DaRUS (University of Stuttgart)
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2037 research outputs found
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Software License Ontology
No full textOntology defining 39 Open Source Software Licenses with their license type (Copyleft. Permissive or Public Domain), their conditions (hasCondition), limitations (hasLimitation), permissions (hasPermission) and recommended use (isRecommendedFor).
In addition, there are compatibility relations defined between license types (isBackwardCompatibleWith, isForwardCompatibleWith) and software licenses (isExplicitelyCompatibleWith, isNotCompatibleWith) to express exceptions of the type based compatibility.</p
Replication Scripts for: "Generating Quantum Reservoir State Representations with Random Matrices"
No full textThe scripts provided here are for reproducing the results of "Generating Quantum Reservoir State Representations with Random Matrices" (https://doi.org/10.48550/arXiv.2404.07278). See the README.md file for details and instructions
Replication Data for: "Modeling Load-, Velocity-, and Temperature-Dependent Transmission Errors of Cycloidal Drives for Industrial Robots Using Fourier Series"
No full textThis dataset contains all identification and validation data used in the conference paper "Modeling Load-, Velocity-, and Temperature-Dependent Transmission Errors of Cycloidal Drives for Industrial Robots Using Fourier Series".
The experimental data was recorded using an experimental setup to identify the transmission error of cycloidal drives as described in the paper.
The data is divided into the two folders, "identification" and "validation" containing one file per measurement. The file names contain the parameter combination of load torque
tau_load in N m, input-side velocity theta_dot in rad/s and lubricant temperature T in °C. Each measurement file contains a table with the input-side position theta in rad in the first column and the transmission error theta_TE in rad in the second column.
The MATLAB script "plot_figures.m" can be used to plot the position domain data from the figures 3 to 6 in the publication.
The function "read_data.m" is applied to import all measurement data into two MATLAB structure arrays "identification" and "validation"
Code for using and training spray segmentation models
No full textThis dataset contains the necessary code for using our spray segmentation model used in the paper, ML-based semantic segmentation for quantitative spray atomization description. See README for more information
Replication Data for: Origin of Stereoselectivity in Ring Opening Metathesis Polymerization with Cationic Molybdenum Imido Alkylidene CAAC Complexes
No full textThis dataset includes the NMR (1H, 19F and 13C) of the novel catalysts used in this article, the single crystal X-ray structure of a catalyst, and the proton NMR of the polymers
Data for: Machine learning potentials for hydrogen absorption in TiCr2 Laves phases
No full textThis dataset supports the development and validation of machine learning interatomic potentials (MLIPs) for modeling hydrogen absorption in C14 (hexagonal) and C15 (cubic) TiCr₂-based Laves phases. It includes density functional theory (DFT) calculations, fitted moment tensor potentials (Level 16), and basin-hopping Monte Carlo (BHMC)-sampled structures across a range of hydrogen concentrations and configurations. The data is organized into several directories: database/ contains DFT-calculated energies, forces, and stresses for training (Training_db/) and independent test configurations (Test_db/); dilute_H_configurations/ provides low-concentration hydrogen structures in both C14 and C15 phases, featuring face-connected (1D) and edge-connected (2D) interstitial arrangements computed with DFT; MC_structures/ includes minimum-energy hydrogenated structures from BHMC simulations using the trained MLIPs, along with relaxed DFT configurations, 108-atom C14 structures excluded from training, and the structures from Makarova; and trained_MTPs/ contains the final fitted MLIPs for both C14 (C14.mtp) and C15 (C15.mtp) phases. The dataset captures key aspects of hydrogen behavior in Laves phases, such as interstitial site occupation, hydrogen-hydrogen interactions, and the predictive performance of the force fields, and is fully referenced in the accompanying manuscript and supplementary materials
Generalized DeepONets for Viscosity Prediction Using Learned Entropy Scaling References
No full textData-driven approaches used to predict thermophysical properties benefit from physical constraints because the extrapolation behavior can be improved and the amount of training data be reduced. In the present work, the well-established entropy scaling approach is incorporated into a neural network architecture to predict the shear viscosity of a diverse set of pure fluids over a large temperature and pressure range. Instead of imposing a particular form of the reference entropy and reference shear viscosity, these properties are learned. The resulting architecture can be interpreted as two linked DeepONets with generalization capabilities
Replication Data for: "Efficient detection of statistical RF fields with a quantum sensor"
No full textCSV data sets to reproduce all plots in the main paper. The datasets are either 1D plots with the x-values in the first column and all plotted y-curves in the following columns or alternating x_i,y_i columns if the x-values are not consistent over all traces. Information on how the data was acquired and what it actually shows can be found in the related manuscript
Reuse Compendium
No full textThis dataset contains a list of 348 references relating to reuse in architecture. It covers historical and contemporary reuse projects and examples in architecture, recent research projects using digital technologies for reuse or developing new building systems, art and design projects, as well as context and statisitcs related websites and a few companies. The dataset includes links to sources and catagorizes the references into three fields; focus (architecture, art & design, research, statistics, granular), area (historical, contemporary, conceptual, statistical, contextual, building technology), and material (wood, concrete, rubble, metal, clay, earth, mixed, bricks, stone, spolia)
BayesValidRox 2.0.0
No full textBayesValidRox is an open-source python package that provides methods for surrogate modeling, Bayesian inference and model comparison. Release 2.0.0 improves the modularity and uniformity of the package and introduces template classes for surrogate models and methods for generating posterior samples.(2025-02-05