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10,553 results for “measurements”
York Archaeological Trust 1989.21.2205 3D Archaeological Use-wear Raw Measurements
<p>This dataset contains the 27 raw measurements/scans taken before the mesh creation step for object 1989.21.2205 in the collections of York Archaeological Trust.</p> <p>1989.21.2205 is a small Samian ware cup fragment. Close analysis was not undertaken at time of data capture.</p> <p>Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres.</p> <p>This dataset consists of 14,583,615 points - additional metadata included in associated spreadsheet.</p>
York Archaeological Trust 1989.21.2393.LL42 Archaeological 3D Use-wear Raw Measurements
<p>This dataset contains the 18 raw measurements/scans taken before the mesh creation step for object 1989.21.2393.LL42 in the collections of York Archaeological Trust.</p> <p>1989.21.2393.LL42 is a dish of Ebor Ware 2 (Monaghan 1997, 875) from 34-41 Blossom Street (Lion and Lamb).</p> <p>Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres.</p> <p>This dataset consists of 26,065,666 points - additional metadata included in associated spreadsheet.</p>
Hunterian GLAHM:B.1951.3137 3D Archaeological Use-wear Raw Measurements
<p>This dataset contains the 32 raw measurements/scans taken before the mesh creation step for object GLAHM:B.1951.3137 in the Hunterian's Archaeology collection in Glasgow, Scotland.</p> <p>GLAHM:B.1951.3137 is a two-handled bowl (Ionic Cup B2) from Greece: <a href="http://collections.gla.ac.uk/#/details/ecatalogue/118198">http://collections.gla.ac.uk/#/details/ecatalogue/118198</a> </p> <p>Comparanda: Gravisca 4, 164-165, 323, tav. 9, type IV/1.</p> <p>Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres.</p> <p>This dataset consists of 45,140,392 points - additional metadata included in associated spreadsheet.</p> <p>Gravisca 4: S. Boldrini, <em>Le Ceramiche Ioniche</em>, Bari 1994.</p>
Hunterian GLAHM:D.160 3D Archaeological Use-wear Raw Measurements
<p>This dataset contains the 40 raw measurements/scans taken before the mesh creation step for object GLAHM:D.160 in the Hunterian's Archaeology collection in Glasgow, Scotland.</p> <p>GLAHM:D.160 is a Black Gloss plate: <a href="http://collections.gla.ac.uk/#/details/ecatalogue/117080">http://collections.gla.ac.uk/#/details/ecatalogue/117080</a></p> <p>Edited in CVA Glasgow, vol. 18, 49, pl. 60.7. Morel 1981, 140, pl. 31, 2141b 1.</p> <p>Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres. </p> <p>This dataset consists of 55,761,532 points - additional metadata included in associated spreadsheet.</p> <p>CVA Glasgow: E. Moginard 1997, <em>Corpus Vasorum Antiquorum, Great Britain, Fascicule 18, Glasgow</em>, Oxford 1997.-wear on archaeological objects.</p> <p>Morel 1981: J.P. Morel, <em>Céramique campanienne: les formes</em>, Rome 1981.</p>
York Archaeological Trust 1988.24.7669-7627 Archaeological 3D Use-wear Raw Measurements
<p>This dataset contains the 32 raw measurements/scans taken before the mesh creation step for object 1988.24.7669-7627 in the collections of York Archaeological Trust.</p> <p>1988.24.7669-7627 is a small campanulate bowl. Close analysis was not undertaken at time of data capture.</p> <p>Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres.</p> <p>This dataset consists of 31,429,144 points - additional metadata included in associated spreadsheet.</p>
York Archaeological Trust 1984.132.4148 3D Archaeological Use-wear (Incomplete Scan) Raw Measurements
<p>This dataset contains the 25 raw measurements/scans taken before the mesh creation step for object 1984.132.4148 in the collections of York Archaeological Trust.</p> <p>1984.132.4148 is a dish. Close analysis was not undertaken at time of data capture. Scanning was not complete. Holes in scan data: one small circle at the very centre of the base of the dish, and gaps in data capture under the rim. </p> <p>Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres.</p> <p>This dataset consists of 27,629,672 points - additional metadata included in associated spreadsheet.</p>
York Archaeological Trust 1975.6.7364.4244 Archaeological 3D Use-wear Raw Measurements
<p>This dataset contains the 78 raw measurements/scans taken before the mesh creation step for object 1975.6.7364.4244 in the collections of York Archaeological Trust.</p> <p>1975.6.7364.4244 is a large Ebor Ware carinated bowl (Monaghan 1993, 783, 875).</p> <p>Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres.</p> <p>This dataset consists of 278,742,689 points - additional metadata included in associated spreadsheet.</p>
Hunterian GLAHM:D.155 3D Archaeological Use-wear Raw Measurements
<p>This dataset contains the 65 raw measurements/scans taken before the mesh creation step for object GLAHM:D.155 in the Hunterian's Archaeology collection in Glasgow, Scotland.</p> <p>GLAHM:D.155 is an Bucchero Kantharos, likely produced in Cerveteri or Vulci: <a href="http://collections.gla.ac.uk/#/details/ecatalogue/117064">http://collections.gla.ac.uk/#/details/ecatalogue/117064</a></p> <p>Edited in CVA Glasgow, vol. 18, 47, pl. 57.7. Gran-Aymerich 2017, groups 3764-3765, pls. 58-88.</p> <p>Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres. </p> <p>This dataset consists of 108,061,041 points - additional metadata included in associated spreadsheet.</p> <p>CVA Glasgow: E. Moginard 1997, <em>Corpus Vasorum Antiquorum, Great Britain, Fascicule 18, Glasgow</em>, Oxford 1997.</p> <p>Gran-Aymerich 2017: J. Gran-Aymerich, <em>Les vases de bucchero. Le monde étrusque entre Orient et Occident,</em> Rome 2017.</p>
Hunterian GLAHM:D.1909.10 3D Archaeological Use-wear Raw Measurements
<p>This dataset contains the 43 raw measurements/scans taken before the mesh creation step for object GLAHM:D.1909.10 in the Hunterian's Archaeology collection in Glasgow, Scotland.</p> <p>GLAHM:D.1909.10 is a Black Gloss bowl from tombs at Cyrenaica, Libya: <a href="http://collections.gla.ac.uk/#/details/ecatalogue/118225">http://collections.gla.ac.uk/#/details/ecatalogue/118225</a> Similar to Morel Series 1735, (Morel 1981, 133, pl. 29).</p> <p>Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres.</p> <p>Final dataset consists of 44,681,096 points - additional metadata included in associated spreadsheet.</p> <p>Morel 1981: J.P. Morel, <em>Céramique campanienne: les formes</em>, Rome 1981.</p>
Hunterian GLAHM:D.163 3D Archaeological Use-wear Raw Measurements
<p>This dataset contains the 58 raw measurements/scans taken before the mesh creation step for object GLAHM:D.163 in the Hunterian's Archaeology collection in Glasgow, Scotland.</p> <p>GLAHM:D.163 is a Bucchero cup: <a href="http://collections.gla.ac.uk/#/details/ecatalogue/117079">http://collections.gla.ac.uk/#/details/ecatalogue/117079</a></p> <p>This is a possible reproduction because the type is unusual and cannot find comparisons. Edited in CVA Glasgow, vol. 18, 49, pl. 60.5-6.</p> <p>Data was captured using a Zeiss Comet L3D 2 5M at 100 FOV to enable the analysis of use-wear on archaeological objects. The model is scaled in millimetres.</p> <p>This dataset consists of 91,703,605 points - additional metadata included in associated spreadsheet.</p> <p>CVA Glasgow: E. Moginard 1997, <em>Corpus Vasorum Antiquorum, Great Britain, Fascicule 18, Glasgow</em>, Oxford 1997.</p>
Data used to create figures in the ACP Letters manuscipt "The value of remote marine aerosol measurements for constraining radiative forcing uncertainty" by Regayre et al. (2020)
<p>This dataset was created from perturbed parameter ensembles (PPEs) using the HadGEM-UKCA atmospheric composition climate model. All data needed to reproduce figures in the Regayre et al. (2020) ACP Letters article "The value of remote marine aerosol measurements for constraining radiative forcing uncertainty" are included. Other output from the PPEs can be obtained by contacting the lead author.</p> <p>The following data are included here:</p> <ul> <li>CCN measurement data degraded to match the model-measurement comparison resolution.</li> <li>Unconstrained and constrained CCN<sub>0.2</sub> output from the PPE used to make Figure 1. These compressed files contain 48 .dat files. Each .dat file contains the PPE mean, variance and 95% creidble interval data. Files are named consecutively, containing data from 90<sup>o</sup>S to 90<sup>o</sup>N at 0<sup>o</sup>E, then continuing Eastward. When combined, these files provide data for each latitude/longitude pair at the N48 spatial resolution.</li> <li>A zip file of an netcdf file containing 26-dimensional data for parameter values, used to create the sample of 1 million model variants from our statistical emulators of model output.</li> <li>A zip file containing a folder of files made of one million ones and zeros that indicate the retention/rejection criteria from applying our constraint methodology for various constraint combination scenarios, for each model variant. A value of 1 indicates the model variant was retained. Data in these files is in the same order as the unconstrained sample file of parameter values.</li> <li>Compressed files containing global, annual mean RF<sub>aci</sub> and ERF<sub>aci</sub> values for the unconstrained set of one million model variants. The compressed netcdf files contain RF (ERF), RF<sub>aci</sub> (ERF<sub>aci</sub>) and RF<sub>ari</sub> (ERF<sub>ari</sub>) values.</li> </ul>
The S&M-HSTPM2d5 dataset: High Spatial-Temporal Resolution PM 2.5 Measures in Multiple Cities Sensed by Static & Mobile Devices
<p>This S&M-HSTPM2d5 dataset contains the high spatial and temporal resolution of the particulates (PM2.5) measures with the corresponding timestamp and GPS location of mobile and static devices in the three Chinese cities: Foshan, Cangzhou, and Tianjin. Different numbers of static and mobile devices were set up in each city. The sampling rate was set up as one minute in Cangzhou, and three seconds in Foshan and Tianjin. For the specific detail of the setup, please refer to the Device_Setup_Description.txt file in this repository and the data descriptor paper.</p> <p>After the data collection process, the data cleaning process was performed to remove and adjust the abnormal and drifting data. The script of the data cleaning algorithm is provided in this repository. The data cleaning algorithm only adjusts or removes individual data points. The removal of the entire device's data was done after the data cleaning algorithm with empirical judgment and graphic visualization. For specific detail of the data cleaning process, please refer to the script (Data_cleaning_algorithm.ipynb) in this repository and the data descriptor paper.</p> <p>The dataset in this repository is the processed version. The raw dataset and removed devices are not included in this repository.</p> <p>The data is stored as a CSV file. Each CSV file which is named by the device ID represents the data that was collected by the corresponding device. Each CSV file has three types of data: timestamp as the China Standard Time (GMT+8), geographic location as latitude and longitude, and PM2.5 concentration with the unit of microgram per cubic meter. The CSV files are stored in either Static or Mobile folder which represents the devices' type. The Static and Mobile folder are stored in the corresponding city's folder.</p> <p>To access the dataset, any programming language that can access CSV files is appropriate. Users can also open the CSV file directly. The get_dataset.ipynb file in this repository also provides an option of accessing the dataset. To successfully execute ipynb file, Jupyter Notebook with Python 3.0 is required. The following python library is also required:</p> <p>get_dataset.ipynb:<br> 1. os library<br> 2. pandas library</p> <p>Data_cleaning_algorithm.ipynb:<br> 1. os library<br> 2. pandas library<br> 3. datetime library<br> 4. math library</p> <p>The instruction of installing the libraries above can be found online. After installing the Jupyter Notebook with Python 3.0 and the required libraries, users can try to open the ipynb file with Jupyter Notebook and follow the instruction inside the file. </p> <p>For questions or suggestions please e-mail Xinlei Chen <xinlei.chen@sv.cmu.edu></p>
Topography extraction and topographic change measurements using PlanetScope data: Shisper Glacier (Pakistan)
<p>The study area is located in the north flank of Hunza Valley in the Central Karakoram. Shisper glacier covers ~53.7 km2 at an elevation range of 2567-611 m a.s.l. It is a surge-type glacier, which has recently gained the attention of the scientific community and disaster response agencies during its surge. In 2018, the glacier surged beyond the confluence with the outlet stream of Mochwar glacier. The blockage resulted in the creation of a lake, which then drained causing a GLOF (Glacial Lake Outbreak Flood) and has recently begun reforming. The melt water from the two glaciers feeds hydropower plants in the Hunza valley and is a major source of fresh water for agriculture. Glacier-related hazards threaten both the town of Hassanabad and the Karakoram Highway, the only paved road through the mountain range. Here we show the potential of CubSat data to monitor such glaciers, which are not easily accessible to field observation and their potential impact on power generation, water resources and infrastructure.</p> <p>We use multi-date L1B DOVE-C PlanetScope data to extract two DEMs in 2017 and 2019 over the study area in order to compute the elevation difference caused by the glacier surge.</p> <p>Supplementary material for our paper: Optimization of optical image geometric modeling, application to topography extraction and topographic change measurements using PlanetScope and SkySat imagery.</p>
Body measurements of human adults, with repeated readings
<p>This data file contains body measurements of participants of a course in morphometrics. The data are entirely anonymized and the compliance for publication of the data in the present form was obtained from each person.</p> <p>The participants were asked to measure themselves twice at intervals of one or two days, which resulted in reading a and reading b. The following measurements were taken (in mm):</p> <p>arm.l -> arm length<br> bod.h -> total body height<br> foo.l -> foot length<br> hea.c -> head circumference<br> leg.l -> leg length</p> <p>The dataset may be considered for demonstration of measurement error.</p>
Field measurements of aerosol particles near a runway at Narita International Airport, Japan
<p>Field measurements of aerosol particles were conducted at an observation point ~180 m from the centerline of runway A (~140 m from the edge of the runway) at Narita International Airport (NRT), Japan, in February 2018. The online aerosol instruments used for the field measurements consisted of an ultrafine condensation particle counter (UCPC; Model 3776, TSI, d<sub>50</sub> = 2.5 nm), a condensation particle counter (CPC; Model 3771, TSI, d<sub>50</sub> = 10 nm), a scanning mobility particle sizer (SMPS; Model 3080, TSI), and an engine exhaust particle sizer (EEPS; TSI). The other instruments included a carbon dioxide (CO<sub>2</sub>) monitor (Model LI-840, Li-Cor Biosciences) and meteorological sensors. The sampling inlet for the UCPC, CPC, and SMPS was switched between an unheated (room temperature) mode and a 350°C heated mode every eight hours during selected time periods to measure the total and the non-volatile particles, respectively. The EEPS was operated independently from the UCPC/CPC/SMPS inlet system and it measured the unheated particle number size distributions during the entire period.</p>
Open-Ended Coaxial Cable Measurements in Diesel-Contaminated soil during Bioremediation
<p>Complex dielectric permittivity was measured over a broad frequency range (200 MHz to 20 GHz) with Keysight 85070D dielectric probe kit connected to a network analyzer (Keysight N5227A), on a series of 6 soil microcosms contaminated with diesel oil, before and after a process of bioremediation. This technology measures separately the real and the imaginary component of complex dielectric permittivity, which are meaningful properties of soil.</p>
Mechanical data of rotary shear experiments and temperature measurements for the manuscript: "Fast and localized temperature measurements during simulated earthquakes in carbonate rocks"
<p>Mechanical data of rotary shear experiments and temperature measurements</p> <p>Each experiment is presented in a file with the experiment name (mechanical data of rotary shear experiment) and a file with the experiment name and _Temp (temperature measurement with the optical fiber).</p> <p>Mechanical data are presented in a tab-delimited file with calibrated measurements of:</p> <ul> <li>Time (milliseconds)</li> <li>Normal stress: Normal (MPa) </li> <li>Fault displacement: Slip (mm)</li> <li>Fault velocity: Velocity (mm/s)</li> <li>Shear stress: Shearstress (MPa)</li> <li>Axial shortening: Shortening (mm).</li> </ul> <p> In a separate file, temperature data are presented as tab-delimited file with calibrated measurements of:</p> <ul> <li>Time (milliseconds)</li> <li>Temperature from optical fiber in the channel at 1.5 µm : Temperature_1,5 (°C) </li> </ul>
PsPM-VIS: SCR, ECG, respiration and eyetracker measurements in a delay fear conditioning task with visual CS and electrical US
<p>This dataset consists of a three-block experiment conducted with 29 healthy unmedicated participants (17 females and 12 males aged 25.3 +/- 3.7). The experiment contains a classical (Pavlovian) discriminant delay fear conditioning test. CSs are 2 full-screen fractals of approximate brightness, contrast, and spatial frequency. US is a train of electric square pulses delivered with a constant current stimulator on participants' dominant forearm through a pin-cathod/ring-anode configuration. SOA between the CS and US is 3.5 s. The first 2 blocks are fear acquisition, with 15 CS+US+, 15 CS+US-, and 30 CS- in each block, and the last block is an extinction phase with 20 CS- and 20 CS+ trials without US delivery. The order of trials in each block was randomized. No fixation cross was presented during CS. ITI is randomly determined on each trial to be an integer between 7 - 11 s. During ITI, a black fixation cross was presented in the center of a grey background (RGB 0.7, 0.7, 0.7). The blocks were recorded on the same day with a self-paced break. For all three blocks this dataset contains skin conductance responses (SCR), electrocardyogram (ECG), respiration, pupil size (PSR), and gaze coordinates measurements.</p>
Reflector heights in the Arctic permafrost areas measured by GNSS interferometric reflectometry
<p>This dataset is about the measurements of reflector height, i.e., the vertical distance between receiver antenna and groud surface, at the GNSS sites in the Arctic permafrost areas. Each data file has four columns. The 1st and 2nd show the time as year and doy, respectively. The 3rd and 4th are the reflector height and its uncertainty, respectively.</p>
Salinity measurements in the Mekong Delta
<p>This data set contains along-channel and over-depth salinity structure measurements along the two lower estuarine distributary channels of the Hau River within the Mekong Delta, Vietnam. The data was collected during the dry season of the year 2016.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.