1167 research outputs found
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Anwendung Forschungsfabriken – Gewichtung der Anforderungen zur Softwareauswahl
No full textDie vorliegenden Daten umfassen einen Paarvergleich für Softwareanforderungen. Insgesamt sind sechs Expert:innen bzgl. Ihrer Meinung zu der Wichtigkeit der zwölf definierten Anforderungen befragt worden. Die jeweiligen Ergebnisse sind in den Tabellen PV 1 – PV 6 dargestellt. Eine Erläuterung der Anforderungen ist dem Tabellenblatt Anforderungsliste zu entnehmen. Die Zusammenfassung und daraus resultierende abschließende Gewichtung findet sich im Tabellenblatt Gewichtung
Forschungsdaten zu "Ein Beitrag zum dynamischen Verhalten beim Gewindebohren durch die Entwicklung eines analytischen Modells sowie den Einsatz eines sensorischen Werkzeughalters"
No full textThis data set is the research data from the dissertation "Ein Beitrag zum dynamischen Verhalten beim Gewindebohren durch die Entwicklung eines analytischen Modells sowie den Einsatz eines sensorischen Werkzeughalters" by Tugrul Öztürk.
The research data is provided via four TAR-archives:
research_data_dissertation_toeztuerk.tar.00,
research_data_dissertation_toeztuerk.tar.01,
research_data_dissertation_toeztuerk.tar.02,
research_data_dissertation_toeztuerk.tar.03,
To access the research data, all four TAR-archives must be downloaded to a common directory. For unpacking on macOSX or Linux systems one can use following command in shell:
cat research_data_dissertation_toeztuerk.tar.* | tar -xvf -
For unpacking on Windows, one can use WinRAR or 7-ZIP
Publication data analysis for TUDa, RWTH and KIT, 2017-2024, based on OpenAlex
No full textPublication data is queried and retrieved from the OpenAlex catalog of scholarly records, using python. A simple script is used (the original script and data can be found here: https://doi.org/10.48328/tudatalib-1391.2), utilizing the OpenAlex API via the pyAlex library. Retrieved record data is dumped in json format to facilitate recurring or iterative analysis. A basic analysis regarding Open-Access is performed by this same script, list comprehension is used to filter records based on type and Open-Access status / features. Lastly, the analysis results are provided via simple printout. The script can be run as is to provide an analysis of peer-reviewed scientific journal articles published by members of Technical University of Darmstadt (TUDa), RWTH Aachen University (RWTH) and Karlsruhe Institute of Technology (KIT) during 2016-2023. As a basic analysis regarding Open-Access, total number of publications is counted per institution per year, as well as number of Open-Access publications and number of "gold" "Open-Access" publications (i.e. primary location of publication is an Open-Access Journal).
This repository entry provides updated data dump from the years between 2017 and 2024
Dataset of Ballet Jumping Experiment
No full textThe experiment involved thirteen healthy young participants (12 females and one male) with a mean age of 21 ± 8.4 years, height 161 ± 13 cm, and weight 46.4 ± 17.3 kg. Participants were divided into three groups based on age and ballet dancing experience: an amateur group (students with varying levels of ballet expertise), a professional group (professional ballet dancers in a ballet company), and a children's group (children with ballet experience ranging from good to basic).
Participants were selected based on the following criteria: having ballet experience from basic to advanced levels, no lower limb injuries in the past six months, and the ability to perform repeated jumps without excessive fatigue. Participants with musculoskeletal disorders were excluded. The study was approved by the Ethical Committee of TU Darmstadt (EK 47/2021) in accordance with the Declaration of Helsinki, and all participants provided written informed consent before participation.
Initially, participants were instructed to perform three consecutive Sauté en suite jumps using their previously learned technique. They were then given an external focus of attention cue: "Take the whole floor with you." This instruction aimed to direct the dancers' attention toward the external effect of movement, which was expected to enhance performance by increasing jump height and improving body axis stability. After receiving the instruction, participants repeated the three jumps.
Motion tracking was conducted using 36 reflective markers placed on specific anatomical locations, captured by an infrared camera system (Qualisys, 460 Hz, Sweden). Ground reaction force (GRF) and center of pressure (CoP) data were collected for both legs using one Kistler force plate (1 kHz, Switzerland). These data were processed using OpenSim's inverse kinematics and dynamics tools. To calculate rest length and stiffness, the Spring-Loaded Inverted Pendulum (SLIP) model is used. For data analysis, 3 jumps were selected per participant
Capacitance Calculation of Ball Bearings - Data
Get PDFThis dataset contains data gathered for the manuscript "Capacitance Calculation of Ball Bearings—An Open-source Model," which was submitted to Tribology Transactions (Taylor Francis). It comprises 14,490 capacitance measurements for 15 s each. Six different bearing types, each tested in three different specimens under various axial and radial loads, were tested in a full-factor design of experiments. Three speeds and oil temperatures were tested. Details, outcomes, and graphs can be found in the corresponding publication.
The following data are attached:
(1) Overview pdf including the naming convention, details on the retrieved variables, and metadata,
(2) Table with mean values of all experiments,
(3) Raw capacitance and impedance readings of all measurements, and
(4) Averaged capacitance readings for single steel ball bearings.V
Scene-Centric Unsupervised Panoptic Segmentation
No full textUnsupervised panoptic segmentation aims to partition an image into semantically meaningful regions and distinct object instances without training on manually annotated data. In contrast to prior work on unsupervised panoptic scene understanding, we eliminate the need for object-centric training data, enabling the unsupervised understanding of complex scenes. To that end, we present the first unsupervised panoptic method that directly trains on scene-centric imagery. In particular, we propose an approach to obtain high-resolution panoptic pseudo labels on complex scene-centric data combining visual representations, depth, and motion cues. Utilizing both pseudo-label training and a panoptic self-training strategy yields a novel approach that accurately predicts panoptic segmentation of complex scenes without requiring any human annotations. Our approach significantly improves panoptic quality, e.g., surpassing the recent state of the art in unsupervised panoptic segmentation on Cityscapes by 9.4% points in PQ. Acknowledgments: This project was partially supported by the European Research Council (ERC) Advanced Grant SIMULACRON, DFG project CR 250/26-1 "4D-YouTube", and GNI Project ``AICC''. This project has also received funding from the ERC under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 866008). Additionally, this work has further been co-funded by the LOEWE initiative (Hesse, Germany) within the emergenCITY center [LOEWE/1/12/519/03/05.001(0016)/72] and by the State of Hesse through the cluster project ``The Adaptive Mind (TAM)''. Christoph Reich is supported by the Konrad Zuse School of Excellence in Learning and Intelligent Systems (ELIZA) through the DAAD programme Konrad Zuse Schools of Excellence in Artificial Intelligence, sponsored by the Federal Ministry of Education and Research. License: Code, predictions, and checkpoints are released under the Apache-2.0 license, except for the ResNet-50 DINO backbone (dino_RN50_pretrain_d2_format.pkl), which is adapted from CutLER and published under the CC BY-NC-SA 4.0 license
Phenomenological analysis of the electrical behavior of helical gears to identify sensory utilizable effects
No full textThis data set contains the research data associated with the dissertation by Maximilian Hausmann. The research data consists on the one hand of measurement data of the electrical impedance of the tooth contact between helical gears and on the other hand of the program code used for preprocessing and evaluation. For further details see the dissertation by Maximilian Hausmann:
Hausmann (2025) - "Phänomenologische Betrachtung des elektrischen Verhaltens schrägverzahnter Stirnräder zur Identifikation sensorisch nutzbarer Effekte
Campus FreeCity: Operation Center HMI Reallabor Evaluation
No full textFragebogendaten und Interviewtranskripte zur Evaluation der Operation Center HMIs (Dispatcher und Teleoperator) im Reallabor im Rahmen des Projekts Campus FreeCity, Anleitung HMI Dispatcherarbeitsplat
SFB 1194 - A07 - Interdiffusion in microfluidic interface rotation between two laminarly flowing liquids of different densities
No full textThe data contains python code used as well as all raw data
Numerical Data: Numerical investigation of model incompatibilities in contact line evaporation
No full textRaw numerical data produced for the publication:
Resolution of model contradicitions in contact line evaporation through
interfacial slip
The dataset contains the results of the conducted simulations, arranged in a
BoSSS database (SlipConvergenceDatabase.zip).
The naming scheme of the contained simulations follows the case classification
from the paper:
Stage[numStage]_SlipDropletOnWall_meshStudy_[numCells]_P[pDeg]_CA[cAngle]_SL[lSlip]_ST[surfT]_HV[hVap]
numStage: number of "stage", 1,2, or 3
numCells: number of cells in the grid (n x n), 4, 8, 16, 32, 64 or 128
pDeg: polynomial degree of the velocity field, 2, 3 or 4
cAngle: contact angle, 80.00 or 90.00
lSlip: slip length, 0.00, 0.10 or Infinity
surfT: surface tension, 0.00 or 0.10
hVap: enthalpy of evaporation, 1000.00 or -Infinity (turns of evaporation in
the solver)
Additionally, .plt files of the simulations are available directly, These can
be opened VisIt or Paraview. The archive contains a folder for each
combination of physical settings. Within they are sorted by polynomial degree
and finally each folder contains the results for the different meshes for that
specific test case.
At last, pictures of the velocity, pressure and temperature fields are
available for a few representative cases.
The BoSSS code is open source and available e.g. at
<https://zenodo.org/doi/10.5281/zenodo.8386633