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412
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ShareScore release 0.7.1
Dataset results
412 results for “sensor data”
PS-BBICS: Pulse Stretching Bulk Built-in Current Sensor for On-chip Measurement of Single Event Transients (raw data from journal article)
<p>This upload contains raw data from the manuscript "PS-BBICS: Pulse Stretching Bulk Built-in Current Sensor for On-chip Measurement of Single Event Transients". The manuscript was published in Microelectronics Reliability, vol. 138, 2022.; DOI: https://doi.org/10.1016/j.microrel.2022.114726</p> <p>The upload consists of .pdf file of the manuscript and .opj files with raw data related to the figures in the manuscript. </p> <p>This work was supported in part by the European Union’s Horizon 2020 research and innovation programme (Grant No. 857558).</p>
Predicting Fall Risk in Stroke Patients Using a Machine Learning Model and Multi-Sensor Data
ClinicalTrials.gov study NCT06380049. IPD Sharing: NO. Countries: 1. Publications: 0.
Nellcor™ Abbreviated Sensor Additional Data Collection
ClinicalTrials.gov study NCT07201961. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Modelling and AI Using Sensor Data to Personalise REHABilitation Following Joint Replacement
ClinicalTrials.gov study NCT04289025. IPD Sharing: YES. Countries: 1. Publications: 0.
Data Collection for Development of a Bladder Sensor During Urodynamics
ClinicalTrials.gov study NCT05305846. IPD Sharing: NO. Countries: 1. Publications: 0.
Collection of Performance Data From the Integrated Sensor and Infusion Set. TRIAL 4
ClinicalTrials.gov study NCT01775059. IPD Sharing: Not stated. Countries: 1. Publications: 0.
NO Sensor to Record Wound Data in Acute or Chronic Wounds
ClinicalTrials.gov study NCT06944899. IPD Sharing: NO. Countries: 1. Publications: 0.
Study Measuring the Effects of Patient Data for Total Hip and Total Knee Arthroplasty Patients Using an APP Based Sensor for Home Exercise Performance Before and After Operation
ClinicalTrials.gov study NCT05182320. IPD Sharing: NO. Countries: 1. Publications: 0.
NCST Caltrans project on sensor data error estimation
Open the record for dataset details and reuse information.
Quality Controlled Lightning Imaging Sensor (LIS) on International Space Station (ISS) Science Data V2
The Quality Controlled Lightning Imaging Sensor (LIS) on International Space Station (ISS) Science Data dataset was collected by the LIS instrument mounted on the ISS and are used to detect the distribution and variability of total lightning occurring in the Earth’s tropical and subtropical regions. This dataset consists of quality controlled science data. This data collection can be used for severe storm detection and analysis, as well as for lightning-atmosphere interaction studies. The LIS instrument makes measurements during both day and night with high detection efficiency. The data are available in both HDF-4 and netCDF-4 formats, with corresponding browse images in GIF format.
KORUS-AQ B200 Remotely Sensed Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) Data
KORUSAQ_AircraftRemoteSensing_GeoTASO_B200_Data are remotely sensed data collected by the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) instrument onboard the B200 aircraft during the KORUS-AQ field campaign. NO2 and HCHO trace gas slant column data are featured in this collection. Data collection for this product is complete.The KORUS-AQ field study was conducted in South Korea during May-June, 2016. The study was jointly sponsored by NASA and Korea’s National Institute of Environmental Research (NIER). The primary objectives were to investigate the factors controlling air quality in Korea (e.g., local emissions, chemical processes, and transboundary transport) and to assess future air quality observing strategies incorporating geostationary satellite observations. To achieve these science objectives, KORUS-AQ adopted a highly coordinated sampling strategy involved surface and airborne measurements including both in-situ and remote sensing instruments.Surface observations provided details on ground-level air quality conditions while airborne sampling provided an assessment of conditions aloft relevant to satellite observations and necessary to understand the role of emissions, chemistry, and dynamics in determining air quality outcomes. The sampling region covers the South Korean peninsula and surrounding waters with a primary focus on the Seoul Metropolitan Area. Airborne sampling was primarily conducted from near surface to about 8 km with extensive profiling to characterize the vertical distribution of pollutants and their precursors. The airborne observational data were collected from three aircraft platforms: the NASA DC-8, NASA B-200, and Hanseo King Air. Surface measurements were conducted from 16 ground sites and 2 ships: R/V Onnuri and R/V Jang Mok.The major data products collected from both the ground and air include in-situ measurements of trace gases (e.g., ozone, reactive nitrogen species, carbon monoxide and dioxide, methane, non-methane and oxygenated hydrocarbon species), aerosols (e.g., microphysical and optical properties and chemical composition), active remote sensing of ozone and aerosols, and passive remote sensing of NO2, CH2O, and O3 column densities. These data products support research focused on examining the impact of photochemistry and transport on ozone and aerosols, evaluating emissions inventories, and assessing the potential use of satellite observations in air quality studies.
An Advanced Learning Framework for High Dimensional Multi-Sensor Remote Sensing Data Project
<p> Improve the use of land cover data by developing an advanced framework for robust classification using multi-source datasets:<br /> Develop, validate and optimize a generalized multi-kernel, active learning (MKL-AL) pattern recognition framework for multi-source data fusion.<br /> Develop both single- and ensemble-classifier versions (MKL-AL and Ensemble-MKL-AL) of the system.<br /> Utilize multi-source remotely sensed and in situ data to create land-cover classification and perform accuracy assessment with available labeled data; utilize first results to query new samples that, if inducted into the training of the system, will significantly improve classification performance and accuracy.<br /> &nbsp;</p>
Lightning Imaging Sensor (LIS) on TRMM Science Data V4
The Lightning Imaging Sensor (LIS) Science Data was collected by the LIS instrument on the Tropical Rainfall Measuring Mission (TRMM) satellite used to detect the distribution and variability of total lightning occurring in the Earth’s tropical and subtropical regions. This data can be used for severe storm detection and analysis, as well as for lightning-atmosphere interaction studies. The LIS instrument makes measurements during both day and night with high detection efficiency. These data are available in both HDF-4 and netCDF-4 formats, with corresponding browse images in GIF format.
Sensors, Pathways and Transcription factors regulating IR-induced inflammatory transcriptional output [RNA-seq data set 2]
GEO Series GSE103903. Mus musculus. 10 samples. Type: Expression profiling by high throughput sequencing.
Activity Data HuaweiActivity Sensor EU
<p>Data related to the activities:</p> <p>a) steps</p> <p>b) energy consumption (calories)</p> <p>c) distance</p> <p>d) altitude</p>
Activity Data HuaweiActivity Sensor JP
<p>Data related to the activities:</p> <p>a) steps</p> <p>b) energy consumption (calories)</p> <p>c) distance</p> <p>d) altitude</p>
Body Composition Data HuaweiHealth Sensor JP
<p>Health data related to the body composition:</p> <p>a) body fat rate</p> <p>b) body fat</p> <p>c) weight</p> <p>d) height</p>
Data from: Synaptotagmin 7 functions as a Ca^2+ -sensor for synaptic vesicle replenishment
[No abstract entered]
Continuous Data Collection and Analysis for Stroke Prevention Using a Wearable Sensor
ClinicalTrials.gov study NCT03441022. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Modeling and Predicting Real World Behavior Using Mobile Sensor Data on Patients With Major Depressive Disorder
ClinicalTrials.gov study NCT02499094. IPD Sharing: Not stated. Countries: 0. Publications: 0.
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.