Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
8,460
datasets available to search
ShareScore release 0.9.0
Dataset results
8,460 results for “MONITORING”
Results from Air Quality Monitoring and Surveys in UK Residences - Appendix (Survey Questions)
<p>Survey questions used in the paper titled "Results from Air Quality Monitoring and Surveys in UK Residences". Abstract below.</p> <p>Air pollution is a persistent issue in dwellings worldwide, costing an estimated 10-25 billion US dollars per year to the United Kingdom’s national health service alone. However, it is an “invisible problem” since background pollutants are often imperceptible except during acute pollution events such as wildfires. Although public awareness of ventilation has increased due to the COVID-19 pandemic, there are few tools available to assess its efficacy. Widely available sensor systems that can measure these pollutants tend to be single units with simple apps and little connection to mitigation, whereas different rooms in a house may have different pollution issues with different recommended actions. In this study, we present the results of a measurement study conducted using a multi-room sensor kit in twenty-nine dwellings across the UK. We also analyze the occupants’ reaction to the hardware, data, and a prototype alerting system. The study shows broad awareness of air quality in the participants. However, this awareness rarely corresponded to effective mitigation actions or ventilation provision. The concept of alerts was welcomed by participants if accompanied by actionable recommendations.</p> <p>The data showed significant pollution events, as measured by proxies such as total VOC and CO<sub>2</sub>, occurring almost daily, particularly in households with gas appliances. These incidents were concentrated around particular times of day and behaviors, indicating that the capacity of infiltration and extract ventilation to bring in adequate fresh air was overwhelmed. No significant outdoor pollution was detected in houses, which was expected given their sheltered peri-urban locations. The study highlights the need for comprehensive implementation of measurement, ventilation, and treatment measures in the UK housing stock to reduce the impact of indoor pollution on health.</p>
Assessing the value of monitoring to biological inference and expected management performance for a European goose population
<p>1. Informed conservation and management of wildlife require sufficient monitoring to understand population dynamics and to direct conservation actions. Because resources available for monitoring are limited, conservation practitioners must strive to make monitoring as cost-effective as possible.</p> <p>2. Our focus was on assessing the value of monitoring to the adaptive harvest management (AHM) program for pink-footed geese (Anser brachyrhynchus). We conducted a retrospective analysis to assess the costs and benefits of a capture-mark-resight (CMR) program, a productivity survey, and biannual population censuses. Using all available data, we fit an integrated population model (IPM) and assumed that inference derived from it represented the benchmark against which reduced monitoring was to be judged. We then fit IPMs to reduced sets of monitoring data and compared their estimates of demographic parameters and expected management performance against the benchmark IPM.</p> <p>3. Costs and the precision and accuracy of key demographic parameters decreased with the elimination of monitoring data. Eliminating the CMR program, while maintaining other monitoring instruments, resulted in the greatest cost savings, usually with small effects on inferential reliability. Productivity surveys were also expensive and some reduction in survey effort may be warranted. The biannual censuses were inexpensive and generally increased inferential reliability.</p> <p>4. The expected performance of AHM strategies was surprisingly robust to a loss of monitoring data. We attribute this result to explicit consideration of parametric uncertainty in harvest-strategy optimization and the fact that a broad range of population sizes is acceptable to stakeholders.</p> <p>5. Synthesis and applications: Our study suggests that existing or potential monitoring instruments for wildlife populations should be scrutinized as to their cost-effectiveness for improving biological inference and management performance. Using Svalbard pink-footed geese as a case study, we show that the loss of some existing monitoring instruments may not be as adverse as commonly assumed if data are jointly analyzed in an integrated population model. Finally, regardless of the monitoring data available, we suggest that conservation strategies that explicitly account for uncertainty in demography are more likely to be successful than those that do not<span>.</span></p>
Cathodoluminescence monitoring of quantum emitter activation in hexagonal boron nitride
<p>Data from the article of S. Roux, C. Fournier, K. Watanabe, T. Taniguchi, J.-P. Hermier, J. Barjon, A. Delteil,<br> "Cathodoluminescence monitoring of quantum emitter activation in hexagonal boron nitride", <a href="https://doi.org/10.1063/5.0126357">Appl. Phys. Lett. <strong>121</strong>, 184002 (2022)</a></p> <p>[<a href="https://arxiv.org/abs/2210.05028">arXiv</a>:2210.05028]</p>
Supporting data sets for "Estimating Carbon Fixation of Plant Organs for Afforestation Monitoring using a Process-based Ecosystem Model and Ecophysiological Parameter Optimization". (the survey of tree breast diameter and tree height in 11-year old Eucommia ulmoides plantation, values of simulation results used in figures and tables.)
<p>Supporting data sets for Miyauchi et al., Ecology and Evolution, 2019 (accepted).</p> <p>The files store: </p> <p>(1) The survey of tree breast diameter and tree height in <em>Eucommia ulmoides</em> plantation<em>.</em> The ring and stem analysis and dry weight of seven harvested sample trees in the plantation.</p> <p>(2) Values of optimization result used fig.7.</p> <p>(3) Values of prediction result used fig.8. and table 4.</p> <p>(4) Values of optimized parameters by optimization methods, parameter range and constrain.</p>
Supplementary material 1 from: Schmeller D, Henle K, Loyau A, Besnard A, Henry P (2012) Bird-monitoring in Europe – a first overview of practices, motivations and aims. Nature Conservation 2: 41-57. https://doi.org/10.3897/natureconservation.2.3644
The questionnaire was designed to assess how biodiversity monitoring schemes were carried out and what the motivation was to launch that scheme.
Figure 7. The outcomes of the Monitoring and Control of the Greenhouse soil and climate Conditions for tomato crops-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p>In the past generation greenhouses it was enough to have one cabled measurement point in<br> the middle to provide the information to the greenhouse automation system. The system itself was<br> usually simple without opportunities to control locally heating, lights, ventilation or some other<br> activity, which was affecting the greenhouse interior climate. The optimal greenhouse climate and<br> soil adjustment can enable us to improve productivity and to achieve remarkable energy savings. In<br> this paper we proposed a multi-agent methodology for integrated management systems in<br> greenhouses. In this regards wireless sensor networks play a vital role to monitor greenhouse and<br> environment parameters. Each controlled process of the greenhouse environment is modeled as an<br> autonomous agent with its own inputs, its own outputs and its own interactions with the other<br> agents. Each agent acts autonomously, as it knows a priori the desired environmental set-points. In<br> this way, any possible conflicting decisions of conventional environmental control methodologies<br> are resolved through negotiations between the agents so that the possible optimal integrated solution<br> is achieved. The developed system is simple, cost effective, and easily installable.</p>
Figure 6. Structure of the MAS for integrated greenhouse management system.-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p>The complete agents “environment” is shown in figure 6. Each agent receives the necessary<br> environmental or plant condition measurements. While each agent keeps its autonomy and has its<br> own “personal” goals, it interacts with the other agents through some specific communication<br> language, in the “Agent discussion area”, where the overall goal is taken into account. This<br> interaction takes place under the presence of information from the existing models and the target<br> goals. At that point, each agent has decided on its best strategy.</p>
Figure 2. Experimental wireless sensors setup in greenhouse-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p>Figure 2 illustrates how the sensor<br> nodes were deployed to the greenhouse block. The idea of the vertical deployment was to get a<br> better understanding of the microclimate layers which typically exist in the greenhouse, and to<br> figure out what kind of differences occur in the climate between lower and upper flora.</p>
Figure 5. Multi-agent system information and knowledge scheme.-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p>The negotiations between agents are subject to optimization based on “knowledge” that is<br> derived from complete production models, yield models or even sparse models as expressed in<br> fuzzy expert rules or practical rules of thumb. In addition, pest control and plant disease models<br> provide additional information useful to the design of a successful strategy for optimal management<br> [15] (illustrated in Figure 5).</p>
Figure 1. Agent Architecture-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p>The multi agent method creates a non-structured environment using agents, these agents, in<br> order to reach the global optimum, must be capable of performing transactions between each other,<br> achieving several “deals”, which is performed though a common vocabulary, a finite set of<br> information exchange, a finite set of possible actions, penalties, etc. The power of each agent<br> depends on the degree of contribution of its represented process to the final output of the entire<br> system. Each agent communicates with the environment and adapts to its own internal state as well<br> as to the state of the entire system. In this systems, for the realization of the multi agent architecture<br> the JADE 4.1.1 (Java Agent DEvelopment Framework) have been used [7].</p>
Figure 4. The multi-agent overall environment for integrated management-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p> The value of the final product incorporates not only quantity issues but also<br> quality issues, which are difficult to be measured or even estimated. The environment of each agent<br> is defined by the same parameters that define the physical environment in addition to internal states<br> reported by each agent.</p>
Figure 3. Photosynthetic activity in different wavelengths of light radiation. 5.-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p>The greenhouse protects the plants from the extreme weather conditions. However, if the<br> period of daylight prevents the photosynthetic activity, the plants do not grow. Horticultural lighting<br> allows the grower to extend the growing season. It enables a year-round producing of plants or<br> makes it possible for the grower to start sowing in early spring and continue season till the first<br> frost. Plants need about 10-12 hours light to improve growth. When the plants are producing<br> flowers or fruits the supplemental need of light per day increases up to 16 hours. Figure 3 shows the<br> photosynthetic activity in different wavelengths of light radiation [16].</p>
Rinker's Treatment Wetland Water Quality monitoring data (2017 - 2019), South Daytona, Florida
<p><span>Water quality was monitored at a constructed treatment wetland in South Daytona, Florida through </span>a<span> </span><span>two-year</span><span> </span><span>project</span><span> </span><span>(Oct</span><span> </span><span>2017-</span><span> </span>Sept<span> </span><span>2019). </span></p> <p><strong><span>The 2017-2018 INDIAN<span> </span><span>RIVER</span><span> </span><span>LAGOON</span><span> </span><span>NATIONAL</span><span> </span><span>ESTUARY</span><span> </span><span>PROGRAM funded Project</span></span></strong></p> <p><strong><span>Submitted to the IRL Council</span></strong></p> <p><strong><span>Oct 8<sup>th</sup>, 2018</span></strong></p> <p><span> </span></p> <p><strong><span>Project<span> </span>Title</span></strong><span>: <span><span> </span></span>Reed<span> </span><span>Canal</span> <span><span> </span></span>Basin <span><span> </span></span>Stormwater <span><span> </span></span>Improvement <span><span> </span></span>through <span><span> </span></span>Treatment <span><span> </span></span>Wetland</span><span> </span><span>Construction<span> </span>in<span> </span>South<span> </span>Daytona,<span> </span>FL</span></p> <p><strong><span>Project<span> </span>Applicant:<span> </span></span></strong><span>Bethune-Cookman</span><span> </span><span>University</span><span> </span><span>(B-CU)</span></p> <p> </p> <p><strong><span>Amount</span></strong><strong><span> </span></strong><strong><span>of</span></strong><strong><span> <span>Request</span></span></strong><span>:</span><span> </span><span>$181,148</span></p> <h3><span>Other</span><span> </span><span>Funding</span> <span>Sources</span><span> </span><span>and</span> <span>Amount</span><span> </span><span>of</span> <span>Total</span><span> </span><span>Match</span><span>:</span><span> </span><span>$183,095</span></h3> <p><span><span>B-C</span></span>U <span><span> </span></span><span>($74,631);</span> <span><span> </span></span><span>EPA</span> <span><span> </span></span><span>319</span> <span><span> </span></span><span>($11,250);</span> <span><span> </span></span><span>Local</span> <span><span> </span></span><span>wetland/tree/shoreline</span> <span><span> </span></span><span>restoration</span> <span><span> </span></span><span>funds</span> <span><span> </span></span><span>(pending</span></p> <p><span>$60,000); AE-Group ($5,000); </span><span>Volunteers</span><span> </span><span>($2,214);</span><span> </span><span>Project </span>H2O<span> </span><span>Academy</span><span> </span><span>and</span><span> </span><span>partners</span><span> </span><span>($30,000)</span></p> <p><span>The project goals were </span><span>to</span><span> </span><span>design,</span><span> </span><span>construct,</span><span> </span><span>and</span><span> </span><span>assess</span><span> </span>a<span> </span><span>treatment</span><span> </span><span>wetland,</span><span> </span><span>retrofit</span><span> </span><span>Rinker’s</span><span> </span><span>pond</span><span> </span><span>within<span> </span><span>the</span><span> </span><span>city</span></span><span>-owned</span> <span>plat, monitor water quality,</span><span> and</span><span> </span><span>conduct plant</span><span> </span><span>surveys</span><span> </span><span>to</span> test<span> the</span> <span>effectiveness</span><span> </span><span>of </span><span>treatment wetlands</span><span> </span>in<span> stormwater</span> <span>management </span><span>and</span><span> habMayitat quality improvement.</span><span> </span><span>This</span><span> </span><span>project</span><span> </span><span>will</span><span> </span><span>engage</span><span> </span><span>the</span><span> </span><span>residents</span><span> </span><span>into</span><span> </span><span>public</span><span> </span><span>education</span><span> </span><span>programs</span><span> </span>in<span> </span><span>order</span><span> </span><span>to</span><span> </span><span>help</span><span> </span><span>them</span><span> </span><span>enhance</span><span> </span><span>their</span><span> </span><span>awareness</span><span> </span><span>of</span> <span>issues</span><span> </span>of <span>and</span><span> solutions</span><span> </span><span>to</span> <span>stormwater</span><span> </span><span>associated</span> <span>problems.</span></p>
Development of a desorption electrospray ionization –multiple-reaction-monitoring mass spectrometry (DESI-MRM) workflow for spatially mapping oxylipins in pulmonary tissue
<p>Data from desorption electrospray ionization mass spectrometry – multiple-reaction-monitoring mass spectrometry (DESI-MRM) analysis of oxylipins in guinea pig lung tissue following<em> in vivo</em> exposure to house dust mite extract.</p> <p>Data are provided as Waters *.raw data folders, each incuding an 'Analyte .txt' file, which is generated from processing within MassLynx (Waters). The 'ion_library.txt' file includes details about the MRM transitions and is required for processing the data with quantMSImageR (<span><a href="https://github.com/targeted-lipidomics/quantMSImageR"><span>https://github.com/targeted-lipidomics/quantMSImageR</span></a></span><span>).</span></p>
Software and data for: VGWatch: A low-cost stand-alone monitor to measure the valve gape of bivalves in the field
<p>Software and data abstract:</p> <p>This archive includes an Arduino script for utilizing the valve gape monitor outlined in the paper. Additionally, it provides an R script for calibrating the monitor and magnet. Finally, it contains valve gape data from three mussels, collected using the described monitor, along with a script for the analysis.</p> <p> </p> <p>Paper abstract:</p> <p>Valve gape monitors are utilised to measure the extent of bivalve’s shell openings. This measurement is correlated with their filter-feeding activity, and valve closure can serve as an indicator of various environmental stressors, including poor water quality, the presence of predators, and human disturbance. We developed an inexpensive, stand-alone, and reusable valve gape monitor; enabling collection of sufficient and independent spatial replication <em>in situ</em>. The monitor is made using Arduino hardware and software, and we share the design and code. We tested it in the field with three mussels as a proof of concept. The mussels were likely actively feeding most of the time. Two of the mussels were in close vicinity and demonstrated similar valve gape patterns. The monitor enables to measure valve gape in high resolution, providing insights into bivalve biology, ecosystem functioning, and the effects of environmental conditions, including anthropogenic stressors.</p>
Fig. 1 in SHORT COMMUNICATION Monitoring a population of Cruziohyla craspedopus (Funkhouser, 1957) using an artificial breeding habitat
Fig. 1. Site map for ABHab points at LPS: dashed line is approximate separation of terra firma and flood plain forest.
Fig. 3 in A single species of mangrove monitor (Varanus) occupies Ambon, Seram, Buru and Saparua, Moluccas, Indonesia
Fig. 3. Distribution map of mangrove monitors in the Moluccas and western New Guinea, the blue tailed monitors not included.
Fig. 2 in A single species of mangrove monitor (Varanus) occupies Ambon, Seram, Buru and Saparua, Moluccas, Indonesia
Fig. 2. Principal Components Analysis of scalation characters for several island populations of V. cerambonensis, V. indicus, and V. rainerguentheri. The two Xs represent ZFMK 70650 and ZMA 11146c.
Fig. 1 in A single species of mangrove monitor (Varanus) occupies Ambon, Seram, Buru and Saparua, Moluccas, Indonesia
Fig. 1. Mangrove monitors and their habitats: V. cerambonensis on Ambon (A), Seram (B), and Buru (C, D). Varanus rainerguentheri on Halmahera (E) and Obi (F). Coastal vegetation on Ambon (G) and Nipa swamp (H). Photographs by Valter Weijola.
Cloud to Thing Continuum based Sports Monitoring System using Machine Learning and Deep Learning Model
<p><span>Sports monitoring and analysis have seen significant advancements with the integration of cloud computing and continuum paradigms, facilitated by machine learning and deep learning techniques. In this study, we present a novel approach for sports monitoring that seamlessly transitions from traditional cloud-based architectures to a continuum paradigm, enabling real-time analysis and insights into player performance and team dynamics. Leveraging machine learning and deep learning algorithms, our framework offers enhanced capabilities for player tracking, action recognition, and performance evaluation in various sports scenarios. This research proposes a Cloud-to-Thing Continuum based Sports Monitoring System utilizing Machine Learning (ML) and Deep Learning (DL) models. The system integrates data acquisition, preprocessing, feature extraction, cloud-based processing, continuum paradigm integration, and decision-making stages. It leverages innovative techniques such as Improved Mask R-CNN for pose estimation, hybrid metaheuristic algorithms with Generative Adversarial Network (GAN) for classification, and fuzzy decision-making Based on the integrated analysis, decisions are made regarding player performance, team strategies, and tactical adjustments. The continuum approach ensures a balance between centralized cloud processing and distributed edge processing, optimizing resource utilization and reducing latency. Through this system, real-time analysis of sports events is achieved, enabling immediate feedback for time-sensitive applications.</span></p>
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.