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At least 523 records · Page 29

Quantifying Graph Uncertainty from Communication Data

Graphs are a widely used abstraction for representing a variety of important real-world problems including emulating cyber networks for situational awareness, or studying social networks to understand human interactions or pandemic spread. Communication data is often converted into graphs to help understand social and technical patterns in the underlying communication data. However, prior to this project, little work had been performed analyzing how best to develop graphs from such data. Thus, many critical, national security problems were being performed against graph representations of questionable quality. Herein, we describe our analyses that were precursors to our final statistically grounded technique for creating static graph snapshots from a stream of communication events. The first analyzes the statistical distribution properties of a variety of real-world communication datasets generally fit best by Pareto, log normal, and extreme value distributions. The second derives graph properties that can be estimated given the expected statistical distribution for communication events and the communication interval to be viewed node observability, edge observability, and expected accuracy of node degree. Unfortunately, as that final process is under review for publication, we can't publish it here at this time.

97 MATHEMATICS AND COMPUTING↗

ResStock: Annual Baseline Results with Component Loads

The ResStock Analysis Tool was developed by NREL with support from the U.S. Department of Energy to provide a new approach to large-scale residential analysis by combining large public and private data sources, statistical sampling, detailed sub hourly building simulations, and high-performance computing. This combination achieves unprecedented granularity and accuracy in modeling the diversity of the housing stock and the distributional impacts of building technologies in different communities. The annual baseline energy results from a national-scale ResStock run use typical meteorological year 3 (TMY3) files for energy simulations. Results include heating and cooling loads for individual components of each building. Component loads describe the heating/cooling load that can be attributed to specific elements of a home, such as heat transfer through walls or internal gains. Additionally, these results include the standard ResStock outputs for housing characteristics and numerous energy outputs by end-use and fuel. A snapshot of the ResStock version used to produce this data, including a configuration file for the run can be found using the Source Code resource link.

Array↗

A Novel Approach for Real-Time Quality Monitoring in Machining of Aerospace Alloy through Acoustic Emission Signal Transformation for DNN

Gamma titanium aluminide (γ-TiAl) is considered a high-performance, low-density replacement for nickel-based superalloys in the aerospace industry due to its high specific strength, which is retained at temperatures above 800 °C. However, low damage tolerance, i.e., brittle material behavior with a propensity to rapid crack propagation, has limited the application of γ-TiAl. Any cracks introduced during manufacturing would dramatically lower the useful (fatigue) life of γ-TiAl components, making the workpiece surface’s quality from finish machining a critical component to product quality and performance. To address this issue and enable more widespread use of γ-TiAl, this research aims to develop a real-time non-destructive evaluation (NDE) quality monitoring technique based on acoustic emission (AE) signals, wavelet transform, and deep neural networks (DNN). Previous efforts have opted for traditional approaches to AE signal analysis, using statistical feature extraction and classification, which face challenges such as the extraction of good/relevant features and low classification accuracy. Hence, this work proposes a novel AI-enabled method that uses a convolutional neural network (CNN) to extract rich and relevant features from a two-dimensional image representation of 1D time-domain AE signals (known as scalograms), subsequently classifying the AE signature based on pedigreed experimental data and finally predicting the process-induced surface quality. The results of the present work show good classification accuracy of 80.83% using scalogram images, in-situ experimental data, and a VGG-19 pre-trained neural network, establishing the significant potential for real-time quality monitoring in manufacturing processes.

36 MATERIALS SCIENCE↗

Mariner Venus/Mercury 1973 navigation strategy

This paper presents the navigational aspects of the Mariner Venus/Mercury 1973 mission. Principal emphasis is on the development of the trajectory correction strategy, propellant costs, and delivery accuracies at Venus and Mercury. Key error sources and mission constraints are discussed. Of particular interest are the statistics of the first, post-Venus, maneuver which must correct for the magnification of errors in the Venus encounter. Finally, although not a primary objective of the mission, the analysis is extended to include a second Mercury encounter.

Mckinley, E. L.↗

Random element method for numerical modeling of diffusional processes

The random element method is a generalization of the random vortex method that was developed for the numerical modeling of momentum transport processes as expressed in terms of the Navier-Stokes equations. The method is based on the concept that random walk, as exemplified by Brownian motion, is the stochastic manifestation of diffusional processes. The algorithm based on this method is grid-free and does not require the diffusion equation to be discritized over a mesh, it is thus devoid of numerical diffusion associated with finite difference methods. Moreover, the algorithm is self-adaptive in space and explicit in time, resulting in an improved numerical resolution of gradients as well as a simple and efficient computational procedure. The method is applied here to an assortment of problems of diffusion of momentum and energy in one-dimension as well as heat conduction in two-dimensions in order to assess its validity and accuracy. The numerical solutions obtained are found to be in good agreement with exact solution except for a statistical error introduced by using a finite number of elements, the error can be reduced by increasing the number of elements or by using ensemble averaging over a number of solutions.

Ghoniem, A. F.↗

Single-dish high sensitivity determination of solar limb emission at 22 and 44 GHz

A large number of solar maps were obtained with the use of Itapetinga 45 ft antenna at 22 GHz and 44 GHz. A statistical study of these maps, reduced using original techniques, permitted the establishment of the solar radius with great accuracy at the two frequencies. It is found that 22 GHz and 44 BHz radiation originates at 16,00 km and 12,500 km above the photosphere, respectively. Excess emission due to active regions was clearly identified at lower solar latitudes above and below the equator, extending up to 26,000 km and 16,500 km above the photosphere, at 22 GHs and 44 GHz, respectively.

Costa, J. E. R.↗

A comparison of Landsat point and rectangular field training sets for land-use classification

Rectangular training fields of homogeneous spectroreflectance are commonly used in supervised pattern recognition efforts. Trial image classification with manually selected training sets gives irregular and misleading results due to statistical bias. A self-verifying, grid-sampled training point approach is proposed as a more statistically valid feature extraction technique. A systematic pixel sampling network of every ninth row and ninth column efficiently replaced the full image scene with smaller statistical vectors which preserved the necessary characteristics for classification. The composite second- and third-order average classification accuracy of 50.1 percent for 331,776 pixels in the full image substantially agreed with the 51 percent value predicted by the grid-sampled, 4,100-point training set.

Tom, C. H.↗

Oculomotor function during space flight and susceptibility to space motion sickness

Horizontal vestibulo-ocular reflex (VOR) and saccadic eye movements (SEM) were studied in 18 subjects before and during five Space Shuttle missions to evaluate the effects of weightlessness and correlations between results and susceptibility to and actual presence of space motion sickness (SMS). Active sinusoidal head oscillation was the stimulus for VOR tests with vision (VVOR), with eyes shaded (VOR-ES), and VOR suppression (VOR-S). Eye movements were recorded by electrooculography and head position by a potentiometer. No pathological nystagmus or other abnormal eye movements were seen. No significant in-flight changes were seen in the gain, phase shift or waveform of VVOR, VOR-ES or VOR-S. Statistically significant increases in saccadic latency and decreases in saccadic velocity were seen, with no change in saccadic accuracy. Preflight differences between SMS susceptible and nonsusceptible subjects were noted only in VOR-S, with less complete suppression in susceptible subjects, a finding also seen in flight. During flight, VVOR gain was significantly increased in three nonaffected subjects. Saccades of SMS-affected subjects showed increased latency and velocity and decreased accuracy compared to saccades of unaffected subjects.

Thornton, William E.↗

Signal Processing and Calibration of Continuous-Wave Focused CO2 Doppler Lidars for Atmospheric Backscatter Measurement

Two continuous-wave(CW)focused C02 Doppler lidars (9.1 and 10.6 micrometers) were developed for airborne in situ aerosol backscatter measurements. The complex path of reliably calibrating these systems, with different signal processors, for accurate derivation of atmospheric backscatter coefficients is documented. Lidar calibration for absolute backscatter measurement for both lidars is based on range response over the lidar sample volume, not solely at focus. Both lidars were calibrated with a new technique using well-characterized aerosols as radiometric standard targets and related to conventional hard-target calibration. A digital signal processor (DSP), a surface acoustic and spectrum analyzer and manually tuned spectrum analyzer signal analyzers were used. The DSP signals were analyzed with an innovative method of correcting for systematic noise fluctuation; the noise statistics exhibit the chi-square distribution predicted by theory. System parametric studies and detailed calibration improved the accuracy of conversion from the measured signal-to-noise ratio to absolute backscatter. The minimum backscatter sensitivity is approximately 3 x 10(exp -12)/m/sr at 9.1 micrometers and approximately 9 x 10(exp -12)/m/sr at 10.6 micrometers. Sample measurements are shown for a flight over the remote Pacific Ocean in 1990 as part of the NASA Global Backscatter Experiment (GLOBE) survey missions, the first time to our knowledge that 9.1-10.6 micrometer lidar intercomparisons were made. Measurements at 9.1 micrometers, a potential wavelength for space-based lidar remote-sensing applications, are to our knowledge the first based on the rare isotope C-12 O(2)-18 gas.

Rothermel, Jeffry↗

VLBI2010 Imaging and Structure Corrections

Simulations show that the next generation VLBI system is generally well suited for imaging extragalactic radio sources. In addition to revealing the morphology of the sources, simulated VLBI2010 images may also be used to generate structure correction maps, which characterize the impact of source structure on the VLBI measurements. By comparing structure corrections for a set of simulated images based on Monte-Carlo generated visibilities with theoretical structure corrections derived from the model, we assess the accuracy of VLBI2010 structure corrections. In the most favorable case (32-station network, source at declination +40 deg.), statistics demonstrate that the structure corrections obtained from simulated images are statistically close to the theoretical model ones, which seems very promising for the VLBI2010 system.

Collioud, Arnaud↗

Constraining the Thickness of Polar Ice Deposits on Mercury Using the Mercury Laser Altimeter and Small Craters in Permanently Shadowed Regions

Radar-bright deposits at the poles of Mercury are located in permanently shadowed regions, which pro- vide thermally stable environments for hosting and retaining water ice on the surface or in the near sub- surface for geologic timescales. While the areal distribution of these radar-bright deposits is well characterized, their thickness, and thus their total mass and volume, remain poorly constrained. Here we derive thickness estimates for selected water-ice deposits using small, simple craters visible within the permanently shadowed, radar-bright deposits. We examine two endmember scenarios: in Case I, these craters predate the emplacement of the ice, and in Case II, these craters postdate the emplacement of the ice. In Case I, we find the difference between estimated depths of the original unfilled craters and the measured depths of the craters to find the estimated infill of material. The average estimated infilled material for 9 craters assumed to be overlain with water ice is ∼41 +30 −14 m, where 1 −σ standard error of the mean is reported as uncertainty. Reported uncertainties are for statistical errors only. Additional systematic uncertainty may stem from georeferencing the images and topographic datasets, from the radial accuracy of the altimeter measurements, or from assumptions in our models including (1) ice is flat in the bowl- shaped crater and (2) there is negligible ice at the crater rims. In Case II, we derive crater excavation depths to investigate the thickness of the ice layer that may have been penetrated by the impact. While the absence of excavated regolith associated with the small craters observed suggests that impacts generally do not penetrate through the ice deposit, the spatial resolution and complex illumination geometry of images may limit the observations. Therefore, it is not possible to conclude whether the small craters in this study penetrate through the ice deposit, and thus Case II does not provide a constraint on the ice thickness. For Mercury’s polar deposits, we argue that Case I of the small craters predating the emplacement of the ice deposits is more likely, given other geologic evidence that suggests that these ice deposits are relatively young. Using the ice thickness estimates from Case I to calculate the total amount of water ice currently contained in Mercury’s polar deposits results in a value of ∼10 14 –10 15 kg. This is equivalent to ∼100–1000 km 3 ice in volume. This volume of water ice is consistent with delivery via micrometeorite bombardment, Jupiter-family comets, or potentially a single impactor.

Deutsch, Ariel N.↗

Improved assessment of mangrove forests in Sundarbans East Wildlife Sanctuary using WorldView 2 and TanDEM-X high resolution imagery

Recent developments of remote sensing techniques which can capture both the structure and function of the ecosystem provide a more representative view of the landscape. These unique Earth observations were used to help improve traditional forestry surveys by providing species-specific land cover classes for mangrove forests in the Sundarbans East Wildlife Sanctuary. By combining optical data from WorldView2 (WV2; 2 m pixel) and a canopy height model derived using radar data from TanDEM-X (TDX; 12 m pixel), we identified nine mangrove and five non-mangrove classes by following an Iterative Self-Organizing Data Analysis Algorithm. Three dominant mangrove species accounted for nearly 50% of the sanctuary. Heritieria fomes disproportionately covered the largest area at 43%, overturning previous field-based estimates of Excoecaria agallocha dominance. E. agallocha and Sonneratia apetala, covered 3% and 1.47% of the sanctuary, respectively. Four mixed species classes were also identified with clear vegetation zonation patterns that trended toward species homogeneity with increasing distance from shore. The overall land cover accuracy (WV2: 89.33%; WV2-TDX: 89.89%), the Kappa Coefficient (WV2:0.88; WV2-TDX: 0.89) and change statistics between WV2 and WV2-TDX landcover classifications indicate that the WV2 imagery can separate mangrove community types without structural data. The combination of the land cover classifications and the canopy height model indicated that H. fomes were not only the most dominant forest but also, on average, the tallest (12.3 m) among the other eight mangrove types. Our large-scale mapping with high resolution optical and radar platforms can capture subtle changes in mangrove vegetation and canopy structural gradients more accurately and be used to monitor biodiversity changes and Aichi Biodiversity Targets and Indicators, which would contribute to biodiversity policy updating.

Md Mizanur Rahman↗

Passive method to measure strength of turbulence

Disclosed is a method to passively measure and calculate the strength of turbulence via the index of refraction structure constant Cn2 from video imagery gathered by an imaging device, such as a video camera. Processing may occur with any type computing device utilizing a processor executing machine executable code stored on memory. This method significantly simplifies instrumentation requirements, reduces cost, and provides rapid data output. This method combines an angle of arrival methodology, which provides scale factors, with a new spatial/temporal frequency domain method. As part of the development process, video imagery from high speed cameras was collected and analyzed. The data was decimated to video rates such that statistics could be computed and used to confirm that this passive method accurately characterizes the atmospheric turbulence. Cn2 accuracy from this method compared well with scintillometer data through two full orders of magnitude and more capability is expected beyond this verification.

O'Neill, Mary Morabito↗

Free-Energy Calculations. A Mathematical Perspective

Ion channels are pore-forming assemblies of transmembrane proteins that mediate and regulate ion transport through cell walls. They are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses. They are also essential to cardiac processes, muscle contraction and epithelial transport. Ion channels from lower organisms can act as toxins or antimicrobial agents, and in a number of cases are involved in infectious diseases. Because of their important and diverse biological functions they are frequent targets of drug action. Also, simple natural or synthetic channels find numerous applications in biotechnology. For these reasons, studies of ion channels are at the forefront of biophysics, structural biology and cellular biology. In the last decade, the increased availability of X-ray structures has greatly advanced our understanding of ion channels. However, their mechanism of action remains elusive. This is because, in order to assist controlled ion transport, ion channels are dynamic by nature, but X-ray crystallography captures the channel in a single, sometimes non-native state. To explain how ion channels work, X-ray structures have to be supplemented with dynamic information. In principle, molecular dynamics (MD) simulations can aid in providing this information, as this is precisely what MD has been designed to do. However, MD simulations suffer from their own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. To assess the reliability of MD simulations it is only natural to turn to the main function of channels - conducting ions - and compare calculated ionic conductance with electrophysiological data, mainly single channel recordings, obtained under similar conditions. If this comparison is satisfactory it would greatly increase our confidence that both the structures and our computational methodologies are sufficiently accurate. Channel conductance, defined as the ratio of ionic current through the channel to applied voltage, can be calculated in MD simulations by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. If the current is small, a voltage significantly higher than the experimental one needs to be applied to collect sufficient statistics of ion crossing events. Then, the calculated conductance has to be extrapolated to the experimental voltage using procedures of unknown accuracy. Instead, we propose an alternative approach that applies if ion transport through channels can be described with sufficient accuracy by the one-dimensional diffusion equation in the potential given by the free energy profile and applied voltage. Then, it is possible to test the assumptions of the equation, recover the full voltage/current dependence, determine the reliability of the calculated conductance and reconstruct the underlying (equilibrium) free energy profile, all from MD simulations at a single voltage. We will present the underlying theory, model calculations that test this theory and simulations on ion conductance through a channel that has been extensively studied experimentally. To our knowledge this is the first case in which the complete, experimentally measured dependence of the current on applied voltage has been reconstructed from MD simulations.

free energy↗

Detection Limits of Low-mass, Long-period Exoplanets Using Gaussian Processes Applied to HARPS-N Solar Radial Velocities

Radial velocity (RV) searches for Earth-mass exoplanets in the habitable zone around Sun-like stars are limited by the effects of stellar variability on the host star. In particular, suppression of convective blueshift and brightness inhomogeneities due to photospheric faculae/plage and starspots are the dominant contribution to the variability of such stellar RVs. Gaussian process (GP) regression is a powerful tool for statistically modeling these quasi-periodic variations. We investigate the limits of this technique using 800 days of RVs from the solar telescope on the High Accuracy Radial velocity Planet Searcher for the Northern hemisphere (HARPS-N) spectrograph. These data provide a well-sampled time series of stellar RV variations. Into this data set, we inject Keplerian signals with periods between 100 and 500 days and amplitudes between 0.6 and 2.4 m s{sup −1}. We use GP regression to fit the resulting RVs and determine the statistical significance of recovered periods and amplitudes. We then generate synthetic RVs with the same covariance properties as the solar data to determine a lower bound on the observational baseline necessary to detect low-mass planets in Venus-like orbits around a Sun-like star. Our simulations show that discovering planets with a larger mass (∼0.5 m s{sup −1}) using current-generation spectrographs and GP regression will require more than 12 yr of densely sampled RV observations. Furthermore, even with a perfect model of stellar variability, discovering a true exo-Venus (∼0.1 m s{sup −1}) with current instruments would take over 15 yr. Therefore, next-generation spectrographs and better models of stellar variability are required for detection of such planets.

47 OTHER INSTRUMENTATION↗

Statistical Modeling and Analysis of k -Layer Coverage of Two-Dimensional Materials in Inkjet Printing Processes

Two-dimensional layered materials/flakes, also known as crystalline atom-thick layer nanosheets, have recently been receiving great attention in electronics fabrication due to their unique and intriguing properties. The k-layer coverage area (i.e., the area covered by k number of overlapping layers) of the printed flake pattern significantly impacts on the properties of the printed electronics. In this work, we constructed a statistical model to describe the k-layer coverage of randomly distributed two-dimensional materials. A series of results are obtained to provide not only the expectation but also the variance of the coverage area. The boundary effects on the random flakes coverage are also studied. In addition, an approximated statistical testing approach is also developed in this work to detect abnormal coverage patterns. Furthermore, the case studies based on simulated data and real flakes images obtained from the inkjet printing process demonstrate the accuracy and effectiveness of the proposed model and analysis methods.

36 MATERIALS SCIENCE↗

Enhancing ZFP: A Statistical Approach to Understanding and Reducing Error Bias in a Lossy Floating-Point Compression Algorithm

The amount of data generated and gathered in scientific simulations and data collection applications is continuously growing, putting mounting pressure on storage and bandwidth concerns. A means of reducing such issues is data compression; but, lossless data compression is typically ineffective when applied to floating-point data. Thus, users tend to apply a lossy data compressor, which allows for small deviations from the original data. It is essential to understand how the error from lossy compression impacts the accuracy of the data analytics. Thus, we must analyze not only the compression properties but the error as well. In this paper, we provide a statistical analysis of the error caused by ZFP compression, a state-of-the-art, lossy compression algorithm explicitly designed for floating-point data. We show that the error is indeed biased and propose simple modifications to the algorithm to neutralize the bias and further reduce the resulting error.

97 MATHEMATICS AND COMPUTING↗

Orbital flux integrations: Parameter values for effective computer time reductions

To improve computer utilization and to reduce the cost of orbital flux integrations, the effects of integration parameters 'duration' (T) and 'stepsize' (delta t) on integration results were investigated. Over given ranges of T and delta t, and within specified acceptable accuracy restraints, optimal values of these parameters were established for circular subsynchronous trajectories, in terms of the variables altitude (H) and inclination (i). It is shown that (1) above a certain statistically important value, duration is independent of both h and i; (2) stepsize has a relative altitude dependence; and (3) stepsize is not a function of inclination. The substantial savings in computer time are discussed along with the possibility of greater savings by relaxing accuracy restrictions while not exceeding the minimum model-associated uncertainty factors of the environments.

Stassinopoulos, E. G.↗