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10,553 results for “measurements”
FOAM 02: Impedance tube measurements of two porous materials with diameter variation
<p>This dataset provides the data for Reference:</p> <p>[1] Alfonso Caiazzo, Florian Kraxberger, Christian Adams, Andreas Wurzinger, Jan Boysen, Giuseppe Petrone, Stefan Schoder, Sergio De Rosa, Manfred Kaltenbacher, and Christian Adams: FOAM 02: A dataset of impedance tube measurements with different materials and diameter variations. Acta Acustica 9 (50), 2025. <a href="https://doi.org/10.1051/aacus/2025033" target="_blank" rel="noopener noreferrer">https://doi.org/10.1051/aacus/2025033</a></p> <p> </p> <p>This dataset consists of three .csv files: </p> <ul> <li>alphas.csv: absorption coefficients vs. frequencies (comma-separated), 864 rows according <br>to 864 measurements </li> <li>targets.csv: one-hot encoded, i.e., binary, vectors of the parameter combinations), 864 rows <br>according to 864 measurements. The Read_Me.pdf gives further information on the one-hot <br>encoded vectors. </li> <li>diameter.csv: calliper diametric measurement in millimetres [mm]. This file contains <br>864 rows according to 864 measurements and 6 columns that, in order, represent: top <br>diameter at 0°, top diameter at 90°, bottom diameter at 0°, bottom diameter at 90°, <br>mean diameter, and standard deviation. </li> </ul> <p><br>The frequencies range from 150 Hz to 1600 Hz with resolution of 2 Hz. Note that these limits are <br>not strictly equal to the frequency limits of the impedance tube, see ISO 10534-2. </p> <p><br>The data and code are licensed under Apache License, Version 2.0 <br>https://opensource.org/licenses/Apache-2.0 </p> <p><br>Any reuse of the data must properly cite the dataset and its authors. </p> <p> </p> <p>Contact:<br>Univ.-Prof. Dr. Christian Adams<br>Graz University of Technology<br>Inffeldgasse 16c<br>8010 Graz, Austria<br>christian.adams@tugraz.at</p>
[5G-IANA] UC6 - 5G Measurement Campaign
<p>5G network metrics (throughput, round trip time, RSRQ, and RSRP) in a particular area are collected between Nokia's Edge server and the OBU. The 5G network status was monitored using a tool developed by UULM/UDE. This dataset serves as the basis for training an LSTM model, enabling it to forecast future quantiles of RTT and throughput."</p>
Data from "Measurement of the superfluid fraction of a supersolid by Josephson effect'
<p>Here we store the data shown in the main text and methods of the manuscript "Measurement of the superfluid fraction of a supersolid by Josephson effect". The data are organized in .dat files with the following scheme: </p> <p>X axis Y axis Y axis error (if available) X axis error (if available)</p> <p>The name of the files refer to the figure number in the paper. If more datasets are plotted in the same figure, the name of the file contains additional information. For example, the file 'FigED5b_Z.dat' contains the data in Extended Data Fig. 5 for the imbalance Z.</p>
Soil respiration data measured with LI-7810 CH4/CO2/H2O Trace Gas Analyzer in Tangermuende/Germany in August 2022
<p>The dataset is associated with the publication Koschorreck, M., Kamjunke, N., Koedel, U., Rode, M., Schuetze, C., and Bussmann, I.: Diurnal versus spatial variability of greenhouse gas emissions from an anthropogenic modified German lowland river, Biogeosciences Discuss. [preprint], https://doi.org/10.5194/bg-2023-176, in review, 2023. </p> <p>It shows CO2 and CH4 initial concentrations and flux data measured with the LICOR 7810 instrument and calculated with the SoilFluxPro software V5.3.</p>
AERPAW helikite spectrum measurements at Lake Wheeler site in May 2022
<p>The AERPAW helikite flew up to 500 feet altitude, at increments of 10 meters, while waiting for 5 minutes in between altitude changes at the Lake Wheeler site on May 2022. The USRP B205mini continuously sweeps the spectrum up to 6 GHz while the helikite is at a fixed altitude, and power measurements at each frequency band are logged. The results are post-processed in Matlab to observe the spectrum occupancy at different bands and the effect of spectrum sensing altitude on the occupancy results.</p> <p>Similar datasets for August 2022 and August 2023 are in separate Dryad deposits. </p>
A Novel Laboratory Technique for Measuring Grain Size Specific Transport Characteristics of Bed Load Pulses
<p>We present a novel, time-efficient and non-destructive laboratory technique to investigate grain size specific transport characteristics of bed load pulses. The method consists of a through-water, high-resolution image acquisition followed by the application of a supervised color classification algorithm (Gaussian Maximum Likelihood Classification). Quality assessment based on a confusion matrix approach and basic random sampling showed a high classification performance. By statistically analyzing the temporal and spatial color distribution of the experimental reach, characteristic parameters to describe the propagation behavior were determined. The analyzed bed load pulse consisted of five different grain size classes of dyed quartz sand and gravel, each having a unique color. The initial experimental bed was uni-colored and contained the same size fractions as the augmented pulse.</p>
Evaluating the efficacy of drone-based thermal images for measuring wildlife abundance and physiology
<p>Monitoring the population dynamics and behaviors of wildlife is crucial for effective conservation. Although drones can provide a promising alternative to traditional monitoring methods, validation studies must be done to quantify the accuracy of drone-based abundance and distribution estimates in various biological systems. Here, we investigate the use of drones equipped with high-resolution Red-Green-Blue (RGB) and thermal cameras, along with machine learning techniques, for assessments of abundance and physiology in northern elephant seals (<em>Mirounga</em> <em>angustirostris</em>). Aerial images of N=3,415 northern elephant seals were collected at Año Nuevo Reserve during N=24 drone flights, along with ambient air temperatures, wind speed, and time-of-day data. The two-dimensional footprints and surface temperatures of seals were measured from the images. Machine learning algorithms were applied to detect seals in the imagery, and model performance was evaluated. Our findings indicate that seal detection was more accurate using RGB images compared to Thermal images, but that Thermal images could be used to determine that time of day and ambient temperature (but not wind speed or body size) strongly influenced seal external skin temperature. In other words, RGB and Thermal cameras have different strengths and weaknesses that should be carefully considered when designing research studies. Our study highlights the promising integration of drones, thermal imaging, and machine learning for wildlife research, contributing to faster, safer, cheaper, less disruptive, and more accurate wildlife monitoring and conservation efforts.</p>
CTD+ hydrographic measurement results from Admiralty Bay, Antarctica from February 2022 to February 2023
<p>The dataset contains CTD+ measurement results from Admiralty Bay on King George Island. It consists of data on conductivity, salinity, temperature, pH, turbidity, optical dissolved oxygen (ODO), fluorescent Dissolved Organic Matter (fDOM), chlorophyll A, and Phycoerythrin, measured from February 2022 to February 2023.</p><p>This dataset is a continuation of a larger measurement campaign described in: </p><p>Osińska, M., Wójcik-Długoborska, K. A., & Bialik, R. J. (2023). Annual hydrographic variability in Antarctic coastal waters infused with glacial inflow. <i>Earth System Science Data</i>, <i>15</i>(2). https://doi.org/10.5194/essd-15-607-2023</p><p>which can be found at:</p><p>Osińska, M., Wójcik-Długoborska, K. A., & Bialik, R. J. (2022). Water conductivity, salinity, temperature, turbidity, pH, fluorescent dissolved organic matter (fDOM), optical dissolved oxygen (ODO), chlorophyll a and phycoerythrin measurements in Admiralty Bay, King George Island, from Dec 2018 to Jan 2022. <i>PANGAEA</i>. https://doi.org/https://doi.org/10.1594/PANGAEA.947909</p>
Anabaena circadian clock behavior under nitrogen-poor conditions from single-cell measurements of fluorescence intensity
<p>Circadian clock arrays in multicellular filaments of the heterocyst-forming cyanobacterium Anabaena sp. strain PCC 7120 display remarkable spatio-temporal coherence under nitrogen-replete conditions. To shed light on the interplay between circadian clocks and the formation of developmental patterns, we followed the expression of a clock-controlled gene under nitrogen deprivation, at the level of individual cells. Our experiments showed that differentiation into heterocysts took place preferentially within a limited interval of the circadian clock cycle, that gene expression in different vegetative intervals along a developed filament was discoordinated, and that the circadian clock was active in individual heterocysts. Furthermore, Anabaena mutants lacking the kaiABC genes encoding the circadian clock core components produced heterocysts but failed in diazotrophy. Therefore, genes related to some aspect of nitrogen fixation, rather than early or mid-heterocyst differentiation genes, are likely affected by the absence of the clock. A bioinformatics analysis supports the notion that RpaA may play a role as master regulator of clock outputs in Anabaena, the temporal control of differentiation by the circadian clock and the involvement of the clock in proper diazotrophic growth. Together, these results suggest that under nitrogen-deficient conditions, the clock coherent unit in Anabaena is reduced from a full filament under nitrogen-rich conditions to the vegetative cell interval between heterocysts.</p>
Dataset for the uncertainty assessment of confocal measurements of industrial samples
<p>These original measurement data relate to the publication: J. Paredes, G. Kortaberria: Towards task-specific uncertainty assessment for imaging confocal microscopes, <a href="https://www.euspen.eu/knowledge-base/ICE23191.pdf">ICE23191.pdf (euspen.eu)</a>. Please refer to this open access publication for a detailed description of the measurement setup and procedure.</p><p>All data are in ASCII-format. Each file contains 2 columns, where they are the measured <i>x/y</i> and <i>z</i>-coordinates of the 2D profile extracted from the surface. All the coordinates are recorded in micrometers. The 0/90 at the end of the file names represent the orientation of the extracted profile being<i> x</i> and <i>y</i> direction respectively.</p><p>The topoghraphy files contain 3 columns, they are the measured<i> x</i>, <i>y</i>, and <i>z</i>-coordinates of the surface.</p><p><strong>Acknowledgement</strong></p><p>This project 20IND07 TracOptic has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme. Funder name: European Metrology Programme for Innovation and Research (EMPIR).</p>
Five-dimensional phase space measurement at the Spallation Neutron Source Beam Test Facility
<p>This data set consists of 285,082 two-dimensional images which collectively describe the five-dimensional phase space distribution \(f(x, x', y, y', w)\) of a 2.5 MeV, -25.6 mA H\(^-\) ion beam in the <a href="https://neutrons.ornl.gov/sns">Spallation Neutron Source</a> Beam Test Facility (SNS-BTF). Here, \(x\) and \(y\) are the transverse positions, \(x' = dx/ds\) and \(y' = dy/ds\) are the transverse slopes, \(s\) is the position along the reference trajectory, and \(w\) is the deviation from the kinetic energy of the synchronous particle.</p><p>The measurement plane is located in the medium energy beam transport (MEBT) section of the SNS-BTF, 1.3 meters after a radio-frequency quadrupole (RFQ). The measurement apparatus consists of three transverse slits (one horizontal, two vertical) and a 90-degree dipole bend followed by a fluorescent screen. The horizontal slit selects \(y\); two vertical slits select \(x\) and \(x'\); \(y'\)is a function of \(y\) and the vertical position on the screen, \(w\) is a function of \(x\), \(x'\), and the horizontal position on the screen. Thus, the image on the screen gives the density \(f(y', w)\) within a small three-dimensional region in \(x-x'-y\) space. The five-dimensional density is obtained by scanning the slits in a nested loop.</p><p>The data set consists of 285,082 images (20 GB). Jupyter notebooks are included to interpolate the data on a regular grid in five-dimensional phase space, as well as to generate interactive figures. See 'README.md' for instructions. (The interpolated five-dimensional image is also included in a separate folder.)</p><p>More information can be found in a corresponding publication: https://doi.org/10.1103/PhysRevAccelBeams.26.064202</p>
Datasets for the article "The temperature and density of a solar flare kernel measured from extreme ultraviolet lines of O IV"
<p>This entry contains the following files:</p><p>20120309_030933_kernel_fe8_shift.save<br>20120309_030933_kernel_fe8_shift_fits.txt<br>20110814_055342_qs_offlimb_si10.save<br>20110814_055342_qs_offlimb_si10_fits.txt</p><p>The .save files are IDL save files that can be restored into IDL using the restore command.</p><p>The 20120309 save file contains:</p><p>swspec - An IDL structure containing a 1D spectrum of the flare kernel for the EIS short wavelength (SW) channel. The format is that returned by eis-mask-spectrum.pro.<br>lwspec - As above, but for the long-wavelength (LW) channel.<br>map185 - An IDL map structure containing the Fe VIII 185.21 image that was used to select the flare kernel.<br>mask185 - An IDL structure containing the pixel mask that is used as input to eis-mask-spectrum.pro.</p><p>The Gaussian fits to the spectra (as performed with the routine spec-gauss-eis.pro) are stored in 20120309_030933_kernel_fe8<i>s</i>hift_fits.txt. This file can be read with read_line_fits.pro in Solarsoft.</p><p>The 20110814 dataset is used to obtain an off-limb coronal spectrum for calibration purposes. The save file contains:</p><p>swspec - An IDL structure containing a 1D spectrum of the off-limb region for the EIS SW channel. The format is that returned by eis-mask-spectrum.pro.<br>lwspec - As above, but for the LW channel.<br>map - An IDL map structure containing the Si X 272 image that was used to select off-limb region.<br>mask - An IDL structure containing the pixel mask that is used as input to eis-mask-spectrum.pro.</p><p>The Gaussian fits to the spectra (as performed with the routine spec-gauss-eis.pro) are stored in 20110814_055342_qs_offlimb_si10_fits.txt. This file can be read with read_line_fits.pro in Solarsoft. </p><p> </p><p> </p><p> </p><p> </p><p> </p><p> </p><p> </p>
Measured data of article "Superconducting NbN–Al hybrid technology for quantum devices"
<p>The folder contains raw data of figure 3 & 4 as well as a preprint of the article:</p> <p><em>Superconducting NbN–Al hybrid technology for quantum devices</em></p> <p>Authors: E. Mutsenik, S. Linzen, E. Il’ichev, M. Schmelz, M. Ziegler, V. Ripka, B. Steinbach, G. Oelsner, U. Hübner, and R. Stolz</p> <p>Journal: Low Temperature Physics/Fizyka Nyzkykh Temperatur, 2023, Vol. 49, No. 1, pp. 98–101</p>
DETERMINISTIC6G COTS 5G latency measurements
<h1>Measurement setup and dataset overview</h1> <p>The dataset contains the data collected during the latency measurements performed on a COTS 5G system. The 5G network operates in band 78, in TDD mode, with a total of 106 PRBs which occupies 40 MHz of bandwidth. The latency (one-way delay) samples were collected in both uplink and downlink directions using the <a href="https://github.com/heistp/irtt" target="_blank" rel="noopener">irtt</a> tool running on the end node (connected to the UE) and the edge node (connected to the 5G gateway). The clocks in the 5G system, end node and edge node were precisely (<200ns) synchronized using Precision Time Protocol (PTP). In addition to recording send and receive timestamps, various network conditions were also recorded for each latency sample.<br>The measurements were carried out in different sessions and for each session, there are about 1M samples in total which are contained in different parquet files corresponding to different rounds (30 mins) per session. Each session corresponds to a combination of direction (uplink or downlink), UE device, a packet interval and payload length, etc. A spreadsheet (COTS5G measurement campaign.xlsx) in this directory contains the information detailed information on the combination for each session.</p> <h1>Acknowledgements </h1> <p>This work was supported by the European Commission through the H2020 project DETERMINISTIC6G (Grant Agreement no. 101096504).</p>
What can radar-based measures of subglacial hydrology tell us about basal shear stress? A case study at Thwaites Glacier, West Antarctica (Interpolated Data)
<p>This dataset accompanies the paper 'What can radar-based measures of subglacial hydrology tell us about basal shear stress? A case study at Thwaites Glacier, West Antarctica' in Journal of Glaciology, and can be used alongside the code found on Github (https://github.com/rohaizharis/inversion_radar2022) to reproduce the figures. The dataset consists of ice-penetrating radar data (specularity and relative reflectivity) and basal shear stress inversions that have been linearly interpolated onto radar flight tracks.</p>
Sagittarius A lunar occultation measured by Dwingeloo Radio Telescope 2023-12-13
<p>This dataset contains raw spectra from the Lunar occultation of Sagittarius A on December 13, 2023. The data were obtained with the Dwingeloo Radio Telescope, which is operated by Stichting CAMRAS.</p> <p>Three bands are measured:</p> <ul> <li>1418MHz, 6MHz wide. The spectra show absorption and emission of the hydrogen line.<br> <ul> <li>Spectra with 2000 bins, integration time 0.2 seconds (corrected for bandpass).</li> <li>Total power with integration time 1 second.</li> </ul> </li> <li>1330MHz, 10MHz wide. <ul> <li>Spectra with 5000 bins, integration time 1 second.</li> <li>Total power with integration time 1 second.</li> </ul> </li> <li>415MHz, 4MHz wide. This data is severely affected by radio frequency interference.<br> <ul> <li>Spectra with 2000 bins, integration time 1 second.</li> <li>Total power with integration time 1 second.</li> </ul> </li> </ul> <p>The telescope was tracking Sagittarius A* during the occultation. The altitude ranged from 1 to 8 degrees above the horizon during the measurements. This is very low, leading to quite severe radio frequency interference. Partially, these are caused by LTE masts transmitting at 1456 MHz, for which the receiving system is insufficiently shielded. All frequencies are topocentric, i.e. no LSR-correction has been applied.</p> <p>Files are in the ECSV format, which can be read with Astropy, or with any other program that can read CSV-data (such as Microsoft Excel). Apart from the spectra, also telescope pointing information and exact times are stored in every row.</p>
Supplementary Data for: A time-calibrated 'Tree of Life' of aquatic insects for knitting historical patterns of evolution and measuring extant phylogenetic biodiversity across the world
<p>This compendium of files includes the dated phylogenetic tree in Newick format (<strong>Data S1</strong>), the list of statistical routines used for the three empirical case studies (<strong>Data S2</strong>), and the high-resolution version of the figures in the supplementary materials and main text (<strong>Data S3</strong>) for the <em>Earth-Science Reviews</em> paper "A time-calibrated ‘Tree of Life’ of aquatic insects for knitting historical patterns of evolution and measuring extant phylogenetic biodiversity across the world", which is under consideration. The best-scoring molecular tree (<strong>Data S1</strong>) can be opened using freely available programs like R (R Development Core Team, 2021), Dendroscope (Huson and Scornavacca, 2012), and FigTree (Rambaut, 2018).</p> <p>Please, feel free to send an email to the maintainer Dr. Jorge García Girón (jogarg@unileon.es OR Jorge.Garcia-Giron@oulu.fi) if you face any trouble downloading, opening, or using these files.</p> <ul> <li>Huson, D. H., & Scornavacca, C. (2012). Dendroscope 3: An interactive tool for rooted phylogenetic trees and networks. <em>Systematic Biology</em>, <em>61(6)</em>, 1061–1067.</li> <li>R Development Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/</li> <li>Rambaut, A. (2018). FigTree. Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK. http://tree.bio.ed.ac.uk/software/figtree/</li> </ul>
Manual active layer and and water table depth measurements from the autochamber sites at Stordalen Mire, northern Sweden (2003-2017)
<p>Files:</p> <ul> <li><strong>Active_Layer_Water_Table_03-17.xlsx</strong> - Data file, with main data in the "DATA" tab.</li> <li><strong>IsoGenieSite_AL_WTD_MapsVisualNotes_200310.pdf</strong> - Visual notes on the measurement locations.</li> </ul> <p>The following site labels (with chamber numbers in parentheses) correspond to the main autochamber sites:</p> <ul> <li>Dry (1,3,5) = Palsa Autochamber Site</li> <li>Mesic (2,4,6) = Sphagnum Autochamber Site</li> <li>Wet (7,8) = Eriophorum Autochamber Site</li> </ul> <p>Water table depth (W D) was measured in wells.</p> <p>Active layer depth (A L) was measured by inserting a metal rod into the surface. The original instruction page is included in page 3 of the pdf.</p> <p>All depths are in centimeters (cm) below peat surface (i.e. peat or <em>Sphagnum</em> spp. vegetation surface = 0), with negative values indicating depth below the surface and positive values (for water table) indicating height of standing water above the surface. Blank data in the Palsa or water table column means no water table observed.</p> <p>Staff gauge was added July 2006 at the edge of a small pond in the fen visible from the shack, with measurements reported in meters. All other measures are in cm.</p> <p> </p> <p>FUNDING:</p> <p>We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164.</p> <p>This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070. The IsoGenie Project (which funded much of the work at these sites during the measurement period) was funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440.</p>
CoUDlabs_WP8_T812_EAWAG_001. Sediment depth measurements for surrogate modeling of sediment build-up in gully pots using temperature data
<p>This dataset contains the results of the experimental campaign and how data were collected on the the <a href="https://co-udlabs.eu/">Co-UDlabs</a> <strong>Work Package 8 (Joint Research Activity 3)</strong>: <i>Improving resilience and sustainability in urban drainage solutions</i>; <strong>Task 8.1</strong>: <i>Development of consensus on measurement of hydraulic and water quality performance of urban drainage technologie</i>s; <strong>Subtask 8.1.2</strong>: <i>Development of scalable measurement protocols to assess the pollutant retention and release potential of urban drainage structures</i>. </p><p>Co-UDlabs is a project funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No 101008626.</p><p>This database was developed as part of the Master Thesis in Environmental Engineering at ETH Zurich (Switzerland). Fuchs, L. (2023). Automated surrogate model to estimate sediment accumulation from temperatures in urban drainage systems. MSc Thesis, ETH Zurich. https://polybox.ethz.ch/index.php/s/IyiM38rRy1vlHWD. Accessed on 10th of October of 2023.</p>
Wrist and Tibia/Shoe Mounted IMU Measurement Results for Gait Analysis
<p>This document describes a dataset of measurement results collected using wrist, tibia and shoe mounted inertial sensors. The main purpose of the dataset was to test signal translation algorithms converting signals registered using the wrist-worn sensor e.g. a smartwatch to signals which would be measured with a shoe or tibia - mounted device. The dataset includes tri-axial acceleration and angular velocity registered during several walks.</p> <p>More details are included in the dataset_description pdf file.</p> <p>When using the data, please consider also citing the original paper, for which it was collected:</p> <p>Kolakowski, M.; Djaja-Josko, V.; Kolakowski, J.; Cichocki, J. Wrist-to-Tibia/Shoe Inertial Measurement Results Translation Using Neural Networks. <em>Sensors</em> <strong>2024</strong>, <em>24</em>, 293. <a href="https://doi.org/10.3390/s24010293" target="_blank" rel="noopener">https://doi.org/10.3390/s24010293</a></p> <p><strong>The dataset will be gradually updated as new data are gathered.</strong></p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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.