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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers

Backdoor data poisoning attacks have recently been demonstrated in computer vision research as a potential safety risk for machine learning (ML) systems. Traditional data poisoning attacks manipulate training data to induce unreliability of an ML model, whereas backdoor data poisoning attacks maintain system performance unless the MLmodel is presented with an input containing an embedded“trigger” that provides a predetermined response advantageous to the adversary. Our work builds upon prior back-door data-poisoning research for ML image classifiers and systematically assesses different experimental conditions including types of trigger patterns, persistence of trigger patterns during retraining, poisoning strategies, architectures (ResNet-50, NasNet, NasNet-Mobile), datasets (Flowers, CIFAR-10), and potential defensive regularization techniques (Contrastive Loss, Logit Squeezing, Manifold Mixup,Soft-Nearest-Neighbors Loss). Experiments yield four key findings. First, the success rate of backdoor poisoning at-tacks varies widely, depending on several factors, including model architecture, trigger pattern and regularization technique. Second, we find that poisoned models are hard to detect through performance inspection alone. Third, regularization typically reduces backdoor success rate, although it can have no effect or even slightly increase it, depending on the form of regularization. Finally, backdoors inserted through data poisoning can be rendered ineffective after just a few epochs of additional training on a small set of clean data without affecting the model’s performance.

Truong, Loc T.↗
DOE OSTI2017

Availability of Neutronics Benchmarks in the ICSBEP and IRPhEP Handbooks for Computational Tools Testing

In the past several decades, numerous experiments have been performed worldwide to support reactor operations, measurements, design, and nuclear safety. Those experiments represent an extensive international investment in infrastructure, expertise, and cost, representing significantly valuable resources of data supporting past, current, and future research activities. Those valuable assets represent the basis for recording, development, and validation of our nuclear methods and integral nuclear data [1]. The loss of these experimental data, which has occurred all too much in the recent years, is tragic. The high cost to repeat many of these measurements can be prohibitive, if not impossible, to surmount. Two international projects were developed, and are under the direction of the Organisation for Co-operation and Development Nuclear Energy Agency (OECD NEA) to address the challenges of not just data preservation, but evaluation of the data to determine its merit for modern and future use. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) was established to identify and verify comprehensive critical benchmark data sets; evaluate the data, including quantification of biases and uncertainties; compile the data and calculations in a standardized format; and formally document the effort into a single source of verified benchmark data [2]. Similarly, the International Reactor Physics Experiment Evaluation Project (IRPhEP) was established to preserve integral reactor physics experimental data, including separate or special effects data for nuclear energy and technology applications [3]. Annually, contributors from around the world continue to collaborate in the evaluation and review of select benchmark experiments for preservation and dissemination. The extensively peer-reviewed integral benchmark data can then be utilized to support nuclear design and safety analysts to validate the analytical tools, methods, and data needed for next-generation reactor design, safety analysis requirements, and all other front- and back-end activities contributing to the overall nuclear fuel cycle where quality neutronics calculations are paramount.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Nuclear Data Sheets for A = 28

Evaluated spectroscopic data and level schemes from radioactive decay and nuclear reaction studies are presented for {sup 28}F, {sup 28}Ne, {sup 28}Na, {sup 28}Mg, {sup 28}Al, {sup 28}Si, {sup 28}P, and {sup 28}S. This evaluation for A=28 supersedes the earlier evaluations by P.M. Endt (1998En04 and 1990En08). However, additional/detailed data for these nuclides can be found in earlier evaluations 1978En02 and 1973EnVA also by P.M. Endt.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Improved renormalization group computation of likelihood functions for cosmological data sets

Evaluation of likelihood functions for cosmological large scale structure data sets (including CMB, galaxy redshift surveys, etc.) naturally involves marginalization, i.e., integration, over an unknown underlying random signal field. Recently, I showed how a renormalization group method can be used to carry out this integration efficiently by first integrating out the smallest scale structure, i.e., localized structure on the scale of differences between nearby data cells, then combining adjacent cells in a coarse graining step, then repeating this process over and over until all scales have been integrated. Here I extend the formulation in several ways in order to reduce the prefactor on the method's linear scaling with data set size. The key improvement is showing how to integrate out the difference between specific adjacent cells before summing them in the coarse graining step, compared to the original formulation in which small-scale fluctuations were integrated more generally. I suggest some other improvements in details of the scheme, including showing how to perform the integration around a maximum likelihood estimate for the underlying random field. In the end, an accurate likelihood computation for a million-cell Gaussian test data set runs in two minutes on my laptop, with room for further optimization and straightforward parallelization.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

Remote sensing of physiographic soil units of Bennett County, South Dakota

A study was conducted in Bennett County, South Dakota, to establish a rangeland test site for evaluating the usefulness of ERTS data for mapping soil resources in rangeland areas. Photographic imagery obtained in October, 1970, was analyzed to determine which type of imagery is best for mapping drainage and land use patterns. Imagery of scales ranging from 1:1,000,000 to 1.20,000 was used to delineate soil-vegetative physiographic units. The photo characteristics used to define physiographic units were texture, drainage pattern, tone pattern, land use pattern and tone. These units will be used as test data for evaluating ERTS data. The physiographic units were categorized into a land classification system. The various categories which were delineated at the different scales of imagery were designed to be useful for different levels of land use planning. The land systems are adequate only for planning of large areas for general uses. The lowest category separated was the facet. The facets have a definite soil composition and represent different soil landscapes. These units are thought to be useful for providing natural resource information needed for local planning.

Frazee, C. J.↗
DOE OSTI2016

Nuclear Data Testing Of Pu{sup 239} CIELO Evaluation With NDaST

Within the Collaborative International Evaluated Library Organisation (CIELO) project a coordinated effort is being made amongst the different nuclear data evaluation projects, ENDF, JEFF, JENDL etc. to improve the cross sections of six of the most important isotopes, Pu{sup 239}, U{sup 235}, U{sup 238}, Fe{sup 56}, O{sup 16} and H{sup 1}. Recently developed, the Nuclear Data and Sensitivity Tool (NDaST) is an online tool (http://www.oecd-nea.org/ndast/) that allows nuclear data evaluators to get rapid feedback about the consequences of changes to nuclear data on integral experiment benchmarks that exist within the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and International Reactor Physics Evaluation (IRPhE) Project handbooks. NDaST links the thousands of nuclear data sensitivity profiles in the Database for ICSBEP (DICE) and the IRPhE Database and Analysis Tool (IDAT), with the nuclear data viewing tool JANIS. NDaST can be used to provide timely feedback to CIELO participants. Normally an evaluator changes the ENDF/B files based on differential data, and subsequently hands the new evaluation to testers who give feedback on the performance of the new evaluation in terms of accurately predicting the integral benchmark results. This process is often slow. With accurate sensitivity coefficients it is feasible to predict the results of changes to differential data without performing the direct substitution, by simply multiplying the change in cross section with the sensitivity. Furthermore, when multiple aspects of the file are changed simultaneously, the impact of each individual change can be muddled in the substitution testing. NDaST when used in conjunction with direct perturbation testing can help provide feedback as to which cross section changes are driving changes in the benchmarks. In this paper we focus on Pu{sup 239}, and comparing the NDaST predictions of CIELO files to direct substitution. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2002

Impact of Quikscat Data on Numerical Weather Prediction

One of the important applications of satellite surface wind observations is to increase the accuracy of weather analyses and forecasts. Satellite surface wind data can improve numerical weather prediction (NWP) model forecasts by contributing to improved analyses of the surface wind field and air sea fluxes. Through the data assimilation process,these data can also improve atmospheric mass and motion fields in the free atmosphere above the surface. The SeaWinds scatterometer on the QuikScat satellite was launched in July 1999 and represented a dramatic departure in design from the other scatterometer instruments launched during the past decade (ERS-1,2 and NSCAT). The NASA Data Assimilation Office (DAO) was the first data assimilation center to assimilate QuikScat Seawinds data and evaluate their impact on numerical weather prediction. Following the launch of QuikScat, a detailed evaluation of the initial surface wind data sets was performed as part of a collaborative project between the Environmental Modeling Center of NCEP, NESDIS and the DAO. More recently, the impact of Quikscat data was evaluated in detailed experiments using the NCEP operational data assimilation system. As a result of the beneficial impact obtained, NCEP began operational utilization of Quikscat data. Results from these experiments as well as recent DAO assimilation experiments showing the impact of Quikscat data on stratospheric analyses and forecasts will be presented at the meeting.

Atlas, Robert↗
DOE OSTI2018

Nuclear Data Sheets for A=217

The evaluated spectroscopic data are presented in this paper for 12 known nuclides with A=217 (Tl, Pb, Bi, Po, At, Rn, Fr, Ra, Ac, Th, Pa, U). For 217Tl, 217Pb, 217Pa, and 217U nuclei, only information on the ground state is available. Levels in 217 Bi are known only from isomer decay following fragmentation reaction and those in 217 At and 217 Rn only from the α decay of 221 Fr and 221 Ra, respectively. High spin levels in 217 Ra are mainly from 1987SuZY and 2011MuZZ which are a lab report and thesis, respectively. Due to differences between these studies, further experimental study is needed to firmly establish the level scheme. This evaluation was carried out as part of a joint IAEA-ICTP workshop for Nuclear Structure and Decay Data, organized and hosted by the IAEA, Vienna and ICTP, Trieste, Aug 22 to Sept 2 2016. The evaluation work was coordinated by E.A. McCutchan (BNL). Finally, this work supersedes the previous previous A=217 evaluation (2003Ak06) by Y.A. Akovali.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Nuclear Data Sheets for A = 70

Spectroscopic data for all nuclei with mass number A = 70 have been evaluated, and the corresponding level schemes from radioactive decay and reaction studies are presented. Since the previous evaluation, the half-life of {sup 70}Mn has been measured and excited states in {sup 70}Fe observed for the first time. Excited states in {sup 70}Ni have been more extensively studied while Coulomb excitation and collinear laser spectroscopy measurements in {sup 70}Cu have allowed for firm Jπ assignments. Despite new measurements, there remain some discrepancies in half-lives of low lying states in {sup 70}Zn. New measurements have extended the knowledge of high-spin band structures in {sup 70}Ge and {sup 70}As. This evaluation supersedes the prior A = 70 evaluation of 2004Tu09.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2014

Evaluation of the Sensor Data Record from the Nadir Instruments of the Ozone Mapping Profiler Suite (OMPS)

This paper evaluates the first 15 months of the Ozone Mapping and Profiler Suite (OMPS) Sensor Data Record (SDR) acquired by the nadir sensors and processed by the National Oceanic and Atmospheric Administration Interface Data Processing Segment. The evaluation consists of an inter-comparison with a similar satellite instrument, an analysis using a radiative transfer model, and an assessment of product stability. This is in addition to the evaluation of sensor calibration and the Environment Data Record product that are also reported in this Special Issue. All these are parts of synergetic effort to provide comprehensive assessment at every level of the products to ensure its quality. It is found that the OMPS nadir SDR quality is satisfactory for the current Provisional maturity. Methods used in the evaluation are being further refined, developed, and expanded, in collaboration with international community through the Global Space-based Inter-Calibration System, to support the upcoming long-term monitoring.

validation↗
DOE OSTI2021

Data–Driven Velocity Model Evaluation Using K–Means Clustering

In this work, we develop a data-driven clustering method to evaluate a velocity model using surface wave velocity dispersion. This is done by first computing theoretical dispersion curves for 1-D velocity profiles of all the grid locations and then splitting the resulting dispersion curves into a certain number of groups via the K-means clustering. The observed dispersion curves are also clustered following the same procedure and the velocity model is assessed by comparing the spatial patterns obtained for the observed and synthetic data sets. The method is applied to evaluate two community velocity models in southern California, CVM-S4.26 and CVM-H15.1, using phase velocity maps derived for 3–16 s Rayleigh waves. We found a good correlation in the spatial distribution of clusters between the result of CVM-S4.26 and that of the observed data, suggesting that the CVM-S4.26 fits the observed dispersion maps better than the CVM-H15.1 in terms of features extracted from the clustering analysis.

58 GEOSCIENCES↗
DOE OSTI2019

Reliability of Photonuclear Data: Various Experiments and Evaluations

The well-known problem of reliability of partial photoneutron cross-section data obtained using beams of quasimonoenergetic annihilation photons was discussed. Noticeable disagreements between data from various experiments were analyzed using physical data reliability criteria. The experimentally-theoretical method for evaluating of reaction cross sections satisfied physical criteria was used and new reliable data were obtained for many nuclei. The disagreements between newly evaluated cross sections and data from the IAEA Digital Photonuclear Data Library were discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗