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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Malicious Cyber Activity Detection using Zigzag Persistence

In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity, and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from various forms of malicious attacks, including network damage, data theft, and activity monitoring. We focus on the cybersecurity domain and investigate the detection of malicious activity using log data. We consider the dynamics of the log data and explore the changing topology of a hypergraph representation of this data to gain insights into the underlying activity. These hypergraphs capture complex interactions between processes, together with their temporal information. To study the changing topology we use zigzag persistence, which captures how topological features persist at multiple dimensions over time. We observe that this detects malicious activity in a cyber data set. To automate this detection we implement an autoencoder trained on a vectorization of the resulting zigzag persistence barcodes. Our experimental results demonstrate the effectiveness of the autoencoder in detecting malicious activity. Overall, this study highlights the potential of zigzag persistence and its combination with temporal hypergraphs for analyzing cybersecurity log data and detecting malicious behavior.

hypergraphs, temporal hypergraph, topological data↗
NASA NTRS1998

Low Luminosity States of the Black Hole Candidate GX 339-4: ASCA and Simultaneous Radio/RXTE Observations - 1

We discuss a series of observations of the black hole candidate GX 339-4 in low luminosity, spectrally hard states. We present spectral analysis of three separate archival Advanced Satellite for Cosmology and Astrophysics (ASCA) data sets and eight separate Rossi X-ray Timing Explorer (RXTE) data sets. Three of the RXTE observations were strictly simultaneous with 843 Mega Hertz and 8.3-9.1 Giga Hertz radio observations. All of these observations have (3-9 keV) flux approximately less than 10(exp-9) ergs s(exp-1) CM(exp -2). The ASCA data show evidence for an approximately 6.4 keV Fe line with equivalent width approximately 40 eV, as well as evidence for a soft excess that is well-modeled by a power law plus a multicolor blackbody spectrum with peak temperature approximately equals 150-200 eV. The RXTE data sets also show evidence of an Fe line with equivalent widths approximately equal to 20-1OO eV. Reflection models show a hardening of the RXTE spectra with decreasing X-ray flux; however, these models do not exhibit evidence of a correlation between the photon index of the incident power law flux and the solid angle subtended by the reflector. 'Sphere+disk' Comptonization models and Advection Dominated Accretion Flow (ADAF) models also provide reasonable descriptions of the RXTE data. The former models yield coronal temperatures in the range 20-50 keV and optical depths of r approximately equal to 3. The model fits to the X-ray data, however, do not simultaneously explain the observed radio properties. The most likely source of the radio flux is synchrotron emission from an extended outflow of extent greater than O(10 (exp7) GM/c2).

Wilms, Joern↗
NASA NTRS2012

Giovanni: The Bridge between Data and Science

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a web-based remote sensing and model data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional data sets, covering atmospheric dynamics, atmospheric chemistry, hydrology, oceanographic, and land surface. Data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. Visualization options enable comparisons of multiple variables and easier refinement. Recently, new features have been developed, such as interactive scatter plots and maps. The performance is also being improved, in some cases by an order of magnitude for certain analysis functions with optimized software. We are working toward merging current Giovanni portals into a single omnibus portal with all variables in one (virtual) location to help users find a variable easily and enhance the intercomparison capability

Shen, Suhung↗
DOE OSTI2022

Transforming Energy Through Computational Excellence: Advanced Scientific Visualization Reveals Energy Insights

The National Renewable Energy Laboratory's world-class researchers and analysts, along with the Insight Center (our state-of-the-art scientific visualization facility) make data immersion a reality, allowing users to step into and explore their data. With the rise of large, diverse, and distributed data sets, scientific visualization is now critical to the process of scientific discovery and to managing and analyzing data and extracting insights. NREL provides visualization capabilities and facilities that are supported by state-of-the-art equipment, leading-edge techniques, and expert staff.

data science↗
NASA NTRS2007

Exploring NASA and ESA Atmospheric Data Using GIOVANNI, the Online Visualization and Analysis Tool

Giovanni, the NASA Goddard online visualization and analysis tool (http://giovanni.gsfc.nasa.gov) allows users explore various atmospheric phenomena without learning remote sensing data formats and downloading voluminous data. Using NASA MODIS (Terra and Aqua) and ESA MERIS (ENVISAT) aerosol data as an example, we demonstrate Giovanni usage for online multi-sensor remote sensing data comparison and analysis.

Leptoukh, Gregory↗
NASA NTRS1981

Data use investigations for applications Explorer Mission A (Heat Capacity Mapping Mission): HCMM's role in studies of the urban heat island, Great Lakes thermal phenomena and radiometric calibration of satellite data

The utility of data from NASA'a heat capacity mapping mission satellite for studies of the urban heat island, thermal phenomena in large lakes and radiometric calibration of satellite sensors was assessed. The data were found to be of significant value in all cases. Using HCMM data, the existence and microstructure of the heat island can be observed and associated with land cover within the urban complex. The formation and development of the thermal bar in the Great Lakes can be observed and quantitatively mapped using HCMM data. In addition, the thermal patterns observed can be associated with water quality variations observed both from other remote sensing platforms and in situ. The imaging radiometer on-board the HCMM satellite is shown to be calibratible to within about 1.1 C of actual surface temperatures. These findings, as well as the analytical procedures used in studying the HCMM data, are included.

Schott, J. R.↗
NASA NTRS1974

An evaluation of the suitability of ERTS data for the purposes of petroleum exploration

This investigation was undertaken to determine the types and amounts of information valuable to petroleum exploration that are extractable from ERTS data and to determine the cost of obtaining the information from ERTS relative to costs using traditional or conventional means. In particular, it was desirable to evaluate this new petroleum exploration tool in a geologically well-known area in order to assess its potential usefulness in an unknown area. In light of the current energy situation, it is felt that such an evaluation is important in order to best utilize technical efforts with customary exploration tools, by rapidly focusing attention on the most promising areas in order to reduce the time required to go through the exploration cycle and to maximize cost savings. The Anadarko Basin lies in western Oklahoma and the panhandle of Texas (Figure 1). It was chosen as a test site because there is a great deal of published information available on the surface and subsurface geology of the area, there are many known structures that act as traps for hydrocarbons, and it is similar to several other large epicontinental sedimentary basins.

Everett, J. R.↗
DOE OSTI2014

Using Historical and Experimental Data to Reveal Warming Effects on Ant Assemblages

Historical records of species are compared with current records to elucidate effects of recent climate change. However, confounding variables such as succession, land-use change, and species invasions make it difficult to demonstrate a causal link between changes in biota and changes in climate. Experiments that manipulate temperature can overcome this issue of attribution, but long-term impacts of warming are difficult to test directly. Here we combine historical and experimental data to explore effects of warming on ant assemblages in southeastern US. Observational data span a 35-year period (1976–2011), during which mean annual temperatures had an increasing trend. Mean summer temperatures in 2010–2011 were ~2.7°C warmer than in 1976. Experimental data come from an ongoing study in the same region, for which temperatures have been increased ~1.5–5.5°C above ambient from 2010 to 2012. Ant species richness and evenness decreased with warming under natural but not experimental warming. These discrepancies could have resulted from differences in timescales of warming, abiotic or biotic factors, or initial species pools. Species turnover tended to increase with temperature in observational and experimental datasets. At the species level, the observational and experimental datasets had four species in common, two of which exhibited consistent patterns between datasets. With natural and experimental warming, collections of the numerically dominant, thermophilic species, Crematogaster lineolata, increased roughly two-fold. Myrmecina americana, a relatively heat intolerant species, decreased with temperature in natural and experimental warming. In contrast, species in the Solenopsis molesta group did not show consistent responses to warming, and Temenothorax pergandei was rare across temperatures. Our results highlight the difficulty of interpreting community responses to warming based on historical records or experiments alone. Because some species showed consistent responses to warming based on thermal tolerances, understanding functional traits may prove useful in explaining responses of species to warming.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2018

Serving NASA GES DISC Multi-Spatiotemporal Earth Science Data to the GIS community

NASA Earth Science (ES) data is essential to a wide range of GIS research and applications. However, for many GIS users, searching, accessing, using and analyzing NASA ES data can be of a great challenge- ranging from the sheer data volumes, types of science parameters, and to the complexity of data encoding formats. As one of the twelve NASA Science Mission Directorate (SMD) Data Centers, Goddard Earth Sciences (GES) Data and Information Services Center (DISC) archives and distributes petabytes of ES parameters covering atmosphere, land, and ocean fields. Most data are multidimensional and multi-spatiotemporal in nature and are encoded in different science data formats (e.g, HDF, HDF-EOS, netCDF, GRIB, binary), which usually contain multiple variables and different metadata information. By far, GES DISC has been developing a number of services and online tools to help GIS users to easily explore our data products. In this presentation, we will describe our ArcGIS-based data accessing and visualization services and portals, which allow users directly exploring the multi-spatiotemporal ES data in ArcGIS clients without having to pre-download/import the data. The ArcGIS services are also compliant with the Open Geospatial Consortium (OGC) Web Coverage Service (WCS) and Web Map Service (WMS) protocols and can be accessed by any other WCS/WMS clients to get customized GES DISC EO data on-the-fly from such services.

Wei, Jennifer↗
NASA NTRS2008

Kinematic Slip Model for 12 May 2008 Wenchuan-Beichuan Mw 7.9 Earthquake from Joint Inversion of ALOS, Envisat, and Teleseismic Data

The presentations explores kinematics of the Wenchaun-Beichuan earthquake using data from ALOS, Envisat, and teleseismic recordings. Topics include geomorphic mapping, ALOS PALSAR range offsets, ALOS PALSAR interferometry, Envisat IM interferometry, Envisat ScanSAR, Joint GPS-InSAR inversion, and joint GPS-teleseismic inversion (static and kinematic).

seismology↗
DOE OSTI2014

Exercises in high-dimensional sampling: maximal poisson-disk sampling and k -d darts

In this paper, we review our recent progress on efficient algorithms for generating well-spaced samples of high dimensional data, and for exploring and characterizing these data, the underlying domain, and functions over the domain. To our knowledge, these techniques have not yet been applied to computational topology, but the possible connections are worth considering. In particular, computational topology problems often have difficulty in scaling efficiently, and these sampling techniques have the potential to drastically reduce the size of the data over which these computational topology algorithms must operate. Lastly, we summarize the definition of these sample distributions; algorithms for generating them in low, moderate, and high dimensions; and applications in mesh generation, rendering, motion planning and simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Nonproportionality of Scintillator Detectors. V. Comparing the Gamma and Electron Response

This paper is the fifth in a series of articles on the basic physics of light yield nonproportionality in scintillators. Here, we compare and contrast the nonproportionality as registered by gamma rays and high-energy electrons. As has been noted in the past, these two types of data have different curve shapes (for plots of the light yield against electron or gamma energy). Herein, we show how the experimental gamma nonproportionality curve can be calculated from the electron response by accounting for the distribution of high energy electrons created by the gamma photon via the photoelectric interaction. Similarly, we measure and model the gamma-induced resolution as a function of energy and compare this data to predictions from our model. The utility of the model is explored using data acquired with the scintillators SrI 2 (Eu), GYGAG(Ce) and CsI(Na).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Uncertainty-Informed Volume Visualization using Implicit Neural Representation

The increasing adoption of Deep Neural Networks (DNNs) has led to their application in many challenging scientific visualization tasks. While advanced DNNs offer impressive generalization capabilities, understanding factors such as model prediction quality, robustness, and uncertainty is crucial. These insights can enable domain scientists to make informed decisions about their data. However, DNNs inherently lack ability to estimate prediction uncertainty, necessitating new research to construct robust uncertainty-aware visualization techniques tailored for various visualization tasks. In this work, we propose uncertainty-aware implicit neural representations to model scalar field data sets effectively and comprehensively study the efficacy and benefits of estimated uncertainty information for volume visualization tasks. We evaluate the effectiveness of two principled deep uncertainty estimation techniques: (1) Deep Ensemble and (2) Monte Carlo Dropout (MC-Dropout). These techniques enable uncertainty-informed volume visualization in scalar field data sets. Our extensive exploration across multiple data sets demonstrates that uncertainty-aware models produce informative volume visualization results. Moreover, integrating prediction uncertainty enhances the trustworthiness of our DNN model, making it suitable for robustly analyzing and visualizing real-world scientific volumetric data sets.

Saklani, Shanu↗