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At least 739 records · Page 41

An On-line Technology Information System (OTIS) for Advanced Life Support

OTIS is an on-line communication platform designed for smooth flow of technology information between advanced life support (ALS) technology developers, researchers, system analysts, and managers. With pathways for efficient transfer of information, several improvements in the ALS Program will result. With OTIS, it will be possible to provide programmatic information for technology developers and researchers, technical information for analysts, and managerial decision support. OTIS is a platform that enables the effective research, development, and delivery of complex systems for life support. An electronic data collection form has been developed for the solid waste element, drafted by the Solid Waste Working Group. Forms for other elements (air revitalization, water recovery, food processing, biomass production and thermal control) will also be developed, based on lessons learned from the development of the solid waste form. All forms will be developed by consultation with other working groups, comprised of experts in the area of interest. Forms will be converted to an on-line data collection interface that technology developers will use to transfer information into OTIS. Funded technology developers will log in to OTIS annually to complete the element- specific forms for their technology. The type and amount of information requested expands as the technology readiness level (TRL) increases. The completed forms will feed into a regularly updated and maintained database that will store technology information and allow for database searching. To ensure confidentiality of proprietary information, security permissions will be customized for each user. Principal investigators of a project will be able to designate certain data as proprietary and only technical monitors of a task, ALS Management, and the principal investigator will have the ability to view this information. The typical OTIS user will be able to read all non-proprietary information about all projects.Interaction with the database will occur over encrypted connections, and data will be stored on the server in an encrypted form. Implementation of OTIS will initiate a community-accessible repository of technology development information. With OTIS, ALS element leads and managers will be able to carry out informed technology selection for programmatic decisions. OTIS will also allow analysts to make accurate evaluations of technology options. Additionally, the range and specificity of information solicited will help educate technology developers of program needs. With augmentation, OTIS reporting is capable of replacing the current fiscal year-end reporting process. Overall, the system will enable more informed R&TD decisions and more rapid attainment of ALS Program goals.

Levri, Julie A.↗

Deep nonparametric estimation of intrinsic data structures by chart autoencoders: Generalization error and robustness

Autoencoders have demonstrated remarkable success in learning low-dimensional latent features of high-dimensional data across various applications. Assuming that data are sampled near a low-dimensional manifold, we employ chart autoencoders, which encode data into low-dimensional latent features on a collection of charts, preserving the topology and geometry of the data manifold. Our paper establishes statistical guarantees on the generalization error of chart autoencoders, and we demonstrate their denoising capabilities by considering n noisy training samples, along with their noise-free counterparts, on a d-dimensional manifold. By training autoencoders, we show that chart autoencoders can effectively denoise the input data with normal noise. We prove that, under proper network architectures, chart autoencoders achieve a squared generalization error in the order of n–$\frac{2}{d+2}$log 4 n, which depends on the intrinsic dimension of the manifold and only weakly depends on the ambient dimension and noise level. We further extend our theory on data with noise containing both normal and tangential components, where chart autoencoders still exhibit a denoising effect for the normal component. As a special case, our theory also applies to classical autoencoders, as long as the data manifold has a global parametrization. Furthermore, our results provide a solid theoretical foundation for the effectiveness of autoencoders, which is further validated through several numerical experiments.

97 MATHEMATICS AND COMPUTING↗

eBPF Community ID Calculation

The code titled “eBPF Community ID Calculation” allows easy correlation of monitoring logs with existing network forensics logs on high-performance computing (HPC) systems. This code implements the Community ID Flow Hashing standard to calculate community ID Flow identifiers. These identifiers will be used to correlate host forensics logs with network forensics logs. The correlation provides valuable insight and the ability to easily pivot between disparate data sources. The computer code removes the libpcap dependency from the code base.

Maerz, StefanA↗

Mauka Energy FEVER Tool Dataset

Mauka Energy’s dataset, developed under the Forestry Electric Vehicle Energy Routing (FEVER) project and funded by the U.S. Department of Energy’s Small Business Innovation Research program, is a high-resolution geospatial resource designed to support energy modeling for electric log trucks in complex forestry environments. The dataset integrates detailed spatial and road network data to enable accurate simulation of vehicle performance across varied terrain. At its core, the dataset incorporates lidar-derived elevation models, road alignments, and surface classifications from Oregon State University’s McDonald-Dunn Research Forest. These data capture fine-scale variations in slope, curvature, and surface conditions across forest road systems, allowing for vehicle-level analysis of energy consumption and recovery. The dataset also includes data collected on the surrounding public and private road networks in Benton County, Oregon, used in real-world haul routes. These connecting segments provide critical context for modeling transitions between forest operations and regional transportation infrastructure, incorporating attributes such as grade profiles, elevation change, and speed constraints. This combined dataset underpins the development of Mauka Energy’s rolldown tool, which quantifies energy use and regenerative braking potential on downhill and variable-grade segments. By leveraging high-resolution terrain and road data, the FEVER project enables more accurate assessment of electric vehicle feasibility and performance in forestry applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Beta-Gamma Data Viewer v2.2.34 User's Manual

This document provides an overview, and procedures, for operating the beta-gamma data viewer for 7 regions of interest (7 ROI) data. The Beta-Gamma 7 ROI Data Viewer is a set of software tools that allow for viewing and analysis of IMS 2.0 Pulse Height Data (PHD) / Pulse Beta Gamma (PBG) files, state of health (SoH) files, and event log files. This is an upgrade from previous release of the tool that includes calibration tools.

97 MATHEMATICS AND COMPUTING↗

The k-space formulation of the n-dimensional scattering problem

The n-dimensional scattering problem is solved by means of a k-space formulation of the field equations, thereby replacing the conventional integral equation formulation by a set of two algebraic equations in two unknowns in two spaces (the constitutive equation being an algebraic equation in x-space). These equations are solved by an iterative method with the aid of the fast Fourier transform (FFT) algorithm connecting the two spaces, requiring very simple initial approximations. Since algebraic and FFT equations are used, the number of arithmetic multiple-add operations and storage allocations required for a numerical solution are reduced from the order of N sq (for solving the matrix equations resulting from the conventional integral equations) to the order of N(log base 2 of N) and N, respectively (where N is the number of data points required for the specification of the problem). The advantage gained in speed and storage is thus of the order of N/log base 2 of N and N, respectively. This method is thus considerably more efficient than the conventional matrix method, and permits exact numerical solutions for much larger problems. Arguments are presented toward the view that the field equations are more fundamental in k-space. The details and some numerical results of the application of this method to the three-dimensional electromagnetic scattering problems are presented as an example.

Bojarski, N. N.↗

Tolerance bounds for log gamma regression models

The present procedure for finding lower confidence bounds for the quantiles of Weibull populations, on the basis of the solution of a quadratic equation, is more accurate than current Monte Carlo tables and extends to any location-scale family. It is shown that this method is accurate for all members of the log gamma(K) family, where K = 1/2 to infinity, and works well for censored data, while also extending to regression data. An even more accurate procedure involving an approximation to the Lawless (1982) conditional procedure, with numerical integrations whose tables are independent of the data, is also presented. These methods are applied to the case of failure strengths of ceramic specimens from each of three billets of Si3N4, which have undergone flexural strength testing.

Jones, R. A.↗

Optical region elemental abundance analyses of B and A stars. IV - Re-evaluation with new critically compiled Fe II oscillator strengths and improved estimates of the damping constants

A new critical compilation of Fe II f-values has recently been completed by Martin et al. To see how these values affect the derived stellar abundances both directly in changing the values of log Fe/H for individual lines and through the determination of the microturbulent velocities, the data for 11 (six normal and five slightly peculiar) sharp-lined B and A stars have been reanalyzed. At the same time, the choice of line damping constants has been investigated, especially for Fe I and Fe II lines.

Adelman, S. J.↗

Locating subsurface gravel with thermal imagery

A method was discussed for using 6 band thermal imagery to locate subsurface gravel deposits in vegetated areas. Geologic history is reviewed to select potential areas of study. An overflight was made using a thermal scanner. The data were processed with a computerized system to delineate areas showing a quartz signature radiated by a gravel deposit. The method was developed during a search for gravel on National Forest land in Louisiana. Processed data from thermal imagery was compared with known gravel deposits and exploratory drill hole logs. A high correlation was noted for a wide range of deposits, from commercial pits to trace deposits only a foot thick. Overburden at these sites varied from zero to sixty feet, near the maximum annual penetration by the thermal wave. It was concluded that the method can be used to locate buried gravel deposits and that more time and effort are needed to verify the usefulness for developing gravel pits adjacent to proposed construction sites.

Scholen, Douglas E.↗

Orbital debris and meteoroid population as estimated from LDEF impact data

Examination of LDEF's various surfaces shows numerous craters and holes due to hypervelocity impacts of meteoroids and man-made orbital debris. In this paper, the crater numbers as reported by Humes have been analyzed in an effort to understand the orbital debris and natural meteoroid environment in LEO. To determine the fraction of man-made to natural impacts, the side to top ratio of impacts and results of the Chemistry of Micrometeoroids Experiment are used. For craters in the 100 micron to 500 micron size range, about 25 percent to 30 percent of the impacts on the forward-facing surfaces and about 10 percent of the impacts on the trailing surfaces were estimated due to man-made orbital debris. A technique has been developed to convert crater numbers to particle fluxes, taking the fact into account that the distributions of impact velocity and incidence angle vary over the different surfaces of LDEF, as well as the ratio of the surface area flux to the cross-sectional area flux. Applying this technique, Humes' data concerning craters with limiting lip diameters of 100 micron, 200 micron and 500 micron have been converted into orbital debris and meteoroid fluxes ranging from about 20 micron to 200 micron particle diameter. The results exhibit good agreement with orbital debris model and meteoroid model. The converted meteoroid flux is slightly larger than Grun's model (by 40 to 70 percent). The converted orbital debris flux is slightly lower than Kessler's model for particle diameter smaller than about 30 micron and slightly larger than the model for particle diameter larger than about 40 micron. Taking also into account the IDE data point at about 0.8 micron particle diameter, it suggests to change the slope log (flux) versus log (diameter) of orbital debris flux in the 1 micron to 100 micron particle diameter range from 2.5 to 1.9.

Zhang, Jingchang↗

Improved Discrete Approximation of Laplacian of Gaussian

An improved method of computing a discrete approximation of the Laplacian of a Gaussian convolution of an image has been devised. The primary advantage of the method is that without substantially degrading the accuracy of the end result, it reduces the amount of information that must be processed and thus reduces the amount of circuitry needed to perform the Laplacian-of- Gaussian (LOG) operation. Some background information is necessary to place the method in context. The method is intended for application to the LOG part of a process of real-time digital filtering of digitized video data that represent brightnesses in pixels in a square array. The particular filtering process of interest is one that converts pixel brightnesses to binary form, thereby reducing the amount of information that must be performed in subsequent correlation processing (e.g., correlations between images in a stereoscopic pair for determining distances or correlations between successive frames of the same image for detecting motions). The Laplacian is often included in the filtering process because it emphasizes edges and textures, while the Gaussian is often included because it smooths out noise that might not be consistent between left and right images or between successive frames of the same image.

Shuler, Robert L., Jr.↗

Leveraging History to Predict Infrequent Abnormal Transfers in Distributed Workflows

Scientific computing heavily relies on data shared by the community, especially in distributed data-intensive applications. This research focuses on predicting slow connections that create bottlenecks in distributed workflows. In this study, we analyze network traffic logs collected between January 2021 and August 2022 at the National Energy Research Scientific Computing Center (NERSC). Based on the observed patterns, we define a set of features primarily based on history for identifying low-performing data transfers. Typically, there are far fewer slow connections on well-maintained networks, which creates difficulty in learning to identify these abnormally slow connections from the normal ones. We devise several stratified sampling techniques to address the class-imbalance challenge and study how they affect the machine learning approaches. Our tests show that a relatively simple technique that undersamples the normal cases to balance the number of samples in two classes (normal and slow) is very effective for model training. This model predicts slow connections with an F1 score of 0.926.

97 MATHEMATICS AND COMPUTING↗

The stellar parameters and elemental abundances from low-resolution spectra – I. 1.2 million giants from LAMOST DR8

As a typical data-driven method, deep learning becomes a natural choice for analysing astronomical data. In this study, we built a deep convolutional neural network (NN) to estimate basic stellar parameters $T\rm {_{eff}}$, log g , metallicity ([M/H] and [Fe/H]) and [α/M] along with nine individual elemental abundances ([C/Fe], [N/Fe], [O/Fe], [Mg/Fe], [Al/Fe], [Si/Fe], [Ca/Fe], [Mn/Fe], and [Ni/Fe]). The NN is trained using common stars between the APOGEE survey and the LAMOST survey. We used low-resolution spectra from LAMOST survey as input, and measurements from APOGEE as labels. For stellar spectra with the signal-to-noise ratio in g band larger than 10 in the test set, the mean absolute error (MAE) is 29 K for $T\rm {_{eff}}$, 0.07 dex for log g , 0.03 dex for both [Fe/H] and [M/H], and 0.02 dex for [α/M]. The MAE of most elements is between 0.02 and 0.04 dex. The trained NN was applied to 1210 145 giants, including sub-giants, from LAMOST DR8 within the range of stellar parameters 3500 K < $T\rm {_{eff}}$ < 5500 K, 0.0 dex < log g < 4.0 dex, −2.5 dex < [Fe/H] < 0.5 dex. The distribution of our results in the chemical spaces is highly consistent with APOGEE labels and stellar parameters show consistency with external high-resolution measurements from GALAH. The results in this study allow us to further studies based on LAMOST data and deepen our understanding of the accretion and evolution history of the Milky Way. The electronic version of the value added catalog is available at http://www.lamost.org/dr8/v1.1/doc/vac.

79 ASTRONOMY AND ASTROPHYSICS↗

Enhancing DSN Operations Efficiency with the Discrepancy Reporting Management System (DRMS)

The DRMS is the Discrepancy Reporting Management System used by the Deep Space Network (DSN). It uses a web interface and is a management tool designed to track and manage: data outage incidents during spacecraft tracks against equipment and software known as DRs (discrepancy Reports), to record "out of pass" incident logs against equipment and software in a Station Log, to record instances where equipment has be restarted or reset as Reset records, and to electronically record equipment readiness status across the DSN. Tracking and managing these items increases DSN operational efficiency by providing: the ability to establish the operational history of equipment items, data on the quality of service provided to the DSN customers, the ability to measure service performance, early insight into processes, procedures and interfaces that may need updating or changing, and the capability to trace a data outage to a software or hardware change. The items listed above help the DSN to focus resources on areas of most need.

Discrepancy Reporting Management Systems (DRMS)↗

Benchmark Dose Analysis of DNA Damage Biomarker Responses Provides Compound Potency and Adverse Outcome Pathway Information for the Topoisomerase II Inhibitor Class of Compounds

Genetic toxicology data have traditionally been utilized for hazard identification to provide a binary call for a compound's risk. Recent advances in the scientific field, especially with the development of high‐throughput methods to quantify DNA damage, have influenced a change of approach in genotoxicity assessment. The in vitro MultiFlow® DNA Damage Assay is one such method which multiplexes γH2AX, p53, phospho‐histone H3 biomarkers into a single‐flow cytometric analysis (Bryce et al., [2016]: Environ Mol Mutagen 57:546–558). This assay was used to study human TK6 cells exposed to each of eight topoisomerase II poisons for 4 and 24 hr. Using PROAST v65.5, the Benchmark Dose approach was applied to the resulting flow cytometric datasets. With “compound” serving as covariate, all eight compounds were combined into a single analysis, per time point and endpoint. The resulting 90% confidence intervals, plotted in Log scale, were considered as the potency rank for the eight compounds. The in vitro MultiFlow data showed a maximum confidence interval span of 1Log, which indicates data of good quality. Patterns observed in the compound potency rank were scrutinized by using the expert rule‐based software program Derek Nexus, developed by Lhasa Limited. Compound sub‐classification and structural alerts were considered contributory to the potencies observed for the topoisomerase II poisons studied herein. The Topo II poison Adverse Outcome Pathway was evaluated with MultiFlow endpoints serving as Key Events. The step‐wise approach described herein can be considered as a foundation for risk assessment of compounds within a specific mode of action of interest. Environ. Mol. Mutagen. 2020. © 2020 Wiley Periodicals, Inc.

Wheeldon, Ryan P.↗

Oregon Coast Range Ecological Conservation: Mapping Recent Logging Within Drinking Watersheds of Oregon’s Coastal Range to Support Future Resource Management Policies

Logging operations are widespread across the Oregon Coast Range and conventional logging practices pose a risk of contamination to surface water quality. The NASA DEVELOP Oregon Coast Ecological Conservation team partnered with nonprofit Oregon Wild to quantify the extent of clearcutting and commercial thinning in 80 Coast Range drinking watersheds between 2000 and 2022. This project used all available Landsat data from 1997 through June 2023 in Google Earth Engine. Sensors used include Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, and Landsat 9 Operational Land Imager-2. The Continuous Change Detection and Classification (CCDC) algorithm was used with Landsat observations to identify clearcutting patches. Percent change in summer median Landsat Normalized Difference Vegetation Index (NDVI) images were used to identify areas of forest disturbance including commercial thinning. The team concluded that logging, including both clearcutting and commercial thinning, impacted 31% of forested area in drinking watersheds and the intensity of logging remained consistent from year to year. Clearcutting occurred primarily on private land while commercial thinning occurred primarily on state and federal lands. This study showed that CCDC effectively identifies clearcutting, and percent change in NDVI successfully identifies disturbances including commercial thinning. Key constraints included the lack of field validation data and the inability to attribute disturbances to logging with certainty. Ultimately, this study identified the drinking watersheds and communities most likely to be impacted by logging activity. These results can inform legislation aimed at balancing the commercial and environmental benefits of forestlands.

Logging↗

NLSCIDNT user's guide maximum likehood parameter identification computer program with nonlinear rotorcraft model

A nonlinear, maximum likelihood, parameter identification computer program (NLSCIDNT) is described which evaluates rotorcraft stability and control coefficients from flight test data. The optimal estimates of the parameters (stability and control coefficients) are determined (identified) by minimizing the negative log likelihood cost function. The minimization technique is the Levenberg-Marquardt method, which behaves like the steepest descent method when it is far from the minimum and behaves like the modified Newton-Raphson method when it is nearer the minimum. Twenty-one states and 40 measurement variables are modeled, and any subset may be selected. States which are not integrated may be fixed at an input value, or time history data may be substituted for the state in the equations of motion. Any aerodynamic coefficient may be expressed as a nonlinear polynomial function of selected 'expansion variables'.

Source record↗

Velocity dispersions for X-ray-emitting clusters of galaxies

Combining spectroscopy for five clusters of galaxies reported to contain X-ray sources with previously published data for 21 X-ray clusters, suggested correlations between the cluster's velocity dispersions and their X-ray properties have been tested. Unlike previous investigations, it is found that, for all reasonable data subsets, the cluster radial velocity dispersions sigma(r) are correlated with the cluster X-ray luminosities L/x/ at a confidence level exceeding 99%. The best-fit slope of the (log sigma/r/, log L/x/)-relation is somewhat larger than theoretically predicted, but accurate determination of that relation requires further X-ray and optical observations. For the 'most reliable' data subsample a correlation between sigma(r) and the X-ray source temperatures is also found but at a much lower confidence level (85%) than derived by previous investigators from smaller samples.

Hintzen, P.↗