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471 results for “monitoring and evaluation”
Telegraf evaluation for AI-SPRINT Monitoring Subsystem
<p>Performance impact evaluation of the AI‑SPRINT Monitoring Subsystem on a system deployment running the AI‑SPRINT Framework with AI applications</p>
Datasets for paper "Evaluating the PurpleAir monitor as an aerosol light scattering instrument"
<p>The data sets included will allow the user to reproduce the plots and analyses described in Ouimette et al. (2022). The Collocated*csv file contains data from multiple collocated PurpleAirs that sampled for a few days. The data in this file was used in the precision analysis in section 2.2.9 of the paper. The other files contain nephelometer and PurpleAir data from Mauna Loa (MLO) and Table Mountain (BOS) and DMPS size distribution files from BOS. Their contents are described in the README.TXT file.</p>
Monitoring feedback to authors on the quality of trials evaluating interventions aimed at preventing and treating COVID-19
<p>We aimed to assess transparency of reporting and risk of bias of randomized trials evaluating interventions aimed at preventing and treating COVID-19.</p> <p>This review is part of a larger project: the COVID-NMA project (Boutron 2020a). The COVID-NMA project aims to provide decision-makers with a complete, high-quality and up-to-date synthesis of evidence on interventions for the prevention and treatment of COVID 19. For this purpose, we perform a living mapping of all registered randomized controlled trials and a living evidence synthesis of data from RCTs. We developed a master protocol on the effect of all interventions for the prevention and treatment of COVID-19 (first published on April 8, 2020; an update on May 11, 2020, June 17, 2020, and September 8, 2020) (Boutron 2020b). We set-up a platform (<a href="https://covid-nma.com/">https://covid-nma.com</a>) where all our results are made available and updated weekly.</p>
Raw Data for Evaluation of Measurement Uncertainty in Structural Health Monitoring Systems Under Temperature Influence
<p>The documentation on these laboraty tests is titled "Documentation.pdf"</p> <p> </p> <p>Raw data from distance measurements using laser triangulation sensors acquired under different temperatures are provided. Six sensors were tested per experiment (CSV file), and in each experiment the boundary conditions are varied as follows:<br><br>00RawData_LTS_1m: The entire measurement system is subject to temperature change, with initial distances chosen as LTS1/LTS2=17 mm, LTS3/LTS4=21 mm nd LTS5/LTS6=25 mm.<br><br>01RawData_LTS_1m_SwitchedDistances: The entire measurement system is subject to temperature change, with the selected initial distances of LTS1/LTS2=25 mm, LTS3/LTS4=17 mm nd LTS5/LTS6=21 mm.<br><br>02RawData_LTS_1m_SwitchedDistances2: The entire measurement system is subject to temperature change, with initial distances selected as LTS1/LTS2=21 mm, LTS3/LTS4=25 mm nd LTS5/LTS6=17 mm.<br><br>03RawData_LTS_1m_OnlySensor: Only the sensors of the measuring system are subject to temperature change, where the selected initial distances are LTS1/LTS2=21 mm, LTS3/LTS4=25 mm nd LTS5/LTS6=17 mm.<br><br>04RawData_LTS_1m_OnlyMeasuringAmplifier: Only the measuring amplifiers of the measuring system are subject to temperature change. The selected initial distances are LTS1/LTS2=21 mm, LTS3/LTS4=25 mm nd LTS5/LTS6=17 mm.<br><br>05RawData_LTS_1m_OnlyCable: Only the cables of the measurement system are subject to the temperature change. The selected initial distances are LTS1/LTS2=21 mm, LTS3/LTS4=25 mm nd LTS5/LTS6=17 mm.<br><br>Tested temperature range: -10°C to 50°C<br>Measuring frequency: 1 Hz<br>Measuring amplifier: Q.bloxx.XL A107 Gantner Instruments<br>Cable: 4-pole, 1.00 m length<br>Sensor: OM20-P0026.HH.YIN laser triangulation sensor from Baumer</p>
Monitoring and evaluation of UKRI's Open Access Policy: Exploring the use of open data sources to inform baseline values - Dataset
<p>This dataset accompanies the report <em>"Monitoring and evaluation of UKRI's Open Access Policy: Exploring the use of open data sources to inform baseline values"</em>, which is available via Zenodo.<br><br>It provides record-level data of UKRI-funded and UK-affiliated research output (limited to journal articles with Crossref DOIs) published between 2012 and 2022 - including bibliographic metadata as well as data on open access availability, publisher, national and international collaborations, citations, views and downloads, altmetrics and subjects (fields). All variables are documented in the data dictionary included in this Zenodo record.</p> <p>The code used to generate the dataset from open data sources is available on GitHub. </p> <p>The following data sources were used:</p> <ul> <li> <p>Gateway to Research (records downloaded between 2023-11-05 and 2023-11-13)</p> </li> <li> <p>Crossref (Metadata Plus snaphot 2023-10-31, Crossref member route API 2024-01-23)</p> </li> <li> <p>OpenAlex (data snapshot 2023-10-18)</p> </li> <li> <p>Unpaywall (data snapshot 2023-11-27)</p> </li> <li> <p>IRUS UK (2024-04-03)</p> </li> <li> <p>Crossref Event Data (2023-04-01)</p> </li> </ul> <p><strong></strong><br><br>The project made use of Curtin Open Knowledge Initiative (COKI) infrastructure, which is documented on GitHub: <a href="https://github.com/The-Academic-Observatory">https://github.com/The-Academic-Observatory</a>. </p>
Peatland restoration in Norway – evaluation of ongoing monitoring and identification of plant indicators of restoration success
<p>Norway launched a national action plan on wetland restoration in 2016. So far, 90% of the restoration effort has been on peatland restoration, with about 140 mires restored so far. There are three main restoration goals stated in the action plan: 1) Limit greenhouse gas (GHG) emissions, 2) climate adaptation, and 3) improve ecological condition. Quantifying the outcome of the restoration actions is necessary to evaluate whether the goals of the action plan are met. A vegetation monitoring protocol was suggested before restoration started and has been implemented at five restoration sites. As the peatland restoration effort in Norway is increasing, it is timely to evaluate if the data currently collected can measure peatland restoration outcomes. We evaluate the monitoring protocol based on statistical analyses of the data collected at two sites, describe how indicator species can be identified using generalized composition data used as the basis for classifying habitats in Norway (EcoSyst framework), and suggest the way forward for peatland restoration monitoring in Norway. Data collected according to the monitoring protocol can document changes in species composition at restoration sites but has limitations when the ecological complexity at the sites increases and reference sites are unavailable. We argue that adjusting the monitoring protocol will: 1) Facilitate alignment with existing peatland research; 2) connect better with monitoring programs where data is collected applying EcoSyst framework principles; and 3) enable upscaling to cover the wide variation emerging in peatland restoration.</p>
Reporting Database of the INCENTIVE project's monitoring and evaluation activities of the Citizen Science Hubs pilot operation (M16-M31)
<p>The current excel file constitutes the INCENTIVE Reporting Database, meaning a repository of the data that were accumulated in WP4 (described within Deliverable 4.1). The results presented here are the main input for the elaboration of Deliverable 4.2 and Deliverable 4.3.</p>
Recordings from: Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy, and exclusion zone monitoring
<p>1.<span> </span>There is strong socio-political support for offshore wind development in US territorial waters, and construction is planned off several east coast states. Some of the planned development sites coincide with important habitat for critically endangered North Atlantic right whales. Both exclusion zones and passive acoustic monitoring are important tools for managing interactions between marine mammals and human activities. Understanding where animals are with respect to exclusion zones is important to avoid costly construction delays while minimizing the potential for negative impacts. Impact piling from construction of hundreds of offshore wind turbines likely requires exclusion zones as large as 10 km.</p> <p>2.<span> </span>We have developed a three-hydrophone passive acoustic monitoring system that provides bearing information along with marine mammal detections to allow for informed management decisions in real-time. Multiple units form a monitoring system designed to determine whether marine mammal calls originate from inside or outside of an exclusion zone. In October 2021 we undertook a full system validation, with a focus on evaluating the detection range and bearing accuracy of the system with respect to right whale upcalls. Five units were deployed in Mid-Atlantic waters and we played more than >3,500 simulated right whale upcalls at known locations to characterize the detection function and bearing accuracy of each unit. The modeled results of the detection function error were then used to compare the effectiveness of a bearing-based system to a single sensor that can only detect a signal but not ascertain directivity.</p> <p>3.<span> </span>Field trials indicated maximum detection ranges from 4–7.3 km depending on source and ambient noise levels. Simulations showed that incorporating bearing detections provides a substantial improvement in false alarm rates (6 to 12 times depending on number of units, placement, and signal to noise conditions) for a small increase in the risk of missed detections inside of an exclusion zone (1–3%). </p> <p>4.<span> </span>We show that the system can be used for monitoring exclusion zones and clearly highlight the value of including bearing estimation into exclusion zone monitoring plans while noting that placement and configuration of units should reflect anticipated ambient noise conditions.</p>
Supplementary Data for "Development of a General Calibration Model and Long-Term Performance Evaluation of Low-Cost Sensors for Air Pollutant Gas Monitoring" (abridged version)
<p>This is a supplementary data set associated with the publication "Development of a General Calibration Model and Long-Term Performance Evaluation of Low-Cost Sensors for Air Pollutant Gas Monitoring" from the Center for Atmospheric Particle Studies, submitted to Atmospheric Measurement Techniques. This is an abbreviated version which does not include the calibrated models; these models must be re-generated by running the codes contained with the data set.</p> <p> </p>
Fig. 2 in Evaluating the use of phenylacetonitrile plus acetic acid to monitor Pandemis pyrusana and Cydia pomonella (Lepidoptera: Tortricidae) in apple
Fig. 2. Mean (SE) number of male, female, and total Pandemis pyrusana caught in traps baited with either the sex pheromone lure (males only) or with phenylacetonitrile plus an acetic acid co-lure (males, females, and total moths). '*' denotes a significant mean difference as compared to male catch in the sex pheromone-baited trap, P <0.05.
Fig. 1 in Evaluating the use of phenylacetonitrile plus acetic acid to monitor Pandemis pyrusana and Cydia pomonella (Lepidoptera: Tortricidae) in apple
Fig. 1. Mean (SE) number of male, female, and total Cydia pomonella caught in traps with a sex pheromone plus pear ester combo lure and an acetic acid (AA) co-lure versus in traps with these same lures with the addition of a phenylacetonitrile (PAN) sachet lure, 7–21 Jul 2014, Moxee Washington, USA. 'N.S.' denotes a nonsignificant difference in moth catches between the 2 types of lures, P> 0.05.
DCASE 2018, Task 5: Monitoring of domestic activities based on multi-channel acoustics - Evaluation dataset
<p>The dataset is a derivative of the SINS dataset and is meant to be used as an evaluation set for the <a href="http://dcase.community/challenge2018/task-monitoring-domestic-activities">DCASE2018 Task 5 challenge</a>. The development set to be used can be found <a href="https://zenodo.org/record/1247102#.WzIF_NUzZhE">here</a>. The dataset is a derivative of the SINS database.</p> <p>The SINS database contains a continuous recording of one person living in a vacation home over a period of one week. The recordings were manually annotated on daily activity level: "Cooking", "Dishwashing", "Eating", "Social activity (visit, phone call)", "Vacuum cleaning", "Watching TV", "Working", "Presence" and "Absence". More information can be found on (please cite this papers when using the dataset):</p> <p>G. Dekkers, S. Lauwereins, B. Thoen, M. W. Adhana, H. Brouckxon, T. van Waterschoot, B. Vanrumste, M. Verhelst, and P. Karsmakers, “The SINS database for detection of daily activities in a home environment using an acoustic<br> sensor network,” in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017), Munich, Germany, November 2017, pp. 32–36.</p> <p>G. Dekkers, L. Vuegen, T. van Waterschoot, B. Vanrumste, and P. Karsmakers, “DCASE 2018 Challenge - Task 5: Monitoring of domestic activities based on multi-channel acoustics,” KU Leuven, Tech. Rep., July 2018.</p> <p>The derivative of the SINS database, 'DCASE 2018 – Task 5 evaluation dataset' consists of data collected by 7 microphone arrays in the combined living room and kitchen area. The continuous recordings were split into audio segments of 10s. These audio segments are provided as individual files. In total 72972 segments are made available, leading to approximately 200 hours of data with annotations.</p> <p>More information about the challenge and the specific dataset can be found here. Information solely related to the content of the dataset is available in 'DCASE2018-task5-eval.doc.zip'.</p> <p>By accessing or using this database, the user accepts the provided EULA (available in DCASE2018-task5-eval.doc.zip).</p>
Data from: evaluating the use of lake sedimentary DNA in palaeolimnology: a comparison with long-term microscopy-based monitoring of the phytoplankton community
<p>Palaeolimnological records provide valuable information about how phytoplankton respond to long-term drivers of environmental change. Traditional palaeolimnological tools such as microfossils and pigments are restricted to taxa that leave sub-fossil remains, and a method that can be applied to the wider community is required. Sedimentary DNA (sedDNA), extracted from lake sediment cores, shows promise in palaeolimnology, but validation against data from long-term monitoring of lake water is necessary to enable its development as a reliable record of past phytoplankton communities. To address this need, 18S rRNA gene amplicon sequencing was carried out on lake sediments from a core collected from Esthwaite Water (English Lake District) spanning ~105 years. This sedDNA record was compared with concurrent long-term microscopy-based monitoring of phytoplankton in the surface water. Broadly comparable trends were observed between the datasets, with respect to the diversity and relative abundance and occurrence of chlorophytes, dinoflagellates, ochrophytes and bacillariophytes. Up to 20% of genera were successfully captured using both methods, and sedDNA revealed a previously undetected community of phytoplankton. These results suggest that sedDNA can be used as an effective record of past phytoplankton communities, at least over timescales of less than 100 years. However, a substantial proportion of genera identified by microscopy were not detected using sedDNA, highlighting the current limitations of the technique that require further development such as reference database coverage. The taphonomic processes which may affect its reliability, such as the extent and rate of deposition and DNA degradation, also require further research.</p>
Evaluation of different settlement substrates for field-based collection of Ostrea edulis. Spatial variation in oyster spat settlement along the Swedish west coast was also monitored.
<p>Aim: Evaluate different types of settlement substrates for field-based collection of <em>Ostrea edulis</em>. Document spatial variation in settlement of oyster spat on coupelle collectors along the Swedish west coast.</p> <p>Different types of substrates (shells of different species and materials with different structures) were placed in the sea and the survival and number of spat attached to the substrates were evaluated. Growth and species identification (<em>O. edulis</em> versus <em>M. gigas</em>) were documented. Data was collected from the Swedish west coast in 2020.</p>
Recordings from: Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy, and exclusion zone monitoring
Open the record for dataset details and reuse information.
Peatland restoration in Norway – evaluation of ongoing monitoring and identification of plant indicators of restoration success
Open the record for dataset details and reuse information.
Data from: evaluating the use of lake sedimentary DNA in palaeolimnology: a comparison with long-term microscopy-based monitoring of the phytoplankton community
Open the record for dataset details and reuse information.
Pilot implementation, monitoring, co-evaluation and validation data_v1
<p>These data have been collected in the context of monitoring and assessing the pilot operation of the INVITE project (H2020 GA 763651) and its OI2lab platform during their 1st deployment round.</p>
Data from: Evaluating genotyping-in-thousands by sequencing as a genetic monitoring tool for a climate sentinel mammal using non-invasive and archival samples
<p>Genetic tools for wildlife monitoring can provide valuable information on spatiotemporal population trends and connectivity, particularly in systems experiencing rapid environmental change. Though many DNA sequencing approaches still require high quality and quantity of DNA obtained from traditional sources (e.g. blood and tissue), rapid genotyping tools such as Genotyping-in-Thousands by sequencing (GT-seq) have improved our ability to make use of degraded and less concentrated DNA commonly obtained from non-invasive and archival samples. Here, we developed a multi-purpose GT-seq panel (307 single nucleotide polymorphisms) for a climate sentinel mammal (the American pika, <em>Ochotona princeps</em>) for use as a genetic tool for monitoring populations in the Canadian Rocky Mountains. We optimized the panel using contemporary tissue samples (n = 77) and subsequently applied it to archival tissue (n = 17) and contemporary fecal pellet samples (n = 129) to evaluate its effectiveness at identifying individuals and sex, estimating relatedness, and inferring population structure. The panel demonstrated high efficacy with contemporary and archival tissue samples (94.7% and 90.5% genotyping success, respectively) and negligible genotyping error (0.001% and 0.0%, respectively). Despite relatively high genotyping success for fecal pellet samples (79.7%), high genotyping error (28.4%) limited its power as a monitoring tool to assess genetic variation using non-invasive samples and highlighted the need for further optimization around sample and data collection.</p>
Dataset for the article "PERFORMANCE EVALUATION OF AN IMAGING RADIATION PORTAL MONITOR SYSTEM"
<p>The dataset includes root files used in generating the main figures for the article "PERFORMANCE EVALUATION OF AN IMAGING RADIATION PORTAL MONITOR SYSTEM" by Jana Vasiljević, Alf Göök and Bo Cederwal. The article will be submitted to MDPI Applied Sciences.</p> <p> </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
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.