121 to 130 of 183 Results
Mar 5, 2025 - SFB 1333 A1+B2 - Buchmeiser group, IPOC-MSF
Kundu, Koushani; Buchmeiser, Michael, 2025, "Replication Data for: Origin of Stereoselectivity in Ring Opening Metathesis Polymerization with Cationic Molybdenum Imido Alkylidene CAAC Complexes", https://doi.org/10.18419/DARUS-4791, DaRUS, V1
This 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. |
Mar 4, 2025 - D03: Development and realisation of validation benchmarks
Kohlhaas, Rebecca; Morales Oreamuno, Maria Fernanda; Lacheim, Alina, 2025, "BayesValidRox 2.0.0", https://doi.org/10.18419/DARUS-4752, DaRUS, V1
Release 2.0.0 of BayesValidRox. BayesValidRox is an open-source python package that provides methods for surrogate modeling, Bayesian inference and model comparison. (2025-02-05) |
Feb 28, 2025 - Analytic Computing
Fathallah, Nadeen, 2025, "Code for Improving Video Caption Accuracy with LLMs", https://doi.org/10.18419/DARUS-4776, DaRUS, V1
As part of the IKILeUS project at the University of Stuttgart, research was conducted to explore how Large Language Models (LLMs) can enhance the accuracy and contextual relevance of automatic speech recognition (ASR)-generated captions. While ASR tools provide a foundation for accessibility, they often produce grammatical errors, misinterpret homo... |
Feb 28, 2025 - Analytic Computing
Fathallah, Nadeen; Staab, Steffen, 2025, "Code for Caption Crowd (IKILeUS)", https://doi.org/10.18419/DARUS-4775, DaRUS, V1, UNF:6:e9mxpfNAwwwZlt8Uc4I+mQ== [fileUNF]
CaptionCrowd is an interactive platform developed within the IKILeUS project at the University of Stuttgart to improve video caption accuracy for the Deaf and Hard of Hearing (DHH) community. While automatic captions provide some accessibility, they often contain errors in grammar, homophones, and domain-specific terminology, making comprehension c... |
Feb 28, 2025 - Analytic Computing
Fathallah, Nadeen; Staab, Steffen, 2025, "Code for EchoTables (IKILeUS)", https://doi.org/10.18419/DARUS-4774, DaRUS, V1
EchoTables is an innovative accessibility tool developed as part of the IKILeUS project at the University of Stuttgart. It is designed to improve the usability of tabular data for visually impaired users by converting structured tables into concise, auditory-friendly textual summaries. Traditional screen readers navigate tables linearly, which impo... |
Feb 27, 2025 - Spray Segmentation
Jose, Basil; Hampp, Fabian, 2025, "Code for using and training spray segmentation models", https://doi.org/10.18419/DARUS-4739, DaRUS, V1
This 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. |
Feb 26, 2025 - InMotion (EXC)
Frank, Daniel, 2025, "Code for statesim - a python package to simulate dynamical systems from ordinary differential equations.", https://doi.org/10.18419/DARUS-4769, DaRUS, V1, UNF:6:afs/qXtsE2p0ZWIJY23a/A== [fileUNF]
Python package for simulating ordinary differential equations in state space form. See README.md for details. |
Feb 26, 2025 - InMotion (EXC)
Frank, Daniel, 2025, "Damped pendulum for nonlinear system identification - inputs are sampled from a multivariate-normal distribution - synthetically generated", https://doi.org/10.18419/DARUS-4770, DaRUS, V1
Overview This dataset contains input-output data of a damped nonlinear pendulum that is actuated at the mounting point. The data was generated with statesim [1], a python package for simulating linear and nonlinear ODEs, for the system actuated pendulum. The configuration .json files for the corresponding datasets (in-distribution and out-of-distri... |
Feb 26, 2025 - InMotion (EXC)
Frank, Daniel, 2025, "Coupled mass-spring-damper system for nonlinear system identification - actuated with random static inputs - synthetically generated", https://doi.org/10.18419/DARUS-4768, DaRUS, V1
Overview This dataset contains input-output data of a coupled mass-spring-damper system with a nonlinear force profile. The data was generated with statesim [1], a python package for simulating linear and nonlinear ODEs, for the system coupled-msd. The configuration .json files for the corresponding datasets (in-distribution and out-of-distribution... |