TU Wien Research Data
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D Reconstruction Model of the Former Synagogue in the Turnergasse 22, Vienna (1871/72 | Architect: Carl König)
No full text<p>This record contains model data originally created in the framework of ongoing research work.</p><p>Facts: Synagoge of the Israelitische Kultusgemeinde Jewish Community Vienna | Erected 1871/72; extension: 1923 (addition of a winter prayer room) | Architect: Carl König | Capacity: seating for 333 women and 496 men | Appearance: neo-Renaissance style building; interior with »Pompeian« decoration</p><p>See also:</p><p>* City Guide --> https://www.lit-verlag.de/isbn/978-3-643-90170-5</p><p> </p><p>The data set includes</p><p>- Modelling software: ArchiCAD *.PLA - Archive</p><p>- Rendering Software: ArtLantis *.ATLA - Archive</p><p>- Panoramic representation: *.HTML & *.PNO</p><p> </p><p> </p>
3D pointcloud model Karlskirche, Vienna Austria
No full text<p>pointcloud model [e57] of the interior and exterior of Karlskirche, Vienna Austria;</p>
<p>please contact <strong>[email protected]</strong> for access</p><p>captured with terrestrial laserscanner Riegl VZ-400i with Sony ILCE-7RMIV planted on top for RGB coloring of scans; <br>positioning with GNSS antenna using EPOSA correction data in RTK mode;</p><p>at time of processing dataset with highest GNSS accuracy and therefore reference for geopositioning of all Karlskirche models; </p><p>coordinate system WGS84_EPSG 4978;</p>
Supplementary data for: "Unconventional superconductivity without doping: infinite-layer nickelates under pressure"
No full text<h2>Supplementary data for "Unconventional superconductivity without doping: infinite-layer nickelates under pressure"</h2><h3>Context and methodology</h3><ul><li>This repository contains supplementary data from the associated research work. It serves the purpose of aiding interested and informed readers to reproduce the results of the associated paper and verify their validity.</li><li>The research area in which this dataset is created is that of condensed matter, strongly correlated electron systems, superconductivity</li><li>This dataset was created manually by collecting and ordering the relevant data. The README file was written by Simone Di Cataldo</li></ul><h3>Technical details</h3><ul><li>The dataset contains a README file which explains in detail the content of the dataset itself. The general structure is the following: the dataset is divided into subfolders for the general topic (DFT calculations, DMFT calculations for 1 band, DMFT calculations for 10 bands). Each folder then contains further subfolders related to physical quantities (i.e. different pressures, different dopings, different temperatures). Consult the README file for detailed explanation of the naming conventions.</li><li>The data contained is of mixed type. Most of it are input and output files of softwares that can be read directly with text editors. In addition, hdf5 files from DMFT calculations containing Green's functions, self-energies and two-particle vertexes require dedicated software, e.g. python code with h5py.</li></ul>
Sentinel-1 Flood Maps Using A Topographic Index As Prior In Bayesian Inference
No full text<h2>Background</h2><p>The TUWien flood mapping algorithm is a Sentinel-1 based workflow using Bayes Inference at the pixel level. However, priors in its formulation have, so far, been reduced to non-informative priors (50%-50% probability). We proposed and tested a Height Above Nearest Drainage (HAND) index based prior probability function compared to the baseline non-informed case. We have conducted experiments on six study sites for both flooded and no-flood scenarios. Full description and discussion is found in the paper: <strong>Improving Sentinel-1 Flood Maps Using A Topographic Index As Prior In Bayesian Inference.</strong></p><h3>Methodology</h3><ul><li>We propose an exponential function defined by a midpoint and steepness parameter for the HAND prior function.</li><li>We determine optimal parameterization for the proposed function by iterating the midpoint (5 - 40) values and steepness (5 - 40).</li><li>Each flood map is compared with reference <a href="https://emergency.copernicus.eu/mapping/list-of-activations-rapid">CEMS</a> Rapid Mapping reference dataset-- generating validation/confusion maps.</li><li>Flood maps were generated using Bayes Inference based SAR Flood mapping algorithm implemented in python using <a href="https://github.com/TUW-GEO/yeoda">Yeoda</a> software package.</li></ul><h3>Technical details</h3><ul><li>Datasets are stored in GeoTiff format using LZW Compression</li><li>Files are compressed per dataset/map product</li><li>Files are orgnized and tiled following T3 <a href="https://github.com/TUW-GEO/Equi7Grid">Equi7Grid</a> tilling system at 20m x 20m resolution.<ul><li>Folder structure: dataset/map product>(continental)subgrid>tile>files.</li></ul></li><li>Files are named follows the <a href="https://github.com/TUW-GEO/geopathfinder/blob/master/src/geopathfinder/naming_conventions/yeoda_naming.py">Yeoda</a> filenaming convention.</li></ul><h3>Datasets:</h3><ul><li>Flood - flood maps generated using different parameterization of HAND prior function and non-informed priors.</li><li>No Flood - maps generated using different parameterization of HAND prior function and non-informed priors at no flood scenarios.</li><li>Validation - confusion maps generated from the difference of the Flood maps generated and rasterized <a href="https://emergency.copernicus.eu/mapping/list-of-activations-rapid">CEMS</a> Rapid Mapping reference dataset.</li><li>HAND - corresponding Height Above Nearest Drainage dataset used in the flood map generation.</li></ul>
CAD files for 3D-printed well plates
No full text<p>Dataset contains CAD-files in stl format for 3D-printing of well plates with 6 inserts</p>
Hierarchically Micro- and Mesoporous Zeolitic Imidazolate Frameworks Through Selective Ligand Removal
No full text<h3>Context and Methodology </h3>
<p>This dataset contains the underlying experimental data supporting the results reported in the research article published in DOI: 10.1002/smll.202307981. </p>
<p>The data provided here covers the structural characterization, thermal stability, and adsorption performance of the reported materials. For detailed discussions on the synthesis protocols, experimental conditions, and comprehensive interpretation of these results, please refer to the original publication and its Supplementary Information.</p>
<h3>Technical Details </h3>
<h3>1. Dataset Structure and Naming Convention: </h3>
<p>Unlike datasets organized by manuscript figure numbers, this dataset is organized by characterization technique. Each file corresponds to a specific analytical method and contains data for multiple samples.</p>
<ul>
<li>File Format: All data is provided in .xlsx format for broad accessibility.</li>
<li>Sample Identification: Inside each .xlsx file, specific datasets are clearly labeled with the corresponding Sample Names/Numbers as used in the manuscript.</li>
</ul>
<h3>2. Description of Files: The dataset consists of the following files:</h3>
<ul>
<li>XRD.xlsx: Powder X-ray Diffraction (PXRD) patterns used to analyze crystal structures.</li>
<li>IR.xlsx: Infrared Spectroscopy (IR) data showing functional group analysis.</li>
<li>NMR.xlsx: Nuclear Magnetic Resonance spectra data.</li>
<li>TGA.xlsx: Thermogravimetric Analysis data illustrating thermal stability and decomposition profiles.</li>
<li>Physisorption.xlsx: Nitrogen adsorption-desorption isotherms (pore size distribution data).</li>
<li>Methylene blue.xlsx: Performance data representing the adsorption capacity of the samples towards Methylene Blue (MB).</li>
</ul>
<h3>3. Software Requirements:</h3>
<p>No proprietary instrument software is required to view this data. Any spreadsheet software (e.g., Microsoft Excel, LibreOffice Calc) can be used to open and process the .xlsx files.</p>
<p><strong>Further Details</strong> Users are kindly requested to cite the original article when reusing any part of this dataset.</p>
Verification of a neural network controller encoded on a PLC program
No full text<p>Different methods to verify a neural network controller encoded on a PLC program are presented in these files. Each of the main folders contains a different approach.</p><ul><li><i>PLCverif_CBMC/PLCverifProject</i> contains the original PLC code.</li><li><i>PLCverif_CBMC</i> has the C code that is executed by CBMC to verify all the properties.</li><li><i>nnenum </i>contains the code used to verify different properties using the neural network verifier nnenum.</li><li><i>testing </i>has the Jupyter notebook that was used to test all the combinations of the inputs and check if the properties were satisfied.</li><li><i>Z3 </i>holds the Jupyter notebook that uses the Python API of Z3 to verify different properties.</li><li>The <i>README </i>file contains some instructions to run the different files.</li></ul>
Excel2UML prototype
No full text<p>Excel2UML is a tool for automated translation of EXCEL data structure requirements into a valid UML class diagram, which can be subsequently displayed and further edited in Modelio (to be found at https://github.com/ModelioOpenSource/Modelio).</p><p>This archive contains a folder that can be unpacked anywhere on a Windows 10 machine. A double click on the executable file, ExcelToEcore.exe, starts the tool. A prerequisite for the full functionality is Modelio, but it is not required. The generated XMI files can be viewed in any other UML-capable software. </p>
RAAV - Quantitative analysis of transport performance and agency costs for five scenarios of the implementation of automated vehicles in public transport.
No full text<h2>Dataset description</h2><p>As a supplement to the paper <strong>"What can be done with today's budget and demand? - Scenarios of rural public transport automation in Mühlwald (South Tyrol)"</strong>, which was published as part of the project <strong>"RAAV - Rural Accessibility and Automated Vehicles"</strong> between the TU Vienna (Austria) and the EURAC institute (Bolzano, Italy), this file serves to summarise the derivation of the in the paper presented results in a comprehensible manner and to make them publicly available.</p><p>The data tables are additional content allowing to illustrate the assumptions regarding the design and structure of the formulated automated vehicle variants and scenarios for public transit systems. They contain agency cost assumptions and scenario performance indicators leading to agency cost estimations. The analysis was done for two seperate municipalities, Sooß in Austria and Mühlwald in South Tyrol, Italy. Both locations underlie different topographic, economic and infrastructural framework conditions which influence transport performance as well as agency costs.</p><p>Additional images are provided which allow a conceptual understanding of the automated driving system variants in their core functional idea.</p><h3>Context and methodology</h3><p>The dataset is supposed to give a more detailed insight into our assumptions and results which are discussed in the paper <strong>"What can be done with today's budget and demand? - Scenarios of rural public transport automation in Mühlwald (South Tyrol)" (DOI not yet available).</strong></p><p>To be as transparent as possible the data is provided in the Microsoft Excel format with all cell references. By doing this, we ensure that the data can also be used and adapted for other research.</p><h3>Technical details</h3><p>The ZIP-folder contains two sub folders, one regarding Mühlwald and one regarding Sooß, with the same content. The primary file is a Microsoft Excel file containing all the data, assumptions, calculations and results. In addition, a JPEG-file contains a visual representation of the analysed automated vehicle variants.</p><p>Other than Microsoft Excel, there is no special software required to open, investigate and manipulate the data.</p><p>To get a complete understanding of the concept and incorporation of the data used and the assumptions made as well as the meaning of some abbreviations, it is highly recommended to also consider the investigation of the paper <strong>"What can be done with today's budget and demand? - Scenarios of rural public transport automation in Mühlwald (South Tyrol)" (DOI not yet available).</strong></p>
3D Reconstruction Model of the Former Synagogue in the Leopoldsgasse 29, Vienna (1892/93 | Architect: Wilhelm Stiassny)
No full text<p>This record contains model data originally created in the framework of ongoing research work.</p><p>Facts: Association synagogue of the Association Beth Israel (House of Israel) according to the Polish-Jewish rite | built 1892/93 | Architect: Wilhelm Stiassny | Capacity: seating for 317 women and 450 men | Appearance: triple-aisled complex with galleries, use of Moorish motifs, the most striking element is the central onion-shaped dome</p><p>See also:</p><p>* City Guide --> https://www.lit-verlag.de/isbn/978-3-643-90170-5</p><p> </p><p>The data set includes</p><p>- Modelling software: ArchiCAD *.PLA - Archive</p><p>- Rendering Software: ArtLantis *.ATLA - Archive</p><p>- Panoramic representation: *.HTML & *.PNO</p><p> </p><p> </p>