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8,460 results for “MONITORING”
Description of the monitoring analysis and evaluation of the new façade elements for building envelopes in both new construction and renovation.
<p>Deliverable with descritpion of Eco-Binder demo buildings</p>
European demonstration program on the effect-based and chemical identification and monitoring of organic pollutants in European surface waters - Supporting Material
<p>This data contains the supporting material of the publicaiton <a href="https://www.sciencedirect.com/science/article/pii/S0048969717314365">European demonstration program on the effect-based and chemical<br> identification and monitoring of organic pollutants in European surface waters.</a></p> <p> </p>
The viral load monitoring cascade in a resource-limited setting: a prospective multicentre cohort study after introduction of routine viral load monitoring in rural Lesotho
<p>Anonymised dataset for the submitted manuscript "The viral load monitoring cascade in a resource-limited setting: a prospective multicentre cohort study after introduction of routine viral load monitoring in rural Lesotho"</p>
Supplementary dataset and source code for the paper "Using Weaker Consistency Models with Monitoring and Recovery for Improving Performance of Key-Value Stores"
<p>Supplementary dataset and source code for the paper "Using Weaker Consistency Models with Monitoring and Recovery for Improving Performance of Key-Value Stores" submitted to Journal of the Brazilian Computer Society, LADC special issue.</p>
Monitoring of the UHPFRC strengthened Chillon viaduct under environmental and operational variability
<p>Datasets corresponding to 3 months of data of the monitoring of Chillon viaduct.</p> <p>Each file contains: </p> <ul> <li>the vibration data from 11 acelerometers, in vertical direction</li> <li>the sampling ratio</li> <li>Temperature </li> <li>Humidity</li> </ul> <p>The accelerometer positions are illustarted in the pdf "accelerometres Position.pdf". </p> <p>When employing this dataset, please cite:"Martín-Sanz, Henar, Konstantinos Tatsis, Vasilis K. Dertimanis, Luis David Avendaño-Valencia, Eugen Brühwiler, and Eleni Chatzi. "Monitoring of the UHPFRC strengthened Chillon viaduct under environmental and operational variability." <em>Structure and Infrastructure Engineering</em> (2019): 1-31."</p>
Validation of a multi-primer assay for monitoring coral diversity using eDNA metabarcoding
<p>Raw data output from Scleractinia eDNA metabarcoding survey completed using multi-assay approach.</p>
Data for: Scalable Flood Level Trend Monitoring with Surveillance Cameras using a Deep Convolutional Neural Network [Version 2]
<p>This package provides material that can be openly published for the paper "Scalable Flood Level Trend Monitoring with Surveillance Cameras using a Deep Convolutional Neural Network". It consists in the code used to generate results and figures as well as the weights of the deep convolutional neural networks trained to segment water in the surveillance camera images.</p>
Supplementary material 1 from: Bowser ML, Burr SJ, Davis I, Dubois GD, Graham EE, Moan JE, Swenson SW (2019) A test of metabarcoding for Early Detection and Rapid Response monitoring for non-native forest pest beetles (Coleoptera). Research Ideas and Outcomes 5: e48536. https://doi.org/10.3897/rio.5.e48536
This file contains the specimen data from the original trap samples, morphological identifications, molecular identifications, and resulting occurrence data.
Fig. 1 in Using dragonflies to monitor and prioritize lotic systems: a South African perspective
Fig. 1 Plot of South Africa Scoring System (SASS)5 scores as a function of Average Score Per Taxon (ASPT). Ecological categories (A–E/F) are explained in Table 1, and SASS5 and ASPT scores are given in Table 2
Fig. 1 in Coleoptera Monitoring Following Prescribed Fire Disturbance Yields 43 New State Species Records for Kentucky, USA
Fig. 1. Traps used for specimen collection in Berea College Forest, Madison County, Kentucky, USA. Lindgren flight intercept traps placed in: A) Burned forest, B) Unburned forest. C) Pitfall trap placed in burned forest, D) Burn Unit 1 photographed 48 h post-burn.
Data for "Statistical Process Monitoring of Isolated and Persistent Defects in Complex Geometrical Shapes"
<p>Simulated data used in the paper "Statistical Process Monitoring of Isolated and Persistent Defects in Complex Geometrical Shapes" by Daniele Zago, Bianca Maria Colosimo, and Giovanna Capizzi.</p> <p>The files includes MATLAB code used to generate the simulated noisy meshes.</p>
Restart uncertainty relation for monitored quantum dynamics. DataSet
<p>Source Data Set for the publication entitled: Restart uncertainty relation for monitored quantum dynamics.</p>
[Simulation] Dynamics, Monitoring and Forecasting of Tephra in the Atmosphere.
<p><span><span>This repository </span><span>contains</span><span> the simulations</span><span> to produce Figures 1</span><span>5</span><span> and 1</span><span>7</span><span> in " </span><span>Dynamics, Monitoring and Forecasting of Tephra in the Atmosphere</span><span> " - Reviews of Geophysics, by </span></span><span><span>Pardini</span> </span><span><span>et al. (2024).</span></span><span> </span></p>
Data for "Entanglement phases, localization and multifractality of monitored free fermions in two dimensions".
<p>This folder contains the numerical data to reproduce all figures in the paper "Entanglement phases, localization and multifractality of monitored free fermions in two dimensions". All data are in csv format and were read and plotted on Jupyter notebooks. </p> <p>Each subfigure has an own subfolder where data is stored. For figures with insets there is a separate subfolder for the main plot and the inset, except the cases where inset and main use the same data (e.g. Fig. 3b). All data is obtained directly from simulations as outlined in the main text except fit data (e.g. Fig. 5a) or data obtained from a scaling collapse (inset of Fig. 3b).</p>
Dataset for cattle growth monitoring in PLF using UAV-based LiDAR
<p>This is the dataset for the data article named "Integrated UAV-based LiDAR and RGB Data for Individual-Level Cattle Growth Monitoring in Precision Livestock Farming".</p>
Replication Package: Anomaly detection via runtime monitoring data for structural equation modeling
<p>This replication package contains the following information:</p> <ul> <li><strong>Data extraction from literature & interviews: </strong><em>Generation Structural & Measurement Model via literature and interviews.xlsx</em> - here you can find the mapping of the extracted phrases to inductively summarise information regarding the structural and measurement models.</li> <li><strong>Dataset</strong> of runtime monitoring data extracted from TrainTicket via EvoMaster: <br> <ul> <li><em>TrainTicket faults classification.xlxs:</em> Describes the datasets and their faults, in which microservice the fault is injected for better explainability of the obtained results</li> <li><em>IndicatorDescriptionbasedonAnomalyDetectionToolsInterviews.xlsx:</em> description and mapping of selected indicators to the defined parameters from <a href="https://arxiv.org/abs/2408.07816" target="_blank" rel="noopener">previous work </a></li> <li>Unfortunately, the size of the datasets generated via EvoMaster and their injected faults are too big to upload here, thus, they will be available here: <a href="https://uibkacat-my.sharepoint.com/:f:/g/personal/monika_steidl_uibk_ac_at/EjLMt8SYWwtJtp2YuSaqavcBKJoCQ3b5H_l_OY0ifbVRCA?e=fatKyD" target="_blank" rel="noopener">Datasets with injected anomalies</a><br> <ul> <li>the error description can be found <a href="https://github.com/FudanSELab/train-ticket/wiki/Fault-Description" target="_blank" rel="noopener">here</a></li> <li>the datasets are named ts-error-<em>indicatorOfError</em>-reset.zip because the databases are getting reset so that no anomalies are introduced with wrong database entries</li> </ul> </li> </ul> </li> <li><strong>Code</strong> for handling and transforming data to extract indicators describing the whole system's and microservices' behavior from the collected runtime monitoring data collected from TrainTicket:<br> <ul> <li><a href="https://github.com/moniSt13/ConTest-Parsing" target="_blank" rel="noopener">link to the Github repository</a></li> </ul> </li> <li><strong>reports</strong> regarding the established PLS-SEM model using previously handled and transformed runtime monitoring data. Please be aware that opening the reports can leas to out of memory due to their size: <ul> <li><em>Assessment of Measurement Model: MeasurementModel_TrainTicket_erorcleaned.zip & MeasurementModel_Bootstrap_ALL_TrainTicket_errorcleaned.zip</em> </li> <li><em>Assessment of Structural Model: StructuralModel_TrainTicket_errorcleaned.zip & StructuralModel_Bootstrap_ALL_TrainTicket_errorcleaned.zip</em></li> </ul> </li> </ul> <p><br><br>---------------------------------------</p> <p><em>Future work </em>not elaborated in the associated paper due to space restrictions:</p> <ul> <li><strong>reports regarding F5 error</strong>: PLS-SEM model results without interpretation and further mediating effects between microservices included: F5_error.zip</li> </ul> <p> </p> <p> </p> <p> </p>
Natural hydrogen and carbon dioxide soil gas emissions in the Perth Basin: Monitoring near DMP Harvey-2
<p>Data in support of the publication "Natural hydrogen and carbon dioxide soil gas emissions in the Perth Basin: Monitoring near DMP Harvey-2"</p>
Monitoring water content variations from seismic noise in a controlled laboratory experiment: PART 2 [Dataset]
<p>This dataset has been obtained with an original laboratory experiment aimed at assessing the sensitivity of passive seismic interferometry imaging (PII) to controlled fluctuations in water content. Multiple controlled cycles of water imbibition and draining at the base of the sandbox produce significant variations in the seismic wavefield and especially in dominant surface waves. PART 2: seismic measurements from 1501 to 2700minutes</p>
Monitoring water content variations from seismic noise in a controlled laboratory experiment: PART 1 [Dataset]
<p>This dataset has been obtained with an original laboratory experiment aimed at assessing the sensitivity of passive seismic interferometry imaging (PII) to controlled fluctuations in water content. Multiple controlled cycles of water imbibition and draining at the base of the sandbox produce significant variations in the seismic wavefield and especially in dominant surface waves. PART 1: seismic measurements from 0001 to 1500minutes</p>
Monitoring instrumentations at italian volcanoes
<p>Excel file, in which the monitoring stations at each Italian volcano have been noted.</p>
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.