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12 results for “quadrature”
Dataset for NMR quadrature echo and T1 saturation recovery pulse sequences underlying the publication 'On the quantification of solid phases in hydrated cement paste by 1H nuclear magnetic resonance relaxometry'
<p>This record comprises the datasets of combined 1H NMR quadrature echo and T1 saturation recovery pulse sequences underlying the publication “On the quantification of solid phases in hydrated cement paste by 1H nuclear magnetic resonance relaxometry” by Robert Schulte Holthausen & Peter J. McDonald, Cement and Concrete Research, https://doi.org/10.1016/j.cemconres.2020.106095.</p> <p><br> In this work different solid phases, important to cement paste hydration, are investigated with low-field bench top 1H nuclear magnetic resonance with a view to developing an alternate characterisation methodology that requires minimal invasive or destructive sample preparation.</p> <p><br> A combination of the well-established quadrature echo pulse sequence with variable pulse gap together with a T1 saturation recovery quadrature echo pulse sequence is used.</p>
Eclipse2017 17-hour CSV quadrature, in-phase WWVB carrier in one-second increments
<p>Boxcar-integrated I&Q data sets of WWVB (60 kHz) received with magnetic loop antenna at 43.21N, 79.89W (Hamilton, ON). Three data files start at 09:00:00 UTC. on Aug 20, Aug 21, Aug 22, 2017. Each file spans seventeen hours.</p> <p>Each I&Q boxcar data point represents average WWVB carrier integrated over the one-second period starting with WWVB's BPSK phase-transition point, one-hundred milliseconds after start-of-second. The 60 kHz carrier downconverter oscillator is a Valpey-Fisher VF150 crystal oscillator which is free-running. Its phase and frequency vary with time and temperature. It is possible to determine WWVB's legacy AM timecodes from <span class="math-tex">\(amplitude = \sqrt{inphase^2+ quadrature^2}\)</span></p> <p>File format is CSV text compatible, quadrature delimited by ASCII space '0x20' from in-phase. Quadrature and In-phase data are signed decimal integers lying in all four phase quadrants.</p>
Efficient spherical quadrature rules with positive weights
<p>The function "SphQuadrat.m" returns efficient quadrature rules on the sphere in a 3-dimensional space. The quadrature rules consist of the coordinates of the samling points and the (positive) weights of each point. Cartesian and spherical coordinate systems are available; please note that the notation of elevation angles <em>θ</em> in the spherical coordinate systems differs from that in MATLAB. That is, the function returns vertical angles <em>θ</em> measured from the z-axis.</p> <p>Available exactitude degrees of the quadratures are 0,2,4,...,100.</p> <p>MAT files containing the points and the weights of the quadratures are named as "xxx-yyyyy.mat", where "xxx" denotes the degree of exactitude and "yyyyy" denotes the number of points.</p> <p>By default, the weights are normalized as sum(weight)=1, while the function also provides 4pi-normalization sum(weight)=4*pi and the-number-of-points-normalization sum(weight)=numel(weight).</p> <p>Reference: Manuel Gräf, <a href="https://www-user.tu-chemnitz.de/~potts/workgroup/graef/quadrature/papers/Gr13Diss.pdf">Efficient Algorithms for the Computation of Optimal Quadrature Points on Riemannian Manifolds</a>, Ph.D. thesis, Technische Universität Chemnitz, (2013)</p>
Dataset and data processing tools of EPL 139 (2022) 55002 — Harmonic calibration of quadrature phase interferometry
<p>Dataset for <em>EPL</em> <strong>139</strong> (2022) 55002 — Harmonic calibration of quadrature phase interferometry</p> <p><strong>Scripts: </strong>the main Matlab script to analyse all data is <strong>analyseall.m</strong>, and uses all other scripts and functions (<strong>*.m</strong>). See comments in this main script for details. The script <strong>DefineDatasets.m,</strong> and its output <strong>Dataset.mat</strong>, were run before to define the main parameters of the 20 datasets, and define the frequency range where to estimate the background noise to be subtracted from the spectra of the driven cantilever when computing the total harmonic distortion.</p> <p><strong>Data:</strong> the 100 data files (.mat) have the following name scheme: [driving-frequency]-[Amplitude]-(low frequency external phase)-001 to 005.mat. For example 1kHz-10nm-w1Hz150nm-001.mat correspond to a driving of the cantilever at 1kHz, with an oscillation amplitude close to 10nm, with a low frequency driving of the external optical phase at 1Hz and equivalent 150nm amplitude. 001 stand for the first of the five files corresponding to this measurement. Note that the low frequency driving is optional. The main driving frequency is either directly given in kHz, or corresponds to one of the 2 first resonance modes of the cantilever (mode1 at 13.4kHz, and mode2approx at 84.6 kHz). Each of these data files contains 5 variables: Cx and Cy are the 2 outputs of the quadrature phase interferometer (1s of acquisition, 2e6 samples), fs is the sampling frequency (2 MHz), Ix and Iy are the mean total intensities on the photodiodes corresponding to Cx and Cy (units: A, this information can be useful to estimate the expected shot noise floor on the measurement).</p>
Data supporting the publication "Quadrature nonreciprocity in bosonic networks without breaking time-reversal symmetry"
<p>Data supporting the publication "Quadrature nonreciprocity in bosonic networks without breaking time-reversal symmetry"</p>
Dataset of stereo and multi-channel IRs for a 50-point Lebedev quadrature.
<p>We present a free dataset of Impulse Response measurements for all positions on a 50-point Lebedev arranged loudspeaker array for a variety of stereo microphone configurations, 32 Eigenmic capsules, and up to 4th Order Ambisonics. This dataset has particular relevance for those interested in training novel stereo to ambisonic upmix algorithms. </p>
Shape functions and Integration quadrature of nine 3D transition elements
<p>This file houses the text files and Matlab function files that contain the shape functions and integration quadrature of nine 3D transition elements. The Matlab function file also computes the Shape function gradient matrix that can be readily used for FE applications.</p>
Non-intrusive semi-analytical uncertainty quantification using Bayesian quadrature with application to CFD simulations
<p>The data contained in the uploaded '.zip' file is for some of the plots in the paper ‘Duan Y*, Eaton MD, Bluck MJ, 2021, Non-intrusive semi-analytical uncertainty quantification using Bayesian quadrature with application to CFD simulations, International Journal of Heat and Fluid Flow.’ (accepted)</p>
Data from: Novel Fourier quadrature transforms and analytic signal representations for nonlinear and non-stationary time series analysis
The Hilbert transform (HT) and associated Gabor analytic signal (GAS) representation are well-known and widely used mathematical formulations for modeling and analysis of signals in various applications. In this study, like the HT, to obtain quadrature component of a signal, we propose novel discrete Fourier cosine quadrature transforms (FCQTs) and discrete Fourier sine quadrature transforms (FSQTs), designated as Fourier quadrature transforms (FQTs). Using these FQTs, we propose sixteen Fourier quadrature analytic signal (FQAS) representations with following properties: (1) real part of eight FQAS representations is the original signal and imaginary part of each representation is FCQT of real part, (2) imaginary part of eight FQAS representations is the original signal and real part of each representation is FSQT of imaginary part, (3) like the GAS, Fourier spectrum of the all FQAS representations has only positive frequencies, however unlike the GAS, real and imaginary parts of FQAS representations are not orthogonal. The Fourier decomposition method (FDM) is an adaptive data analysis approach to decompose a signal into a set Fourier intrinsic band functions. This study also proposes new formulations of the FDM using discrete cosine transform with GAS and FQAS representations, and demonstrate its efficacy for improved time-frequency-energy representation and analysis of many real-life nonlinear and non-stationary signals.
Data from: Novel Fourier quadrature transforms and analytic signal representations for nonlinear and non-stationary time series analysis
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Dataset for "Quantitative evaluation of probabilistic hazard mapping with polynomial chaos quadrature and its practical application"
<p>Dataset for the manuscript entitled "Quantitative evaluation of probabilistic hazard mapping with polynomial chaos quadrature and its practical application" by T. Tanabe, K. Tsunematsu, and K. Nishimura submitted to Journal of Geophysical Research: Earth Surface.</p> <p> </p>
Wind Solar Wind Experiment (SWE) Electron Quadrature Moments Parameters (12-15s rate) (New Mode)
Wind SWE electron moments from a later mode (post-VEIS-era) of the electron instrument. The electron moments included in this data set are derived from quadrature integration of the solar wind electron distributions (with some fitting) measured by the Wind/SWE electron instrument (see Ogilvie et al., "SWE, a comprehensive plasma instrument for the Wind spacecraft", Space Sci. Rev., 71, 55, 1995). Moment parameters are computed from 9s measurements which are usually separated by one or more 3s spin-periods. These quantities are reliable and citable with caution, meaning that the PI advises that the user should discuss their interpretations with a member of the SWE science team before publishing. The following comments are intended to aid in the use and interpretation of the prime quantities of this data set, the electron density, bulk-velocity and temperature. We compensate for the limited nature of our observations under this instrument mode by combining electron observations with bulk-velocity estimates derived from corresponding ion observations. The (13) energy channels over which observations are made are: E = 19.34, 38.68, 58.03, 77.37, 96.71, 116.1, 193.4, 290.1, 425.5, 580.3, 773.7, 1006., and 1238. eV; f(E,Az,El) [#/{cc*(cm/s)^3}] being obtained for each E, using an 8x6 grid of look-directions (Azimuth x Elevation, with ~45x9 deg. "pixels")--thus constituting an 'electron distribution'. A fitted Maxwellian model supplements the "core" regime of each distribution. N_elec [#/cc] gives the density value derived for the full distribution, while NcElec [#/cc] gives that of the core. U_eGSE and UceGSE [km/s, GSE], resp. supply the full and core bulk-velocity. P_eGSE [erg/cc, GSE] has the [Pxx, Pxy, Pxz, Pyy, Pyz, Pzz] components of the derived pressure-tensor. T_elec and TcElec [K], resp. provide the full and core total-temperatures; W_elec and WcElec [eV] specifying the corresponding thermal-energies. Te_pal, Te_per, TecPal and TecPer [K] give resp. full and core parallel- and perpendicular-temperatures (wrt B), with Te_ani and TecAni [unitless] furnishing the perpendicular/parallel temperature-anisotropies for each regime. Finally, Gyrtrp [unitless] indicates the derived electron gyrotropy. The data set reported here contains: N_elec, NcElec, U_eGSE, UceGSE, P_eGSE, T_elec, TcElec, W_elec, WcElec, Te_pal, Te_per, TecPal, TecPer, Te_ani, TecAni, and Gyrtrp (as described above).
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.