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400 results for “immersion”
Influence of Anode Immersion Speed on Current and Power in Plasma Electrolytic Polishing
<p><span>Plasma electrolytic polishing (PeP) is mainly used to improve the surface quality and thus </span><span>the performance of electrically conductive parts. It is usually used as an anodic process, i.e., the </span><span>workpiece is positively charged. However, the process is susceptible to high current peaks during</span> <span>the formation of the vapour–gaseous envelope, especially when polishing workpieces with a large </span><span>surface area. In this study, the influence of the anode immersion speed on the current peaks and the</span> <span>average power during the initialisation of the PeP process is investigated for an anode the size of a </span><span>microreactor mould insert. Through systematic experimentation and analysis, this work provides</span> <span>insights into the control of the initialisation process by modulating the anode immersion speed. The </span><span>results clarify the relationship between immersion speed, peak current, and average power and</span> <span>provide a novel approach to improve process efficiency in PeP. The highest peak current and average </span><span>power occur when the electrolyte splashes over the top of the anode and not, as expected, when the </span><span>anode touches the electrolyte. By immersion of the anode while the voltage is applied to the anode</span> <span>and counterelectrode, the reduction of both parameters is over 80 %.</span></p>
Self-Attribution of Distorted Reaching Movements in Immersive Virtual Reality Dataset
<p>This dataset accompanies the paper “Self-Attribution of Distorted Reaching Movements in Immersive Virtual Reality” published in the Computer and Graphics journal from Elsevier. It contains 3 datasets related to the experiments described in the paper. All datasets are in “.csv” format and can be easily loaded by statistical analysis tools (e.g. a dataset can be loaded in r using the command read.csv(“filename.csv”)). It also contains the C# Unity implementation of the distortion function presented in the paper.</p> <p>Paper reference:</p> <p>Galvan Debarba H, Boulic R, Salomon R, Blanke O, Herbelin B. Self-Attribution of Distorted Reaching Movements in Immersive Virtual Reality. Computers & Graphics. 2018; ISSN 0097-8493. Elsevier.</p> <p>DOI: doi.org/10.1016/j.cag.2018.09.001</p>
Self-attribution of distorted reaching movements in immersive virtual reality
<p>This dataset and Unity 3D code scripts are associated to the following paper : H. Debarba, R. Boulic, R. Solomon, O. Blanke, B. Herbelin (Computers & Graphics, Vol 76, November 2018, pp 142-152, <a href="https://www.sciencedirect.com/science/article/pii/S0097849318301353?utm_campaign=STMJ_75273_AUTH_SERV_PPUB&utm_medium=email&utm_dgroup=&utm_acid=810891&SIS_ID=0&dgcid=STMJ_75273_AUTH_SERV_PPUB&CMX_ID=&utm_in=DM377782&utm_source=AC_30">in Open Access</a>) : “Self-attribution of distorted reaching movements in immersive virtual reality”. <a href="https://doi.org/10.1016/j.cag.2018.09.001">https://doi.org/10.1016/j.cag.2018.09.001</a></p> <p> </p>
A New Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications
<p>This database is created by the Realistic 3D research group at Mid Sweden University, Sundsvall, Sweden. The database details are explained thoroughly in the publication which was published at the 16th International Conference on Quality of Multimedia Experience (QoMEX) in 2024. This database was also reviewed as part of the submission and publication process.</p> <p>You can use this database in your work under the Creative Commons Attribution 4.0 International (CC-BY 4.0) licence, provided that you cite the database as below:</p> <blockquote> <p>Zerman, E., Gond, M., Takhtardeshir, S., Olsson, R., & Sjöström, M. (2024). A Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications. <em>The 16th International Conference on Quality of Multimedia Experience (QoMEX)</em>. IEEE. DOI: <a href="https://ieeexplore.ieee.org/abstract/document/10598264">10.1109/QoMEX61742.2024.10598264</a></p> </blockquote> <p>BibTeX:</p> <blockquote> <p>@inproceedings{zerman2024spherical,<br> title = {A Spherical Light Field Database for Immersive Telecommunication and Telepresence Applications},<br> author = {Zerman, Emin and Gond, Manu and Takhtardeshir, Soheib and Olsson, Roger and Sj{\"o}str{\"o}m, M{\aa}rten},<br> booktitle = {The 16th International Conference on Quality of Multimedia Experience (QoMEX)},<br> year = {2024},<br> organization = {IEEE},<br> doi = {10.1109/QoMEX61742.2024.10598264}<br>}</p> </blockquote> <p>This database contains 20 spherical light fields of 1 x 60 views, captured with a consumer-grade 360-degree camera: Insta360 X3. The capture was done using a dolly to ensure the separation between consecutive views is exactly 1 cm. In addition to the original captures, this database also provides outputs for two different use cases: compression and view synthesis. Several parameters, features, and objective quality metric values are also included.</p> <p>N.B. Only the README file and this description have been updated after the initial submission on 2024-02-09.</p>
Data supporting publication: Nanoscale Mechanical Manipulation of Ultrathin SiN Membranes Enabling Infrared Near-Field Microscopy of Liquid-Immersed samples
<p>This repository includes the data corresponding to the figures shown in the journal article entitled Nanoscale Mechanical Manipulation of Ultrathin SiN Membranes Enabling Infrared Near-Field Microscopy of Liquid-Immersed samples, published in small. </p>
Shopping in Immersive Virtual Reality: Effects of Visual, Auditory, and Cognitive Demands on Mental Workload
<p>The dataset - of the journal article "Shopping in Immersive Virtual Reality: Effects of Diminishing Visual, Auditory, and Cognitive Demands on Workload" - consists of heart rate and eye-tracking data per participant and experimental condition. It also contains the figures inserted in the manuscript, the MATLAB scripts, the Unity project of an immersive virtual supermarket, and a demo video of a participant performing a grocery task across the experimental conditions in the virtual supermarket.</p>
Data from: Capacity and selection in immersive visual working memory following naturalistic object disappearance
<p>Trial datasets and timeseries datasets associated with the experiment reported in the manuscript "Capacity and selection in immersive visual working memory following naturalistic object disappearance", by Babak Chawoush, Dejan Draschkow & Freek van Ede</p>
IMMERSE Horizon 2020 Project Downstream User Toolbox – data for tutorial on impact of wave coupling on surface particle dispersion simulations
<p>Exemplary data for tutorial on impact of wave coupling on surface particle dispersal simulations<br> <a href="https://github.com/immerse-project/Downstream-Users-Toolbox/tree/main/T8.3_WaveCoupling_ParticleTransport_UniU">https://github.com/immerse-project/Downstream-Users-Toolbox/tree/main/T8.3_WaveCoupling_ParticleTransport_UniU</a><br> created as part of the downstream user toolbox of the IMMERSE Horizon 2020 project (<a href="https://immerse-ocean.eu/">https://immerse-ocean.eu/</a>).</p> <p>In the tutorial the impact of new options for the representation of wave-current interactions in the NEMO ocean model (<a href="https://www.nemo-ocean.eu/">https://www.nemo-ocean.eu/</a>) on surface particle simulations are tested in a case study for the Mediterranean Sea. The tutorial consists of two jupyter notebooks: Parcels_CalcTraj.ipynb and CompTraj_uncoupledVScoupled.ipynb. Parcels_CalcTraj.ipynb calculates Lagrangian particle trajectories based on velocity output from ocean only as well as coupled ocean-wave model simulation by making use of the OceanParcels software (<a href="https://oceanparcels.org/">https://oceanparcels.org/</a>). CompTraj_uncoupledVScoupled.ipynb compares dispersal statistics of Lagrangian particle trajectories calculated from ocean-only vs coupled ocean-wave model simulations.</p> <p>This repository contains the surface velocity and ocean model grid data needed to run Parcels_CalcTraj.ipynb, as well as the trajectory data produced by Parcels_CalcTraj.ipynb, which is needed to run CompTraj_uncoupledVScoupled.ipynb. The surface velocity data stems from two simulations with a regional high-resolution (1/24° horizontal resolution) model configuration for the Mediterranean Sea: a coupled ocean-wave model simulation and a complimentary ocean-only simulation. These model simulations make use of the NEMO v4.2-RC ocean model, the Wave Watch 3 v.6.07 wave model, the OASIS3-MCT coupler, and ECMWF atmospheric fields; they are described in detail in IMMERSE deliverable D5.7 “Assessment of wave-current effects on the circulation in theMed-MFC system”<strong>.</strong></p>
Dataset for "Quantum bath suppression in a superconducting circuit by immersion cooling"
<p>Dataset supporting the findings in the manuscript "Quantum bath suppression in a superconducting circuit by immersion cooling" by M Lucas et al. (<em>Nature Communications</em> <strong>14</strong>, 3522 (2023), arxiv:2210.03816) Containing: description of files & figures, raw datasets obtained from superconducting resonator noise and quality factor measurements, electron spin resonance measurements.</p>
Project's repository for: Co-immersion in Audio Augmented Virtuality: the Case Study of a Static and Approximated Late Reverberation Algorithm
<p>Repository of the VR scene and the audio data used for the experiment reported in the publication <a href="https://ieeexplore.ieee.org/document/10269056" target="_blank" rel="noopener">available in Open Access</a>:</p> <blockquote> <p>Davide Fantini, Giorgio Presti, Michele Geronazzo, Riccardo Bona, Alessandro Giuseppe Privitera and Federico Avanzini (2023) "Co-immersion in Audio Augmented Virtuality: the Case Study of a Static and Approximated Late Reverberation Algorithm" in <em>IEEE Transactions on Visualization and Computer Graphics (ISMAR special issue)</em></p> </blockquote> <p>The file <a href="../api/files/06c374e2-c54d-40f1-ae23-c4c7afbfba5b/README.md">README.md</a> includes some instructions to use the data in this repository.</p> <p> </p> <p><strong>AUDIO</strong></p> <p>The file <a href="../api/files/06c374e2-c54d-40f1-ae23-c4c7afbfba5b/audio.zip">audio.zip</a> includes the Reaper's projects and audio files used in the experiment to provide the auditory stimuli (simultaneous reverberated speeches) to the participants. Each subfolder corresponds to a different Virtual Acoustics Environment (VAE):</p> <ul> <li><<em>LivingRoom</em>|<em>MARCo</em>|<em>METU</em>> <ul> <li><<em>Living Room</em>|<em>MARCo</em>|<em>METU</em>><em>.rpp</em>: Reaper's project for the VAE</li> <li><em>Bin</em>: folder including the speech data convolved with the late reverberation part of the reverb condition \(B\) for each source position in the VAE</li> <li><em>Freeverb</em>: folder including the speech data convolved with the late reverberation part of the reverb condition \(F_\text{d}\) for each source position in the VAE</li> <li><em>HOA</em>: <ul> <li><em>ER</em>: folder including the speech data convolved with the early reflections part (HOA in A-format) of the reference reverb condition \(H\) for each source position in the VAE</li> <li><em>Ref</em>: folder including the speech data convolved with the entire reference reverb condition \(H\) (HOA in A-format) for each source position in the VAE</li> </ul> </li> </ul> </li> </ul> <p>The reverberated speech data in the <a href="../api/files/06c374e2-c54d-40f1-ae23-c4c7afbfba5b/audio.zip">audio.zip</a> file are obtained using third-party datasets:</p> <ul> <li>The anechoic speech data are retrieved from four speakers (F2, F5, M3, M6) of the <a href="https://doi.org/10.5281/zenodo.6257551">ACE challenge corpus</a></li> <li>The Room Impulse Responses (RIR) in High-Order Ambisonics (HOA) format used to reverberate the speeches are retrieved from: <ul> <li><a href="https://doi.org/10.5281/zenodo.5747753">Living Room</a></li> <li><a href="https://doi.org/10.5281/zenodo.3477602">Concert hall (MARCo)</a></li> <li><a href="https://doi.org/10.5281/zenodo.2635758">Classroom (METU)</a></li> </ul> </li> </ul> <p> </p> <p><strong>VR SCENE</strong></p> <p>The file <a href="../api/files/06c374e2-c54d-40f1-ae23-c4c7afbfba5b/VRscene.zip">VRscene.zip</a> includes the Virtual Reality (VR) scene provided to the participants during the experiment via an Oculus Quest 2. This file includes two subfolders:</p> <ul> <li><em>UDPServer</em>: C# code for the UDP server used for sending the OSC messages for head tracking <ul> <li><em>external/SharpOSC.dll</em>: external library (<a href="https://github.com/ValdemarOrn/SharpOSC">SharpOSC</a>) used to interact with the OSC protocol</li> </ul> </li> <li><em>VR_Headtracking</em>: folder including the Unity project with the VR scene</li> </ul> <p> </p>
Evaluation Results - Semantic Zoom With Immersive Detail View for ExplorViz
<p>This archive contains the evaluation results of the master thesis 'Semantic Zoom With Immersive Detail View for ExplorViz'.</p> <p>The evaluation is divided into a user evaluation of usability and user performance and a rendering performance evaluation.</p> <p>The evaluation compares the version of ExplorViz with Semantic Zoom and without Semantic Zoom.</p> <p>The complete user survey can be viewed in the PDF: 'Printed version of the survey - ExplorViz with Semantic Zoom.pdf'.</p> <p><br>- The file 'survey_archive_277626.lsa' is exported from LimeSurvey and contains the survey and the responses.<br>- results-survey277626.csv' contains the results in csv format.<br>- The file 'results-statistics.pdf' is a pdf that contains statistics about the survey results.<br>- The file 'results-all-answers-ExplorViz with Semantic Zoom.pdf' lists all the participants' answers in text format.<br>- The file 'allChartImages.zip' displays the results data in graphs.</p> <p><br>As part of a performance evaluation of the frontend, a Python script using Selenium was used.<br>The results can be found in the csv files:<br>- 'performance_RendertimeTracegen - XXXL world with high communication2024-11-19--22-13-36-SZLongTerm'<br>- 'performance_RendertimeTracegen - XXXL world with high communication2024-11-19--22-09-24-NoSZLongTerm'</p> <p>The Python script is split into two files:<br>- 'selenium_test.py'<br>- 'helpers.py'</p>
Dataset related to article "How Academics and the Public Experienced Immersive Virtual Reality for Geo-education"
<p>The dataset is associated with the paper entitled: How Academics and the Public Experienced Immersive Virtual Reality for Geo-education.</p> <p>It contains feedback regarding users’ experience with Immersive Virtual Reality for geological exploration, through a tailored approach developed by Tibaldi et al. (2020) where the Virtual Landscape is based on 3D photogrammetry-based high-resolution models.</p> <p>Such feedback has been acquired through anonymous questionnaires during nine dissemination events held in 2018 and 2019 in various locations (Vienna in Austria, Milan and Catania in Italy and Santorini in Greece), in the framework of the following projects: i) the MIUR project ACPR15T4_00098–Argo3D (http://argo3d.unimib.it/); ii) 3DTeLC Erasmus+Project 2017-1-UK01-KA203-036719 (<a href="http://www.3dtelc.com">http://www.3dtelc.com</a>); iii) EGU 2018 Public Engagement Grant (https://www.egu.eu/outreach/peg/) .</p> <p>In the dataset, feedback has been grouped into categories, based on users age and background:</p> <p>i) Middle and High School Students (Schools students, results in Sheet 1);</p> <p>ii) MSc Students in Earth Sciences (MSc, results in Sheet 2);</p> <p>iii) Academics/Researchers in Earth Sciences, that include PhD students and postdocs (Academics, results in Sheet 3);</p> <p>iv) Lay Public (i.e. participants that do not belong to the other groups, results in Sheet 4).</p> <p>It lists a total of 459 records; further details are available in the manuscript.</p> <p>If you use this dataset, please do cite the following papers:</p> <p>Bonali et al., How Academics and the Public Experienced Immersive Virtual Reality for Geo-education. Geosciences.</p> <p>Tibaldi, A.; Bonali, F.L.; Vitello, F.; Delage, E.; Nomikou, P.; Antoniou, V.; Becciani, U.; Van Wyk de Vries, B.; Krokos, M.; Whitworth, M. Real world–based immersive Virtual Reality for research, teaching and communication in volcanology. Bull. Volcanol. 2020, 82, 1–12.</p> <p> </p> <p> </p> <p> </p>
Towards Collaborative Immersive Qualitative Analysis
<p>Figures for a published conference article in the 15th International Conference on Computer Supported Collaborative Learning, June 2022.</p> <ul> <li>Figure 1 - Screenshot of a CAVA360VR session R1 (left) and R2 (right)</li> <li>Figure 2 - Aerial view of participants and camera posi</li> <li>Figure 3 - Student group collaboration represented by a comic transcript</li> <li>Figure 4 - Bringing up an additional camera view to accomplish an alternative viewing</li> <li>Figure 5 - Drawing as a way of highlighting and creating shared awareness</li> </ul>
Augmented Objects as Portals into Virtual Worlds: Using Audio to Create Immersive Experiences in Extended Realities - UMBRELLA AUDIO SPATIALIZATION DEMO
<p><strong>Technical demonstration</strong></p> <p>The results of the projection mapping system in the project are clear from the <a href="https://blog.zhdk.ch/immersivearts/dreaming-of-time-and-space/">main documentation video</a>; however, the impact of the spatial audio system in particular, is best experienced from directly underneath the umbrellas, where one can best appreciate the various levels of mixed reality. Unfortunately, it is difficult to document these effects within the artistic context of the project, and as such, we include a brief set of examples to better demonstrate the 6 degree of freedom sound spatialization capabilities of the umbrella system.</p> <p><em><strong>NOTE:</strong></em> The audio in the following examples is recorded from a fixed perspective (initially underneath the umbrella) and rendered binaurally. Unfortunately, the ambisonic microphone used does not capture directionality very well when the source (in this case, the umbrella speakers) is less than ~1 meter away, and in retrospect, a single channel of pink noise was not a wise choice as a source material, as it appears to cause additional phasing issues. Additionally, the effectiveness of binaural audio varies from listener to listener, so <em>the perceived effect in the video is not as strong as when experienced in person</em>; nonetheless, it is possible to get the basic idea of the spatialization algorithm in action from these examples.</p> <p>PLEASE WEAR HEADPHONES IN ORDER TO EXPERIENCE THE 3D EFFECT.</p> <p>In addition to the view of the entire scene from an outside perspective, several other views of the underlying software are displayed throughout the video, including:</p> <ul> <li> <p>A radar view of the scene (umbrella and sound source) as seen by the space manager software, where the:</p> <ul> <li> <p>Blue circle = umbrella</p> </li> <li> <p>Cyan triangle, yellow square = sound source</p> </li> </ul> </li> <li> <p>A view of elements of the spatialization software running on the umbrella, specifically the:</p> <ul> <li> <p>Relative gain calculations and current output levels of each speaker</p> </li> <li> <p>Results of supporting calculations (e.g. sound location after transformation from the global to local coordinate system, and scaling factors used to attenuate the overall volume of the sound as the distance from the umbrella to the sound changes)</p> </li> </ul> </li> </ul> <p><strong>Demo #1</strong></p> <p>Stationary umbrella with a moving virtual sound source (anchored to a rigid body)</p> <p><strong>Demo #2</strong></p> <p>Rotating umbrella with a stationary sound source (anchored to a rigid body)</p> <p><strong>Demo #3</strong></p> <p>Moving umbrella with a fixed sound source (anchored to a rigid body)</p> <p><strong>Demo #4</strong></p> <p>Moving umbrella with a fixed sound source (anchored to a virtual point in space, located above the microphone); as the umbrella approaches the source, the sound first fades into the room, then collapses into the umbrella, as show in Figure 7 ("Fading between umbrella and room with distance") in the main paper</p>
Text-fig. 4. Paramblypterus vratislaviensis (AGASSIZ, 1833). Locality Olivětín. Scale bars 5 mm. a, b: photograph and drawing of the skull. Photograph immersed in ethyl alcohol, NM-M 2461; c, d: photograph and drawing of the skull. Photograph immersed in ethyl alcohol, NM-M 900. Abbreviations: Dhy – dermohyal, Dpt – dermopterotic, Dsph – dermosphenotic, Ext – extrascapular, Fr – frontal, Ios – infraorbital superior, Ju – jugal, La – lacrymal, Md – mandible, Mx – maxilla, Na – nasal, Na+So – nasal coalesces with the supraorbital anterior, Op – operculum, Otol – otolith, Pa – parietal, Pop – preoperculum, Pt – posttemporal, Ptr – postrostral, Scl – supracleithrum, soc – supraorbital canal, sr – sclerotic ring. in Actinopterygians Of The Broumov Formation (Permian) In The Czech Part Of The Intra-Sudetic Basin (The Czech Republic)
Text-fig. 4. Paramblypterus vratislaviensis (AGASSIZ, 1833). Locality Olivětín. Scale bars 5 mm. a, b: photograph and drawing of the skull. Photograph immersed in ethyl alcohol, NM-M 2461; c, d: photograph and drawing of the skull. Photograph immersed in ethyl alcohol, NM-M 900. Abbreviations: Dhy – dermohyal, Dpt – dermopterotic, Dsph – dermosphenotic, Ext – extrascapular, Fr – frontal, Ios – infraorbital superior, Ju – jugal, La – lacrymal, Md – mandible, Mx – maxilla, Na – nasal, Na+So – nasal coalesces with the supraorbital anterior, Op – operculum, Otol – otolith, Pa – parietal, Pop – preoperculum, Pt – posttemporal, Ptr – postrostral, Scl – supracleithrum, soc – supraorbital canal, sr – sclerotic ring.
Video material for: "Immersive audio inside the Greek-Roman theatre of Tyndaris: comparison between past, current and future conditions"
<p>The two folders contain 24 spherical videos with 3OA audio used for the subjective listening tests described in the paper:<br> Lavagna L, Shtrepi L, Farina A, Bevilacqua A, Astolfi A. <em>Immersive audio inside the Greek-Roman theatre of Tyndaris: comparison between past, current and future conditions</em> In: Proceedings of the 24th International Congress on Acoustics. Gyeongju; 2022.<br> <br> The listening test, structured as an AB comparison, were presented inside the virtual reality environment using a Head Mounted Display (HMD), specifically a Meta Quest 2, and open headphones (Sennheiser HD 650).<br> <br> </p>
Dataset: Immersion Corporation (IMMR) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
FIGURE 3. A. Low immersion conditions used a handheld smartphone. B. High immersion conditions used a in Designing scientifically-grounded paleoart for augmented reality at La Brea Tar Pits
FIGURE 3. A. Low immersion conditions used a handheld smartphone. B. High immersion conditions used a smartphone inserted into an inexpensive headset. C. To provide binocular vision in the headset, the smartphone screen is split into two smaller images, greatly reducing available screen space and resolution.
ESMA-3D Immersive Soundscape Recordings
<p>ESMA3D (Equal Segment Microphone Array 3D) is a 3D mic array technique for 360° recording developed by Hyunkook Lee of the APL. It consists of 8 microphones arranged in a horizontally spaced, vertically coincident fashion. This provides a very good spaciousness and stable/accurate horizontal and vertical imaging as well as a realistic impression of being there and strong immersion. The main layer (mainly responsible for capture sound sources) is a 50cm x 50cm square of four cardioid microphones spaced with a 90° subtended angle between each pair of mics. The upper layer uses 4 supercardioid mics facing upwards for capturing ambience and elevated sources like birds. The lower and upper layers are coincident (0 spacing, but with a subtended angle of 90 to 120° to have enough level difference between the layers for stable vertical localisation). This design is based on our previous findings showing that vertical mic spacing has little or no contribution to spatial impression in 3D recording. The Schoeps ORTF3D is a brother/sister mic array sharing the same concept - horizontal spacing/vertical coincidence.</p> <p>The reproduction of ESMA3D requires the 8-channel Cube speaker array or 9.1 Dolby Atmos or Auro-3D setup (without the centre and sub), or it can be also binaurally or/and Ambisonically rendered, which still preserves a good quality if used with a good quality decoder, e.g. IEM plugin suite or Aalto SPARTA suite.</p> <p>More details about the array design and listening test results can be found in our AES papers below.</p> <p><a href="http://www.aes.org/e-lib/browse.cfm?elib=19883&fbclid=IwAR26HtDS31P_QHphsMBDFnqDnbJ51x0rFLX2p5syM1hbvVibXZYOdncaMhQ">http://www.aes.org/e-lib/browse.cfm?elib=19883</a></p> <p><a href="https://l.facebook.com/l.php?u=http%3A%2F%2Fwww.aes.org%2Fe-lib%2Fbrowse.cfm%3Felib%3D19401%26fbclid%3DIwAR3jTsNIKKNzQcOueQxKz9UN6nWMUU2EO-A2JSZj4SPKnYBdc9zKSAe_ccU&h=AT0Cbs9tBV7yK9oP1HZSpvyZg_6fuMIDFzQ28eMGdyk-ZWvvLFNFbSIVhs2DACkEdpkIKViisoc0sTfdh2rvOqMG00DaOP4oUOtI5k0gXwleexBnieOE5kqT6es9_4z4FFtXtUFUNMXQVdr2HpsOKCc6S0H2x0KxwTh-s6mrlS14X52JaMj7WkFY1zwyCgpT40fUVueMSJ4mB9kMPjlj-879w3EVKqvsB-Cl8OMT9ct2_k_5A0pbHd77swb6JDSNskcXFEKdyDQ9pfEbcDtFx72CY3aTsj_yv6vYxcSm5BPxObP8EYpfcAyoFcln1O0WnYUYX6uzMRTGd3OU-_YQvWHuDQqlORQIWpAF4BB9QnX7rxfR3Rm_kIfO1QIgjqgcPDJo2nKCjd8gP2KG7Ac4ufXHC8a9BcC1S7WrV91f_pIHWzqj11OB8pbeOeGjuY5Y6jfRY-LAyW3eFGrUMgxd8UUbnFBwDpSIpZRsx9YyKTpNs983FXWsqr2XsJ1KavjFc-JQ05k8MXGyH5NLuihYqJxth1GQw_W9xcdtWBFmJtf8uQpnpF-8wbMozclJuqQoA-rxPCONOZvwHQUsAgJowyOoDUEDpUVe0Sjkww14KneRo9NVu2CkYTYwVgZUTplRBRi2wySV">http://www.aes.org/e-lib/browse.cfm?elib=19401</a></p> <p><a href="https://l.facebook.com/l.php?u=http%3A%2F%2Fwww.aes.org%2Fe-lib%2Fbrowse.cfm%3Felib%3D17560%26fbclid%3DIwAR2GrKGsTPT2gJsBu7vkWSnLqh5mq0cU1lRXeE5aCsBpb71A25mV6JIP8Ew&h=AT1YZ64xnlawwJUc7Mcmu00BnfpfaBvjr6HrvNhFQgDBHyq5xszwHe5_VhQK3i_EXjF4B4kgukWHxlCRNjL3VrQH0ry9XMPLmaGiqByTAfsM9GpGgGHvyVnSXVr3-zfHUXZe-ZM6Hb0kHV8y2ioAXaYKiITNCi_XySMmK7qS4FCoAKlHlSMeGzrsPiRoIz4NngSiNkBx0cQCZViHzhwfGB9RNnZYaXQ3vRr2t5biOljgRrKFLPXrgp6CDLvxxtUNerovi7aK0FEHPFow5GUYCPtVhA5eUK0pVES5iy7H34pBv0GvHHvmvR9VSfaS1F1j8VaXqT_9DP5NyiWo8Ap4Lpj6cZqIi0YLH1UP7nAy6LNoW11bxH1fbuugC__jxDG-j6Un_dr_d_m2CY35avEaili6yjNTbgm9u5Wqi1JSXX5fdskdopCAIpLwrgC0pPcXYktG6Q1Ayeb5VX0qlOYtRwbGyuucRrIvJMLB9aH2iHSTHRbCS7fcV0WemP6UQCzHzx6tJ03v9mp42QBbnZ_J03Sr7heeoHEvO7stMyirKMb5e5k5q1RwEevqN_-h75vRm5SzRuhytSINldyDABM6r9vfizp252hQ4fDKcM6dyVT6Jh3gD4F7DqTZ7E2-gsUNaj_hFklV">http://www.aes.org/e-lib/browse.cfm?elib=17560</a></p> <p><a href="https://l.facebook.com/l.php?u=http%3A%2F%2Fwww.aes.org%2Fe-lib%2Fbrowse.cfm%3Felib%3D20392%26fbclid%3DIwAR1QEGE8Qq7okwveKMDBNCKVy26ywNJGsbZSVArcg1Bve8nzgB8QH0dYsNE&h=AT3gags5AuxycQ_h8BEzuFaae9wnEkp1r8nXRgdnzVSQlRd0uvcVhqtNcg_J-Swwag5EroiqIEDp-tQgWcRmyTBkAvPOKJ-a9V78ao1ebKW9tUKdp5MGe1y9gK2scHHDptZvPtbxBqS_3vsyhX-9JrriqHyCTzYhgeqp3HfQeAIKNe80AYnXLi1g0Q9TGkyeeChY5ZApLuRWYAwtypWgVMMB5TE7j9RKY1V0Pq7i1-aOV98LwDfFcr3W4bm2GPy8NXNTD-DSv8b61Ez0KCwGRTwMDzwlDE9gSUL5o9CqedzXS4dySoFP4qXrFei3vB33zlrI5uYGzro6ncISIYqnk1ugzHpy4lza-vcHETsa_RNNDrYP_2MenN7QALbaZFhy3ORzGZC0Du98NZ5ycvmOgmv4ChnHhDUzDOnT-B0KfKEn9xn3cOwE_eC28OxxRd9z38kPDyFlZRDc1Asu-9ERNIeYt1npeIulLsr-V8QZApe6BYLHROhYvSjmdiUqVP9aeyem4Mp7XOdo5zjZvfmcpXY0n5y1wsdnWy9N-l0WcSEJkpvEpgApdOnACwNhrv21eIciLwF1xgbb5xTAgeSmGa14mNNxGFwV2PDb6ouF30QtrIrIl-Qv8da92EARBI100LkZahfLGFTXPXo">http://www.aes.org/e-lib/browse.cfm?elib=20392</a></p>
Towards personalized immersive virtual reality neurorehabilitation: A human-centered design
<p>The dataset - of the journal article "Towards personalized immersive virtual reality neurorehabilitation: A human-centered design<strong></strong>" - consists of transcripts data of semi-structured (per participant) and of a participatory design workshop (per group). It also contains responses of twenty-four participants to an online questionnaire, and .xlsx files showing the analysis of the transcripts. </p> <p>This repository also includes the Unity project of an immersive virtual environment - a replica of a training room of a Dutch Rehabilitation center - six videos of different versions of the same virtual environment, and two videos of participants exploring the virtual environment, demonstrating real-time changes made by VR developers based on participant feedback.</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.