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At least 667 records · Page 37

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image segmentations. The automated selection of a single segmentation level is often necessary. We propose and investigate the use of automatically selected markers for this purpose. In this paper, a novel Marker-based HSEG (M-HSEG) method for spectral-spatial classification of hyperspectral images is proposed. Two classification-based approaches for automatic marker selection are adapted and compared for this purpose. Then, a novel constrained marker-based HSEG algorithm is applied, resulting in a spectral-spatial classification map. Three different implementations of the M-HSEG method are proposed and their performances in terms of classification accuracies are compared. The experimental results, presented for three hyperspectral airborne images, demonstrate that the proposed approach yields accurate segmentation and classification maps, and thus is attractive for remote sensing image analysis.

Tarabalka, Y.↗

Modified Light Use Efficiency Model for Assessment of Carbon Sequestration in Grasslands of Kazakhstan: Combining Ground Biomass Data and Remote-sensing

A modified light use efficiency (LUE) model was tested in the grasslands of central Kazakhstan in terms of its ability to characterize spatial patterns and interannual dynamics of net primary production (NPP) at a regional scale. In this model, the LUE of the grassland biome (εn) was simulated from ground-based NPP measurements, absorbed photosynthetically active radiation (APAR) and meteorological observations using a new empirical approach. Using coarse-resolution satellite data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), monthly NPP was calculated from 1998 to 2008 over a large grassland region in Kazakhstan. The modelling results were verified against scaled up plot-level observations of grassland biomass and another available NPP data set derived from a field study in a similar grassland biome. The results indicated the reliability of productivity estimates produced by the model for regional monitoring of grassland NPP. The method for simulation of εn suggested in this study can be used in grassland regions where no carbon flux measurements are accessible.

Kazakhstan↗

Machine learning properties of binary wurtzite superlattices

The burgeoning paradigm of high-throughput computations and materials informatics brings new opportunities in terms of targeted materials design and discovery. The discovery process can be significantly accelerated and streamlined if one can learn effectively from available knowledge and past data to predict materials properties efficiently. Indeed, a very active area in materials science research is to develop machine learning based methods that can deliver automated and cross-validated predictive models using either already available materials data or new data generated in a targeted manner. In the present paper, we show that fast and accurate predictions of a wide range of properties of binary wurtzite superlattices, formed by a diverse set of chemistries, can be made by employing state-of-the-art statistical learning methods trained on quantum mechanical computations in combination with a judiciously chosen numerical representation to encode materials’ similarity. These surrogate learning models then allow for efficient screening of vast chemical spaces by providing instant predictions of the targeted properties. Moreover, the models can be systematically improved in an adaptive manner, incorporate properties computed at different levels of fidelities and are naturally amenable to inverse materials design strategies. Finally, while the learning approach to make predictions for a wide range of properties (including structural, elastic and electronic properties) is demonstrated here for a specific example set containing more than 1200 binary wurtzite superlattices, the adopted framework is equally applicable to other classes of materials as well.

36 MATERIALS SCIENCE↗

Effect of Microscopic Damage Events on Static and Ballistic Impact Strength of Triaxial Braid Composites

The reliability of impact simulations for aircraft components made with triaxial-braided carbon-fiber composites is currently limited by inadequate material property data and lack of validated material models for analysis. Methods to characterize the material properties used in the analytical models from a systematically obtained set of test data are also lacking. A macroscopic finite element based analytical model to analyze the impact response of these materials has been developed. The stiffness and strength properties utilized in the material model are obtained from a set of quasi-static in-plane tension, compression and shear coupon level tests. Full-field optical strain measurement techniques are applied in the testing, and the results are used to help in characterizing the model. The unit cell of the braided composite is modeled as a series of shell elements, where each element is modeled as a laminated composite. The braided architecture can thus be approximated within the analytical model. The transient dynamic finite element code LS-DYNA is utilized to conduct the finite element simulations, and an internal LS-DYNA constitutive model is utilized in the analysis. Methods to obtain the stiffness and strength properties required by the constitutive model from the available test data are developed. Simulations of quasi-static coupon tests and impact tests of a represented braided composite are conducted. Overall, the developed method shows promise, but improvements that are needed in test and analysis methods for better predictive capability are examined.

Littell, Justin D.↗

Data-driven approach to parameterize SCAN + U for an accurate description of 3 d transition metal oxide thermochemistry

Semilocal density-functional theory (DFT) methods exhibit significant errors for the phase diagrams of transition-metal oxides that are caused by an incorrect description of molecular oxygen and the large self-interaction error in materials with strongly localized electronic orbitals. Empirical and semiempirical corrections based on the DFT + U method can reduce these errors, but the parameterization and validation of the correction terms remains an on-going challenge. Here we develop a systematic methodology to determine the parameters and to statistically assess the results by considering interlinked thermochemical data across a set of transition metal compounds. We consider three interconnected levels of correction terms: (1) a constant oxygen binding correction, (2) Hubbard-U correction, and (3) DFT/DFT + U compatibility correction. The parameterization is expressed as a unified optimization problem. We demonstrate this approach for 3d transition metal oxides, considering a target set of binary and ternary oxides. With a total of 37 measured formation enthalpies taken from the literature, the dataset is augmented by the reaction energies of 1710 unique reactions that were derived from the formation energies by systematic enumeration. To ensure a balanced dataset across the available data, the reactions were grouped by their similarity using clustering and suitably weighted. The parameterization is validated using leave-one-out cross validation (CV), a standard technique for the validation of statistical models. We apply the methodology to the strongly constrained and appropriately normed (SCAN) density functional. Based on the CV score, the error of binary (ternary) oxide formation energies is reduced by 40% (75%) to 0.10 (0.03) eV/atom. A simplified correction scheme that does not involve SCAN/SCAN + U compatibility terms still achieves an error reduction of 30% (25%). The method and tools demonstrated here can be applied to other classes of materials or to parameterize the corrections to optimize DFT + U performance for other target physical properties.

36 MATERIALS SCIENCE↗

Efficient Calculation of NMR Shielding Constants Using Composite Method Approximations and Locally Dense Basis Sets

This paper presents a systematic study of applying composite method approximations with locally dense basis sets (LDBS) to efficiently calculate NMR shielding constants in small and medium-sized molecules. The pcSseg-n series of basis sets are shown to have similar accuracy to the pcS-n series when n ≥ 1 and can slightly reduce computational costs. We identify two different LDBS partition schemes that perform very effectively for density functional calculations. Here, we select a large subset of the recent NS372 database containing 290 H, C, N, and O shielding values evaluated by reference methods on 106 molecules to carefully assess methods of the high, medium, and low computational costs to make practical recommendations. Our assessment covers conventional electronic structure methods (density functional theory and wave function) with global basis calculations, as well as their use in one of the satisfactory LDBS approaches, and a range of composite approaches, also with and without LDBS. Altogether 99 methods are evaluated. On this basis, we recommend different methods to reach three different levels of accuracy and time requirements across the four nuclei considered.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrogen Bond Benchmark: Focal‐Point Analysis and Assessment of DFT Functionals

We performed a hierarchical, convergent ab initio benchmark study and systematically analyzed the performance of density functional approximations for describing hydrogen bonds in small neutral, cationic, and anionic complexes, as well as in larger systems involving amide, urea, deltamide, and squaramide moieties. Focal point analyses (FPA), extrapolating to the ab initio limit, were carried out using correlated wave function methods up to CCSDT(Q) for the small complexes and CCSD(T) for the larger systems, together with correlation-consistent Gaussian basis sets up to the complete basis set limit. Optimized geometries and vibrational frequencies were obtained at the CCSD(T) level. The resulting FPA hydrogen-bond energies converge within a few tenths of a kcal mol −1 . These reference data were used to evaluate 60 density functionals (including 12 dispersion-corrected), spanning the local-density approximation (LDA), generalized gradient approximations (GGAs), meta-GGAs, hybrids, meta-hybrids, double-hybrids, and range-separated hybrids. Overall, the meta-hybrid M06-2X provides the best performance for both hydrogen bond energies and geometries, while the dispersion-corrected GGAs BLYP-D3(BJ) and BLYP-D4 also yield accurate hydrogen-bond data and can serve as cost-effective options for studying large and complex systems.

coupled cluster theory↗

Improving coastal water level estimation by merging nadir-only satellite altimetry data into a hydrodynamic model

Providing robust real time flood warnings is of paramount importance to coastal communities. Although state-of-the-art hydrodynamic models are capable of robustly predicting Coastal Water Levels (CWL), unresolved drivers affecting level fluctuations are often not represented by the model governing equations. This work evaluates a novel method to improve the performance of the ADvanced CIRCulation (ADCIRC) hydrodynamic model by assimilating observations from four nadir-only satellite altimetry missions against a set of National Oceanic and Atmospheric Administration (NOAA) gauge stations located across the entire U.S. East Coast. Two different types of simulations were performed – Open Loop (OL) and Data Assimilation (DA). Five different simulations were performed where four different satellite altimetry observations were assimilated individually and combined with two different scenarios – with and without considering the data quality flags. Results indicate that, despite their limited spatial coverage, merging nadir-only observations into ADCIRC from the newly launched Surface Water and Ocean Topography (SWOT)’s nadir altimeter can improve the model performance at 76% of the gauge locations, whereas Sentinel-6 improves 73% of the total locations, Jason-3 74%, and SARAL 21%. Furthermore, combining observations from SWOT-nadir, Jason-3, and Sentinel-6 can improve the ADCIRC performance at more than 80% of the gauge locations for 107-day simulation. Nadir-only satellite altimetry observations can be useful for improving the model performance even if flagged as “poor quality” near the coast. When the flagged data are disregarded, SWOT can improve ADCIRC at 78%, Sentinel-6 at 73%, Jason-3 at 53%, and SARAL at 21% of the gauge locations. The ability to improve the model simulations largely depends on the availability of a satellite overpass nearby. Therefore, model performance can be further enhanced if satellite observations are available during a storm surge event, stressing the importance of frequent satellite overpasses.

Aafnan Bhuiyan, Soelem↗

A machine learning photon detection algorithm for coherent x-ray ultrafast fluctuation analysis

X-ray free electron laser experiments have brought unique capabilities and opened new directions in research, such as creating new states of matter or directly measuring atomic motion. One such area is the ability to use finely spaced sets of coherent x-ray pulses to be compared after scattering from a dynamic system at different times. This enables the study of fluctuations in many-body quantum systems at the level of the ultrafast pulse durations, but this method has been limited to a select number of examples and required complex and advanced analytical tools. By applying a new methodology to this problem, we have made qualitative advances in three separate areas that will likely also find application to new fields. As compared to the “droplet-type” models, which typically are used to estimate the photon distributions on pixelated detectors to obtain the coherent x-ray speckle patterns, our algorithm achieves an order of magnitude speedup on CPU hardware and two orders of magnitude improvement on GPU hardware. We also find that it retains accuracy in low-contrast conditions, which is the typical regime for many experiments in structural dynamics. Finally, it can predict photon distributions in high average-intensity applications, a regime which up until now has not been accessible. Our artificial intelligence-assisted algorithm will enable a wider adoption of x-ray coherence spectroscopies, by both automating previously challenging analyses and enabling new experiments that were not otherwise feasible without the developments described in this work.

47 OTHER INSTRUMENTATION↗

Bardeen-Cooper-Schrieffer pairing of composite fermions

Topological pairing of composite fermions has led to remarkable ideas, such as excitations obeying non-Abelian braid statistics and topological quantum computation. Here, we construct a p-wave paired Bardeen-Cooper-Schrieffer (BCS) wave function for composite fermions in the torus geometry, which is a convenient geometry for formulating momentum space pairing as well as for revealing the underlying composite-fermion Fermi sea. Following the standard BCS approach, we minimize the Coulomb interaction energy at half filling in the lowest and the second Landau levels, which correspond to filling factors ν = 1/2 and ν = 5/2 in GaAs quantum wells, by optimizing two variational parameters that are analogous to the gap and the Debye cut-off energy of the BCS theory. Our results show no evidence for pairing at ν = 1/2 but a clear evidence for pairing at ν = 5/2. To a good approximation, the highest overlap between the exact Coulomb ground state at ν = 5/2 and the BCS state is obtained for parameters that minimize the energy of the latter, thereby providing support for the physics of composite-fermion pairing as the mechanism for the 5/2 fractional quantum Hall effect. We discuss the issue of modular covariance of the composite-fermion BCS wave function, and calculate its Hall viscosity and pair correlation function. By similar methods, we look for but do not find an instability to s-wave pairing for a spin-singlet composite-fermion Fermi sea at half-filled lowest Landau level in a system where the Zeeman splitting has been set to zero.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Effect of Blade Planform Variation on a Small-Scale Hovering Rotor

A hover test was conducted on a small-scale rotor model for three sets of tapered rotor blades and a baseline rectangular planform rotor blade. All configurations had the same airfoils, twist, and thrust-weighted solidity. The tapered blade planforms had taper initiating at 50, 75, and 94 percent of the blade radius with a taper ratio of 3 to 1 for each blade set. The experiment was conducted for a range of thrust coefficients, and the data were compared to the predictions of three hover analysis methods. The data show the 94 percent tapered blade was slightly more efficient at the higher rotor thrust levels. The other tapered planform rotors did not show the expected improvement over the baseline rotor, and all configurations had similar performance for low thrust coefficients. None of the analysis methods correlated well with the experimental data.

Althoff, Susan L.↗

Efficient design of CMOS TSC checkers

This paper considers the design of an efficient, robustly testable, CMOS Totally Self-Checking (TSC) Checker for k-out-of-2k codes. Most existing implementations use primitive gates and assume the single stuck-at fault model. The self-testing property has been found to fail for CMOS TSC checkers under the stuck-open fault model due to timing skews and arbitrary delays in the circuit. A new four level design using CMOS primitive gates (NAND, NOR, INVERTERS) is presented. This design retains its properties under the stuck-open fault model. Additionally, this method offers an impressive reduction (greater than 70 percent) in gate count, gate inputs, and test set size when compared to the existing method. This implementation is easily realizable and is based on Anderson's technique. A thorough comparative study has been made on the proposed implementation and Kundu's implementation and the results indicate that the proposed one is better than Kundu's in all respects for k-out-of-2k codes.

Biddappa, Anita↗

Resource-Efficient Chemistry on Quantum Computers with the Variational Quantum Eigensolver and The Double Unitary Coupled-Cluster approach

Applications of quantum simulation algorithms to obtain electronic energies of molecules on noisy intermediate-scale quantum (NISQ) devices require careful consideration of resources describing the complex electron correlation effects. In modeling second-quantized problems, the biggest challenge confronted is that the number of qubits scales linearly with the size of molecular basis. This poses a significant limitation on the size of the basis sets and the number of correlated electrons included in quantum simulations of chemical processes. To address this issue and to enable more realistic simulations on NISQ computers, we employ the double unitary coupled-cluster (DUCC) method to effectively downfold correlation effects into the reduced-size orbital space, commonly referred to as the active space. Using downfolding techniques, we demonstrate that properly constructed effective Hamiltonians can capture the effect of the whole orbital space in small-size active spaces. Combining the downfolding pre-processing technique with the Variational Quantum Eigensolver, we solve for the ground-state energy of H2 and Li2 in the cc-pVTZ basis using the DUCC-reduced active spaces. We compare these results to full configuration-interaction and high-level coupled-cluster reference calculations.

quantum computing, variational quantum solver, cou↗

Complete collision data set for electrons scattering on molecular hydrogen and its isotopologues: II. Fully vibrationally-resolved electronic excitation of the isotopologues of H 2 (X 1 $Σ^{+}_{g}$)

Here, we present a comprehensive set of vibrationally-resolved cross sections for electron-impact electronic excitation of the isotopologues of molecular hydrogen (D 2 , T 2 , HD, HT, and DT) initially in the ground electronic state. We apply the adiabatic-nuclei molecular convergent close-coupling (MCCC) method to calculate cross sections from threshold to 500 eV for excitation of all bound vibrational levels and dissociative excitation of the B 1 $Σ^{+}_{g}$, C 1 Π u , EF 1 $Σ^{+}_{g}$, B' 1 $Σ^{+}_{g}$, GK 1 $Σ^{+}_{g}$, I 1 Π g , J 1 Δ g , D 1 Π u , H 1 $Σ^{+}_{g}$, b 1 $Σ^{+}_{g}$, c 3 Π u , a 3 $Σ^{+}_{g}$, e 3 $Σ^{+}_{u}$, d 3 Π u , h 3 $Σ^{+}_{g}$, g 3 $Σ^{+}_{g}$, i 3 Π g , and j 3 Δ g electronic states from all bound vibrational levels of the ground electronic (X 1 $Σ^{+}_{g}$) state. Including the previously-published MCCC e-H2 cross sections the data set contains cross sections for over 60,000 electronic and vibrational transitions. The cross sections are presented in graphical form and provided as both numerical values and analytic fit functions in supplementary data files. The data can also be downloaded from the MCCC database at mccc-db.org.

74 ATOMIC AND MOLECULAR PHYSICS↗

Surface wind convergence as a short-term predictor of cloud-to-ground lightning at Kennedy Space Center

Cloud-to-ground lightning is a significant forecast problem at the Kennedy Space Center (KSC) in Florida. In this study, cloud-to-ground lightning is related in time and space to surface convergence for 244 days during the convective seasons of 1985 and 1986 over a 790 sq-km network at KSC. The method uses surface convergence, particularly the average over the area, to identify the potential for new, local thunderstorm growth, and it can be used to specify the likely time and location of lightning during the life cycle of the convection. A threshold of 75 x 10 to the -6th/s change in divergence is the main criterion used to define a convergence event, and a set of flashes less than 30 min apart defines a lightning event. Time intervals are found from the study to be approximately 1 h from beginning convergence to first flash, and another hour to the end of lightning. The influences of low-level winds and midlevel moisture in determining the location and intensity of convection are discussed. This is the first known dynamically-based forecast method for lightning prediction. The technique, currently in use at KSC, has been shown to be a systematic, quantitative tool for predicting lightning onset in situations where conventional analysis tools such as radar and satellite are limited.

Watson, Andrew I.↗

Satellite/radiosonde comparison

Collocated measurements of radiosonde and TIROS Operational Vertical Sounder (TOVS) data are compared to determine whether significant latitudinal, seasonal, or instrumental biases exist. Long-wave structure determined by each system is being examined for correlation. Because U.S. radiosonde data are archived uncorrected, an effort to correct the measurements is being considered. These corrections will be applied to 7 years of measurements. New comparisons will then be made using corrected radiosonde and TOVS data. A regression method is used to retrieve temperatures, and radiosonde zonal means are used to update the regression coefficients. Preliminary results of auto-correlation analysis indicate that detection of long-wave structure in each set of data is slightly different with some levels and locations experiencing different wave periods or amplitudes. Scatter diagrams and linear regression for each layer show bias in the mean temperatures. Winter-time measurements show poorer correlations due to noisy measurements.

Schmidlin, F. J.↗

The NASA Ocean Data System at the Jet Propulsion Laboratory

Global change studies require satellite oceanographic observations archived in an active data center. This paper describes the activities of an experimental active oceanographic data archive center specializing in distribution of high-level oceanographic data products produced by research oceanographers from satellite altimeter, scatterometer, and microwave and infrared radiometer measurements. Methods to encourage data sharing practices were developed. Services initiated to help oceanographers conduct research more effectively included rapid delivery of data, reprocessing data sets, subsetting of large data sets, and distribution of multiple data sets on a single medium.

Halpern, David↗

Interfacial Reaction Studies Using ONIOM

In this report, we focus on the calculations of the energetics and chemical kinetics of heterogeneous reactions for Organometallic vapor phase epitaxy (OMVPE). The work described in this report builds upon our own previous thermochemical and chemical kinetics studies. The first of these articles refers to the prediction of thermochemical properties, and the latter one deals with the prediction of rate constants for gaseous homolytic dissociation reactions. The calculations of this investigation are at the microscopic level. The systems chosen consisted of a gallium nitride (GaN) substrate, and molecular nitrogen (N2) and ammonia (NH3) as adsorbants. The energetics for the adsorption and the adsorbant dissociation processes were estimated, and reaction rate constants for the dissociation reactions of free and adsorbed molecules were predicted. The energetics for substrate decomposition was also computed. The ONIOM method, implemented in the Gaussian98 program, was used to perform the calculations. This approach has been selected since it allows dividing the system into two layers that can be treated at different levels of accuracy. The atoms of the substrate were modeled using molecular mechanics6 with universal force fields, whereas the adsorbed molecules were approximated using quantum mechanics, based on density functional theory methods with B3LYP functionals and 6-311G(d,p) basis sets. Calculations for the substrate were performed in slabs of several unit cells in each direction. The N2 and NH3 adsorbates were attached to a central location at the Ga-lined surface.

Cardelino, Beatriz H.↗