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685 results for “errors”
Datasets for 'Estmating autonomous vehicle localization error using 2D Geographic Information'
<p>Datasets for 'Estmating autonomous vehicle localization error using 2D Geographic Information'</p>
Risk of Wrong-Patient Errors With Multiple Records Open
ClinicalTrials.gov study NCT02876588. IPD Sharing: YES. Countries: 1. Publications: 9.
Data from: Robustness of divergence time estimation despite gene tree error: A case study of fireflies (Coleoptera: Lampyridae)
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Data from: Improved robustness to gene tree incompleteness, estimation errors, and systematic homology errors with weighted TREE-QMC
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Using unoccupied aerial vehicles to estimate availability and group size error for aerial surveys of coastal dolphins
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Data for: Assortative mating in an ecological context: Effects of mate choice errors and relative species abundance on the frequency and asymmetry of hybridization
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Data from: Avoiding impacts of phylogenetic tip-state-errors on dispersal and extirpation rates in alpine plant biogeography
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Boosting multiplexing capabilities for error-robust spatial transcriptomic methods using a set exchange approach
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Low vision impairs implicit sensorimotor adaptation in response to small errors, but not large errors
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Dataset for Mininig Off-by-One Errors
<p>The dataset that was made by downloading top 500 starred Java projects from GitHub and then eliminating common projects found with java-large-training and java-large-testing raw datasets*. The resulting dataset consists of 155 GitHub projects.</p> <p>The repositories were downloaded and the code analyzed using code found in the following repository: <a href="https://github.com/serg-ml4se-2019/group5-deep-bugs/tree/master">https://github.com/serg-ml4se-2019/group5-deep-bugs/tree/master</a> (more specifically, the code found in bug_mining folder)</p> <p>* java-large raw dataset can be found at <a href="https://github.com/tech-srl/code2seq/blob/master/README.md#datasets">https://github.com/tech-srl/code2seq/blob/master/README.md#datasets</a></p>
Data for the publication "Reconciling compensating errors between precipitation constraints and the energy budget in a climate model"
<p>These data are a set of 6yr simulations using the MIROC6-SPRINTARS global aerosol-climate model with different treatments (diagnostic and prognostic) of precipitation under the present-day (PD, aerosol emission at the year 2000) and preindustrial (PI, aerosol emission at the year 1850) conditions.<br> The data are used in the manuscript entitled "Reconciling compensating errors between<br> precipitation constraints and the energy budget in a climate model".</p>
Confronting sources of systematic error to resolve historically contentious relationships: a case study using gadiform fishes (Teleostei, Paracanthopterygii, Gadiformes)
<p>Reliable estimation of phylogeny is central to avoid inaccuracy in downstream macroevolutionary inferences. However, limitations exist in the implementation of concatenated and summary coalescent approaches, and Bayesian and full coalescent inference methods may not yet be feasible for computation of phylogeny using complicated models and large datasets. Here, we explored methodological (e.g., optimality criteria, character sampling, model selection) and biological (e.g., heterotachy, branch length heterogeneity) sources of systematic error that can result in biased or incorrect parameter estimates when reconstructing phylogeny by using the gadiform fishes as a model clade. Gadiformes include some of the most economically important fishes in the world (e.g., Cods, Hakes, and Rattails). Despite many attempts, a robust higher-level phylogenetic framework was lacking due to limited character and taxonomic sampling, particularly from several species-poor families that have been recalcitrant to phylogenetic placement. We compiled the first phylogenomic dataset, including <span>14,208 loci (>2.8 M bp) from 58 species representing all recognized gadiform families, to infer a time-calibrated phylogeny for the group. </span>Data were generated with a gene-capture approach targeting coding DNA sequences from single-copy protein-coding genes. Species-tree and concatenated maximum-likelihood analyses resolved all family-level relationships within Gadiformes. While there were a few differences between topologies produced by the DNA and the amino acid datasets, most of the historically unresolved relationships among gadiform lineages were consistently well resolved with high support in our analyses regardless of the methodological and biological approaches used. However, at deeper levels, we observed inconsistency in branch support estimates between bootstrap and gene and site coefficient factors (gCF, sCF). Despite numerous short internodes, all relationships received unequivocal bootstrap support while gCF and sCF had very little support, reflecting hidden conflict across loci. Most of the gene-tree and species-tree discordance in our study is a result of short divergence times, and consequent lack of informative characters at deep levels, rather than incomplete lineage sorting (ILS). We use this phylogeny to establish a new<span> higher-level classification of Gadiformes as a way of clarifying the evolutionary diversification of the order.</span> We recognize 17 families in five suborders: Bregmacerotoidei, Gadoidei, Ranicipitoidei, Merluccioidei, and Macrouroidei (including two subclades). A time-calibrated analysis using 15 fossil taxa suggests that Gadiformes evolved ~79.5 million years ago (Ma) in the late Cretaceous, but that most extant lineages diverged after the Cretaceous-Paleogene (K-Pg) mass extinction (66 Ma)<span>. </span>Our results reiterate the importance of examining phylogenomic analyses for evidence of systematic error that can emerge as a result of unsuitable modeling of biological factors and/or methodological issues, even when datasets are large and yield high support for phylogenetic relationships.</p>
Do children learn from their mistakes? A registered report evaluating error-based theories of language acquisition
<p>Error-based theories of language acquisition suggest that children, like adults, continuously make and evaluate predictions in order to reach an adult-like state of language use. However, while these theories have become extremely influential, their central claim - that unpredictable input leads to higher rates of lasting change in linguistic representations – has scarcely been tested. We designed a prime surprisal-based intervention study to assess this claim.</p> <p>As predicted, both 5- to 6-year-old children (n=72) and adults (n=72) showed a pre- to post-test shift towards producing the dative syntactic structure they were exposed to in surprising sentences. The effect was significant in both age groups together, and in the child group separately when participants with ceiling performance in the pre-test were excluded. Secondary predictions were not upheld: there were no verb-based learning effects and there was only reliable evidence for immediate prime surprisal effects in the adult, but not in the child group. To our knowledge this is the first published study demonstrating enhanced learning rates for the same syntactic structure when it appeared in surprising as opposed to predictable contexts, thus providing crucial support for error-based theories of language acquisition.</p>
Results for paper "Energy dependent mesh adaptivity of discontinuous isogeometric discrete ordinate methods with dual weighted residual error estimators"
<p>This spreadsheet contains the results used to generate the plots in the paper "Energy dependent mesh adaptivity of discontinuous isogeometric discrete ordinate methods with dual weighted residual error estimators".</p>
JavaScript and html Validity Errors
<p>This data is captured by tool ‘Artemis’, which is a test generation tool for javascript based web applications. The data contained here has benchmarks and html validity errors found out by Artemis tool, when ran against live applications. This data can be used to analyse the html coding errors committed by the programmers and see how we can prevent these errors.</p>
Assessment of error variation in high-fidelity two-qubit gates in silicon
<p>The data and the analysis files for the paper titled: "Assessment of the errors of high-fidelity two-qubit gates in silicon quantum dots" https://arxiv.org/abs/2303.04090 Analysis files written in python and in matlab. Some files need the PyGSTi to run.</p>
Synthetic automotive LiDAR with non-systematic error and automotive LiDAR based on active stereo dataset
<p>The synthetic dataset was generated by transforming the original dataset using several methods. Each of these transformations occurs from a use case:</p><ul><li>UC1 is the original dataset obtained from [1] and represents a point cloud dataset captured by an ideal LiDAR</li><li>UC2 is a realistic point cloud dataset obtained by simulating the non-systematic error of a Velodyne HDL-64E and applying to UC1</li><li>UC3 is our approach to replace the LiDAR with an active stereo setup. Where the point cloud are captured using two cameras, operating stereoscopically, and a dot projector. The cameras are perfectly calibrated and the triangulation is always correct.</li><li>UC4 also obtains the point clouds through triangulation. However we introduced a calibration error on the right camera. The error has the value of 1 pixel and is added to every dimension of the rotation matrix of the right camera.</li><li>UC5 performs an ideal triangulation, same as UC3. However, in this use case, we introduce camera noise to the point clouds.</li><li>UC6 is a combination of the triangulation from UC4 and the camera noise from UC5.</li></ul><p>Additionally, the labels, images and calibration file are also in [1]. For further details, please check the dataset generation source code [2]. </p><p>[1] https://zenodo.org/records/7184990</p><p>[2] https://github.com/RobertoGraca/Active_Stereo_Based_LiDAR</p>
Position error-free control of magnetic-domain wall devices via spin-orbit torque modulation
<p>Magnetic domain-wall devices such as racetrack memory and domain-wall shift registers facilitate massive data storage as hard disk drives with low power portability as flash memory devices. The key issue to be addressed is how perfectly the domain-wall motion can be controlled without deformation, as it can replace the mechanical motion of hard disk drives. However, such domain-wall motion in real media is subject to the stochasticity of thermal agitation with quenched disorders, resulting in severe deformations with pinning and tilting. To sort out the problem, we propose and demonstrate a new concept of domain-wall control with a position error-free scheme. The primary idea involves spatial modulation of the spin-orbit torque along nanotrack devices, where the boundary of modulation possesses broken inversion symmetry. In this work, by showing the unidirectional motion of domain wall with position-error free manner, we provide an important missing piece in magnetic domain-wall device development.</p>
Position error-free control of magnetic-domain wall devices via spin-orbit torque modulation
<p>Magnetic domain-wall devices such as racetrack memory and domain-wall shift registers facilitate massive data storage as hard disk drives with low power portability as flash memory devices. The key issue to be addressed is how perfectly the domain-wall motion can be controlled without deformation, as it can replace the mechanical motion of hard disk drives. However, such domain-wall motion in real media is subject to the stochasticity of thermal agitation with quenched disorders, resulting in severe deformations with pinning and tilting. To sort out the problem, we propose and demonstrate a new concept of domain-wall control with a position error-free scheme. The primary idea involves spatial modulation of the spin-orbit torque along nanotrack devices, where the boundary of modulation possesses broken inversion symmetry. In this work, by showing the unidirectional motion of domain wall with position-error free manner, we provide an important missing piece in magnetic domain-wall device development.</p>
Data for "Qubit fractionalization and emergent majorana liquid in the honeycomb floquet code induced by coherent errors and weak measurements"
<p>From the perspective of quantum many-body physics, the Floquet code of Hastings and Haah can be thought of as a measurement-only version of the Kitaev honeycomb model where a periodic sequence of two-qubit XX, YY, and ZZ measurements dynamically stabilizes a toric code state with two logical qubits. However, the most striking feature of the Kitaev model is its intrinsic fractionalization of quantum spins into an emergent gauge field and itinerant Majorana fermions that form a Dirac liquid, which is absent in the Floquet code. Here we demonstrate that by varying the measurement strength of the honeycomb Floquet code one can observe features akin to the fractionalization physics of the Kitaev model at finite temperature. Introducing coherent errors to weaken the measurements we observe three consecutive stages that reveal qubit fractionalization (for weak measurements), the formation of a Majorana liquid (for intermediate measurement strength), and Majorana pairing together with gauge ordering (for strong measurements). Our analysis is based on a mapping of the imperfect Floquet code to random Gaussian fermionic circuits (networks) that can be Monte Carlo sampled, exposing two crossover peaks. With an eye on circuit implementations, our analysis demonstrates that the Floquet code, in contrast to the toric code, does not immediately break down to a trivial state under weak measurements, but instead gives way to a long-range entangled Majorana liquid state.</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.