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8,460 results for “MONITORING”
Fig. 2 in Monitoring the establishment and flight phenology of parasitoids of emerald ash borer (Coleoptera: Buprestidae) in Michigan by using sentinel eggs and larvae
Fig. 2. Percentage of parasitism by Tetrastichus planipennisi of emerald ash borer larvae in larval sentinel logs (pooled by sample date, i.e., the date that larval sentinel logs were collected) in Nancy Moore and Burchfield Parks, Michigan, in (A) 2011, (C) 2012, and (E) 2013, and by Atanycolus spp. in (B) 2011, (D) 2012, and (F) 2013. The secondary Y-axis is growing degree day base 10 °C (GDD10) using the Baskerville–Emin method.
Fig. 1 in Monitoring the establishment and flight phenology of parasitoids of emerald ash borer (Coleoptera: Buprestidae) in Michigan by using sentinel eggs and larvae
Fig. 1. Percentage of parasitism by Oobius agrili of emerald ash borer eggs on all egg sentinel logs (pooled by sample date, i.e., the date that egg sentinel logs were collected) in Central Park, Michigan, in (A) 2011 and (C) 2012, and on individual egg sentinel logs pooled over all sample dates in (B) 2011 and (D) 2012. The secondary Y-axis is growing degree day base 10 °C (GDD10) using the Baskerville–Emin method.
Рис. 1. Схема точек отбора проб на ООПТ в бассейне Амура Fig. 1. Map of sampling points at the protected areas in the Amur River Basin in Molting feathers and eggshells in monitoring rare bird species populations: Evidence from special protected natural territories
Рис. 1. Схема точек отбора проб на ООПТ в бассейне Амура Fig. 1. Map of sampling points at the protected areas in the Amur River Basin
Рис. 3. Соотношение концентраций биогенных микроэΛементов в очинах перьев (а) и скорΛупе яиц аистов (b), мг/кг Fig. 3. Concentratiom ratio of biogenic trace elements in the edges of feathers (a) and eggshells (b) of storks, mg/kg in Molting feathers and eggshells in monitoring rare bird species populations: Evidence from special protected natural territories
Рис. 3. Соотношение концентраций биогенных микроэΛементов в очинах перьев (а) и скорΛупе яиц аистов (b), мг/кг Fig. 3. Concentratiom ratio of biogenic trace elements in the edges of feathers (a) and eggshells (b) of storks, mg/kg
Dataset in "Near real-time in-situ monitoring of nearshore ocean currents using Distributed Acoustic Sensing on submarine fiber-optic cable"
<p>Dataset in "Near real-time in-situ monitoring of nearshore ocean currents using Distributed Acoustic Sensing on submarine fiber-optic cable" </p> <p><a href="../api/records/13133835/draft/files/tmdcm.txt/content" target="_blank" rel="noopener noreferrer">tmdcm.txt</a>: current meter data </p> <p><a href="../api/records/13133835/draft/files/tide.txt/content" target="_blank" rel="noopener noreferrer">tide.txt</a>: tidal gauge data </p> <p><a href="../api/records/13133835/draft/files/windspeed.txt/content" target="_blank" rel="noopener noreferrer">windspeed.txt</a>: windspeed data </p> <p>Figure 2: Figure2.npy</p> <p>Figure 3: Figure 3 abc .npy</p> <p>Figure16: <a href="../api/records/13133835/draft/files/spatial_Vc.npy/content" target="_blank" rel="noopener noreferrer">spatial_Vc.npy</a> & <a href="13133835" target="_blank" rel="noopener noreferrer">spatial_h.npy</a> </p> <p>Figure 17: <a href="../api/records/13133835/draft/files/streching_ncf.npy/content" target="_blank" rel="noopener noreferrer">streching_ncf.npy</a></p>
Data and results for manuscript "Imaging groundwater infiltration dynamics in karst vadose zone with long-term ERT monitoring"
<p>This data set contains raw and inverted data from an Electrical Resistivity Tomography (ERT) monitoring experiment conducted over a period of three years at the Rochefort Cave Laboratory (RCL) site in South Belgium. It highlights variable hydrodynamics in the karst vadose zone of Lorette Cave. More conventional hydrological measurements (drip discharge monitoring, soil moisture and water conductivity data sets) are also included in the package, which aims at provide a thorough understanding of the groundwater infiltration. Seasonal changes affect all the imaged areas leading to increases in resistivity in spring/summer attributed to enhanced evapotranspiration, whereas winter is characterised by a general decrease in resistivity associated with a groundwater recharge of the vadose zone. This study provides detailed images of the sources of drip discharge spots traditionally monitored in caves and aims to support modelling approaches of karst hydrological processes.</p>
Dataset for: IoT deployment for city scale air quality monitoring with Low-Power Wide Area Networks
<p>Air Quality (AQ) is a very topical issue for many cities and has a direct impact on the health of its citizens. We propose to investigate the air quality of a large UK city using low-cost commodity Particulate Matter (PM) sensors, and compare them with government operated air quality stations. In this pilot deployment we design and build six AQ IoT devices, each with four different low-cost PM sensors and deploy them at two locations within the city. These devices are equipped with LoRaWAN wireless network transceivers to test city scale Low-Power Wide-Area Network network coverage. We conclude that some low-cost PM sensors are viable for monitoring AQ and demonstrate that our device design can be used via LoRaWAN to facilitate more granular city coverage without limitations of network access. Based on these findings we intend to deploy a larger LoRaWAN enabled Air Quality sensor network deployment across the city.</p>
DCASE 2018, Task 5: Monitoring of domestic activities based on multi-channel acoustics - Development dataset
<p>This repository contains the development data of task 5 of the DCASE 2018 challenge. 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 development dataset' consists of data collected by 4 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 along with the ground truth. In total 72984 segments are made available, leading to approximately 200 hours of data.</p> <p>More information about the challenge and the specific dataset can be found <a href="http://dcase.community/challenge2018/task-monitoring-domestic-activities">here</a>. Information solely related to the content of the dataset is available in 'DCASE2018-task5-dev.doc.zip'. <br> <br> <strong>By accessing or using this database, the user accepts the provided EULA (available in DCASE2018-task5-dev.doc.zip).</strong></p>
Data sheet for Monitoring of trimming operation for lightweight composite structure
<p>Each file consists of the following data :</p> <p>- Acceleration measurements in the spindle during machining.</p> <p>- Acceleration measurements in the workpiece during machining.</p> <p>- Spindle power consumption during machining.</p> <p> </p>
EnerGAware monitored energy consumption data
<p>Energy consumption data acquired during the monitoring period, from the houses that were part of the EnerGAware pilot.</p> <p>The data discriminated by dwelling, but it is anonymized.</p>
Photoplethysmography in dogs and cats: selection of measurement sites for pet monitor
<p>The PPG measurements of the study Cugmas et al, 2018.</p> <p>Notes.txt include all information about the dataset.</p>
Data providers package for reporting monitoring results for veterinary medicinal product residues (official data reporting phase)
<p>This data providers package provides the data collection configuration and supporting materials for reporting veterinary medicinal product residues (VMPR) results according to Council Directive 96/23/EC of 29 April 1996 on measures to monitor certain substances and residues thereof in live animals and animal products and repealing Directives 85/358/EEC and 86/469/EEC and Decisions 89/187/EEC and 91/664/EEC. These are to be used for the official data reporting phase.</p> <p>The package includes:</p> <p>Advice on the values to be reported for the mandatory fields specified for this data collection.</p> <p>The Standard Sample Description Version 2 XML schema definition for VMPR reporting.</p> <p>The STX transformation file which automatically assigns sampEventId and sampAnId when this information is not provided.</p> <p>The general and VMPR specific business rules applied for the automatic validation of the submitted datasets.</p> <p>The VMPR specific terminologies to be used for reporting analytical methods and the residues included in the scope of the analytical methods.</p> <p>An example of a reportable dataset following the Quick Start Reporting guide.</p> <p>Excel Mapping tool to convert excel files after mapping into XML document.</p> <p>Guidance on how to use the Excel Mapping tool.</p> <p>Guidance on how to run the validation report after submitting data to the DCF.</p>
EV Data monitoring
<p>Electric Vehicle (EV) data collected by Emotion, expert Italian company specialized in the sector of electric mobility, partner of SOFIE project.</p> <p>These data were collected using a particular OBD device connected on each EV. OBD communicates using a TCP/IP system.</p> <p>Data shown in this dataset were updated every 10 seconds. </p>
EV data monitoring
<p>Electric Vehicle (EV) data collected by Emotion, expert Italian company specialized in the sector of electric mobility, partner of SOFIE project.</p> <p>These data were collected using a particular OBD device connected on each EV. OBD communicates using a TCP/IP system.</p> <p>Data shown in this dataset were updated every 10 seconds. </p>
Dataset: Enabling SSH Protocol Visibility in Flow Monitoring
<p>Dataset contains SSH flows from Masaryk University campus network. Captured during August 2018. IP addresses are hashed using salted SHA-256.</p> <p>The header for both data files is as follows:</p> <pre><code>Date flow start|Date flow end|Src IP|sPort|Dst IP|dPort|Proto|Packets|Bytes|Flags|SSH Client Version|SSH Client Application|SSH Server Version|SSH Server Application|SSH Login Attempts|SSH Login|SSH Kex|SSH Host Key|SSH Client Encryption|SSH Server Encryption|SSH Client MAC|SSH Server MAC|SSH Client Compression|SSH Server Compression</code></pre> <p> </p> <p>When using this dataset, please cite the original work as follows:</p> <pre><code>@inproceedings{1519096, author = {Celeda, Pavel and Velan, Petr and Kral, Benjamin and Kozak, Ondrej}, address = {Washington DC, USA}, booktitle = {IFIP/IEEE International Symposium on Integrated Network Management (IM 2019)}, keywords = {SSH; flow; monitoring; network; dataset}, howpublished = {online}, language = {eng}, location = {Washington DC, USA}, isbn = {978-3-903176-15-7}, pages = {569-574}, publisher = {IFIP Open Digital Library}, title = {Enabling SSH Protocol Visibility in Flow Monitoring}, url = {http://dl.ifip.org/db/conf/im/im2019exp/189410.pdf}, year = {2019} }</code></pre> <p> </p>
EV data monitoring
<p>Electric Vehicle (EV) data collected by Emotion, expert Italian company specialized in the sector of electric mobility, partner of SOFIE project.</p> <p>These data were collected using a particular OBD device connected on each EV. OBD communicates using a TCP/IP system.</p> <p>Data shown in this dataset were updated every 10 seconds. </p>
EV data monitoring
<p>Electric Vehicle (EV) data collected by Emotion, expert Italian company specialized in the sector of electric mobility, partner of SOFIE project.</p> <p>These data were collected using a particular OBD device connected on each EV. OBD communicates using a TCP/IP system.</p> <p>Data shown in this dataset were updated every 10 seconds. </p>
EV data monitoring
<p>Electric Vehicle (EV) data collected by Emotion, expert Italian company specialized in the sector of electric mobility, partner of SOFIE project.</p> <p>These data were collected using a particular OBD device connected on each EV. OBD communicates using a TCP/IP system.</p> <p>Data shown in this dataset were updated every 10 seconds. </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>
EV data monitoring
<p>Electric Vehicle (EV) data collected by Emotion, expert Italian company specialized in the sector of electric mobility, partner of SOFIE project.</p> <p>These data were collected using a particular OBD device connected on each EV. OBD communicates using a TCP/IP system.</p> <p>Data shown in this dataset were updated every 10 seconds. </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.