Eldorado - Repository of the TU Dortmund
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Amtliche Mitteilungen der Technischen Universität Dortmund Nr. 16/2025
(Technische Universität Dortmund, 2025-06-06)
Amtliche Mitteilungen der Technischen Universität Dortmund Nr. 15/2025
(Technische Universität Dortmund, 2025-06-05)
Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management
(2024-02-07) Behr, Alexander S.; Borgelt, Hendrik; Kockmann, Norbert
As scientific digitization advances it is imperative ensuring data is Findable, Accessible, Interoperable, and Reusable (FAIR) for machine-processable data. Ontologies play a vital role in enhancing data FAIRness by explicitly representing knowledge in a machine-understandable format. Research data in catalysis research often exhibits complexity and diversity, necessitating a respectively broad collection of ontologies. While ontology portals such as EBI OLS and BioPortal aid in ontology discovery, they lack deep classification, while quality metrics for ontology reusability and domains are absent for the domain of catalysis research. Thus, this work provides an approach for systematic collection of ontology metadata with focus on the catalysis research data value chain. By classifying ontologies by subdomains of catalysis research, the approach is offering efficient comparison across ontologies. Furthermore, a workflow and codebase is presented, facilitating representation of the metadata on GitHub. Finally, a method is presented to automatically map the classes contained in the ontologies of the metadata collection against each other, providing further insights on relatedness of the ontologies listed. The presented methodology is designed for its reusability, enabling its adaptation to other ontology collections or domains of knowledge. The ontology metadata taken up for this work and the code developed and described in this work are available in a GitHub repository at: https://github.com/nfdi4cat/Ontology-Overview-of-NFDI4Cat.
Semi-automated computer vision-based tracking of multiple industrial entities
(2024-03-22) Rutinowski, Jérôme; Youssef, Hazem; Franke, Sven; Priyanta, Irfan Fachrudin; Polachowski, Frederik; Roidl, Moritz; Reining, Christopher
This contribution presents the TOMIE framework (Tracking Of Multiple Industrial Entities), a framework for the continuous tracking of industrial entities (e.g., pallets, crates, barrels) over a network of, in this example, six RGB cameras. This framework makes use of multiple sensors, data pipelines, and data annotation procedures, and is described in detail in this contribution. With the vision of a fully automated tracking system for industrial entities in mind, it enables researchers to efficiently capture high-quality data in an industrial setting. Using this framework, an image dataset, the TOMIE dataset, is created, which at the same time is used to gauge the framework’s validity. This dataset contains annotation files for 112,860 frames and 640,936 entity instances that are captured from a set of six cameras that perceive a large indoor space. This dataset out-scales comparable datasets by a factor of four and is made up of scenarios, drawn from industrial applications from the sector of warehousing. Three tracking algorithms, namely ByteTrack, Bot-Sort, and SiamMOT, are applied to this dataset, serving as a proof-of-concept and providing tracking results that are comparable to the state of the art.
Design requirements for aEVCS
(2025-06-03) Knipschild, Lars; Sicking, Frederik; Künne, Bernd; Bartz, Marcel
This study investigates the dynamic behavior of electric vehicle (EV) inlets under various
real-world load scenarios to contribute to the design requirements of automated EV
charging systems (aEVCS). Inlet movements were tracked using a camera system in
combination with AprilTag markers during typical usage scenarios such as passenger
boarding and alighting, as well as cargo loading and unloading. The results show that
while translational displacements generally remain within the limits defined by ISO 5474-5,
rotational movements, especially in smaller vehicles, often exceed these thresholds. The
findings underscore the impact of vehicle type and inlet location on displacement behavior,
suggesting that current standards require refinement to better reflect real-world variability.