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619 results for “configuration”
H2020 ENODISE Analytical Data Set configuration C ECL
<p>Preliminary wake-interaction noise and steady-loading noise estimates for a contrarotating propeller system, using analytical modeling.</p>
H2020 ENODISE: VKI Numerical Aeroacoustic Database of Configuration B1
<p>This database represents the resultant data from a hybrid methodology consisting of aerodynamic simulations using uRANS and acoustic propagation simulations using FEM. The simulation of both the aerodynamic installation effects and the acoustic installation effects is available. The data from the aerodynamic simulations is given in the<em> .cgns </em>format and are in the <em>Aerodynamic_Results</em> folder. The resulting acoustic directivities from these sources using the FEM-Source Mode method are stored in the <em>Acoustic_Results</em> folder as <em>.csv </em>files. Both folders have a README file available with more details.</p>
H2020 ENODISE: VKI and SISW Numerical Aeroacoustic Database of Configuration C
<p>The hybrid aeroacoustic methodology prediction findings produced by VKI and SISW for configuration C within the scope of the European project ENODISE are contained in this database. In this setup, contra-rotating propellers with and without a shroud are investigated. Simulations of single rotors with and without the shroud are also included. The measurements made at the anechoic facility ALCOVES at VKI (https://zenodo.org/record/7966211) and further simulations made by ONERA (https://zenodo.org/record/8191815) can be compared to the findings provided here . </p> <p>A description of the numerical set up and database file structure are included in the PDF: <em>VKI-SISW_Simulation_Methodology_and_File_Organization_Config_C.pdf</em></p> <p><br> </p>
H2020 ENODISE: TUD Experimental database configuration B1
<p>This dataset contains experimental data for aerodynamics and acoustics of configuration B1, which was defined in the H2020 ENODISE project (<a href="https://www.vki.ac.be/index.php/about-enodise">https://www.vki.ac.be/index.php/about-enodise</a>). The measurements were taken in the Low-Speed, Low-Turbulence Tunnel (LTT) at Delft University of Technology, using a Distributed Electric Propulsion (DEP) configuration model that consists of three propellers installed side-by-side on the leading edge of a wing.</p>
H2020 ENODISE: ONERA Auralizations Configuration B2
<p>A quick evaluation of the SISW numerical data (<a href="https://zenodo.org/record/8176756">https://zenodo.org/record/8176756) </a>and the ECL experimental data (<a href="https://zenodo.org/record/7925336">https://zenodo.org/record/7925336</a>) was done on an auditory level through auralisations. The in-house auralisation tool FLAURA was used. Sound signatures were evaluated at the microphone positions 17 and 22 (at 90° to the propeller plane) for single and double propeller configurations, with and without flow.</p> <p>The database is composed of .wav files, presenting the measured temporal data (ECL) either compared to auralised measured spectral data (ECL) or simulated data (SISW).</p> <p>A description of the data is included in a pdf file.</p>
ONERA Numerical Database Configuration A1 (static propeller)
<p>This database contains the numerical results obtained by ONERA on the configuration A1, using ZDES mode 2 and ZDES mode 3 methods. The ZDES mode 3 approach offers an explicit resolution of the turbulent scales present in the outer region of the flat plate boundary layer and their interaction with the propeller.</p>
Magnetic Bloch point and vortex configurations
<p>This dataset is associated to the arxiv publication "Energetics and Dynamics of a stable Bloch point" by Winkler et al., arxiv:2303.10091 (2023). Link: https://arxiv.org/abs/2303.10091</p> <p>The set contains stable Bloch point and vortex configurations in various discretizations, disk shapes and models (Heisenberg or micromagnetic), as well as snapshots of dynamics after shifting the structures out of equilibrium. One jupyter notebook is added to plot the data directly within this repository.</p> <p>The github repsitory to produce this states and to verify the results of the study can be found here: https://github.com/WinklerTB/BP_paper_2023</p> <p>The simulation code (MicMag2) can be found here: https://github.com/WinklerTB/MicMag2</p> <p>Also the ubermag framework was partly used to evaluate the data: https://ubermag.github.io/</p>
[Dataset] Green hydrogen exports in New Zealand and Chile can improve electricity supply security if configured as local energy insurance
<p>This file contains the main outputs of the preprint: "Green hydrogen exports in New Zealand and Chile can improve electricity supply security if configured as local energy insurance"</p>
Magnetic elastomers as specific soft actuators – predicting particular modes of deformation from selected configurations of magnetizable inclusions
<p>This dataset contains the underlying data and python programs to generate the plots in the manuscript</p> <p><em>L. Fischer and Andreas M. Menzel</em><br>Magnetic elastomers as specific soft actuators – predicting particular modes of deformation from selected configurations of magnetizable inclusions<br>J. Magn. Magn. Mater. <strong>591</strong>, 171695 (2024) (DOI: <a href="https://doi.org/10.1016/j.jmmm.2023.171695" target="_blank" rel="noopener">10.1016/j.jmmm.2023.171695</a>).<br>Part of the special issue "ICMF 2023".</p> <p>arXiv Version: <a href="https://arxiv.org/abs/2310.16833" target="_blank" rel="noopener">arXiv:2310.16833</a>.</p> <p>For more information, please see the included "Readme.txt" in the dataset "Zenodo.zip".</p>
AggreBots: configuring CiliaBots through guided, modular tissue aggregation
Open the record for dataset details and reuse information.
Data from: Restoring marine ecosystems: spatial reef configuration triggers taxon-specific responses among early colonizers
Open the record for dataset details and reuse information.
Where are the trees? Extent, configuration, and drivers of poor forest recovery 30 years after the 1988 Yellowstone Fires.
Postfire recovery of fire-adapted forests remains uncertain as climate and fire regimes continue to change. Areas of poor postfire tree regeneration following late-20th-century fires may reveal characteristics associated with increased vulnerability to forest decline. However, sufficient time must have elapsed and pre- and postfire forest cover must be compared to distinguish areas that have not recovered. We used remotely sensed data and the Normalized Difference Vegetation Index (NDVI) to detect areas of poor forest recovery across >250,000 ha of area burned as stand-replacing fire 30 years after the 1988 Yellowstone fires. We asked three questions: (1) What is the extent and configuration of sparse and reduced forest recovery? (2) How do vegetation characteristics compare between areas of sparse and reduced recovery vs. recovered forest? (3) What environmental characteristics explain the distribution and patch size of sparse and reduced recovery? We related postfire (2013-14) NDVI to field-measured stem density to establish an NDVI threshold of sparse tree regeneration, and we contrasted pre- (1986-87) and postfire (2018-19) NDVI as a proxy for pre- and postfire forest cover. Sparse and reduced forest recovery occupied ~41,000 ha across the burned area, about half of which was ≥150 m from ex situ seed sources. Patches of poor recovery were generally large, with ~13,400 ha in patches ≥50 ha and an area-weighted mean patch size of 97 ha. Vegetation was short (<2 m) in areas of sparse and reduced recovery and non-evergreen biomass was three times greater than in recovered forest. Sparse and reduced recovery was more likely at high elevations, on steep slopes, and far from ex situ seed sources, and patches were larger at high elevations and far from seed sources. It took 20 years for sparse and reduced recovery to be distinguishable from recovered forest using NDVI, suggesting a time lag before remotely sensed data can detect alternative pathways of postfire forest r
Can we manage a future with more fire? Effectiveness of defensible space treatment depends on housing amount and configuration
Context: Fire in forested wildland urban interface (WUI) landscapes is increasing throughout the western United States. Spatial patterns of fuels treatments affect fire behavior, but it is unclear how fire risk and fuel treatment effectiveness will change under future conditions. Objectives: (1) How do area burned, forest and fuel characteristics, and fire risk change over time under 21st-century climate? (2) When defensible space fuels treatments are applied around all houses, which scenarios of WUI housing amount and configuration minimize fire risk? Methods: In generic 10,000-ha US Northern Rocky Mountain subalpine forest landscapes, we simulated 21 scenarios differing in fuels treatment, housing amount and configuration (neutral landscape models), and projected future climate using the process-based model iLand. We compared fire risk at three scales: 1-ha home ignition zone (HIZ), 9-ha safe suppression zone (SSZ), and landscape. Results: Under warm-dry climate, annual area burned increased, but area burned at high fire intensity peaked in the 2060s and then declined sharply; fire risk followed similar trends. Defensible space treatments maintained low flame lengths in HIZs. Clustered housing was more effective at reducing SSZ risk compared to dispersed housing. At landscape scales, treating more of the landscape reduced fire risk but configuration was unimportant. Conclusions: The most effective strategy for reducing fire risk depends on the scale at which risk is assessed. Clustering WUI developments and treating between 10 to 30% of the landscape every 10 years can reduce fire risk across multiple scales.
Dataset of empirical study on product configuration and traceability in UML-based product-lines
<p>Dataset of empirical study on product configuration and traceability in UML-based product-lines</p>
Experimental Data Sets for the study "Benchmarking a $(\mu+\lambda)$ Genetic Algorithm with Configurable Crossover Probability"
<p>This is the experimental result of the study "Benchmarking a (μ+λ) Genetic Algorithm with Configurable Crossover Probability". A novel (μ+λ) GA is proposed and benchmarked, in which we stochastically determine whether to apply the crossover operator either for each individual or generation with a crossover probability <span class="math-tex">\(p_c\)</span>. This data set consists of two parts:</p> <ol> <li>The results of (μ+λ) GA on 25 pseudo-Boolean problems defined in <em>IOHprofiler </em>(<a href="https://iohprofiler.github.io/">https://iohprofiler.github.io/</a>) with the following setup: <span class="math-tex">\(\mu \in \{10, 50, 100\}, \lambda \in \{1, \lceil\mu/2\rceil, \mu\}, p_c\in\{0, 0.5\}.\)</span> <ul> <li>'IOHprofiler_Problems_standard_bit_mutation.csv' --> the (μ+λ) GA with standard bit mutation.</li> <li>'IOHprofiler_Problems_fast_mutation.csv' --> the (μ+λ) GA with fast mutation.</li> </ul> </li> <li>The results of (μ+λ) GA on OneMax and LeadingOnes problems with the following setup: <span class="math-tex">\(n \in \{64,100,150,200,250,500\}, \mu \in \{2,3,5,8,10,20,30,...,100\}, \\ \lambda \in \{1, \lceil \mu/2 \rceil, \mu\}, \text{and }p_c \in \{0.1 k \mid k \in [0..9]\}\cup\{0.95\}.\)</span> <ul> <li>'OneMax_raw.csv' --> the fixed-target running time/first hitting time from 100 independent runs for target values in <span class="math-tex">\([1..n]\)</span>.</li> <li>'OneMax_summary.csv' --> the mean, median, standard deviation, some quantiles, expected running time (ERT), the number of successful runs, and the success rate from 100 independent runs for target values in <span class="math-tex">\([1..n]\)</span>.</li> <li>'LeadingOnes_raw.csv' --> the same with 'OneMax_raw.csv' for LeadingOnes.</li> <li>'LeadingOnes_summary.csv' --> the same with 'OneMax_summary.csv' for LeadingOnes.</li> </ul> </li> </ol> <p><strong>Contact</strong>: if you have any questions or suggestions, please feel free to contact <a href="https://www.universiteitleiden.nl/en/staffmembers/furong-ye#tab-1">Furong Ye</a> or <a href="http://www-ia.lip6.fr/~doerr/">Carola Doerr</a>.</p>
NEMO Reference configurations inputs
<p>This page refers to input archives for running the configurations included in NEMO 4.2 (beta version) and earlier. Subsequent releases have been served from an alternative site: <a href="https://gws-access.jasmin.ac.uk/public/nemo/sette_inputs">SETTE input files delivered through JASMIN</a>. Users are advised to download from that site for versions 4.2.0 onwards. The <a href="https://sites.nemo-ocean.io/user-guide/sette.html#obtaining-configuration-input-files">NEMO User Guide</a> contains a detailed section on running SETTE, including further information on obtaining the input files. </p> <p>This site is retained to provide a DOI for citing these datasets but remember to state clearly the exact version used.</p> <p>Input archives for running the configurations included in <strong>NEMO 4.2 (beta version) -not suitable for releases 4.2.0 and later</strong>:</p> <ul> <li>AGRIF_DEMO: <em>AGRIF_DEMO_v4.0.tar</em> and <em>ORCA2_ICE_v4.0.tar</em></li> <li>AMM12: <em>AMM12_v4.0.tar</em></li> <li>C1D_PAPA: <em>INPUTS_C1D_PAPA_v4.0.tar</em></li> <li>ISOMIP+: ISOMIP+_v4.0.tar, input for the new ISOMIP+ test case on ice shelf module and the coupling with an ice sheet model</li> <li>ORCA2_ICE_PISCES: <em>ORCA2_ICE_v4.2.tar</em>, <em>INPUTS_PISCES_v4.2.tar and ORCA2_ABL_4.2.tar</em></li> <li>ORCA2_OFF_PISCES: <em>ORCA2_OFF_v4.0.tar</em> and <em>INPUTS_PISCES_v4.0.tar</em></li> <li>ORCA2_OFF_TRC: <em>ORCA2_OFF_v4.0.tar</em></li> <li>ORCA2_SAS_ICE: <em>ORCA2_ICE_v4.0.tar</em> and <em>INPUTS_SAS_v4.0.tar</em></li> <li>SPITZ12: <em>SPITZ12_v4.0.tar</em></li> <li>WED025: WED025_v4.2.tar, input for the new WED025 reference configuration, now replacing SPITZ12 to demonstrate ice shelf module, SI3, bdy with tide and sea ice capabilities<br> </li> </ul>
Data Sets for Measuring and Modeling the Performance Configurations of Distributed DBMS
<p>These data sets contain the performance measurements and additional metadata as accompanying material for the research paper <strong>Baloo: Measuring and Modeling the Performance Configurations of Distributed DBMS</strong><em> </em>that is published in the <em>Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) 2020.</em></p> <p>The attached readme describes the data set structure.</p>
Conservation in post-industrial cities: how does vacant land management and landscape configuration influence urban bees?
<p>1. Rich pollinator assemblages are documented in some cities despite habitat fragmentation and degradation, suggesting that urban areas have potential as pollinator refuges. To inform urban bee conservation, we assessed local and landscape scale drivers of bee community composition and foraging within vacant lots of Cleveland, Ohio, USA. Cleveland is a shrinking city, a type of urban area that has an over-abundance of vacated greenspaces as a result of population loss and subsequent demolition of abandoned infrastructure. As such, Cleveland represents over 350 post-industrial cities worldwide, that are all promising locations for bee conservation.</p> <p>2. Across a network of 56 residential vacant lots (each ~30m x 12m), we established seven unique habitats, including seeded native prairies, to investigate how vegetation management and landscape context at a 1500m radius influenced urban bee communities. We assessed the distribution of several bee functional traits, diversity, and abundance with pan and malaise traps. Foraging frequency was determined with plant-pollinator interaction networks derived from vacuum collections of bees at flowers.</p> <p>3. We observed higher bee richness and increased abundance of smaller sized bees as the size of surrounding greenspace patches increased within a 1500m radius landscape buffer. Within habitats, greater plant biomass positively influenced bee community richness and abundance whereas taller vegetation was a negative influence. Plant-pollinator interaction networks were dominated by spontaneous non-native vegetation, illustrating that this forage supports urban bees.</p> <p>4. Synthesis and applications: Our study indicates that proximity to larger greenspaces within an urban landscape promotes overall bee richness and increased occurrence of smaller bee species within residential vacant lots. While we did not observe our seeded native plants enhancing the bee community, native wildflowers were still establishing during the study and may have a greater influence when blooming at higher densities. Importantly, spontaneous non-native vegetation provided the majority of urban bee's forage. Thus, vacant land that is minimally managed and vegetated with what many consider undesirable "weeds", provides valuable habitat for bee conservation in cities.</p>
SATune: An Auto-tuning Approach for Configurable Static Analysis Tools
<p>Version 2.0.0 updates: Renamed tool to SATune.</p> <p>-------</p> <p>This contains both the executables and the data for our ICST 2021 submission, "SATune: An Auto-tuning Approach for Configurable Static Analysis Tools." The results are in results.tar.xz, and the SATune source code and experimental environment is is experiments.tar.xz.</p>
Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - 2 degree WaveWatchIII configuration files
<p>This dataset contains the mesh and model configuration information for a WaveWatchIII run using a 2 degree structured grid.</p> <ul> <li>glo_2d.bot <ul> <li>Bottom depth file for 2 degree structured grid</li> </ul> </li> <li>glo_2d.mask <ul> <li>Mask file for 2 degree structured grid</li> </ul> </li> <li>obstructions_local.glo_2d.in <ul> <li>local obstructions file for use with UOST source term switch</li> </ul> </li> <li>obstructions_shadow.glo_2d.in <ul> <li>shadow obstructions file for use with UOST source term switch</li> </ul> </li> <li>ww3_grid.inp <ul> <li>Input file for the ww3_grid pre-processing program. This file specifies many of the model configuration settings.</li> </ul> </li> <li>ww3_shel.inp <ul> <li>Input file for the ww3_shel program.</li> </ul> </li> </ul>
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.