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1,506 results for “objects”
Wooden Object, Kirkjubø - Træ 7
Høgdur trælutur úr Kirkjubø. *Carved wooden object from Kirkjubø, Faroe Islands.* Created by Petur Hansen, using Artec Space Spider scanner and Artec Studio 16. Dimensions: 138cm x 17cm x 2cm. Source: Objaverse 1.0 / Sketchfab
IDInteraction Object Tracking Analysis
<p>Scripts and results for Object Tracking analysis for Automated Behavioural Coding.</p> <p>See https://github.com/IDInteraction/tracking-analysis for more information.</p>
Europe Pubmed Central Lite metadata (JSON object stream)
<p>The raw JSON object stream associated with https://zenodo.org/deposit/107781/</p>
Cortical idiosyncrasies predict the perception of object size
<p>This archive contains preprocessed pRF data from our manuscript "Cortical idiosyncrasies predict the perception of object size" (originally name "Mapping the subjective experience of object size"). This has been published in Nature Communications in 2016: http://www.nature.com/ncomms/2016/160630/ncomms12110/full/ncomms12110.html. Stimulus presentation and data analysis code is available on FigShare: https://dx.doi.org/10.6084/m9.figshare.1579442.v5</p>
Multi-Objective Optimization of Load Test Designs
<p>Supplementary material for the paper: "Multi-Objective Optimization of Load Test Designs".</p> <p>Included in the supplementary material are the evaluation results and the proof and concept implementation.</p>
Shape, motion and optical cues to stiffness of elastic objects
<p>Dataset relative to the following publication:</p> <p>Paulun, V.C., Schmidt, F., van Assen, J.J.R., & Fleming, R. W. (2017). Shape, motion and optical cues to stiffness of elastic objects. <em>Journal of Vision, 17(1):20, </em>1-20, doi:10.1167/17.1.20</p> <p>Each folder contains the data and stimulus material relative to one experiment and a text file with comments.</p>
A modular set of synthetic spectral energy distributions for young stellar objects - Robitaille (2017) - v1.1
<p>These are the models released with the following publication:</p> <p><em>A modular set of synthetic spectral energy distributions for young stellar objects</em>, Robitaille (2017)</p> <p>A companion repository is available on GitHub:</p> <p>https://github.com/hyperion-rt/paper-2017-sed-models</p> <p>In particular, a notebook is provided, demonstrating how the models here can be used:</p> <p>https://github.com/hyperion-rt/paper-2017-sed-models/blob/master/notebook/using_the_models.ipynb</p> <p><strong>Note:</strong> the files here do not include polarization results, nor do they include the SEDs split by components (e.g. scattered versus direct light). The raw Hyperion output files which contain this information will be made available at a later date, and a link will be provided here.</p> <p>For <strong>announcements</strong> of new versions of these models, you can subscribe to the following mailing list:</p> <p>https://groups.google.com/forum/#!forum/protostars</p> <p>For <strong>questions or issues</strong> using these models, you can open a GitHub issue in the companion repository:</p> <p>https://github.com/hyperion-rt/paper-2017-sed-models/issues/new</p> <p><strong>MacOS X users:</strong> there is a bug in the bundled version of tar in MacOS X that causes issues when expanding some of the largest files here (this results in the <em>flux.fits</em> file being empty). To avoid this, you can use the GNU tar version which can be installed e.g. with Homebrew using <em>brew install gnu-tar</em> then using the <em>gtar</em> command instead of <em>tar</em>.</p>
Inferring the stiffness of unfamiliar objects from optical, shape and motion cues
<p>Dataset relative to the following publication:</p> <p>Schmidt, F., Paulun, V. C., van Assen, J. J. R., & Fleming, R. W. (2017). Inferring the stiffness of unfamiliar objects from optical, shape, and motion cues. <em>Journal of Vision, 17(3):18</em>, 1-17. <a href="http://dx.doi.org/10.1167/17.3.18">http://dx.doi.org/10.1167/17.3.18 </a></p> <p>Each folder contains the stimuli and data relative to one experiment and a text file with comments.<br> The folder of Experiment 1 (Material) also contains the Maxwell (NextLimit Technologies, Madrid, Spain) material files that were used to render the stimuli in all experiments.</p> <p> </p>
Distinct Visual Processing of Real Objects and Pictures of Those Objects in 7- to 9-month-old Infants
<p>Data set of Gerhard, T.M., Culham, J.C. & Schwarzer, G. (2016). Distinct visual processing of real objects and pictures of those objects in 7- to 9-month-old infants. <em>Frontiers in Psychology, 7. doi:10.3389/fpsyg.2016.00827</em></p>
Concurrent anticipation of two object dimensions during grasping in 10-month-old infants: A quantitative analysis
<p>Data set of Concurrent anticipation of two object dimensions during grasping in 10-month-old infants: A quantitative analysis</p>
Bent out of shape: The visual inference of non-rigid shape transformations applied to objects
<p>Dataset relative to the following publication:</p> <p>Spröte, P., & Fleming, R. W. (2016). Bent out of shape: The visual inference of non-rigid shape transformations applied to objects. <em>Vision research, 126</em>, 330-346. <a href="https://doi.org/10.1016/j.visres.2015.08.009">https://doi.org/10.1016/j.visres.2015.08.009</a></p> <p>Each folder contains the data relative to one experiment and a text file with comments.</p>
The relation between crawling and non-crawling 9-month-old infants' visual prediction abilities in spatial object processing.
<p>The data set Kubicek et al._JECP_DataSet.sav containts the data of the paper from Kubicek, C., Jovanovic, B., & Schwarzer, G. (2017). The relation between crawling and non-crawling 9-month-old infants' visual prediction abilities in spatial object processing. Journal of Experimental Child Psychology, 158, 64–76.</p>
Manipulation of complex objects dataset - Rhythmic Cup Task experiment
<p>This dataset contains raw data from a behavioral neuroscience experiment conducted at Northeastern University, Boston, MA, USA.</p> <p>Ten participants rhythmically manipulated a virtual cup containing a ball via a robotic manipulandum which controlled the cup position and provided haptic feedback of the force applied by the ball. The cup movement was constrained to 1 dimension. Participants were free to choose the frequency of oscillation, while the amplitude was imposed by visual constraints. The cup and ball system was represented mathematically by a cart and pendulum system. The following dimensions were used for the experiment: pendulum length = 0.45m, pendulum mass = 0.6kg, cart mass = 2.4kg.</p> <p>Each participant performed 5 blocks of 10 trials. For each data file, the first 2 letters identify (anonymously) a participant, the first number identifies the block and the second number identifies the trial within the block.</p> <p>The data are in Matlab data format. "RackPosition" (resp. Velocity, Acceleration) corresponds to the cart position (resp. velocity, acceleration). Y is the axis of the movement. "BallTheta" and "BallOmega" are the pendulum angular position and velocity. Please note that in this dataset angles are positive in clockwise direction (contrary to usual mechanical conventions). "BallForce" is the force applied by the pendulum on the cart.</p> <p>This experimental dataset was confronted to simulation results obtained with two different models. One ("Uncoupled Model") only simulates the dynamics of a cart and pendulum system (Matlab script "cup_task_uncoupled_model_inverde_dynamics.m" and "simulation_cup_task_uncoupled_model_inverse_dynamics.m"). Simulations of this Uncoupled Model are run using inverse dynamics, assuming a sinusoidal trajectory of the cart. The second model ("Coupled Model") includes a simplified model of hand dynamics, represented by an ideal force generator in parallel with a spring and a damper to simulate hand impedance (Matlab and Simulink scripts "cup_task_coupled_model.slx" and "simulation_coupled_model_forward_dynamics.m"). Simulations of this Coupled Model are run using forward dynamics</p> <p> </p>
Predictive and sensory signals systematically lower peak forces in the exploration of softer objects
<p>An object’s softness is stereotypically judged by pressure movements indenting the surface [1]. In exploration without movement constraints, participants repeat such indentation movements. We investigated how people modulate executed peak forces for different indentations depending on stimulus softness. Participants performed a 2AFC discrimination task for stimulus pairs from one of 4 softness categories. We assumed that movement control at different exploration moments is based on variations in the predictive and sensory signals available. We manipulated availability of predictive signals on softness category, by presenting either stimuli of the same category in a blocked fashion (high predictability) or by randomly mixing stimuli from different categories (low predictability). Effects of sensory signals were examined by contrasting first and last indentation, as sensory signals are hardly available when initiating exploration but gathered during exploration. The results show that participants systematically apply lower forces when sensory or predictive signals indicate softer objects as compared to harder objects. We conclude that softness exploration can be considered as a sensorimotor control loop, in which predictive and sensory signals determine movement control. Further, the results indicate a high importance of predictive processes throughout the entire exploration, as effects of predictive signals maintain in the last indentation.</p> <p><strong>Lezkan</strong>, A. & <strong>Drewing</strong>, K. (2015). Predictive and sensory signals systematically lower peak forces in the exploration of softer objects. World Haptics Conference, 2015 IEEE (pp. 69-74). IEEE.</p> <p>The Zip file contains all data relative to the publication. For each participant code and each session exists a *txt and</p> <p>A description of the variables is contained in the file VARIABLE_CODES.txt</p>
Inter-imperial negotiation and heritage: Moving objects, people, ideas
<p>This interactive map was created based on the correspondence exchanged between and by Dimitrie Papazoglu, private collector in 19th century Wallachia, and Alexandru Odobescu, Commissioner General for the Romanian Pavilion at the 1867 Paris Universal Exhibition. The letters that Papazoglu and Odobescu exchanged either with each other or with other interlocutors, map the circulation of ideas, objects, and add depth to the nationalism and inter-imperiality context. Here heritage is constructed, selected, instrumentalized for national branding. The archival documents used come from the National Archives of Romania, the National Library and the Romanian Academy Library, Manuscript section. </p>
Animal Diversity Web: ADW Traits & image objects from Quaardvark Tool
This morphometry and life history dataset for size characteristics of birds is from undergraduate students who contributed to the Animal Diversity Web. Traits and images are harvested using ADW__s Quaardvark data download tool.<p></p>
Data supporting "Lessons learned from multi-objective automatic optimizations of classical three-site rigid water models using microscopic and macroscopic target experimental observables"
<p>This repository contains the set of data and the code to reproduce the results shown in "Lessons learned from multi-objective automatic optimizations of classical three-site rigid water models using microscopic and macroscopic target experimental observables" published on Journal of Chemical Engineering and Data (DOI: 10.1021/acs.jced.3c00538).</p>
Research data supporting ""Lessons learned from multi-objective automatic optimizations of classical three-site rigid water models using microscopic and macroscopic target experimental observables""
<p>This repository contains the set of data and the code to reproduce the results shown in "Lessons learned from multi-objective automatic optimizations of classical three-site rigid water models using microscopic and macroscopic target experimental observables" published on Journal of Chemical Engineering and Data (DOI: 10.1021/acs.jced.3c00538).</p>
Macrohaplotype cache objects and databases
<p>These are (bzip compressed) objects; each individual file represents a single PCR simulation of a single cell's worth of DNA. All results assume 100% sequencing efficiency and 0 sequencing error (but yes to PCR error, in the form of +/- stutter as well as single nucleotide PCR error).</p> <p>These objects can be used by mhapSimulator.py (https://github.com/Ahhgust/MacrohapSimulator.git) to (more quickly) generate simulations of the PCR process (single source, DNA mixtures, any amount of DNA template)</p> <p>Also included are macrohaplotypes drawn from the 1000 Genomes Project.</p> <p> </p> <p> </p>
Performance Evaluation of Objective Quality Assessment Methods for Omnidirectional Images Under Emerging Compressions
<p>This dataset provides extensive data from large-scale subjective experiments, encompassing MOS values, eye-tracking data, and raw subjective scores, collected from two laboratories Brno University of Technology and Czech Technical University in Prague (BUT and CTU). This new dataset serves as a comprehensive foundation for future research endeavors into novel objective quality metrics for omnidirectional IQA (OIQA).</p> <p> </p> <p><strong>▷ </strong> contact: xsimka01@vut.cz</p>
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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.