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8,460
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Dataset results
8,460 results for “MONITORING”
Data sets for "On the detection of a solar radio burst event that occurred on 28 August 2022 and its effect on GNSS signals as observed by ionospheric scintillation monitors distributed over the American sector" by Wright et al.
<p>Copy of data described in 'On the detection of a solar radio burst event that occurred on 28 August 2022 and its effect on GNSS signals as observed by ionospheric scintillation monitors distributed over the American sector' by Wright et. al and to appear in the Journal of Space Weather and Space Climate (JSWSC), 2023.</p><p> </p>
Population links between an insectivorous bird and moths disentangled through national scale monitoring data
<p>Code in support of "Population links between an insectivorous bird and moths disentangled through national scale monitoring data"</p> <p>Luke Christopher Evans, Malcolm D. Burgess, Simon G. Potts, William E. Kunin, Tom H. Oliver</p>
Assessing the Maturity level of Wearable Sensors for Home Monitoring in Parkinson's Disease through Evidence Evaluation Levels (EEL) and User Experience: A Comprehensive Review
<p>Source files for the PRISMA diagram and Figure 1 of the comprehensive review: Assessing the Maturity level of Wearable Sensors for Home Monitoring in Parkinson’s Disease through Evidence Evaluation Levels (EEL) and User Experience</p>
Dataset for "Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data"
<p>"<span>Benchmarking automated detection and classification approaches for long-term acoustic monitoring of endangered species: a case study on gibbons from Cambodia</span>"</p> <div> <p><span>Recent advances in deep learning and transfer learning have revolutionized our ability for the automated detection of acoustic signals from long-term soundscape recordings. Here, we provide a benchmark for the automated detection of southern yellow-cheeked crested gibbon (<em>Nomascus gabriellae</em>) calls recorded in Jahoo, Cambodia. For the benchmarking, we compared the performance of support vector machines (SVMs), a quasi-DenseNet architecture (Koogu), transfer learning with ResNet50 models trained on the ‘ImageNet’ dataset (ResNet), and transfer learning with embeddings from a global birdsong model (BirdNET). We also investigated the impact of varying the number of training samples on the performance of these models. Transfer learning models based on <span>BirdNET embeddings had superior performance with a smaller number of training samples, whereas Koogu and ResNet models only had acceptable performance with a larger number of training samples (>200 gibbon samples). We deployed the BirdNET-based model over </span>> 130,000 hours<span> of continuous soundscape data, which, after manual review, resulted in >12,000 verified true positive detections. We found that gibbon calling events occurred mostly in the early morning hours between 05:00 to 0:600 local time. We had fewer gibbon detections during the monsoon period and found substantial variation in spatial patterns of calling events across months and years. </span>We show that automated detection can be used to investigate long-term spatial and temporal patterns of gibbon calling events. Reliable automated detection approaches are a critical first step for using passive acoustic monitoring to assess endangered gibbon populations at ecologically relevant temporal- and spatial-scales. </span></p> <p> Detailed instructions regarding use are provided on GitHub.</p> </div> <p>Link to GitHub: https://github.com/DenaJGibbon/benchmark-gibbon-calls.</p> <p>Please cite both if you use these data: </p> <p>Clink, D., Cross-Jaya, H., Kim, J., Ahmad, A. H., Hong, M., Sala, R., Birot, H., Agger, C., Vu, T. T., Thi, H. N., Chi, T. N., & Klinck, H. (2024). Dataset for "Benchmarking for the automated detection of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data" [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.12706803" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.12706803</a></p> <p>Clink DJ, Cross-Jaya H, Kim J, Ahmad AH, Hong M, Sala R, Birot H, Agger C, Vu TT, Thi HN, Chi TN. Benchmarking for the automated detection and classification of southern yellow-cheeked crested gibbon calls from passive acoustic monitoring data. bioRxiv. 2024:2024-08.</p>
Data for monitoring stakeholder engagement
<p>This data is collected during the project’s stakeholder engagement activities with a view to effectively measuring and reporting the progress of these activities. With that in mind, a dedicated methodological tool has been designed and is being employed throughout the duration of INVITE, namely the Stakeholder Matrix. In this respect, this Stakeholder matrix includes anonymised and aggregated data about key stakeholders (organization type, gender and region / country).</p>
Remote Monitoring in Obstructive Sleep Apnea
ClinicalTrials.gov study NCT01678560. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Feasibility of Monitoring Health Data in Pediatric Patients Undergoing Chemotherapy
ClinicalTrials.gov study NCT04134429. IPD Sharing: YES. Countries: 1. Publications: 1.
Treatment and Recovery Monitoring of Post TBI Symptoms
ClinicalTrials.gov study NCT02426749. IPD Sharing: NO. Countries: 1. Publications: 1.
NIRS Monitoring to Detect AKI in Preterm Infants
ClinicalTrials.gov study NCT03384173. IPD Sharing: NO. Countries: 1. Publications: 5.
Safety and Efficacy Study of IPG Patient With Home Monitoring
ClinicalTrials.gov study NCT01523704. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Monitoring Eating Across Locations (MEAL) - Timing, Intake, and Mealtime Evaluation (TIME)
ClinicalTrials.gov study NCT07095166. IPD Sharing: YES. Countries: 1. Publications: 7.
Accuracy of the Dexcom G6 Continuous Glucose Monitoring System Following Cardiac Surgery
ClinicalTrials.gov study NCT04569240. IPD Sharing: NO. Countries: 1. Publications: 5.
Full Early Atrial Diagnostics in Single Chamber ICD Patients Using the DX Lead and Home Monitoring in Brazil.
ClinicalTrials.gov study NCT04869527. IPD Sharing: NO. Countries: 1. Publications: 0.
Closed-Loop Fluid Administration System Using Hemodynamic Monitors
ClinicalTrials.gov study NCT02020863. IPD Sharing: UNDECIDED. Countries: 1. Publications: 15.
Feasibility and Clinical Utility of the Dexcom G6 Continuous Glucose Monitoring Device for Type 2 Diabetes
ClinicalTrials.gov study NCT05523362. IPD Sharing: NO. Countries: 1. Publications: 0.
Prolongation of the Interval Between Monitoring of Warfarin in Stable Patients
ClinicalTrials.gov study NCT00356759. IPD Sharing: NO. Countries: 1. Publications: 1.
Inpatient Monitoring of Unfractionated Heparin
ClinicalTrials.gov study NCT06329921. IPD Sharing: YES. Countries: 1. Publications: 6.
Continuous Glucose Monitoring for Screening for Diabetes in Pregnancy
ClinicalTrials.gov study NCT05430204. IPD Sharing: NO. Countries: 1. Publications: 1.
Self-monitoring Activity: a Randomized Trial of Game-oriented Applications
ClinicalTrials.gov study NCT02341235. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Wireless Physiologic Monitoring in Postpartum Women
ClinicalTrials.gov study NCT04060667. IPD Sharing: NO. Countries: 1. Publications: 1.
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.