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Dataset results
201 results for “SAT”
A comparison between SBP-SAT and DG operators for computational aeroacoustics on non-conforming meshes
<p>Contains:</p> <ul> <li>classic SBP operators of global order three, four and five</li> <li>classic DRP SBP operators of global order three, four and five</li> <li>DDRP SBP operator of order four using 32 nodes</li> <li>Projection operators for h- and p-refinement</li> </ul>
SAT Competition Benchmark – Trigonometric Functions
<p>Benchmark family for the <a href="http://www.satcompetition.org">SAT Competition</a> verifying properties of trigonometric function approximations. The implemented functions are sine, cosine and tangent. All three functions are composed of a single partial cosine implementation in the interval [-π/2, π/2] for which three different methods of approximation are provided.</p>
Dataset for High-Round QAOA for MAX k-SAT on Trapped Ion NISQ Devices
<p>Dataset for the paper titled `High-Round QAOA for MAX k-SAT on Trapped Ion NISQ Devices`</p> <p>LA-UR-23-28505</p>
Sleep Apnea Treatment After Stroke (SATS)
ClinicalTrials.gov study NCT00282815. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Study 33: Adherence to Latent Tuberculosis Infection Treatment 3HP SAT Versus 3HP DOT
ClinicalTrials.gov study NCT01582711. IPD Sharing: Not stated. Countries: 4. Publications: 7.
Data from: STREAM-Sat: a novel near-realtime quasi-global satellite-only ensemble precipitation
Open the record for dataset details and reuse information.
Small Uniform Random SAT Samples
<p>Small Random SAT samples generated with the following <em>samplers</em>:</p> <ul> <li>BDDSampler</li> <li>Spur</li> <li>QuickSampler </li> <li>KUS</li> <li>Unigen2</li> <li>Smarch </li> </ul>
Inventory of principles, criteria and indicators in relation to SAT-ProBio blueprint
<p>The dataset provide indication for principles and criteria in relation to SAT-ProBio blueprint as well as a compilation of available data related to sustainability principles, criteria and indicators provided by EN 16751 and STAR-ProBio project partners USC-UNITELMA et al. on social indicators and Quantis et al. on selected environmental indicators and AUA et al. on techno-economic indicators.</p>
SAT Coaching in Kolkata
<p>A study abroad and overseas education consultancy. <a href="https://www.eduaims.in/">EduAims</a> provides test preparation and coaching classes for SAT, ACT, GRE, GMAT, IELTS, and TOEFL. SAT coaching in Kolkata, GRE preparation, GMAT preparation, study abroad, statement of purpose, overs.</p>
A SAT-based Resolution of Lam's Problem (SAT instances and certificates)
<p>This repository contains SAT instances and certificates accompanying the paper "A SAT-based Resolution of Lam's Problem" appearing at <a href="https://aaai.org/Conferences/AAAI-21/">AAAI 2021</a>. This paper developed a method to generate certificates proving the nonexistence of a word of weight 19 in the code generated by a projective plane of order ten. Together with previously computed certificates this solves Lam's Problem.</p> <p>The 'a1' archive contains a certificate showing that there are exactly 66 A1 matrices up to isomorphism. Run the provided check.sh script to verify the certificate.</p> <p>The 'a2' archive contains certificates showing that there are exactly 650,370 A2 matrices up to isomorphism. Run the provided check.sh script to verify the certificates.</p> <p>The 'main' archive contains precomputed SAT instances for each of the A2 matrices up to isomorphism and partial solutions of the SAT instances. The main certificates may be generated and verified by extracting the main archive into the weight19/main directory of the MathCheck2 repository for Lam's problem (available from <a href="https://bitbucket.org/cbright/mathcheck2/src/master/">bitbucket.org/cbright/mathcheck2</a> or in the lams-problem-code.7z archive) and running the driver.sh script. The final-step/solve.sh script verifies that no partial solution can be completed to a full incidence matrix of a projective plane of order ten.</p>
SAT data
<p>UEA Climatic Research Unit (CRU) Gridded Datasets production project </p>
Experimental data for "sampling Configurations From Software Product Lines Via Probability-aware Diversification and SAT Solving"
<p>Experimental data for "sampling Configurations From Software Product Lines Via Probability-aware Diversification and SAT Solving" submitted to ASE. </p> <p>1. rSATJ4, PaD+rSATJ4, ProbSAT and PaD+ProbSAT are data for RQs1-2;</p> <p>2. NSbS and PaD+NSbS are data for RQ3;</p> <p>3. SATVaEA, PaD+SATVaEA, ProbSATVaEA, PaD+ProbSATVaEA are data for RQ4.</p> <p> </p> <p> </p>
The OPS-SAT case dataset
<p>The "OPS-SAT case" dataset is the official dataset of <a href="https://kelvins.esa.int/opssat/home/"><strong>ESA's Kelvins</strong> </a><strong><a href="https://kelvins.esa.int/opssat/home/">"the OPS-SAT case" challenge</a>, </strong>created in collaboration<strong> with ESA's Phi-lab </strong>and <strong>ESA's OPS-SAT spacecraft operations team</strong>. It consists of<strong> 26 raw and unprocessed images</strong> of Earth that have been taken by the OPS-SAT cube-sat using its on-board camera. The images have a resolution of around <strong>2048x1944 </strong>or similar and are provided in <strong>.png</strong> format.</p> <p>The goal of the competition is, given a model of a neural network (in this case the <strong>EfficientNet-Lite0</strong>), to provide best possible network parameters to perform an <strong>on-board classification</strong> task. For each of the 8 target classes, there are only 10 labelled images provided, severely limiting the number of "shots" that the neural network has on learning. The size of the labeled patches is <strong>200x200</strong> pixels and the labels are related to the following types of landcover/content: <strong>Agricultural, Cloud, Mountain, Natural, River, Sea_Ice, Snow </strong>and <strong>Water.</strong></p> <p>More details about the competition setup and solution evaluation are on the <a href="https://kelvins.esa.int/opssat/home/">Kelvins competition platform</a>.</p> <p>The following publication outlines the generation of the dataset:</p> <ul> <li>Derksen, D., Meoni, G., Lecuyer, G., Mergy, A., Märtens, M. and Izzo, D. Few-Shot Image Classification Challenge On-Board. NEURIPS2021</li> </ul>
A SAT Attack on Rota's Basis Conjecture: Supplemental data for rank 4
<p>The file contains a DRAT-proof for Rota's Basis Conjecture for Rank 4 generated by a program. For verifying the output and intermediate files, we refer to <a href="https://doi.org/10.5281/zenodo.6616343">source</a>.</p>
Computing Optimal Hypertree Decompositions with SAT - Results
<p>The data from our experiments.</p>
SAT Competition 2016 Application Track Benchmarks
<p>These are the 299 CNF files in DIMACS format from the application track of the SAT competition 2016.</p> <p>Originally the competition advocated 300 benchmarks but <code>sncf_model_ixl_bmc_depth_14.cnf</code> was truncated (terminating zero and many clauses were missing). Thus only 299 valid DIMACS benchmarks were actually made available. This broken benchmark is from a family of SNCF BMC encodins for the bounds 7 to 15. In 2016 no solver solved any of these bounds nor were the bounds 9, 10, 15 solved in the following anniversary track from the SAT competition 2022 by any solver.</p>
SAT Competition 2022 Main Track Benchmarks
<div> <p>These are the 400 CNF files in DIMACS format from the main track of the SAT competition 2022.</p> <p> </p> </div>
SAT Competition 2011 Application Track Benchmarks
<p>These are the 300 CNF files in DIMACS format from the application track of the SAT competition 2011.</p>
SAT Competition 2013 Application Track Benchmarks
<div> <p>These are the 300 CNF files in DIMACS format from the application track of the SAT competition 2013.</p> </div>
SAT Competition 2014 Application Track Benchmarks
<p>These are the 300 CNF files in DIMACS format from the application track of the SAT competition 2014.</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.