Search NASA⌕ Search

SEARCH · Search NASA

Results for “text analytics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

SchemaOnRead: A Package for Schema-on-Read in R

Schema-on-read is an agile approach to data storage and retrieval that defers investments in data organization until production queries need to be run by working with data directly in native form. Schema-on-read functions have been implemented in a wide range of analytical systems, most notably Hadoop. SchemaOnRead is a CRAN package that uses R’s flexible data representations to provide transparent and convenient support for the schema-on-read paradigm in R. The schema-on- read tools within the package include a single function call that recursively reads folders with text, comma separated value, raster image, R data, HDF5, NetCDF, spreadsheet, Weka, Epi Info, Pajek network, R network, HTML, SPSS, Systat, and Stata files. The provided tools can be used as-is or easily adapted to implement customized schema-on-read tool chains in R. This paper’s contribution is that it introduces and describes SchemaOnRead, the first R package specifically focused on providing explicit schema-on-read support in R.

Data Science↗

SchemaOnRead: A Package for Schema-on-Read in R

Schema-on-read is an agile approach to data storage and retrieval that defers investments in data organization until production queries need to be run by working with data directly in native form. Schema-on-read functions have been implemented in a wide range of analytical systems, most notably Hadoop. SchemaOnRead is a CRAN package that uses R’s flexible data representations to provide transparent and convenient support for the schema-on-read paradigm in R. The schema-on- read tools within the package include a single function call that recursively reads folders with text, comma separated value, raster image, R data, HDF5, NetCDF, spreadsheet, Weka, Epi Info, Pajek network, R network, HTML, SPSS, Systat, and Stata files. The provided tools can be used as-is or easily adapted to implement customized schema-on-read tool chains in R. This paper’s contribution is that it introduces and describes SchemaOnRead, the first R package specifically focused on providing explicit schema-on-read support in R.

Data Science↗

Kinetics and Energetics of Electron Transfer to Dimer Radical Cations

In this work, spectra of the dimer cations naphthalene (Nap 2 •+ ) and ethene (Ethene 2 •+ ) were measured in liquid dichloromethane (DCM). The spectra peak at very different energies, 1.2 and 3.3 eV. In DCM dimerization stabilizes Nap 2 •+ by Δ$G_\text{d}°$(Nap 2 •+ ) = -218 meV relative to the monomer Nap •+ as determined from the dimerization equilibrium constant. Both dimers can transfer a positive charge to hole acceptor molecules, but for both the rate constants rise more gradually with reaction energetics than do many charge transfer reactions previously studied. A striking observation finds that the rate constant for hole transfer from the Nap 2 •+ dimer to phenanthrene is smaller by two decades than that from biphenyl•+ monomer to Nap, although both reactions have the same –Δ$\textit{G}°$=0.05 eV. A plausible interpretation for these observations is the presence of an energy of reorganization, λ(M 2 ), for the dimer that involves movement apart of the two partners in the dimer. While the dimerization equilibrium cannot be measured for Ethene 2 •+ the charge transfer data imply that both Δ$G_\text{d}°$(Ethene 2 •+ ) and λ(Ethene 2 •+ ), are considerably larger, perhaps by factors of 2-4 than for Nap 2 •+ .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Convective carbon dioxide dissolution in a closed porous medium at low pressure

Motivated by the persistence of natural carbon dioxide ( $\text{CO}_{2}$ ) fields, we investigate the convective dissolution of $\text{CO}_{2}$ at low pressure (below 1 MPa) in a closed system, where the pressure in the gas declines as convection proceeds. This introduces a negative feedback that reduces the convective dissolution rate even before the brine becomes saturated. We analyse the case of an ideal gas with a solubility given by Henry’s law, in the limits of very low and very high Rayleigh numbers. The equilibrium state in this system is determined by the dimensionless dissolution capacity, $\unicode[STIX]{x1D6F1}$ , which gives the fraction of the gas that can be dissolved into the underlying brine. Analytic approximations of the pure diffusion problem with $\unicode[STIX]{x1D6F1}>0$ show that the diffusive base state is no longer self-similar and that diffusive mass transfer declines rapidly with time. Direct numerical simulations at high Rayleigh numbers show that no constant flux regime exists for $\unicode[STIX]{x1D6F1}>0$ ; nevertheless, the quantity $F/C_{s}^{2}$ remains constant, where $F$ is the dissolution flux and $C_{s}$ is the dissolved concentration at the top of the domain. Simple mathematical models are developed to predict the evolution of $C_{s}$ and $F$ for high-Rayleigh-number convection in a closed system. The negative feedback that limits convection in closed systems may explain the persistence of natural $\text{CO}_{2}$ accumulations over millennial time scales.

Mechanics↗

Diving into a holographic superconductor

Charged black holes in anti-de Sitter space become unstable to forming charged scalar hair at low temperatures T < T_\text{c} T < T c . This phenomenon is a holographic realization of superconductivity. We look inside the horizon of these holographic superconductors and find intricate dynamical behavior. The spacetime ends at a spacelike Kasner singularity, and there is no Cauchy horizon. Before reaching the singularity, there are several intermediate regimes which we study both analytically and numerically. These include strong Josephson oscillations in the condensate and possible `Kasner inversions’ in which after many e-folds of expansion, the Einstein-Rosen bridge contracts towards the singularity. Due to the Josephson oscillations, the number of Kasner inversions depends very sensitively on T T , and diverges at a discrete set of temperatures \{T_n\} { T n } that accumulate at T_c T c . Near these T_n T n , the final Kasner exponent exhibits fractal-like behavior.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗

MArVD2: a machine learning enhanced tool to discriminate between archaeal and bacterial viruses in viral datasets

Abstract Our knowledge of viral sequence space has exploded with advancing sequencing technologies and large-scale sampling and analytical efforts. Though archaea are important and abundant prokaryotes in many systems, our knowledge of archaeal viruses outside of extreme environments is limited. This largely stems from the lack of a robust, high-throughput, and systematic way to distinguish between bacterial and archaeal viruses in datasets of curated viruses. Here we upgrade our prior text-based tool (MArVD) via training and testing a random forest machine learning algorithm against a newly curated dataset of archaeal viruses. After optimization, MArVD2 presented a significant improvement over its predecessor in terms of scalability, usability, and flexibility, and will allow user-defined custom training datasets as archaeal virus discovery progresses. Benchmarking showed that a model trained with viral sequences from the hypersaline, marine, and hot spring environments correctly classified 85% of the archaeal viruses with a false detection rate below 2% using a random forest prediction threshold of 80% in a separate benchmarking dataset from the same habitats.

Vik, Dean (ORCID:000000027546899X)↗

A low-luminosity core-collapse supernova very similar to SN 2005cs

ABSTRACT We present observations and analysis of PSN J17292918+7542390, a low-luminosity Type II-P supernova (LL SN IIP). The observed sample of such events is still low, and their nature is still under debate. Such SNe are similar to SN 2005cs, a well-observed LL Type II-P event, having low expansion velocities, and small ejected 56Ni mass. We have developed a robust and relatively fast Monte Carlo code that fits semi-analytic models to light curves of core-collapse SNe. This allows the estimation of the most important physical parameters, like the radius of the progenitor star, the mass of the ejected envelope, the mass of the radioactive nickel synthesized during the explosion, among others. PSN J17292918+7542390 has $R_0 = 91_{-70}^{+119} \times 10^{11} \, \text{cm}$, $M_\text{ej} = 9.89_{-1.00}^{+2.10} \, \mathrm{ M}_{\odot }$, $E_{\mbox{kin}} = 0.65_{-0.18}^{+0.19} \, \text{foe}$, and $v_{\mbox{exp}} = 3332_{-347}^{+216}$ km s−1, for its progenitor radius, ejecta mass, kinetic energy, and expansion velocity, respectively. The initial nickel mass of the PSN J17292918+7542390 turned out to be $1.55_{-0.70}^{+0.75} \times 10^{-3} \, \mathrm{M}_{\odot }$. The measured photospheric velocity at the earliest observed phase is 7000 km s−1. As far as we can tell based on the small population of observed LL SNe IIP, the determined values are typical for these events.

Jäger, Jr, Zoltán↗

The expressivity of classical and quantum neural networks on entanglement entropy

Abstract Analytically continuing the von Neumann entropy from Rényi entropies is a challenging task in quantum field theory. While then-th Rényi entropy can be computed using the replica method in the path integral representation of quantum field theory, the analytic continuation can only be achieved for some simple systems on a case-by-case basis. In this work, we propose a general framework to tackle this problem using classical and quantum neural networks with supervised learning. We begin by studying several examples with known von Neumann entropy, where the input data is generated by representing$${\text {Tr}}\rho _A^n$$ Tr ρ A n with a generating function. We adopt KerasTuner to determine the optimal network architecture and hyperparameters with limited data. In addition, we frame a similar problem in terms of quantum machine learning models, where the expressivity of the quantum models for the entanglement entropy as a partial Fourier series is established. Our proposed methods can accurately predict the von Neumann and Rényi entropies numerically, highlighting the potential of deep learning techniques for solving problems in quantum information theory.

Physics↗

Direct computation of orbital sunrise or sunset event parameters

An analytical method is developed for determining the geometrical parameters which are needed to describe the viewing angles of the Sun relative to an orbiting spacecraft when the Sun rises or sets with respect to the spacecraft. These equations are rigorous and are frequently used for parametric studies relative to mission planning and for determining instrument parameters. The text is wholly self-contained in that no external reference to ephemerides or other astronomical tables is needed. Equations are presented which allow the computation of Greenwich sidereal time and right ascension and declination of the Sun generally to within a few seconds of arc, or a few tenths of a second in time.

Buglia, J. J.↗

Rotational Modulation of à 2 A State Photodissociation of HCO via Renner-Teller Nonadiabatic Transitions

By examining the product-state distribution of a prototypical non- adiabatic predissociation system, HCO($Ã^2A''–\tilde X^2A'$), we demonstrate here that the dissociation dynamics is strongly modulated by parent rotational quantum numbers. The predissociation of the nominal ($ν_{\text{C–H}} = 0, ν_{\text{bend}}, ν_{\text{C–O}} = 1$) vibronic levels of the $AÃ^2A''$ state surprisingly gives rise to both vibrational ground and excited states of the CO product, despite the assumed spectator nature of the CO moiety. This anomaly is attributed to the dependence of the lifetime of the vibronic resonance facilitated by the Renner–Teller interaction on the parent rotational angular momentum quantum numbers coupled with transient intensity borrowing from nearby vibronic resonances with $ν_{\text{C–O}} = 0$. This unique phenomenon is a purely quantum mechanical behavior that has no classical analogue.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

System engineering toolbox for design-oriented engineers

This system engineering toolbox is designed to provide tools and methodologies to the design-oriented systems engineer. A tool is defined as a set of procedures to accomplish a specific function. A methodology is defined as a collection of tools, rules, and postulates to accomplish a purpose. For each concept addressed in the toolbox, the following information is provided: (1) description, (2) application, (3) procedures, (4) examples, if practical, (5) advantages, (6) limitations, and (7) bibliography and/or references. The scope of the document includes concept development tools, system safety and reliability tools, design-related analytical tools, graphical data interpretation tools, a brief description of common statistical tools and methodologies, so-called total quality management tools, and trend analysis tools. Both relationship to project phase and primary functional usage of the tools are also delineated. The toolbox also includes a case study for illustrative purposes. Fifty-five tools are delineated in the text.

Goldberg, B. E.↗

Gradient-based optimization of 3D MHD equilibria

Using recently developed adjoint methods for computing the shape derivatives of functions that depend on magnetohydrodynamic (MHD) equilibria (Antonsen et al. , J. Plasma Phys. , vol. 85, issue 2, 2019; Paul et al. , J. Plasma Phys. , vol. 86, issue 1, 2020), we present the first example of analytic gradient-based optimization of fixed-boundary stellarator equilibria. We take advantage of gradient information to optimize figures of merit of relevance for stellarator design, including the rotational transform, magnetic well and quasi-symmetry near the axis. With the application of the adjoint method, we reduce the number of equilibrium evaluations by the dimension of the optimization space ( ${\sim }50\text {--}500$ ) in comparison with a finite-difference gradient-based method. We discuss regularization objectives of relevance for fixed-boundary optimization, including a novel method that prevents self-intersection of the plasma boundary. We present several optimized equilibria, including a vacuum field with very low magnetic shear throughout the volume.

Physics↗

Estimation of Melting-Layer Cooling Rate from Dual-Polarization Radar: Spectral Bin Model Simulations

Diabatic cooling from hydrometeor phase changes in the stratiform melting layer is of great interest to both operational forecasters and modelers for its societal and dynamical consequences. Attempts to estimate the melting-layer cooling rate typically rely on either the budgeting of hydrometeor content estimated from reflectivity Z or model-generated lookup tables scaled by the magnitude of Z in the bright band. Recent advances have been made in developing methods to observe the unique polarimetric characteristics of melting snow and the additional microphysical information they may contain. However, to date no work has looked at the thermodynamic information available from the polarimetric radar brightband signature. In this study, a one-dimensional spectral bin model of melting snow and a coupled polarimetric operator are used to study the relation between the polarimetric radar bright band and the melting-layer cooling rate. Simulations using a fixed particle size distribution (PSD) and variable environmental conditions show that the height and thickness of the bright band and the maximum brightband Z and specific differential phase shift [Formula: see text] are all sensitive to the ambient environment, while the differential reflectivity [Formula: see text] is relatively insensitive. Additional simulations of 2700 PSDs based on in situ observations above the melting layer indicate that the maximum Z, [Formula: see text], and [Formula: see text] within the melting layer are poorly correlated with the maximum cooling rate while [Formula: see text] is strongly correlated. Finally, model simulations suggest that, in addition to riming, concurrent changes in aggregation and precipitation intensity and the associated cooling may plausibly cause observed sagging brightband signatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Force-Modulated Selectivity of the Rhodium-Catalyzed Hydroformylation of 1-Alkenes

Here we quantify the regio- chemo-, and enantioselectivity of the hydroformylation of 1-alkenes catalyzed by Rh(I) complexes containing chiral macrocyclic biaryl bis(phosphine) ligands as a function of mechanical force applied to the biaryl backbone of these ligands. Extension forces increase the regioselectivity of the hydroformylation of 1-octene from l:b = 1.2 to 1.9 and decrease the chemoselectivity for C 9 aldehyde relative to 2-octene from 96% to 20% across a ~230 pN change in applied force. Extension forces decrease the enantioselectivity of the hydroformylation of styrene from 28% to 18% ee across a similar force range. Variable temperature 1 H and 31 P NMR analysis of five-coordinate rhodium complexes of the form (P–P)Rh(CO) 2 H established structures in which the bisphosphine ligand occupies one equatorial and one apical position in the trigonal bipyramid with rapid interconversion of the equatorial and apical phosphorus atoms ($ΔG^‡_{223 \text{K}}$ = 9.6–9.9 kcal/mol). Neither the isomeric composition nor fluxional behavior of these complexes was detectably perturbed across a ~300 pN change in applied force.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Complete collision data set for electrons scattering on molecular hydrogen and its isotopologues: I. Fully vibrationally-resolved electronic excitation of H 2 $X^1Σ^+_g)$

Here, we present a comprehensive set of vibrationally-resolved cross sections for electron-impact electronic excitation of molecular hydrogen suitable for implementation in collisional-radiative models. The adiabatic-nuclei molecular convergent close-coupling method is used to calculate cross sections for excitation of all bound vibrational levels and dissociative excitation of the B 1 &#x3A3; u + , C 1 &#x3A0; u , E F 1 &#x3A3; g + , B &#x2032; 1 &#x3A3; u + , G K 1 &#x3A3; g + , I 1 &#x3A0; g , J 1 &#x394; g , D 1 &#x3A0; u , H 1 &#x3A3; g + , b 3 &#x3A3; u + , c 3 &#x3A0; u , a 3 &#x3A3; g + , e 3 &#x3A3; u + , d 3 &#x3A0; u , h 3 &#x3A3; g + , g 3 &#x3A3; g + , i 3 &#x3A0; g , and j 3 &#x394; g electronic states from all –14 bound vibrational levels of the ground electronic ($\text{X}$ $^1&#x3A3^+_g$) state. The data set consists of cross sections from threshold to 500 eV for over 5000 transitions, representing all possible electronic and vibrational transitions between the state and the –3 singlet and triplet states (where refers to the united-atoms-limit principle quantum number). The cross sections are presented in graphical form and provided as both numerical values and analytic fit functions in supplementary data files.

74 ATOMIC AND MOLECULAR PHYSICS↗