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1,774
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Dataset results
1,774 results for “accelerators”
Supporting data for "KOCL: Power Self-awareness for Arbitrary FPGA-SoC-accelerated OpenCL Applications"
<p>Supporting data for "KOCL: Power Self-awareness for Arbitrary FPGA-SoC-accelerated OpenCL Applications"</p>
Electronic Companion - Accelerated Benders Decomposition for Enhanced Co-Optimized T&D System Planning
<p>This release is associated with a paper entitled "Accelerated Benders Decomposition for Enhanced Co-Optimized T&D System Planning".</p> <p>In this document, we include information regarding the physical parameters of the transmission and distribution power systems adopted to present the results shown in the paper. Additionally, data regarding investment and operative costs, as well as the scenarios used to describe the uncertainty of renewable-based generation availability and demand, are provided in this document.</p>
Data for "Accelerating QM/MM simulations of electrochemical interfaces through machine learning of electronic charge densities"
Open the record for dataset details and reuse information.
Local Inertial Acceleration for P-wave Shaking Table
<p>The database provides detailed measurements of acceleration along the x-axis within a local reference frame. These measurements are acquired using a Shaking Table that simulates P-wave motion along the x-axis in an IMU (Inertial Measurement Unit). The data is processed with a gravity filter and compensate the Coriolis effect in the IMU.</p> <p>The dataset contains four experiments at 6.25hz, 6.94hz, 7.81hz and 8.92hz. Each experiment presents the acquired accelerations in the x-axis and the corresponding dt.</p> <p> </p> <p><strong>IF YOU USE THIS DATASET, PLEASE CITE OR ARTICLE</strong></p> <p>Title: Inertial Methodology for the Monitoring of Structures in Motion Caused by Seismic Vibrations"<br>Journal: Infrastructures<br>Volume: 9<br>Year: 2024<br>ISSN: 2412-3811<br>DOI: 10.3390/infrastructures9070116</p>
Ultrarelativistic electron beams accelerated by terawatt scalable kHz laser
<p>This repository contains data for the paper C. M. Lazzarini et al., Phys. Plasmas 31, 030703 (2024); <a href="https://doi.org/10.1063/5.0189051" target="_blank" rel="noopener">https://doi.org/10.1063/5.0189051</a>. The data were obtained by experiment using L1-Allegra laser system (<a href="https://www.eli-beams.eu/facility/lasers/laser-1-allegra-100-mj-1-khz" target="_blank" rel="noopener">https://www.eli-beams.eu/facility/lasers/laser-1-allegra-100-mj-1-khz</a>) and simulation using the EPOCH (v4.18.0) particle-in-cell code (<a href="https://epochpic.github.io/" target="_blank" rel="noopener">https://epochpic.github.io/</a>). The data analysis can be found on GitHub (<a href="https://github.com/valenpe7/5.0189051" target="_blank" rel="noopener">https://github.com/valenpe7/5.0189051</a>).</p>
Electronic Companion - Accelerated Benders Decomposition for Enhanced Co-Optimized T&D System Planning
<p>This release is associated with a paper entitled "Accelerated Benders Decomposition for Enhanced Co-Optimized T&D System Planning".</p> <p>In this document, we include information regarding the physical parameters of the transmission and distribution power systems adopted to present the results shown in the paper. Additionally, data regarding investment and operative costs, as well as the scenarios used to describe the uncertainty of renewable-based generation availability and demand, are provided in this document.</p>
DeepLNE++ leveraging knowledge distillation for accelerated multi-state path-like collective variables
<p>Supporting data related to manuscript 'DeepLNE++ leveraging knowledge distillation for accelerated multi-state path-like collective variables'</p>
Ambitious hydropower plans will accelerate greenhouse gases emissions from the Hindu-Kush Himalaya region
<p>01-<em>07: Database of GHG emisisons from existing and future hydropower plants in the Hindu-Kush Himalaya region. 08</em> : Source codes for simulating reservoir flooded area and GHG fluxes.</p>
Accelerating Whole-Sample Polarization-Resolved Second Harmonic Generation imaging in Mammary Gland Tissue via Generative Adversarial Networks
<p>Authors:</p> <p>Arash Aghigh, Jysiane Cardot, Melika Saadat Mohammadi, Gaëtan Jargot, Heide Ibrahim, Isabelle Plante, François Légaré</p> <p>Affiliations:</p> <p> 1. Centre Énergie Matériaux Télécommunications, Institut National de la Recherche Scientifique, Varennes, Québec, Canada.<br> 2. Centre Armand-Frappier Santé Biotechnologie, Institut National de la Recherche Scientifique, Laval, Québec, Canada.</p> <p>Corresponding Author:</p> <p>Arash Aghigh, arash.aghigh@inrs.ca</p> <p>Description:</p> <p>This dataset accompanies the research on improving whole-sample Polarization-Resolved Second Harmonic Generation (P-SHG) imaging in mammary gland tissue using Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN). The novel approach significantly reduces imaging time while maintaining high image quality and analytical accuracy, demonstrating a reduction in imaging time by more than 95%. This method also minimizes laser-induced photodamage, lowers costs of optical components, and increases the accessibility and applicability of P-SHG imaging in various fields.</p> <p>Keywords:</p> <p>Polarization-Resolved Second Harmonic Generation, P-SHG, Generative Adversarial Networks, GAN, ESRGAN, Mammary Gland Imaging, Super-Resolution, Image Upscaling, Deep Learning, Biomedical Imaging</p> <p>Funding Information:</p> <p> • Canada Foundation for Innovation<br> • Fonds de recherche du Québec–Nature et technologies<br> • Natural Sciences and Engineering Research Council of Canada<br> • New Frontiers Research Fund<br> • NSERC CREATE program (scholarship for Arash Aghigh)</p> <p>Related Identifiers:</p> <p> • GitHub repository for ChaiNNer program: https://github.com/chaiNNer-org/chaiNNer<br> • Download links for models used: https://openmodeldb.info</p> <p>Additional Information:</p> <p>Animal studies were conducted according to the procedures provided by the Canadian Council on Animal Care. The protocol (2005-02) was reviewed and approved by the Institutional Committee for Animal Protection of the Laboratoire National de Biologie Expérimentale (LNBE), the animal facilities based at the Institut National de Recherche Scientifique (INRS).</p>
"Laser wakefield accelerator driven by the super-Gaussian laser beam in the focus" - Input files for the PIC simulations in the EPOCH Code
<p>These are particle-in-cell simulation set-ups for the EPOCH code. The simulations show the super-Gaussian beam diffraction in free space and in plasma (LWFA acceleration).</p> <p>Coresponding publication is currently reviewed.</p>
A parametric study of quasi-static electron acceleration by Modified Electron Acoustic wave and comparison to Knight relation
Open the record for dataset details and reuse information.
Accelerating Discovery of Mechanically Stable Metal−Organic Frameworks for Vinylidene Fluoride Storage by Active Learning
<p><span>Supplementary data including dataset and python scripts for "<strong>Accelerating Discovery of Mechanically Stable </strong></span><strong><span>Metal−Organic Frameworks </span></strong><span><strong>for Vinylidene Fluoride Storage by Active Learning</strong>"</span></p>
Accelerating Python Applications with Dask and ProxyStore
<p>Applications are increasingly written as dynamic workflows underpinned by an execution framework that manages asynchronous computations across distributed hardware. However, execution frameworks typically offer one-size-fits-all solutions for data flow management, which can restrict performance and scalability. ProxyStore, a middleware layer that optimizes data flow via an advanced pass-by-reference paradigm, has shown to be an effective mechanism for addressing these limitations. Here, we investigate integrating ProxyStore with Dask Distributed, one of the most popular libraries for distributed computing in Python, with the goal of supporting scalable and portable scientific workflows. Dask provides a easy-to-use and flexible framework, but is less optimized for scaling certain data-intensive workflows. We investigate these limitations and detail the technical contributions necessary to develop a robust solution for distributed applications and demonstrate improved performance on synthetic benchmarks and real applications.</p>
Accelerated genome shuffling associated with rapid evolution of sexual conflicts in seed beetles
<p><strong><span>Accelerated genome shuffling associated with rapid evolution of sexual conflicts in seed beetles</span></strong></p>
Data and codes in support of "Accelerating Green Shipping by Spatially Optimized Offshore Charging Stations"
<p>Data and codes in support of "Accelerating Green Shipping by Spatially Optimized Offshore Charging Stations", including data, codes and figures.</p>
Data and codes in support of "Accelerating Green Shipping by Spatially Optimized Offshore Charging Stations"
<p>Data and codes in support of "Accelerating Green Shipping by Spatially Optimized Offshore Charging Stations", including data, codes and figures.</p>
Data and codes in support of "Accelerating Green Shipping by Spatially Optimized Offshore Charging Stations"
<p>Data and codes in support of "Accelerating Green Shipping by Spatially Optimized Offshore Charging Stations", including data, codes and figures.</p>
Data and codes in support of "Accelerating Green Shipping by Spatially Optimized Offshore Charging Stations"
<p>Data and codes in support of "Accelerating Green Shipping by Spatially Optimized Offshore Charging Stations", including data, codes and figures.</p>
SQL database with detailed characteristic measurement results of photovoltaic modules that were subjected to accelerated aging sequences
<p>All measurement results are organized in an optimized database, which forms the information base for setting up models for climate sensitive ageing and degradation processes/mechanisms. The database is structured around the modules (module = device under test), see general scheme given in <a href="https://doi.org/10.1002/pip.3090">https://doi.org/10.1002/pip.3090</a>. Modules are logically connected via their specific ageing module groups with strictly associated ageing actions and instances. As stated above, a set of three identical modules is stored together in each specific ageing action (= accelerated ageing test as described in detail in Table <a title="Link to table" href="https://onlinelibrary.wiley.com/doi/10.1002/pip.3090#pip3090-tbl-0001">1</a> of <a href="https://doi.org/10.1002/pip.3090">https://doi.org/10.1002/pip.3090</a>) in order to increase the statistical reliability. Those triples are logically grouped in the database with the corresponding acquired measurement results being canonicalized and stored in the database as well. For future applications (modelling), all measurement information is kept as complete as possible; aggregation is avoided.</p> <a href="https://onlinelibrary.wiley.com/cms/asset/d5235350-b448-4094-b022-3b572d4c9317/pip3090-fig-0001-m.jpg" target="_blank" rel="noopener"></a>
Dataset for the plots in paper: 'A Kronecker product accelerated efficient sparse Gaussian Process (E-SGP) for flow emulation' in 'Journal of Computational Physics'
<p>The .xlsx file contains the data used for the plots Fig. 3, 4, 7, 8 and 9 in the paper 'Kronecker product accelerated efficient sparse Gaussian Process (E-SGP) for flow emulation'.</p>
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.