231 to 240 of 1,830 Results
Sep 16, 2024 - SFB-TRR 161 A01 "Uncertainty Quantification and Analysis in Visual Computing"
Evers, Marina; Weiskopf, Daniel, 2024, "Supplementary Material for Uncertainty-aware Spectral Visualization", https://doi.org/10.18419/DARUS-4447, DaRUS, V1
In this supplemental material, we provide supplemental information (PDF document with derivations of the results presented in the paper and two additional use cases) and the supplementary video for uncertainty-aware spectral analysis. We model an uncertain time series as a multivariate Gaussian process. We propagate the uncertainty and explicitly c... |
Sep 13, 2024 - Institute of Aerodynamics and Gas Dynamics
Appelbaum, Jason; Kloker, Markus J.; Wenzel, Christoph, 2024, "Data for: A systematic DNS approach to isolate wall-curvature effects in spatially developing boundary layers", https://doi.org/10.18419/DARUS-4345, DaRUS, V3
Spanwise [z] and temporal [t] averaged turbulent fields of four direct numerical simulations (DNS) of a turbulent boundary layer (TBL) calculated using the code NS3D. Datasets ZPG-C & ZPG-F both have approximately zero pressure gradient along the wall boundary, whereas PG-C & PG-F have a nearly identical non-zero pressure gradient. Both ZPG-C and P... |
Sep 13, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Datasets: 6 Heat Pumps, Simulation - Raw + Prepared", https://doi.org/10.18419/DARUS-4473, DaRUS, V1
This dataset serves as training data for modeling the temperature field emanating from several open loop groundwater heat pumps (six heat pumps, randomly placed). It is simulated with Pflotran and stored in h5 format. The two datasets contain 1000 and additional 4000 data points. Each data point consists of one simulation run until a near steady st... |
Sep 13, 2024 - Projects without PN Affiliation
Hermann, Sibylle, 2024, "Database for: Documenting Research in Simulation Science to Enhance Understanding for Reusability", https://doi.org/10.18419/DARUS-4142, DaRUS, V1, UNF:6:mhHYSODfUq/dE3D6o/V/ww== [fileUNF]
Replication Data for an analysis of research articles from computational mechanics, all using the software Pasimodo https://www.itm.uni-stuttgart.de/en/software/pasimodo/ Categories for analysing the articles: To understand the context of the citation, we classified the citations into referring and reuse. Where referring is meant to be, when a cita... |
Sep 10, 2024 - Surrogate models for groundwater flow simulations
Pelzer, Julia, 2024, "Raw Simulation Datasets for Extending Heat Plumes", https://doi.org/10.18419/DARUS-4133, DaRUS, V2
These data sets serve as training and testing data for modelling the extension of temperature field emanating from one groundwater heat pump. There are simulated with Pflotran and saved in h5 format. The data set for training is called "dataset_medium_k_3e-10_1000dp". It contains 999 simulation runs, each simulated until a near steady state is reac... |
Sep 6, 2024 - Institute of Applied Analysis and Numerical Simulation
Bordignon, Andrea; Cances, Eric; Dusson, Geneviève; Kemlin, Gaspard; Lainez Reyes, Rafael; Stamm, Benjamin, 2024, "Replication Data for: Fully guaranteed and computable error bounds on the energy for periodic Kohn-Sham equations with convex density functionals", https://doi.org/10.18419/DARUS-4469, DaRUS, V1
Data for reproducibility of the numerical simulations of the research paper "Fully guaranteed and computable error bounds on the energy for periodic Kohn-Sham equations with convex density functionals". The .zip file contains everything needed to generate the plots shown in the paper, as well as the code to run your own simulations with the bounds... |
Reichmann, Luca; Hägele, David; Weiskopf, Daniel, 2024, "Supplemental Material for Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions", https://doi.org/10.18419/DARUS-4441, DaRUS, V1, UNF:6:WoQ4MNffz92VcvZ/qCGL5w== [fileUNF]
This dataset contains the supplemental material for "Out-of-Core Dimensionality Reduction for Large Data via Out-of-Sample Extensions". The contents and usage of this dataset are described in the README.md files. |
Aug 27, 2024 - PN 7-6
Kneifl, Jonas; Rettberg, Johannes; Herb, Julius, 2024, "ApHIN - Autoencoder-based port-Hamiltonian Identification Networks (Software Package)", https://doi.org/10.18419/DARUS-4446, DaRUS, V1
Software package for data-driven identification of latent port-Hamiltonian systems. Abstract Conventional physics-based modeling techniques involve high effort, e.g.~time and expert knowledge, while data-driven methods often lack interpretability, structure, and sometimes reliability. To mitigate this, we present a data-driven system identification... |
Aug 27, 2024 - ESPARGOS WiFi Channel State Information Measurements
Euchner, Florian; ten Brink, Stephan, 2024, "CSI Dataset espargos-0002: Larger combined antenna array, indoor lab room with metal wall, LoS and NLoS areas", https://doi.org/10.18419/DARUS-4456, DaRUS, V1
Dataset containing WiFi channel state information (CSI) alongside ground truth data (position tags, timestamps) measured with ESPARGOS antenna arrays. Measurement parameters and machine-readable file format descriptions are provided in a JSON file (spec.json). Four ESPARGOS arrays are combined into one large array with 8 by 4 antennas. A metal wall... |
Aug 26, 2024 - EXC IntCDC Research Project 10 'Co-Design from Architectural, Social and Computational Perspectives'
Öney, Seyda; Abdelaal, Moataz; Kurzhals, Kuno; Betz, Paul; Kropp, Cordula; Weiskopf, Daniel, 2024, "Supplemental Material for: Testing the Test: Observations When Assessing Visualization Literacy of Domain Experts", https://doi.org/10.18419/DARUS-4448, DaRUS, V1, UNF:6:acOzV3rGb0G3gj7FIA/o4w== [fileUNF]
These documents contain supplemental material for the paper "Testing the Test: Observations When Assessing Visualization Literacy of Domain Experts" which was conditionally accepted at the BELIV 2024 Workshop in conjunction with the IEEE VIS 2024 Conference. The CSV file contains the summaries of the important parts of the interview, each assigned... |
