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373
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Dataset results
373 results for “November”
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: fqdn, weighting: IDENTITY, days: 1, dates: 17 October 2023-08 November 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: IDENTITY, days: 1, dates: 15 November 2023-05 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: IDENTITY, days: 7, dates: 17 October 2023-08 November 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: IDENTITY, days: 7, dates: 15 November 2023-05 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: TTLBOUNDED, days: 7, dates: 17 October 2023-08 November 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: IDENTITY, days: 1, dates: 15 November 2023-05 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: IDENTITY, days: 7, dates: 17 October 2023-08 November 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: IDENTITY, days: 7, dates: 15 November 2023-05 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: TTLBOUNDED, days: 1, dates: 17 October 2023-08 November 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: TTLBOUNDED, days: 7, dates: 15 November 2023-05 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: TTLBOUNDED, days: 1, dates: 15 November 2023-05 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: TTLBOUNDED, days: 7, dates: 15 November 2023-05 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: TTLBOUNDED, days: 7, dates: 17 October 2023-08 November 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: TTLBOUNDED, days: 1, dates: 17 October 2023-08 November 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: root, weighting: TTLBOUNDED, days: 1, dates: 15 November 2023-05 December 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
Evaluating the impact of design decisions on passive DNS-based domain rankings: ranking files (type: web, weighting: IDENTITY, days: 1, dates: 17 October 2023-08 November 2023)
See <a href="https://domain-ranking-design-decisions.distrinet-research.be/">https://domain-ranking-design-decisions.distrinet-research.be/</a> for a full project description.
HailPixel Survey Data and Analysis from 26 November 2018, San Rafael, Argentina
<p>The following collection is used to demonstrate the HailPixel survey technique as part of an EGU ATM publication.</p> <p>The following is an abstract for this paper:<br> A new technique, named "HailPixel," is introduced for measuring the maximum dimension and intermediate dimension of hailstones from aerial imagery. The photogrammetry procedure applies a convolutional neural network for robust detection of hailstones against complex backgrounds and an edge detection method for measuring the shape of identified hailstones. This semi-automated technique is capable of measuring many thousands of hailstones within a single survey, which is several orders of magnitude larger than population sizes from existing sensors (e.g., a hail pad). Comparison with a co-located hail pad for an Argentinan hailstorm event demonstrates the larger population size of the HailPixel survey significantly improves the shape and tails of the observed hail size distribution. When hailfall is sparse, such as during large and giant hail events, the large survey area of this technique is especially advantageous for resolving the hail size distribution.</p> <p>The dataset contains the DEM and orthomosaic imagery, processing reports, final location of hail centroids, final measurements of hail major and minor axis, subset offsets and hail pad data. For more information applying the subset offsets to calculate the true position of the hail centroids please see the paper.</p>
RAMS simulation: 30 October-17 November 2002. Six domains, which include Europe , N-Africa and the Eastern coast of America
<pre>The dataset contains hourly 2D and 3D meteorological variables from the output of the Mesoscale model RAMS in 6 nested domains, which cover Europe, N-Africa and the Eastern coast of America, for the period 30 October-17 November 2002. 1) * iee files: the data is in binary format (**iee files) and can be represented using the Grid Analysis and Visualization System (GrADS). GrADS is copyrighted under the terms of the GNU Public License and is freely distributed. 2) *.ctl files: the Grads control files (data descriptor files). They contain in ASCII format the mapping of the binary data (*iee) for each of the model grids. They can be edited with Wordpad, Kwrite ... and they have to be changed to point to the directory that contains the binary files (**iee).These files also contain a description of all variables and units</pre>
Extended evaluation datasets for IIoT TestBed (Release version 1 from November 28th, 2023)
<p>This contribution serves as an extension of the existing evaluation data set and thus also for the evaluation of planning strategies for the IIoT test bed environment, which was presented here: https://zenodo.org/records/10212298.</p> <p>This evaluation data set presented here comprises a total of four different files, each containing 1000 entries and thus describing 1000 different initial situations. </p> <p> </p> <p>The objective of this dataset is to assess and compare the policies achieved with different algorithms.</p> <p>The first data set (#1) is identical to the data set already published in https://zenodo.org/records/10212319. The same environmental conditions apply here as in the training, however the situations for the agents are unseen. </p> <p>In the second evaluation data set (#2), the number of carriers used at the same time was increased by 25%, i.e. from 16 to 20.</p> <p>In evaluation data set three (#3), the number of products to be completed varies between 50 and 500. </p> <p>In evaluation data set four (#4), the lot size was limited to 1, which means that each order only includes one product. This increases the diservity (product types and families) that are manufactured at the same time, which can lead to higher set-up efforts. <br><br>In evaluation data set five (#5), the number of carriers used at the same time was increased by 50%, i.e. from 16 to 24.</p> <p><br>In evaluation data set six (#6), the previously used work plans are no longer used, instead 3 new, previously unknown product variants are presented:<br>variant number 7: A -> C -> E -> G -> I<br>variant number 8: A -> B -> D -> F -> H -> I<br>variant number 8: A -> B -> C -> G -> H -> I</p> <p>In evaluation data set seven (#7), The probability of occurrence of the errors as well as the error duration were doubled.<br><br></p> <p>In evaluation data set eight (#8), various environmental changes are combined together. <br>- The probability of occurrence of errors and the error duration have been increased by a factor of 1.2<br>- The number of products to be produced has been set to 128 instead of 64 per episode<br>- The batch size can vary between 1 and 10 instead of 1 and 3<br>- The number of carriers has been set to 20 instead of 16<br>- The previous 6 routings have been extended by 3 new, previously unknown work plans (analogous to dataset #6), so that an order can now be composed of 9 different product variants.</p> <p> </p>
Figs. 4–5. Society award winners. 4 in Minutes of the Annual Meeting St. Louis, Missouri, 19 November 2019
Figs. 4–5. Society award winners. 4) Brittany Owens receives her Outstanding Paper of the Year Award from President Smith; 5) Christopher Wirth describes his ongoing work on generic boundaries in Edrotini (Tenebrionidae) as winner of the Program Award of the Graduate Student Research Enhancement Awards.
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.