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12 results for “3D Virtual Learning Environments”

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zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 10. Room model generated with Autodesk 123D Catch - the 3D model (screen capture from GLC Player)

<p>Structure from motion was used for rapid modeling of a small room with all its objects. Two files were generated, a Wavefront obj and mtl (corresponding to the texture). The 3D model was post-processed with MeshLab, during which several filters were applied to clean up the model. The mesh model was also connected with the scanned model, by choosing at least 4 connection points. The 2D and 3D results are shown in Figures 9, 10. A post-processing could also be performed using the Autodesk 123D Catch web application.</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 2. The model of the 3D virtual campus - details from the building interior (3D modeling by Marius Hodea)

<p>The processing workflow for 3D modeling and design for a 3DVLE represents a time- consuming stage in the overall pipeline production. One reason is that a range of technologies and tools are typically used. In (Cudworth 2014) a 3-week period is indicated for experienced users to perform the 3D modeling of a virtual space. In our case, a 3-month work was needed for designing a working model of a 3D virtual campus (see Figure 1 and Figure 2 for final results).</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 1. The model of the 3D virtual campus - an outdoor view (3D modeling by Marius Hodea)

<p>The processing workflow for 3D modeling and design for a 3DVLE represents a time- consuming stage in the overall pipeline production. One reason is that a range of technologies and tools are typically used. In (Cudworth 2014) a 3-week period is indicated for experienced users to perform the 3D modeling of a virtual space. In our case, a 3-month work was needed for designing a working model of a 3D virtual campus (see Figure 1 and Figure 2 for final results).</p>

opencc-by-4.0Dec 2017View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 9. Room model generated with Autodesk 123D Catch - the 2D model

<p>Structure from motion was used for rapid modeling of a small room with all its objects. Two files were generated, a Wavefront obj and mtl (corresponding to the texture). The 3D model was post-processed with MeshLab, during which several filters were applied to clean up the model. The mesh model was also connected with the scanned model, by choosing at least 4 connection points. The 2D and 3D results are shown in Figures 9, 10. A post-processing could also be performed using the Autodesk 123D Catch web application.</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 8. The 3D model of the faculty building in a HTML page

<p>The pipeline processing was the following: a) the 3D model from Sketchup was saved as a Collada file; b) this file has been imported in MeshLab (MESHLAB 2017) and converted to VRML97 format (wrl); c) aopt utility was used to convert wrl files to X3D and HTML5 files. The model was visualized in the OpenSim virtual world setting using an external browser (Figure 8).</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 5. Iteration of the 3D modeling of the virtual faculty building (3D modeling by Marius Hodea)

<p>For our research, several iterations and methods were employed for the 3D design of an online campus. &nbsp;Different virtual models of a faculty building (see Figures 4,5) were designed and finally a virtual model of a 3D campus comprising a simplified 3-story faculty building (Figure 6) was created. The objective was the optimization of the 3D model and the demonstration of the desired functionalities. For these purposes two 3D modeling and post-processing software were used, i.e. 3DSMax and Trimble Sketchup. The model of the building resulted in 5962 vertices and 4528 faces. The textures and illumination were applied using OpenSim&rsquo;s in-world tools. Furniture objects (tables, chair, computer monitors) were taken from the Google 3D Warehouse, distributed and shared under Trimble General Model License.</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 12. Diagram of the proposed working methodology

<p>The chart below (Figure 12) summarizes the workflow recommended for the implementation of a prototype of a 3D online campus.</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 11. Online accessible repository of digital data on cultural heritage with X3D models (STARC Web Repository, 2017, © Copyright 2017, STARC, Cyprus Institute. Used with permission)

<p>Prototyping can also include the development of toolkits for automatic content generation simulator, but in the case of an architectural environment, the components are too complex to be automatically generated. Furniture elements or the learning artifacts (i.e. content created by learners) can be converted to be viewed in X3D compatible browsers or included in online galleries (Figure 11). After functional and 3D content prototyping, certain components of the virtual campus can be easily modified and adapted as needed.</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 3. The graphic stack of X3DOM (Havele 2011)

<p>The current release of X3DOM supports native implementations (iOS8, Chrome, and Firefox for Android), with fallback to WebGL API, and partially to X3D/SAI plugins (INSTANTREALITY 2017). X3DOM is above WebGL, OpenGL and DirectX, and subsequently has less complexity (in Figure 3 is shown the graphical stack). Integrated into the HTML DOM, X3DOM allows web programmers to continue their experience, based on known web technologies such as CSS, Java Script, JQuery or Ajax. Standard technologies can streamline a VR or AR application development, by hiding the low-level complex tasks, and allow the access to device sensors and video camera via high-level API functions. X3DOM supports embedded X3D-XML files references using inline nodes, i.e. an X3D- XML file can reference other X3D-XML files and build a hierarchy of assets (X3DOM 2017) which can be loaded in the background with a higher throughput.</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 6. The first implementation of the virtual campus (OpenSim import of the 3D model)

<p>For our research, several iterations and methods were employed for the 3D design of an online campus. &nbsp;Different virtual models of a faculty building (see Figures 4,5) were designed and finally a virtual model of a 3D campus comprising a simplified 3-story faculty building (Figure 6) was created. The objective was the optimization of the 3D model and the demonstration of the desired functionalities. For these purposes two 3D modeling and post-processing software were used, i.e. 3DSMax and Trimble Sketchup. The model of the building resulted in 5962 vertices and 4528 faces. The textures and illumination were applied using OpenSim&rsquo;s in-world tools. Furniture objects (tables, chair, computer monitors) were taken from the Google 3D Warehouse, distributed and shared under Trimble General Model License.</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 7. The HTML source (partial) code, integrating the X3D model

<p>To integrate the model into a web page, a model conversion to X3D format and an X3DOM output under the form of an HTML5 encoded webpage (Figure 7) were needed. Instant Reality distribution provides a command line transcoding tool, named Avalon Optimizer (aopt), that was used to convert a VRML format (wrl extension) of the model to X3D.&nbsp;</p>

opencc-by-4.0Apr 2018View details →
zenodo40/100

Prototyping 3D Virtual Learning Environments with X3D-based Content and Visualization Tools-Figure 4. Iteration of the 3D modeling of the virtual faculty building (3D modeling by Marius Hodea)

<p>For our research, several iterations and methods were employed for the 3D design of an online campus. &nbsp;Different virtual models of a faculty building (see Figures 4,5) were designed and finally a virtual model of a 3D campus comprising a simplified 3-story faculty building (Figure 6) was created. The objective was the optimization of the 3D model and the demonstration of the desired functionalities. For these purposes two 3D modeling and post-processing software were used, i.e. 3DSMax and Trimble Sketchup. The model of the building resulted in 5962 vertices and 4528 faces. The textures and illumination were applied using OpenSim&rsquo;s in-world tools. Furniture objects (tables, chair, computer monitors) were taken from the Google 3D Warehouse, distributed and shared under Trimble General Model License.</p>

opencc-by-4.0Apr 2018View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

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Last verified 2026-04-30Open record

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behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

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electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

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behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

ScienceDex for faculty

Your academic CV and NIH biosketch

Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.