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206 results for “electronic monitoring”
MOSID (Microcontroller On-chip Sensor IDentification): A dataset of readings from the internal monitoring sensors of STM32L152RTXX microcontrollers during the stimulation of their electronic activity
<p>The MOSID (Microcontroller On-chip Sensor IDentification) dataset consists of 5 acquired data subsets (6,72 GB total, compressed into 560 MB), each collected during different experiments and periods using various equipment (HMP4040, DF1731SB & HM305) and acquisition strategies. These subsets contain readings from the temperature and voltage sensors embedded in 20 STM32L-DISCOVERY devices. The data was captured during the execution of 5 different workloads as stimuli, repeated over 20 iterations. The stimuli employed are as follows:</p><ol><li>20x20 Long-type matrix product.</li><li>20x20 Float-type matrix product.</li><li>Algorithm for ascending sorting, Bubble Sort.</li><li>Algorithm for 2D-point clustering, Convex Hull.</li><li>Encryption algorithm AES 128-bit.</li></ol><p>The subsets are structured according to the folder format "X_Y," where X is the manually assigned number to the board, and Y is the corresponding number for the executed algorithm. Within each of these folders, files are present in the format "data_Z.txt," where Z represents the iteration number to which the file belongs. In total, the dataset comprises 9600 files with a final size of approximately 7 GB. The different presented subsets are as follows:</p><ul><li>ACQ1: Derived from the experiment named "Automatic Acquisition 1 (HMP4040)" conducted using a daisy-chain topology (20 out of 20 boards, 2000 files).</li><li>ACQ2: Derived from the experiment named "Automatic Acquisition 2 (HMP4040)" conducted using a daisy-chain topology (20 out of 20 boards, 2000 files).</li><li>ACQ3: Derived from the experiment named "Individual Acquisitions (HMP4040)", performed board by board from idle conditions (20 out of 20 boards, 2000 files).</li><li>ACQ4: Derived from the experiment named "GOLD SOURCE DF1731SB Acquisitions" conducted using a partial daisy-chain setup (2 devices at a time, 18 out of 20 boards excluding boards , 1800 files).</li><li>ACQ5: Derived from the experiment named "HANMATEK HM305 Acquisitions" conducted using a partial daisy-chain setup (2 devices at a time, 18 out of 20 boards, 1800 files).</li></ul><p>In each "data_Z.txt" file, starting from the 5th line, temperature and voltage raw ADC conversions from the sensors are provided, captured during the execution of the stimulus in successive lines. Additionally, a table (Table_UIDS.csv) with metadata for each of the boards used in the experiments is included, which is needed in order to normalize the data in terms of ºC and Volts.</p><ul><li>BOARD_NUM, which contains the manually assigned board number.</li><li>UID, which contains the Unique Identifier of the board assigned by the manufacturer.</li><li>T_CAL_1, which holds the calibration value of the board's temperature sensor at 30ºC.</li><li>T_CAL_2, which holds the calibration value of the board's temperature sensor at 100ºC.</li><li>VREFINT_CAL, which contains the calibration value of the board's voltage sensor.</li></ul>
Covid-19 Vaccine Monitoring project (CVM)-Electronic Health Record data sources Codelist
<p>This is the code list that was used to identify outcomes and covariates (those tagged as in narrow) in electronic health records of participating data sources in the the CVM study which was addressing the following questions</p> <p> </p> <p>1)<strong> To create and assess readiness of electronic health record data sources for rapid evaluation of safety signals by </strong></p> <ul> <li> <p>Providing an overview of the methods for identification of COVID-19 vaccine exposure in the data sources </p> </li> <li> <p>Monitoring the number of individuals exposed to any COVID-19 vaccine and to compare this to COVID-19 vaccine exposure (benchmark: ECDC vaccine tracker)1 </p> </li> <li> <p>Generation of updated background rates for AESIs </p> </li> </ul> <p><strong>2) To conduct rapid safety assessment studies using electronic healthcare records and support EMA safety assessments. </strong></p> <p>The protocol for this study is publicly available www.encepp.eu/encepp/viewResource.htm?id=42637. The report with results using the code list is publicly available on Zenodo as well. </p> <p> </p> <p> </p> <p> </p>
Electronic appendix for "Are we there yet? A critical experimental assessment of the application of induced polarization for monitoring geochemical processes", Strobel, C., Störiko, A, Olaf, O.A. & Mellage, A.
Open the record for dataset details and reuse information.
ScintPi 2.0 and 3.0: low-cost GNSS-based monitors of ionospheric scintillation and total electron content
<p> </p> <p>This data set provides measurements made by PolaR5x and ScintPi3.0 receivers in Presidente Prudente, Brazil for two consecutive days.</p>
Ion-Pair Dynamics upon Photoinduced Electron Transfer Monitored by Pump-Pump-Probe Spectroscopy
<p>The files contain all the data that are shown in the figures of the main text and of the supporting information of the article:</p> <p>Beckwith, J.; Lang, B.; Grilj, J.; Vauthey, E. Ion-Pair Dynamics upon Photoinduced Electron Transfer Monitored by Pump-Pump-Probe Spectroscopy. J. Phys. Chem. Lett. 10 (2019), 10.1021/acs.jpclett.9b01431</p>
Data repository of the paper "The First Terrestrial Electron Beam Observed by The Atmosphere-Space Interactions Monitor" by D. Sarria et al.
<p>Data repository / Supporting information of the paper "The First Terrestrial Electron Beam Observed by The Atmosphere-Space Interactions Monitor" (2019) by D. Sarria et al.</p> <p>Access to the article: <a href="https://doi.org/10.1029/2019JA027071">https://doi.org/10.1029/2019JA027071</a></p>
E-MOSAIC Electronic Tool to Monitor Symptoms
ClinicalTrials.gov study NCT00477919. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Monitoring of Palliative Care Needs in Specialized Palliative Home Care Using the Electronic Version of the Integrated Palliative Care Outcome Scale
ClinicalTrials.gov study NCT03879668. IPD Sharing: NO. Countries: 1. Publications: 3.
Electronic Monitoring and Improvement of Adherence to DOACs in Polymedicated Stroke Patients
ClinicalTrials.gov study NCT03344146. IPD Sharing: NO. Countries: 1. Publications: 5.
Electronic Patient-reported Outcome Monitoring in Aplastic Anemia and Paroxysmal Nocturnal Hemoglobinuria
ClinicalTrials.gov study NCT04128943. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Reduction in Time With Electronic Monitoring In Stroke
ClinicalTrials.gov study NCT02808806. IPD Sharing: UNDECIDED. Countries: 1. Publications: 15.
Electronic Pill Bottle Monitoring to Promote Medication Adherence for People With Multiple Sclerosis
ClinicalTrials.gov study NCT04130256. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Connecting Smartphones With Electronic Health Record to Facilitate Behavioral Goal Monitoring in Diabetes Care
ClinicalTrials.gov study NCT02664233. IPD Sharing: Not stated. Countries: 1. Publications: 1.
LabAlert: Enhancing Medication Safety Through Electronic Interventions to Improve Laboratory Monitoring
ClinicalTrials.gov study NCT00256386. IPD Sharing: Not stated. Countries: 1. Publications: 38.
My Healthy Diary - An Electronic Diary for Remote Migraine Monitoring
ClinicalTrials.gov study NCT04828941. IPD Sharing: UNDECIDED. Countries: 1. Publications: 11.
Electronic Self-monitoring on Regulation of the Sleep-wake Cycle to Reduce Relapse of Depression After Discharge
ClinicalTrials.gov study NCT02679768. IPD Sharing: YES. Countries: 1. Publications: 2.
An Electronic Registry to Improve Adherence to Active Surveillance Monitoring at a Safety-net Hospital
ClinicalTrials.gov study NCT03553732. IPD Sharing: NO. Countries: 1. Publications: 1.
Monitoring Your Exercise-related Metrics Over Time Via Wearable Electronic Devices
ClinicalTrials.gov study NCT05124405. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Electronic Monitoring Combined With Weekly Feedback and Reminders
ClinicalTrials.gov study NCT03277664. IPD Sharing: NO. Countries: 1. Publications: 1.
Heart Failure Monitoring With Eko Electronic Stethoscopes (CardioMEMS)
ClinicalTrials.gov study NCT05080504. IPD Sharing: UNDECIDED. Countries: 1. Publications: 16.
ScienceDex guides
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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.