were conducted to investigate spacecraft environmental effects associated with injection of electron beams, plasma clouds, and neutral gas clouds from the Shuttle orbiter. The data analysis indicates that Extremely Low Frequency oscillations from 150 to 200 Hz were seen in the Langmuir probe current when the beam was fired in a continuous mode. The strongest oscillations occurred when the ambient pressure was augmented by neutral gas releases from the SEPAC plasma accelerator magnetoplasma-dynamic (MPD) arcjet. To understand the dependence of spacecraft charging potential on beam density and other plasma parameters, a two-dimensional electrostatic particle code was used to simulate the injection of electron beams from an infinite conductor into a plasma. The simulations show that the conductor charging potential depends critically on the reflection coefficient of the conductor surface, which is defined as the percentage of incident particles reflected by the conductor. The ionization effects on spacecraft charging were examined by including interactions of electrons with neutral gas. The simulations show that the conductor charging potential decreases with increasing neutral background density due to the production of secondary electrons near the conductor surface. The simulations also indicate that the beam radius is generally proportional to the beam electron gyroradius when the conductor is charged to a large potential. It appears that the charge buildup at the beam stagnation point causes the beam radial expansion. A survey of the simulation results suggests that the ratio of the beam radius to the beam electron gyroradius increases with the square root of beam density and decreases inversely with beam injection velocity. These results are useful for explaining the spacecraft charging phenomena observed during SEPAC experiments from Spacelab 1.

Lin, Chin S.↗

A data analysis expert system for large established distributed databases

A design for a natural language database interface system, called the Deductively Augmented NASA Management Decision support System (DANMDS), is presented. The DANMDS system components have been chosen on the basis of the following considerations: maximal employment of the existing NASA IBM-PC computers and supporting software; local structuring and storing of external data via the entity-relationship model; a natural easy-to-use error-free database query language; user ability to alter query language vocabulary and data analysis heuristic; and significant artificial intelligence data analysis heuristic techniques that allow the system to become progressively and automatically more useful.

Gnacek, Anne-Marie↗

Pre/Post Data Analysis - Simple or Is It?

This slide presentation reviews some of the problems of data analysis in analyzing pre and post data. Using as an example, ankle extensor strength (AES) experiments, to measure bone density loss during bed rest, the presentation discusses several questions: (1) How should we describe change? (2) Common analysis methods for comparing post to pre results. (3) What do we mean by "% change"? and (4) What are we testing when we compare % changes?

Feiveson, Al↗

Features for a Modern Strain-Gage Balance Data Analysis Software Tool

Required, recommended, and optional features are discussed that benefit preparation and evaluation of the load prediction equations in a strain-gage balance data analysis tool. First, milestones in the evolution of load prediction methods are reviewed so that suggested features can be put into a historical context. Afterwards, independent and dependent variable choices for the balance data analysis are discussed. Then, it is illustrated how three different metrics may be used for the identification of the root cause of an unwanted divergence of the load iterations that may be observed during an iterative load prediction. Finally, a list of features is provided to guide software development efforts.

wind tunnel test↗

Estimating the Diffusion Coefficient of Lithium in Graphite: Extremely Fast Charging and a Comparison of Data Analysis Techniques

Galvanostatic intermittent titration experiments were performed in three-electrode cells to characterize the effect of C/2, 2-C and 4-C charge rates on the observed lithium diffusion coefficient. As part of the data analysis process, we compared the classic Weppner-Huggins analysis of polarization data with a newer (Wang et al.) analysis method for depolarization data. At low values of x in Li x C 6 , both analysis methods showed the same general trend in the apparent lithium diffusion coefficient, 4-C > 2-C > C/2. The two techniques differed in the magnitude of the estimated diffusion coefficient by about a factor of 100. The observed increase in diffusion coefficient does not last over a large compositional range. Since the estimates from the method of Weppner and Huggins may contain artifacts due to the use of particulate electrodes and high charge rates, the method of Wang et al. may produce better values.

25 ENERGY STORAGE↗

Status of MTP Data Analysis for TCSP

Topics covered include: a) MTP temperature calibration and data analysis; b) Background for interpreting MTP data; c) Large amplitude temperature structure; d) Gravity waves (GWs) in MTP data; and e) Subsidence over hurricanes.

hurricanes↗

Analysis of Uranian radio emissions, Uranus Data Analysis Program (UDAP)

Progress under this grant has included identifying certain new radio emission components and determining the source location of both these and the two major Uranian radio emission (the SHF and bursty components) by a unique new statistical minimization technique. This new source location technique has subsequently also been applied at Neptune, with considerable success. New radio spectrograms have been prepared to clarify the behavior of such emissions, using both the usual 48-second, log-averaged data and the original 6-second PRA data, the latter showing a number of interesting new features. Also, a plasmasphere was discovered at Uranus, auroral plasma cavities were discovered at both Uranus and Neptune, and it was found that the currently-accepted rotation period for Uranus is in error by a small amount.

Calvert, W.↗

Topological data analysis of task-based fMRI data from experiments on schizophrenia

We use methods from computational algebraic topology to study functional brain networks, in which nodes represent brain regions and weighted edges represent similarity of fMRI time series from each region. With these tools, which allow one to characterize topological invariants such as loops in high-dimensional data, we are able to gain understanding into low-dimensional structures in networks in a way that complements traditional approaches based on pairwise interactions. In the present paper, we analyze networks constructed from task-based fMRI data from schizophrenia patients, healthy controls, and healthy siblings of schizophrenia patients using persistent homology, which allows us to explore the persistence of topological structures such as loops at different scales in the networks. We use persistence landscapes, persistence images, and Betti curves to create output summaries from our persistent-homology calculations, and we study the persistence landscapes and images using k-means clustering and community detection. Based on our analysis of persistence landscapes, we find that the members of the sibling cohort have topological features (specifically, their 1-dimensional loops) that are distinct from the other two cohorts. From the persistence images, we are able to distinguish all three subject groups and to determine the brain regions in the loops (with four or more edges) that allow us to make these distinctions.

60 APPLIED LIFE SCIENCES↗