--- _id: '55159' abstract: - lang: eng text: "We introduce a method based on Gaussian process regression to identify discrete variational principles from observed solutions of a field theory. The method is based on the data-based identification of a discrete Lagrangian density. It is a geometric machine learning technique in the sense that the variational structure of the true field theory is reflected in the data-driven model by design. We provide a rigorous convergence statement of the method. The proof circumvents challenges posed by the ambiguity of discrete Lagrangian densities in the inverse problem of variational calculus.\r\nMoreover, our method can be used to quantify model uncertainty in the equations of motions and any linear observable of the discrete field theory. This is illustrated on the example of the discrete wave equation and Schrödinger equation.\r\nThe article constitutes an extension of our previous article arXiv:2404.19626 for the data-driven identification of (discrete) Lagrangians for variational dynamics from an ode setting to the setting of discrete pdes." author: - first_name: Christian full_name: Offen, Christian id: '85279' last_name: Offen orcid: 0000-0002-5940-8057 citation: ama: Offen C. Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification. apa: Offen, C. (n.d.). Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification. bibtex: '@article{Offen, title={Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification}, author={Offen, Christian} }' chicago: Offen, Christian. “Machine Learning of Discrete Field Theories with Guaranteed Convergence and Uncertainty Quantification,” n.d. ieee: C. Offen, “Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification.” . mla: Offen, Christian. Machine Learning of Discrete Field Theories with Guaranteed Convergence and Uncertainty Quantification. short: C. Offen, (n.d.). date_created: 2024-07-10T13:43:50Z date_updated: 2024-08-12T13:43:32Z ddc: - '510' department: - _id: '636' external_id: arxiv: - '2407.07642' file: - access_level: open_access content_type: application/pdf creator: coffen date_created: 2024-07-10T13:39:32Z date_updated: 2024-07-10T13:39:32Z description: |- We introduce a method based on Gaussian process regression to identify discrete variational principles from observed solutions of a field theory. The method is based on the data-based identification of a discrete Lagrangian density. It is a geometric machine learning technique in the sense that the variational structure of the true field theory is reflected in the data-driven model by design. We provide a rigorous convergence statement of the method. The proof circumvents challenges posed by the ambiguity of discrete Lagrangian densities in the inverse problem of variational calculus. Moreover, our method can be used to quantify model uncertainty in the equations of motions and any linear observable of the discrete field theory. This is illustrated on the example of the discrete wave equation and Schrödinger equation. The article constitutes an extension of our previous article for the data-driven identification of (discrete) Lagrangians for variational dynamics from an ode setting to the setting of discrete pdes. file_id: '55160' file_name: L_Collocation.pdf file_size: 4569314 relation: main_file title: Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification file_date_updated: 2024-07-10T13:39:32Z has_accepted_license: '1' keyword: - System identification - inverse problem of variational calculus - Gaussian process - Lagrangian learning - physics informed machine learning - geometry aware learning language: - iso: eng oa: '1' page: '28' project: - _id: '52' name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing' publication_status: submitted related_material: link: - description: GitHub relation: software url: https://github.com/Christian-Offen/Lagrangian_GP_PDE status: public title: Machine learning of discrete field theories with guaranteed convergence and uncertainty quantification type: preprint user_id: '85279' year: '2024' ... --- _id: '56948' abstract: - lang: ger text: Das Fachdidaktische Wissen (FDW) steht als zentrale Komponente des Professionswissens angehender Lehrkräfte bereits länger im Fokus der fachdidaktischen Forschung. Bisherige Ergebnisse zu möglichen Entwicklungsstufen oder prototypischen Ausprägungen des FDW ermöglichen eine differenzierte Einordnung von Lernenden auf Basis der Bearbeitung erprobter, validierter Testinstrumente. Diese Testinstrumente sind häufig mit offenen Antwortformaten gestaltet und die nachträgliche Schließung solcher Testinstrumente hat sich als nicht unproblematisch in Hinblick auf Validität und Authentizität erwiesen. Um ein automatisiertes reichhaltiges Assessment-System auf Basis der bisherigen Forschungsergebnisse zu entwickeln, können alternativ erprobte offene Testinstrumente in Kombination mit Machine-Learning basierten Auswertungsverfahren genutzt werden. Im Vortrag werden Ergebnisse einer entsprechenden Analyse auf Basis eines vergleichsweise großen (844 Bearbeitungen) Datensatzes präsentiert. Dabei wird ein zweistufiger Assessment Prozess, in dem zunächst die offenen Aufgaben mithilfe eines Sprachmodells bepunktet werden und anschließend aus den Bepunktungen inhaltlich reichhaltiges Feedback erstellt wird, genutzt. author: - first_name: Jannis full_name: Zeller, Jannis id: '99022' last_name: Zeller orcid: 0000-0002-1834-5520 - first_name: Josef full_name: Riese, Josef id: '429' last_name: Riese orcid: 0000-0003-2927-2619 citation: ama: 'Zeller J, Riese J. Assessment des physikdidaktischen Wissens mithilfe von Machine Learning. In: Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024.' apa: Zeller, J., & Riese, J. (n.d.). Assessment des physikdidaktischen Wissens mithilfe von Machine Learning. Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024. Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024, Bochum. bibtex: '@inproceedings{Zeller_Riese, title={Assessment des physikdidaktischen Wissens mithilfe von Machine Learning}, booktitle={Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024}, author={Zeller, Jannis and Riese, Josef} }' chicago: Zeller, Jannis, and Josef Riese. “Assessment des physikdidaktischen Wissens mithilfe von Machine Learning.” In Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024, n.d. ieee: J. Zeller and J. Riese, “Assessment des physikdidaktischen Wissens mithilfe von Machine Learning,” presented at the Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024, Bochum. mla: Zeller, Jannis, and Josef Riese. “Assessment des physikdidaktischen Wissens mithilfe von Machine Learning.” Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024. short: 'J. Zeller, J. Riese, in: Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024, n.d.' conference: end_date: 2024-09-12 location: Bochum name: Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024 start_date: 2024-09-09 date_created: 2024-11-08T07:39:57Z date_updated: 2024-11-08T07:40:44Z ddc: - '370' department: - _id: '15' - _id: '299' file: - access_level: closed content_type: application/pdf creator: jzeller date_created: 2024-11-08T07:39:37Z date_updated: 2024-11-08T07:39:37Z file_id: '56949' file_name: Tagungsbandbeitrag-Jannis-Zeller-GDCP2024_preprint.pdf file_size: 622347 relation: main_file success: 1 file_date_updated: 2024-11-08T07:39:37Z keyword: - Physikdidaktisches Wissen - Assessment - Machine Learning language: - iso: ger publication: Entdecken, lehren und forschen im Schülerlabor. GDCP Jahrestagung 2024 publication_status: inpress status: public title: Assessment des physikdidaktischen Wissens mithilfe von Machine Learning type: conference user_id: '99022' year: '2024' ... --- _id: '62078' abstract: - lang: eng text: 'Fiber reinforced plastics (FRP) exhibit strongly non-linear deformation behavior. To capture this in simulations, intricate models with a variety of parameters are typically used. The identification of values for such parameters is highly challenging and requires in depth understanding of the model itself. Machine learning (ML) is a promising approach for alleviating this challenge by directly predicting parameters based on experimental results. So far, this works mostly for purely artificial data. In this work, two approaches to generalize to experimental data are investigated: a sequential approach, leveraging understanding of the constitutive model and a direct, purely data driven approach. This is exemplary carried out for a highly non-linear strain rate dependent constitutive model for the shear behavior of FRP.The sequential model is found to work better on both artificial and experimental data. It is capable of extracting well suited parameters from the artificial data under realistic conditions. For the experimental data, the model performance depends on the composition of the experimental curves, varying between excellently suiting and reasonable predictions. Taking the expert knowledge into account for ML-model training led to far better results than the purely data driven approach. Robustifying the model predictions on experimental data promises further improvement. ' author: - first_name: Johannes full_name: Gerritzen, Johannes id: '105344' last_name: Gerritzen orcid: 0000-0002-0169-8602 - first_name: Andreas full_name: Hornig, Andreas last_name: Hornig - first_name: Peter full_name: Winkler, Peter last_name: Winkler - first_name: Maik full_name: Gude, Maik last_name: Gude citation: ama: 'Gerritzen J, Hornig A, Winkler P, Gude M. Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. In: ECCM21 - Proceedings of the 21st European Conference on Composite Materials. Vol 3. European Society for Composite Materials (ESCM); 2024:1252–1259. doi:10.60691/yj56-np80' apa: Gerritzen, J., Hornig, A., Winkler, P., & Gude, M. (2024). Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. ECCM21 - Proceedings of the 21st European Conference on Composite Materials, 3, 1252–1259. https://doi.org/10.60691/yj56-np80 bibtex: '@inproceedings{Gerritzen_Hornig_Winkler_Gude_2024, title={Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning}, volume={3}, DOI={10.60691/yj56-np80}, booktitle={ECCM21 - Proceedings of the 21st European Conference on Composite Materials}, publisher={European Society for Composite Materials (ESCM)}, author={Gerritzen, Johannes and Hornig, Andreas and Winkler, Peter and Gude, Maik}, year={2024}, pages={1252–1259} }' chicago: Gerritzen, Johannes, Andreas Hornig, Peter Winkler, and Maik Gude. “Direct Parameter Identification for Highly Nonlinear Strain Rate Dependent Constitutive Models Using Machine Learning.” In ECCM21 - Proceedings of the 21st European Conference on Composite Materials, 3:1252–1259. European Society for Composite Materials (ESCM), 2024. https://doi.org/10.60691/yj56-np80. ieee: 'J. Gerritzen, A. Hornig, P. Winkler, and M. Gude, “Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning,” in ECCM21 - Proceedings of the 21st European Conference on Composite Materials, 2024, vol. 3, pp. 1252–1259, doi: 10.60691/yj56-np80.' mla: Gerritzen, Johannes, et al. “Direct Parameter Identification for Highly Nonlinear Strain Rate Dependent Constitutive Models Using Machine Learning.” ECCM21 - Proceedings of the 21st European Conference on Composite Materials, vol. 3, European Society for Composite Materials (ESCM), 2024, pp. 1252–1259, doi:10.60691/yj56-np80. short: 'J. Gerritzen, A. Hornig, P. Winkler, M. Gude, in: ECCM21 - Proceedings of the 21st European Conference on Composite Materials, European Society for Composite Materials (ESCM), 2024, pp. 1252–1259.' date_created: 2025-11-04T12:47:06Z date_updated: 2026-02-27T06:46:21Z doi: 10.60691/yj56-np80 intvolume: ' 3' keyword: - Direct parameter identification - Machine learning - Convolutional neural networks - Strain rate dependency - Fiber reinforced plastics - woven composites - segmentation - synthetic training data - x-ray computed tomography language: - iso: eng page: 1252–1259 project: - _id: '130' name: 'TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen Prozessketten' - _id: '137' name: TRR 285 - Subproject A03 - _id: '131' name: TRR 285 - Project Area A publication: ECCM21 - Proceedings of the 21st European Conference on Composite Materials publication_identifier: isbn: - 978-2-912985-01-9 publisher: European Society for Composite Materials (ESCM) status: public title: Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning type: conference user_id: '105344' volume: 3 year: '2024' ... --- _id: '57895' abstract: - lang: eng text: "In our paper, we present a study in which we investigate which strategies pre-service teachers (PSTs) use to find and, if necessary, reject possible candidates for congruence theorems for quadrilaterals. This study was conducted before the PTSs attended a university geometry course. In this way, statements about learning prerequisites can be made. For the study, we analyzed group discussions of PSTs to identify typical approaches and evaluate them from a mathematical perspective. The results can be considered for the further development of courses for PSTs and generate hypotheses\r\nfor further research." author: - first_name: Max full_name: Hoffmann, Max id: '32202' last_name: Hoffmann orcid: 0000-0002-6964-7123 - first_name: Sarah full_name: Schlüter, Sarah last_name: Schlüter citation: ama: 'Hoffmann M, Schlüter S. How Do Advanced Pre-Service Teachers Develop Congruence Theorems for Quadrilaterals? In: González-Martín AS, Gueudet G, Florensa I, Lombard N, eds. Proceedings of the Fifth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2024, 10-14 June 2024). Escola Univerist`aria Salesiana de Sarri`a – Univ. Aut`onoma de Barcelona and INDRUM; 2024.' apa: Hoffmann, M., & Schlüter, S. (2024). How Do Advanced Pre-Service Teachers Develop Congruence Theorems for Quadrilaterals? In A. S. González-Martín, G. Gueudet, I. Florensa, & N. Lombard (Eds.), Proceedings of the Fifth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2024, 10-14 June 2024). Escola Univerist`aria Salesiana de Sarri`a – Univ. Aut`onoma de Barcelona and INDRUM. bibtex: '@inproceedings{Hoffmann_Schlüter_2024, place={Barcelona}, title={How Do Advanced Pre-Service Teachers Develop Congruence Theorems for Quadrilaterals?}, booktitle={Proceedings of the Fifth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2024, 10-14 June 2024)}, publisher={Escola Univerist`aria Salesiana de Sarri`a – Univ. Aut`onoma de Barcelona and INDRUM}, author={Hoffmann, Max and Schlüter, Sarah}, editor={González-Martín, Alejandro S. and Gueudet, Ghislaine and Florensa, Ignasi and Lombard, Nathan}, year={2024} }' chicago: 'Hoffmann, Max, and Sarah Schlüter. “How Do Advanced Pre-Service Teachers Develop Congruence Theorems for Quadrilaterals?” In Proceedings of the Fifth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2024, 10-14 June 2024), edited by Alejandro S. González-Martín, Ghislaine Gueudet, Ignasi Florensa, and Nathan Lombard. Barcelona: Escola Univerist`aria Salesiana de Sarri`a – Univ. Aut`onoma de Barcelona and INDRUM, 2024.' ieee: M. Hoffmann and S. Schlüter, “How Do Advanced Pre-Service Teachers Develop Congruence Theorems for Quadrilaterals?,” in Proceedings of the Fifth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2024, 10-14 June 2024), 2024. mla: Hoffmann, Max, and Sarah Schlüter. “How Do Advanced Pre-Service Teachers Develop Congruence Theorems for Quadrilaterals?” Proceedings of the Fifth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2024, 10-14 June 2024), edited by Alejandro S. González-Martín et al., Escola Univerist`aria Salesiana de Sarri`a – Univ. Aut`onoma de Barcelona and INDRUM, 2024. short: 'M. Hoffmann, S. Schlüter, in: A.S. González-Martín, G. Gueudet, I. Florensa, N. Lombard (Eds.), Proceedings of the Fifth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2024, 10-14 June 2024), Escola Univerist`aria Salesiana de Sarri`a – Univ. Aut`onoma de Barcelona and INDRUM, Barcelona, 2024.' date_created: 2025-01-02T10:45:53Z date_updated: 2025-01-02T10:45:59Z ddc: - '370' - '510' department: - _id: '97' - _id: '643' editor: - first_name: Alejandro S. full_name: González-Martín, Alejandro S. last_name: González-Martín - first_name: Ghislaine full_name: Gueudet, Ghislaine last_name: Gueudet - first_name: Ignasi full_name: Florensa, Ignasi last_name: Florensa - first_name: Nathan full_name: Lombard, Nathan last_name: Lombard file: - access_level: closed content_type: application/pdf creator: maxh date_created: 2025-01-02T10:42:21Z date_updated: 2025-01-02T10:42:21Z file_id: '57896' file_name: 2024_Hoffmann_Schlueter_CongruenceQuadrilaterals.pdf file_size: 315111 relation: main_file success: 1 file_date_updated: 2025-01-02T10:42:21Z has_accepted_license: '1' keyword: - Teachers’ and students’ practices at university level - Transition to - across and from university mathematics - Teaching and learning of specific topics in university mathematics - Congruence - Quadrilaterals language: - iso: eng main_file_link: - open_access: '1' url: https://indrum2024.sciencesconf.org/data/pages/Proceedings_INDRUM2024.pdf oa: '1' place: Barcelona publication: Proceedings of the Fifth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2024, 10-14 June 2024) publication_status: published publisher: Escola Univerist`aria Salesiana de Sarri`a – Univ. Aut`onoma de Barcelona and INDRUM quality_controlled: '1' status: public title: How Do Advanced Pre-Service Teachers Develop Congruence Theorems for Quadrilaterals? type: conference user_id: '32202' year: '2024' ... --- _id: '56983' abstract: - lang: eng text: Detecting the veracity of a statement automatically is a challenge the world is grappling with due to the vast amount of data spread across the web. Verifying a given claim typically entails validating it within the framework of supporting evidence like a retrieved piece of text. Classifying the stance of the text with respect to the claim is called stance classification. Despite advancements in automated fact-checking, most systems still rely on a substantial quantity of labeled training data, which can be costly. In this work, we avoid the costly training or fine-tuning of models by reusing pre-trained large language models together with few-shot in-context learning. Since we do not train any model, our approach ExPrompt is lightweight, demands fewer resources than other stance classification methods and can serve as a modern baseline for future developments. At the same time, our evaluation shows that our approach is able to outperform former state-of-the-art stance classification approaches regarding accuracy by at least 2 percent. Our scripts and data used in this paper are available at https://github.com/dice-group/ExPrompt. author: - first_name: Umair full_name: Qudus, Umair id: '83392' last_name: Qudus orcid: 0000-0001-6714-8729 - first_name: Michael full_name: Röder, Michael id: '67199' last_name: Röder orcid: https://orcid.org/0000-0002-8609-8277 - first_name: Daniel full_name: Vollmers, Daniel last_name: Vollmers - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: ama: 'Qudus U, Röder M, Vollmers D, Ngonga Ngomo A-C. ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification. In: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management. Vol 9. ACM; 2024:3994-3999. doi:10.1145/3627673.3679923' apa: 'Qudus, U., Röder, M., Vollmers, D., & Ngonga Ngomo, A.-C. (2024). ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification. Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 9, 3994–3999. https://doi.org/10.1145/3627673.3679923' bibtex: '@inproceedings{Qudus_Röder_Vollmers_Ngonga Ngomo_2024, title={ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification}, volume={9}, DOI={10.1145/3627673.3679923}, booktitle={Proceedings of the 33rd ACM International Conference on Information and Knowledge Management}, publisher={ACM}, author={Qudus, Umair and Röder, Michael and Vollmers, Daniel and Ngonga Ngomo, Axel-Cyrille}, year={2024}, pages={3994–3999} }' chicago: 'Qudus, Umair, Michael Röder, Daniel Vollmers, and Axel-Cyrille Ngonga Ngomo. “ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification.” In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 9:3994–99. ACM, 2024. https://doi.org/10.1145/3627673.3679923.' ieee: 'U. Qudus, M. Röder, D. Vollmers, and A.-C. Ngonga Ngomo, “ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification,” in Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, Boise, ID, USA, 2024, vol. 9, pp. 3994–3999, doi: 10.1145/3627673.3679923.' mla: 'Qudus, Umair, et al. “ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification.” Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, vol. 9, ACM, 2024, pp. 3994–99, doi:10.1145/3627673.3679923.' short: 'U. Qudus, M. Röder, D. Vollmers, A.-C. Ngonga Ngomo, in: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, ACM, 2024, pp. 3994–3999.' conference: end_date: 2024-10-25 location: Boise, ID, USA name: 'CIKM ''24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management' start_date: 2024-10-21 date_created: 2024-11-11T13:15:25Z date_updated: 2025-09-11T09:49:07Z ddc: - '006' doi: 10.1145/3627673.3679923 file: - access_level: closed content_type: application/pdf creator: uqudus date_created: 2024-11-11T13:24:19Z date_updated: 2024-11-11T13:24:19Z file_id: '56984' file_name: public.pdf file_size: 531579 relation: main_file success: 1 file_date_updated: 2024-11-11T13:24:19Z has_accepted_license: '1' intvolume: ' 9' keyword: - Stance Classification - Few-shot in-context learning - Pre-trained large language models language: - iso: eng main_file_link: - url: https://dl.acm.org/doi/10.1145/3627673.3679923 page: 3994 - 3999 popular_science: '1' project: - _id: '412' name: 'NEBULA: Nutzerzentrierte KI-basierte Erkennung von Fake-News und Fehlinformationen' publication: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management publication_identifier: isbn: - 79-8-4007-0436-9/24/10 publication_status: published publisher: ACM quality_controlled: '1' status: public title: 'ExPrompt: Augmenting Prompts Using Examples as Modern Baseline for Stance Classification' type: conference user_id: '83392' volume: 9 year: '2024' ... --- _id: '57240' abstract: - lang: eng text: Validating assertions before adding them to a knowledge graph is an essential part of its creation and maintenance. Due to the sheer size of knowledge graphs, automatic fact-checking approaches have been developed. These approaches rely on reference knowledge to decide whether a given assertion is correct. Recent hybrid approaches achieve good results by including several knowledge sources. However, it is often impractical to provide a sheer quantity of textual knowledge or generate embedding models to leverage these hybrid approaches. We present FaVEL, an approach that uses algorithm selection and ensemble learning to amalgamate several existing fact-checking approaches that rely solely on a reference knowledge graph and, hence, use fewer resources than current hybrid approaches. For our evaluation, we create updated versions of two existing datasets and a new dataset dubbed FaVEL-DS. Our evaluation compares our approach to 15 fact-checking approaches—including the state-of-the-art approach HybridFC—on 3 datasets. Our results demonstrate that FaVEL outperforms all other approaches significantly by at least 0.04 in terms of the area under the ROC curve. Our source code, datasets, and evaluation results are open-source and can be found at https://github.com/dice-group/favel. author: - first_name: Umair full_name: Qudus, Umair id: '83392' last_name: Qudus orcid: 0000-0001-6714-8729 - first_name: Michael full_name: Röder, Michael id: '67199' last_name: Röder orcid: https://orcid.org/0000-0002-8609-8277 - first_name: Franck Lionel full_name: Tatkeu Pekarou, Franck Lionel last_name: Tatkeu Pekarou - first_name: Ana Alexandra full_name: Morim da Silva, Ana Alexandra id: '72108' last_name: Morim da Silva - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: ama: 'Qudus U, Röder M, Tatkeu Pekarou FL, Morim da Silva AA, Ngonga Ngomo A-C. FaVEL: Fact Validation Ensemble Learning. In: Rospocher M, Mehwish Alam, eds. EKAW 2024. ; 2024.' apa: 'Qudus, U., Röder, M., Tatkeu Pekarou, F. L., Morim da Silva, A. A., & Ngonga Ngomo, A.-C. (2024). FaVEL: Fact Validation Ensemble Learning. In M. Rospocher & Mehwish Alam (Eds.), EKAW 2024.' bibtex: '@inproceedings{Qudus_Röder_Tatkeu Pekarou_Morim da Silva_Ngonga Ngomo_2024, title={FaVEL: Fact Validation Ensemble Learning}, booktitle={EKAW 2024}, author={Qudus, Umair and Röder, Michael and Tatkeu Pekarou, Franck Lionel and Morim da Silva, Ana Alexandra and Ngonga Ngomo, Axel-Cyrille}, editor={Rospocher, Marco and Mehwish Alam}, year={2024} }' chicago: 'Qudus, Umair, Michael Röder, Franck Lionel Tatkeu Pekarou, Ana Alexandra Morim da Silva, and Axel-Cyrille Ngonga Ngomo. “FaVEL: Fact Validation Ensemble Learning.” In EKAW 2024, edited by Marco Rospocher and Mehwish Alam, 2024.' ieee: 'U. Qudus, M. Röder, F. L. Tatkeu Pekarou, A. A. Morim da Silva, and A.-C. Ngonga Ngomo, “FaVEL: Fact Validation Ensemble Learning,” in EKAW 2024, Amsterdam, Netherlands, 2024.' mla: 'Qudus, Umair, et al. “FaVEL: Fact Validation Ensemble Learning.” EKAW 2024, edited by Marco Rospocher and Mehwish Alam, 2024.' short: 'U. Qudus, M. Röder, F.L. Tatkeu Pekarou, A.A. Morim da Silva, A.-C. Ngonga Ngomo, in: M. Rospocher, Mehwish Alam (Eds.), EKAW 2024, 2024.' conference: end_date: 2024-11-28 location: Amsterdam, Netherlands name: 24th International Conference on Knowledge Engineering and Knowledge Management start_date: 2024-11-26 corporate_editor: - Mehwish Alam date_created: 2024-11-19T14:12:49Z date_updated: 2025-09-11T09:48:12Z ddc: - '600' department: - _id: '34' editor: - first_name: Marco full_name: Rospocher, Marco last_name: Rospocher file: - access_level: closed content_type: application/pdf creator: uqudus date_created: 2024-11-19T14:14:14Z date_updated: 2024-11-19T14:14:14Z file_id: '57241' file_name: favel.pdf file_size: 190661 relation: main_file success: 1 file_date_updated: 2024-11-19T14:14:14Z has_accepted_license: '1' keyword: - fact checking - ensemble learning - transfer learning - knowledge management. language: - iso: eng popular_science: '1' project: - _id: '412' name: 'NEBULA: Nutzerzentrierte KI-basierte Erkennung von Fake-News und Fehlinformationen' - _id: '285' name: 'SAIL: SAIL - Nachhaltiger Lebenszyklus von intelligenten soziotechnischen Systemen' - _id: '410' name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale' publication: EKAW 2024 quality_controlled: '1' status: public title: 'FaVEL: Fact Validation Ensemble Learning' type: conference user_id: '83392' year: '2024' ... --- _id: '61273' abstract: - lang: eng text: "In human-machine explanation interactions, such as tutoring systems or customer support chatbots, it is important for the machine explainer to infer the human user's understanding. Nonverbal signals play an important role for expressing mental states like understanding and confusion in these interactions. However, an individual's expressions may vary depending on other factors. In cases where these factors are unknown, machine learning methods that infer understanding from nonverbal cues become unreliable. Stress for example has been shown to affect human expression, but it is not clear from the current research how stress affects the expression of understanding.\r\nTo address this gap, we design a paradigm that induces understanding and confusion through game rule explanations. During the explanations, self-perceived understanding and confusion are annotated by the participants. A stress condition is also introduced to enable the investigation of changes in the expression of social signals under stress.\r\nWe conducted a study to validate the stress induction and participants reported a statistically significant increase in stress during the stress condition compared to the neutral control condition. \r\nAdditionally, feedback from participants shows that the paradigm is effective in inducing understanding and confusion. \r\nThis paradigm paves the way for further studies investigating social signals of understanding to improve human-machine explanation interactions for varying contexts." author: - first_name: Jonas full_name: Paletschek, Jonas id: '98941' last_name: Paletschek citation: ama: 'Paletschek J. A Paradigm to Investigate Social Signals of Understanding and Their Susceptibility to Stress. In: 12th International Conference on  Affective Computing & Intelligent Interaction. IEEE; 2024. doi:10.1109/ACII63134.2024.00040' apa: Paletschek, J. (2024). A Paradigm to Investigate Social Signals of Understanding and Their Susceptibility to Stress. 12th International Conference on  Affective Computing & Intelligent Interaction. 12th International Conference on  Affective Computing & Intelligent Interaction, Glasgow. https://doi.org/10.1109/ACII63134.2024.00040 bibtex: '@inproceedings{Paletschek_2024, title={A Paradigm to Investigate Social Signals of Understanding and Their Susceptibility to Stress}, DOI={10.1109/ACII63134.2024.00040}, booktitle={12th International Conference on  Affective Computing & Intelligent Interaction}, publisher={IEEE}, author={Paletschek, Jonas}, year={2024} }' chicago: Paletschek, Jonas. “A Paradigm to Investigate Social Signals of Understanding and Their Susceptibility to Stress.” In 12th International Conference on  Affective Computing & Intelligent Interaction. IEEE, 2024. https://doi.org/10.1109/ACII63134.2024.00040. ieee: 'J. Paletschek, “A Paradigm to Investigate Social Signals of Understanding and Their Susceptibility to Stress,” presented at the 12th International Conference on  Affective Computing & Intelligent Interaction, Glasgow, 2024, doi: 10.1109/ACII63134.2024.00040.' mla: Paletschek, Jonas. “A Paradigm to Investigate Social Signals of Understanding and Their Susceptibility to Stress.” 12th International Conference on  Affective Computing & Intelligent Interaction, IEEE, 2024, doi:10.1109/ACII63134.2024.00040. short: 'J. Paletschek, in: 12th International Conference on  Affective Computing & Intelligent Interaction, IEEE, 2024.' conference: end_date: 2024-09-18 location: Glasgow name: 12th International Conference on Affective Computing & Intelligent Interaction start_date: 2024-09-15 date_created: 2025-09-15T11:24:56Z date_updated: 2025-09-16T07:57:53Z ddc: - '150' department: - _id: '660' doi: 10.1109/ACII63134.2024.00040 file: - access_level: closed content_type: application/pdf creator: paletsch date_created: 2025-09-15T11:18:01Z date_updated: 2025-09-15T11:18:01Z file_id: '61274' file_name: ACII2024_Camera_Ready.pdf file_size: 8807478 relation: main_file success: 1 file_date_updated: 2025-09-15T11:18:01Z has_accepted_license: '1' keyword: - Understanding - Nonverbal Social Signals - Stress Induction - Explanation - Machine Learning Bias language: - iso: eng project: - _id: '1200' name: TRR 318 - Teilprojekt A6 - Inklusive Ko-Konstruktion sozialer Signale des Verstehens publication: 12th International Conference on Affective Computing & Intelligent Interaction publication_status: published publisher: IEEE status: public title: A Paradigm to Investigate Social Signals of Understanding and Their Susceptibility to Stress type: conference user_id: '98941' year: '2024' ... --- _id: '55999' abstract: - lang: eng text: Clean hydrogen is a key aspect of carbon neutrality, necessitating robust methods for monitoring hydrogen concentration in critical infrastructures like pipelines or power plants. While semiconducting metal oxides such as In2O3 can monitor gas concentrations down to the ppm range, they often exhibit cross-sensitivity to other gases like H2O. In this study, we investigated whether cyclic optical illumination of a gas-sensitive In2O3 layer creates identifiable changes in a gas sensor´s electronic resistance that can be linked to H2 and H2O concentrations via machine learning. We exposed nanostructured In2O3 with a large surface area of 95 m2 g-1 to H2 concentrations (0-800 ppm) and relative humidity (0-70%) under cyclic activation utilizing blue light. The sensors were tested for 20 classes of gas combinations. A support vector machine achieved classification rates up to 92.0%, with reliable reproducibility (88.2 ± 2.7%) across five individual sensors using 10-fold cross-validation. Our findings suggest that cyclic optical activation can be used as a tool to classify H2 and H2O concentrations. article_type: original author: - first_name: 'Dominik ' full_name: 'Baier, Dominik ' last_name: Baier - first_name: 'Alexander ' full_name: 'Krüger, Alexander ' last_name: Krüger - first_name: 'Thorsten ' full_name: 'Wagner, Thorsten ' last_name: Wagner - first_name: Michael full_name: Tiemann, Michael id: '23547' last_name: Tiemann orcid: 0000-0003-1711-2722 - first_name: Christian full_name: Weinberger, Christian id: '11848' last_name: Weinberger citation: ama: 'Baier D, Krüger A, Wagner T, Tiemann M, Weinberger C. Gas Sensing with Nanoporous In2O3 under Cyclic Optical Activation: Machine Learning-Aided Classification of H2 and H2O. Chemosensors. 2024;12(9):178. doi:10.3390/chemosensors12090178' apa: 'Baier, D., Krüger, A., Wagner, T., Tiemann, M., & Weinberger, C. (2024). Gas Sensing with Nanoporous In2O3 under Cyclic Optical Activation: Machine Learning-Aided Classification of H2 and H2O. Chemosensors, 12(9), 178. https://doi.org/10.3390/chemosensors12090178' bibtex: '@article{Baier_Krüger_Wagner_Tiemann_Weinberger_2024, title={Gas Sensing with Nanoporous In2O3 under Cyclic Optical Activation: Machine Learning-Aided Classification of H2 and H2O}, volume={12}, DOI={10.3390/chemosensors12090178}, number={9}, journal={Chemosensors}, publisher={MDPI}, author={Baier, Dominik and Krüger, Alexander and Wagner, Thorsten and Tiemann, Michael and Weinberger, Christian}, year={2024}, pages={178} }' chicago: 'Baier, Dominik , Alexander Krüger, Thorsten Wagner, Michael Tiemann, and Christian Weinberger. “Gas Sensing with Nanoporous In2O3 under Cyclic Optical Activation: Machine Learning-Aided Classification of H2 and H2O.” Chemosensors 12, no. 9 (2024): 178. https://doi.org/10.3390/chemosensors12090178.' ieee: 'D. Baier, A. Krüger, T. Wagner, M. Tiemann, and C. Weinberger, “Gas Sensing with Nanoporous In2O3 under Cyclic Optical Activation: Machine Learning-Aided Classification of H2 and H2O,” Chemosensors, vol. 12, no. 9, p. 178, 2024, doi: 10.3390/chemosensors12090178.' mla: 'Baier, Dominik, et al. “Gas Sensing with Nanoporous In2O3 under Cyclic Optical Activation: Machine Learning-Aided Classification of H2 and H2O.” Chemosensors, vol. 12, no. 9, MDPI, 2024, p. 178, doi:10.3390/chemosensors12090178.' short: D. Baier, A. Krüger, T. Wagner, M. Tiemann, C. Weinberger, Chemosensors 12 (2024) 178. date_created: 2024-09-03T13:49:42Z date_updated: 2025-11-26T12:14:21Z ddc: - '540' department: - _id: '2' - _id: '307' doi: 10.3390/chemosensors12090178 file: - access_level: closed content_type: application/pdf creator: cweinber date_created: 2024-09-03T13:58:18Z date_updated: 2024-09-03T13:58:18Z file_id: '56000' file_name: chemosensors-12-00178.pdf file_size: 3275869 relation: main_file success: 1 file_date_updated: 2024-09-03T13:58:18Z has_accepted_license: '1' intvolume: ' 12' issue: '9' keyword: - resistive gas sensor - chemiresistor - semiconductor - metal oxide - In2O3 - mesoporous - hydrogen - humidtiy - machine learning - sustainable language: - iso: eng main_file_link: - open_access: '1' url: https://www.mdpi.com/2227-9040/12/9/178 oa: '1' page: '178' publication: Chemosensors publication_identifier: issn: - 2227-9040 publication_status: published publisher: MDPI quality_controlled: '1' status: public title: 'Gas Sensing with Nanoporous In2O3 under Cyclic Optical Activation: Machine Learning-Aided Classification of H2 and H2O' type: journal_article user_id: '11848' volume: 12 year: '2024' ... --- _id: '63109' abstract: - lang: ger text: Game-based Learning (GBL) und Gamification (GF) gewinnen im schulischen Umfeld zunehmend an Bedeutung. Ihr Einsatz bietet die Möglichkeit, eigenverantwortliches Lernen im Unterricht zu fördern, bringt aber auch Herausforderungen für Lehr- und Lernprozesse mit sich. Daher ist es von großer Bedeutung, angehenden Lehrkräften die notwendigen Kompetenzen zu vermitteln, um GBL und GF effektiv in den Unterricht zu integrieren. Vor diesem Hintergrund wurde ein Lehrkonzept für die Hochschullehre entwickelt und hinsichtlich der Zielerreichung evaluiert. Der vorliegende Beitrag gibt einen Einblick in die Gestaltungsaspekte des Seminars sowie erste Erkenntnisse und Erfahrungen der Studierenden. - lang: eng text: Game-based learning (GBL) and gamification (GF) are becoming increasingly relevant in the school environment. Their use offers the opportunity to promote independent learning in the classroom, but also poses challenges for teaching and learning processes. Therefore, it is of great importance to provide future teachers with the necessary competencies to effectively integrate GBL and GF into the classroom. Against this background, a teaching concept for higher education was developed and evaluated in terms of achievement. This article provides insights into the design aspects of the seminar as well as initial findings and experiences of the students. author: - first_name: Ha My full_name: Truong, Ha My id: '44239' last_name: Truong citation: ama: 'Truong HM. Level Up! Gamification in der Lehrkräfteausbildung - Konzeption und Erfahrung eines gamifizierten Seminars in der Hochschullehre für Lehramtsstudierende. In: Herzig B, Eickelmann B, Schwabl F, Schulze J, Niemann J, eds. Lehrkräftebildung in Der Digitalen Welt. Zukunftsorientierte Forschungs- Und Praxisperspektiven. Waxmann Verlag GmbH; 2024:179-189. doi:10.31244/9783830998372' apa: Truong, H. M. (2024). Level Up! Gamification in der Lehrkräfteausbildung - Konzeption und Erfahrung eines gamifizierten Seminars in der Hochschullehre für Lehramtsstudierende. In B. Herzig, B. Eickelmann, F. Schwabl, J. Schulze, & J. Niemann (Eds.), Lehrkräftebildung in der digitalen Welt. Zukunftsorientierte Forschungs- und Praxisperspektiven (pp. 179–189). Waxmann Verlag GmbH. https://doi.org/10.31244/9783830998372 bibtex: '@inbook{Truong_2024, title={Level Up! Gamification in der Lehrkräfteausbildung - Konzeption und Erfahrung eines gamifizierten Seminars in der Hochschullehre für Lehramtsstudierende}, DOI={10.31244/9783830998372}, booktitle={Lehrkräftebildung in der digitalen Welt. Zukunftsorientierte Forschungs- und Praxisperspektiven}, publisher={Waxmann Verlag GmbH}, author={Truong, Ha My}, editor={Herzig, Bardo and Eickelmann, Birgit and Schwabl, Franziska and Schulze, Johanna and Niemann, Jan}, year={2024}, pages={179–189} }' chicago: Truong, Ha My. “Level Up! Gamification in Der Lehrkräfteausbildung - Konzeption Und Erfahrung Eines Gamifizierten Seminars in Der Hochschullehre Für Lehramtsstudierende.” In Lehrkräftebildung in Der Digitalen Welt. Zukunftsorientierte Forschungs- Und Praxisperspektiven, edited by Bardo Herzig, Birgit Eickelmann, Franziska Schwabl, Johanna Schulze, and Jan Niemann, 179–89. Waxmann Verlag GmbH, 2024. https://doi.org/10.31244/9783830998372. ieee: H. M. Truong, “Level Up! Gamification in der Lehrkräfteausbildung - Konzeption und Erfahrung eines gamifizierten Seminars in der Hochschullehre für Lehramtsstudierende,” in Lehrkräftebildung in der digitalen Welt. Zukunftsorientierte Forschungs- und Praxisperspektiven, B. Herzig, B. Eickelmann, F. Schwabl, J. Schulze, and J. Niemann, Eds. Waxmann Verlag GmbH, 2024, pp. 179–189. mla: Truong, Ha My. “Level Up! Gamification in Der Lehrkräfteausbildung - Konzeption Und Erfahrung Eines Gamifizierten Seminars in Der Hochschullehre Für Lehramtsstudierende.” Lehrkräftebildung in Der Digitalen Welt. Zukunftsorientierte Forschungs- Und Praxisperspektiven, edited by Bardo Herzig et al., Waxmann Verlag GmbH, 2024, pp. 179–89, doi:10.31244/9783830998372. short: 'H.M. Truong, in: B. Herzig, B. Eickelmann, F. Schwabl, J. Schulze, J. Niemann (Eds.), Lehrkräftebildung in Der Digitalen Welt. Zukunftsorientierte Forschungs- Und Praxisperspektiven, Waxmann Verlag GmbH, 2024, pp. 179–189.' date_created: 2025-12-16T08:36:17Z date_updated: 2025-12-16T13:05:59Z department: - _id: '33' doi: 10.31244/9783830998372 editor: - first_name: Bardo full_name: Herzig, Bardo last_name: Herzig - first_name: Birgit full_name: Eickelmann, Birgit last_name: Eickelmann - first_name: Franziska full_name: Schwabl, Franziska last_name: Schwabl - first_name: Johanna full_name: Schulze, Johanna last_name: Schulze - first_name: Jan full_name: Niemann, Jan last_name: Niemann keyword: - Game-based learning - Gamification - Hochschullehre - Lehrkräftebildung language: - iso: eng page: 179-189 publication: Lehrkräftebildung in der digitalen Welt. Zukunftsorientierte Forschungs- und Praxisperspektiven publication_identifier: isbn: - '9783830948377' publication_status: published publisher: Waxmann Verlag GmbH status: public title: Level Up! Gamification in der Lehrkräfteausbildung - Konzeption und Erfahrung eines gamifizierten Seminars in der Hochschullehre für Lehramtsstudierende type: book_chapter user_id: '44239' year: '2024' ... --- _id: '65163' abstract: - lang: ger text: "Dieser Beitrag untersucht aktuelle pädagogische und hermeneutische Ansätze der\r\njüdischen, christlichen und muslimischen Religionspädagogik in Kindertora, Kinderbibel\r\nund Kinderkoran. Er betont die Notwendigkeit für Lehrkräfte, sich mit den spezifischen\r\npädagogischen und hermeneutischen Ansätzen der drei monotheistischen Religionen\r\nvertraut zu machen, um die didaktischen Heiligen Schriften im Unterricht angemessen\r\nnutzen zu können. Beispiele aus dem aktuellen Religionsunterricht zeigen\r\nMissverständnisse und Überraschungen auf, die durch unzureichendes Wissen entstehen.\r\nDer Artikel hebt die Bedeutung einer jüdischen Identitätsbildung, einer christlichen\r\ndiversitätssensiblen Perspektive und von muslimischen normativen Diskursen in den\r\nverschiedenen Religionspädagogiken hervor und diskutiert die Herausforderungen und\r\nChancen, die mit der Nutzung didaktisierter Heiliger Schriften verbunden sind.\r\n" - lang: eng text: "This article examines current pedagogical and hermeneutical approaches to Jewish,\r\nChristian and Muslim religious education in the Children’s Torah, Children’s Bible and\r\nChildren’s Quran. It emphasizes the need for teachers to familiarize themselves with the\r\nspecific pedagogical and hermeneutical approaches of the three monotheistic religions in\r\norder to be able to use the didactic Holy Scriptures appropriately in the classroom.\r\nExamples from current religious education lessons show misunderstandings and\r\nsurprises that arise due to insufficient knowledge. The article emphasizes the importance\r\nof Jewish identity formation, a Christian diversity-sensitive perspective and Muslim\r\nnormative discourses in the various religious pedagogies and discusses the challenges\r\nand opportunities associated with the use of didactic Holy Scriptures.\r\n" article_type: original author: - first_name: Marion full_name: Keuchen, Marion id: '251' last_name: Keuchen orcid: https://orcid.org/0009-0000-9904-6479 citation: ama: 'Keuchen M. Aktuelle pädagogische und hermeneutische Ansätze aus Judentum, Christentum und Islam in Kindertora, Kinderbibel und Kinderkoran: Identitätsbildung, diversitätssensible Religionspädagogik und normative Diskurse. TheoWeb Zeitschrift für Religionspädagogik. 2024;2:224-237. doi:10.23770/tw0360' apa: 'Keuchen, M. (2024). Aktuelle pädagogische und hermeneutische Ansätze aus Judentum, Christentum und Islam in Kindertora, Kinderbibel und Kinderkoran: Identitätsbildung, diversitätssensible Religionspädagogik und normative Diskurse. TheoWeb. Zeitschrift für Religionspädagogik, 2, 224–237. https://doi.org/10.23770/tw0360' bibtex: '@article{Keuchen_2024, title={Aktuelle pädagogische und hermeneutische Ansätze aus Judentum, Christentum und Islam in Kindertora, Kinderbibel und Kinderkoran: Identitätsbildung, diversitätssensible Religionspädagogik und normative Diskurse}, volume={2}, DOI={10.23770/tw0360}, journal={TheoWeb. Zeitschrift für Religionspädagogik}, author={Keuchen, Marion}, year={2024}, pages={224–237} }' chicago: 'Keuchen, Marion. “Aktuelle pädagogische und hermeneutische Ansätze aus Judentum, Christentum und Islam in Kindertora, Kinderbibel und Kinderkoran: Identitätsbildung, diversitätssensible Religionspädagogik und normative Diskurse.” TheoWeb. Zeitschrift für Religionspädagogik 2 (2024): 224–37. https://doi.org/10.23770/tw0360.' ieee: 'M. Keuchen, “Aktuelle pädagogische und hermeneutische Ansätze aus Judentum, Christentum und Islam in Kindertora, Kinderbibel und Kinderkoran: Identitätsbildung, diversitätssensible Religionspädagogik und normative Diskurse,” TheoWeb. Zeitschrift für Religionspädagogik, vol. 2, pp. 224–237, 2024, doi: 10.23770/tw0360.' mla: 'Keuchen, Marion. “Aktuelle pädagogische und hermeneutische Ansätze aus Judentum, Christentum und Islam in Kindertora, Kinderbibel und Kinderkoran: Identitätsbildung, diversitätssensible Religionspädagogik und normative Diskurse.” TheoWeb. Zeitschrift für Religionspädagogik, vol. 2, 2024, pp. 224–37, doi:10.23770/tw0360.' short: M. Keuchen, TheoWeb. Zeitschrift für Religionspädagogik 2 (2024) 224–237. date_created: 2026-03-27T08:06:54Z date_updated: 2026-03-27T18:41:17Z ddc: - '200' department: - _id: '20' - _id: '500' doi: 10.23770/tw0360 file: - access_level: closed content_type: application/pdf creator: keuchen date_created: 2026-03-27T08:04:06Z date_updated: 2026-03-27T08:04:06Z file_id: '65164' file_name: aktuelle-paedagogische-und-hermeneutische-ansaetze-aus-judentum-christentum-und-islam-in-kindertora-kinderbibel-und-kinderkoran-identitaetsbildung-diversitaetssensible-religionspaedagogik-und-normative-diskurse.pdf file_size: 223437 relation: main_file success: 1 file_date_updated: 2026-03-27T08:04:06Z has_accepted_license: '1' intvolume: ' 2' keyword: - Heilige Schriften - interreligiöses Lernen - Schrifthermeneutik - Identität - diversitätssensible Religionspädagogik - jüdische Religionspädagogik - muslimische Religionspädagogik - christliche Religionspädagogik - Holy scriptures - interreligious learning - hermeneutics of scripture - identity - diversity-sensitive religious education - Jewish religious education - Muslim religious education - Christian religious education language: - iso: ger main_file_link: - open_access: '1' url: https://www.theo-web.de/fileadmin/user_upload/theo-web/pdfs/23-jahrgang-2024-heft-2/aktuelle-paedagogische-und-hermeneutische-ansaetze-aus-judentum-christentum-und-islam-in-kindertora-kinderbibel-und-kinderkoran-identitaetsbildung-diversitaetssensible-religionspaedagogik-und-normative-diskurse.pdf oa: '1' page: 224-237 publication: TheoWeb. Zeitschrift für Religionspädagogik publication_status: published quality_controlled: '1' related_material: link: - relation: confirmation url: https://www.theo-web.de/fileadmin/user_upload/theo-web/pdfs/23-jahrgang-2024-heft-2/aktuelle-paedagogische-und-hermeneutische-ansaetze-aus-judentum-christentum-und-islam-in-kindertora-kinderbibel-und-kinderkoran-identitaetsbildung-diversitaetssensible-religionspaedagogik-und-normative-diskurse.pdf status: public title: 'Aktuelle pädagogische und hermeneutische Ansätze aus Judentum, Christentum und Islam in Kindertora, Kinderbibel und Kinderkoran: Identitätsbildung, diversitätssensible Religionspädagogik und normative Diskurse' type: journal_article user_id: '251' volume: 2 year: '2024' ... --- _id: '45270' abstract: - lang: eng text: Clinical depression is a serious mental disorder that poses challenges for both personal and public health. Millions of people struggle with depression each year, but for many, the disorder goes undiagnosed or untreated. Over the last decade, early depression detection on social media emerged as an interdisciplinary research field. However, there is still a gap in detecting hesitant, depression-susceptible individuals with minimal direct depressive signals at an early stage. We, therefore, take up this open point and leverage posts from Reddit to fill the addressed gap. Our results demonstrate the potential of contemporary Transformer architectures in yielding promising predictive capabilities for mental health research. Furthermore, we investigate the model’s interpretability using a surrogate and a topic modeling approach. Based on our findings, we consider this work as a further step towards developing a better understanding of mental eHealth and hope that our results can support the development of future technologies. author: - first_name: Haya full_name: Halimeh, Haya id: '87673' last_name: Halimeh - first_name: Matthew full_name: Caron, Matthew id: '60721' last_name: Caron - first_name: Oliver full_name: Müller, Oliver id: '72849' last_name: Müller citation: ama: 'Halimeh H, Caron M, Müller O. Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features. In: Hawaii International Conference on System Sciences. ; 2023.' apa: 'Halimeh, H., Caron, M., & Müller, O. (2023). Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features. Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences.' bibtex: '@inproceedings{Halimeh_Caron_Müller_2023, title={Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features}, booktitle={Hawaii International Conference on System Sciences}, author={Halimeh, Haya and Caron, Matthew and Müller, Oliver}, year={2023} }' chicago: 'Halimeh, Haya, Matthew Caron, and Oliver Müller. “Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features.” In Hawaii International Conference on System Sciences, 2023.' ieee: 'H. Halimeh, M. Caron, and O. Müller, “Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features,” presented at the Hawaii International Conference on System Sciences, 2023.' mla: 'Halimeh, Haya, et al. “Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features.” Hawaii International Conference on System Sciences, 2023.' short: 'H. Halimeh, M. Caron, O. Müller, in: Hawaii International Conference on System Sciences, 2023.' conference: end_date: 2023-01-06 name: Hawaii International Conference on System Sciences start_date: 2023-01-03 date_created: 2023-05-25T10:25:21Z date_updated: 2024-01-10T15:16:37Z department: - _id: '195' - _id: '196' keyword: - Social Media and Healthcare Technology - early depression detection - liwc - mental health - transfer learning - transformer architectures language: - iso: eng main_file_link: - open_access: '1' url: https://scholarspace.manoa.hawaii.edu/items/2ddab486-5d2f-4302-8de3-a8b24017da3d oa: '1' publication: Hawaii International Conference on System Sciences publication_status: published related_material: link: - relation: confirmation url: https://hdl.handle.net/10125/103046 status: public title: 'Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features' type: conference user_id: '60721' year: '2023' ... --- _id: '50479' abstract: - lang: eng text: Verifying assertions is an essential part of creating and maintaining knowledge graphs. Most often, this task cannot be carried out manually due to the sheer size of modern knowledge graphs. Hence, automatic fact-checking approaches have been proposed over the last decade. These approaches aim to compute automatically whether a given assertion is correct or incorrect. However, most fact-checking approaches are binary classifiers that fail to consider the volatility of some assertions, i.e., the fact that such assertions are only valid at certain times or for specific time intervals. Moreover, the few approaches able to predict when an assertion was valid (i.e., time-point prediction approaches) rely on manual feature engineering. This paper presents TEMPORALFC, a temporal fact-checking approach that uses multiple sources of background knowledge to assess the veracity and temporal validity of a given assertion. We evaluate TEMPORALFC on two datasets and compare it to the state of the art in fact-checking and time-point prediction. Our results suggest that TEMPORALFC outperforms the state of the art on the fact-checking task by 0.13 to 0.15 in terms of Area Under the Receiver Operating Characteristic curve and on the time-point prediction task by 0.25 to 0.27 in terms of Mean Reciprocal Rank. Our code is open-source and can be found at https://github.com/dice-group/TemporalFC. author: - first_name: Umair full_name: Qudus, Umair last_name: Qudus - first_name: Michael full_name: Röder, Michael last_name: Röder - first_name: Sabrina full_name: Kirrane, Sabrina last_name: Kirrane - first_name: Axel-Cyrille Ngonga full_name: Ngomo, Axel-Cyrille Ngonga last_name: Ngomo citation: ama: 'Qudus U, Röder M, Kirrane S, Ngomo A-CN. TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs. In: R. Payne T, Presutti V, Qi G, et al., eds. The Semantic Web – ISWC 2023. Vol 14265. Lecture Notes in Computer Science. Springer, Cham; 2023:465–483. doi:10.1007/978-3-031-47240-4_25' apa: 'Qudus, U., Röder, M., Kirrane, S., & Ngomo, A.-C. N. (2023). TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs. In T. R. Payne, V. Presutti, G. Qi, M. Poveda-Villalón, G. Stoilos, L. Hollink, Z. Kaoudi, G. Cheng, & J. Li (Eds.), The Semantic Web – ISWC 2023 (Vol. 14265, pp. 465–483). Springer, Cham. https://doi.org/10.1007/978-3-031-47240-4_25' bibtex: '@inproceedings{Qudus_Röder_Kirrane_Ngomo_2023, place={Cham}, series={ Lecture Notes in Computer Science}, title={TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs}, volume={14265}, DOI={10.1007/978-3-031-47240-4_25}, booktitle={The Semantic Web – ISWC 2023}, publisher={Springer, Cham}, author={Qudus, Umair and Röder, Michael and Kirrane, Sabrina and Ngomo, Axel-Cyrille Ngonga}, editor={R. Payne, Terry and Presutti, Valentina and Qi, Guilin and Poveda-Villalón, María and Stoilos, Giorgos and Hollink, Laura and Kaoudi, Zoi and Cheng, Gong and Li, Juanzi}, year={2023}, pages={465–483}, collection={ Lecture Notes in Computer Science} }' chicago: 'Qudus, Umair, Michael Röder, Sabrina Kirrane, and Axel-Cyrille Ngonga Ngomo. “TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs.” In The Semantic Web – ISWC 2023, edited by Terry R. Payne, Valentina Presutti, Guilin Qi, María Poveda-Villalón, Giorgos Stoilos, Laura Hollink, Zoi Kaoudi, Gong Cheng, and Juanzi Li, 14265:465–483. Lecture Notes in Computer Science. Cham: Springer, Cham, 2023. https://doi.org/10.1007/978-3-031-47240-4_25.' ieee: 'U. Qudus, M. Röder, S. Kirrane, and A.-C. N. Ngomo, “TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs,” in The Semantic Web – ISWC 2023, Athens, Greece, 2023, vol. 14265, pp. 465–483, doi: 10.1007/978-3-031-47240-4_25.' mla: 'Qudus, Umair, et al. “TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs.” The Semantic Web – ISWC 2023, edited by Terry R. Payne et al., vol. 14265, Springer, Cham, 2023, pp. 465–483, doi:10.1007/978-3-031-47240-4_25.' short: 'U. Qudus, M. Röder, S. Kirrane, A.-C.N. Ngomo, in: T. R. Payne, V. Presutti, G. Qi, M. Poveda-Villalón, G. Stoilos, L. Hollink, Z. Kaoudi, G. Cheng, J. Li (Eds.), The Semantic Web – ISWC 2023, Springer, Cham, Cham, 2023, pp. 465–483.' conference: end_date: 2023-11-10 location: Athens, Greece name: The Semantic Web – ISWC 2023 start_date: 2023-11-06 date_created: 2024-01-13T11:22:15Z date_updated: 2024-01-13T11:48:28Z ddc: - '006' department: - _id: '34' doi: 10.1007/978-3-031-47240-4_25 editor: - first_name: Terry full_name: R. Payne, Terry last_name: R. Payne - first_name: Valentina full_name: Presutti, Valentina last_name: Presutti - first_name: Guilin full_name: Qi, Guilin last_name: Qi - first_name: María full_name: Poveda-Villalón, María last_name: Poveda-Villalón - first_name: Giorgos full_name: Stoilos, Giorgos last_name: Stoilos - first_name: Laura full_name: Hollink, Laura last_name: Hollink - first_name: Zoi full_name: Kaoudi, Zoi last_name: Kaoudi - first_name: Gong full_name: Cheng, Gong last_name: Cheng - first_name: Juanzi full_name: Li, Juanzi last_name: Li file: - access_level: closed content_type: application/pdf creator: uqudus date_created: 2024-01-13T11:25:48Z date_updated: 2024-01-13T11:25:48Z file_id: '50480' file_name: ISWC 2023 TemporalFC-A Temporal Fact Checking approach over Knowledge Graphs.pdf file_size: 1944818 relation: main_file success: 1 file_date_updated: 2024-01-13T11:25:48Z has_accepted_license: '1' intvolume: ' 14265' jel: - C keyword: - temporal fact checking · ensemble learning · transfer learning · time-point prediction · temporal knowledge graphs language: - iso: eng page: 465–483 place: Cham project: - _id: '410' grant_number: '860801' name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale' publication: The Semantic Web – ISWC 2023 publication_identifier: isbn: - '9783031472398' - '9783031472404' issn: - 0302-9743 - 1611-3349 publication_status: published publisher: Springer, Cham series_title: ' Lecture Notes in Computer Science' status: public title: 'TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs' type: conference user_id: '83392' volume: 14265 year: '2023' ... --- _id: '52816' abstract: - lang: eng text: "Manufacturing companies face the challenge of reaching required quality standards. Using\r\noptical sensors and deep learning might help. However, training deep learning algorithms\r\nrequire large amounts of visual training data. Using domain randomization to generate synthetic\r\nimage data can alleviate this bottleneck. This paper presents the application of synthetic\r\nimage training data for optical quality inspections using visual sensor technology. The results\r\nshow synthetically generated training data are appropriate for visual quality inspections." author: - first_name: Iris full_name: Gräßler, Iris id: '47565' last_name: Gräßler orcid: 0000-0001-5765-971X - first_name: Michael full_name: Hieb, Michael id: '72252' last_name: Hieb citation: ama: 'Gräßler I, Hieb M. Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing. In: Lectures. AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany; 2023:253-524. doi:10.5162/smsi2023/d7.4' apa: Gräßler, I., & Hieb, M. (2023). Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing. Lectures, 253–524. https://doi.org/10.5162/smsi2023/d7.4 bibtex: '@inproceedings{Gräßler_Hieb_2023, title={Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing}, DOI={10.5162/smsi2023/d7.4}, booktitle={Lectures}, publisher={AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany}, author={Gräßler, Iris and Hieb, Michael}, year={2023}, pages={253–524} }' chicago: Gräßler, Iris, and Michael Hieb. “Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing.” In Lectures, 253–524. AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 2023. https://doi.org/10.5162/smsi2023/d7.4. ieee: 'I. Gräßler and M. Hieb, “Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing,” in Lectures, Nuremberg, 2023, pp. 253–524, doi: 10.5162/smsi2023/d7.4.' mla: Gräßler, Iris, and Michael Hieb. “Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing.” Lectures, AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 2023, pp. 253–524, doi:10.5162/smsi2023/d7.4. short: 'I. Gräßler, M. Hieb, in: Lectures, AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 2023, pp. 253–524.' conference: end_date: 2023-05-11 location: Nuremberg name: SMSI 2023. Sensor and Measurement Science International start_date: 2023-05-08 date_created: 2024-03-25T10:16:24Z date_updated: 2024-03-25T11:05:53Z department: - _id: '152' doi: 10.5162/smsi2023/d7.4 keyword: - synthetic training data - machine vision quality gates - deep learning - automated inspection and quality control - production control language: - iso: eng page: 253-524 publication: Lectures publication_status: published publisher: AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany quality_controlled: '1' status: public title: Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing type: conference user_id: '5905' year: '2023' ... --- _id: '49434' abstract: - lang: ger text: Die Rollenspiel-Methode ist ein handlungs- und anwendungsbezogenes Instrument, um Studierende bereits während der universitären Ausbildung für unterschiedliche professionelle Sicht- und Handlungsweisen zu sensibilisieren. In diesem Sinne stellt der folgende Beitrag ein Rollenspiel vor, welches als hochschuldidaktisches Material für die inklusionssensible Lehrer*innenbildung genutzt werden kann und Studierende auf zukünftige multiprofessionelle Kooperationshandlungen in der schulischen Praxis vorbereiten soll. Dieses bietet einen geeigneten Anlass, um die professionsübergreifende Zusammenarbeit „gefahrlos“ im Rahmen einer fiktiven kollegialen Fallkonferenz zu erproben sowie unterschiedliche pädagogische Professionsverständnisse aufzudecken und zu reflektieren. Darüber hinaus werden erste Durchführungserfahrungen und Evaluationsergebnisse diskutiert, die im Zuge der wissenschaftlichen Begleitforschung der Teilmaßnahme „Multiprofessionelle Kooperation in inklusiven Ganztagsschulen“ des Bielefelder QLB-Projekts BiProfessional erhoben wurden. author: - first_name: 'Alessa ' full_name: 'Schuldt, Alessa ' last_name: Schuldt - first_name: Manfred full_name: Palm, Manfred last_name: Palm - first_name: Phillip full_name: Neumann, Phillip id: '95559' last_name: Neumann - first_name: Oliver full_name: Böhm-Kasper, Oliver last_name: Böhm-Kasper - first_name: Christine full_name: Demmer, Christine last_name: Demmer - first_name: Birgit full_name: Lütje-Klose, Birgit last_name: Lütje-Klose citation: ama: Schuldt A, Palm M, Neumann P, Böhm-Kasper O, Demmer C, Lütje-Klose B. „Jede*r von uns sieht die Situation eben unterschiedlich – das ist zwar eine Schwierigkeit, aber auch eine Bereicherung“. Zeitschrift für Konzepte Und Arbeitsmaterialien für Lehrer*innenbildung Und Unterricht. 2023;5(4). doi:10.11576/DIMAWE-6699 apa: Schuldt, A., Palm, M., Neumann, P., Böhm-Kasper, O., Demmer, C., & Lütje-Klose, B. (2023). „Jede*r von uns sieht die Situation eben unterschiedlich – das ist zwar eine Schwierigkeit, aber auch eine Bereicherung“. Zeitschrift Für Konzepte Und Arbeitsmaterialien Für Lehrer*innenbildung Und Unterricht, 5(4). https://doi.org/10.11576/DIMAWE-6699 bibtex: '@article{Schuldt_Palm_Neumann_Böhm-Kasper_Demmer_Lütje-Klose_2023, title={„Jede*r von uns sieht die Situation eben unterschiedlich – das ist zwar eine Schwierigkeit, aber auch eine Bereicherung“}, volume={5}, DOI={10.11576/DIMAWE-6699}, number={4}, journal={Zeitschrift für Konzepte Und Arbeitsmaterialien für Lehrer*innenbildung Und Unterricht}, author={Schuldt, Alessa and Palm, Manfred and Neumann, Phillip and Böhm-Kasper, Oliver and Demmer, Christine and Lütje-Klose, Birgit}, year={2023} }' chicago: Schuldt, Alessa , Manfred Palm, Phillip Neumann, Oliver Böhm-Kasper, Christine Demmer, and Birgit Lütje-Klose. “„Jede*r von Uns Sieht Die Situation Eben Unterschiedlich – Das Ist Zwar Eine Schwierigkeit, Aber Auch Eine Bereicherung“.” Zeitschrift Für Konzepte Und Arbeitsmaterialien Für Lehrer*innenbildung Und Unterricht 5, no. 4 (2023). https://doi.org/10.11576/DIMAWE-6699. ieee: 'A. Schuldt, M. Palm, P. Neumann, O. Böhm-Kasper, C. Demmer, and B. Lütje-Klose, “„Jede*r von uns sieht die Situation eben unterschiedlich – das ist zwar eine Schwierigkeit, aber auch eine Bereicherung“,” Zeitschrift für Konzepte Und Arbeitsmaterialien für Lehrer*innenbildung Und Unterricht, vol. 5, no. 4, 2023, doi: 10.11576/DIMAWE-6699.' mla: Schuldt, Alessa, et al. “„Jede*r von Uns Sieht Die Situation Eben Unterschiedlich – Das Ist Zwar Eine Schwierigkeit, Aber Auch Eine Bereicherung“.” Zeitschrift Für Konzepte Und Arbeitsmaterialien Für Lehrer*innenbildung Und Unterricht, vol. 5, no. 4, 2023, doi:10.11576/DIMAWE-6699. short: A. Schuldt, M. Palm, P. Neumann, O. Böhm-Kasper, C. Demmer, B. Lütje-Klose, Zeitschrift Für Konzepte Und Arbeitsmaterialien Für Lehrer*innenbildung Und Unterricht 5 (2023). date_created: 2023-12-04T10:11:17Z date_updated: 2024-03-27T11:27:33Z department: - _id: '479' doi: 10.11576/DIMAWE-6699 intvolume: ' 5' issue: '4' keyword: - Rollenspiel - mulitprofessionelle Kooperation - inklusionssensible Lehrerbildung - Hochschuldidaktik - Blended Learning language: - iso: eng publication: Zeitschrift für Konzepte Und Arbeitsmaterialien für Lehrer*innenbildung Und Unterricht status: public title: „Jede*r von uns sieht die Situation eben unterschiedlich – das ist zwar eine Schwierigkeit, aber auch eine Bereicherung“ type: journal_article user_id: '77750' volume: 5 year: '2023' ... --- _id: '39976' abstract: - lang: eng text: "The context of the study is the increasing digitalisation of the living environment of primary school students, which is to be introduced into primary schools according to theoretical and educational policy guidelines. In this regard, further teacher\r\ntraining on digital media in classrooms are particularly relevant, on the one hand to promote teachers’ digital-related pedagogical knowledge and content knowledge (DPaCK). On the other hand, studies also reveal positive correlations among teacher training, teaching activities, and students’ learning outcomes. In-service teacher training courses with adaptive support by a trainer in particular have\r\nproven to be effective. Against the background of various research studies on professional development of teachers, a corresponding model of tripartite learning outcomes has been established and serves as a broad theoretical framework. However, the specific relationship between in-service teacher training with adaptive support, DPaCK, and computational thinking of primary school students in the context of the German primary school subject Sachunterricht has not been sufficiently studied. Therefore, the following research questions can be derived: (1) To what extent does training with adaptive support on the topic of learning robots contribute to the development of teachers’ DPaCK? (2) Which effects can be ascertained on the students’ computational thinking in technology-related Sachunterricht? To investigate this relationship, an intervention study in a pre-post design with an experimental group, a control group, and a baseline is appropriate. As results are not yet available at this point, the present paper focuses on the presentation of the theoretical background and empirical approaches." article_type: original author: - first_name: Nicole full_name: Janicki, Nicole id: '50915' last_name: Janicki - first_name: Claudia full_name: Tenberge, Claudia id: '67302' last_name: Tenberge citation: ama: Janicki N, Tenberge C. Technology education in elementary school using the example of “learning robots” – development and evaluation of an in-service teacher training concept. Australasian Journal of Technology Education. 2023;9. doi:https://doi.org/10.15663/ajte.v9.i0.103 apa: Janicki, N., & Tenberge, C. (2023). Technology education in elementary school using the example of “learning robots” – development and evaluation of an in-service teacher training concept. Australasian Journal of Technology Education, 9. https://doi.org/10.15663/ajte.v9.i0.103 bibtex: '@article{Janicki_Tenberge_2023, title={Technology education in elementary school using the example of “learning robots” – development and evaluation of an in-service teacher training concept}, volume={9}, DOI={https://doi.org/10.15663/ajte.v9.i0.103}, journal={Australasian Journal of Technology Education}, author={Janicki, Nicole and Tenberge, Claudia}, year={2023} }' chicago: Janicki, Nicole, and Claudia Tenberge. “Technology Education in Elementary School Using the Example of ‘learning Robots’ – Development and Evaluation of an in-Service Teacher Training Concept.” Australasian Journal of Technology Education 9 (2023). https://doi.org/10.15663/ajte.v9.i0.103. ieee: 'N. Janicki and C. Tenberge, “Technology education in elementary school using the example of ‘learning robots’ – development and evaluation of an in-service teacher training concept,” Australasian Journal of Technology Education, vol. 9, 2023, doi: https://doi.org/10.15663/ajte.v9.i0.103.' mla: Janicki, Nicole, and Claudia Tenberge. “Technology Education in Elementary School Using the Example of ‘learning Robots’ – Development and Evaluation of an in-Service Teacher Training Concept.” Australasian Journal of Technology Education, vol. 9, 2023, doi:https://doi.org/10.15663/ajte.v9.i0.103. short: N. Janicki, C. Tenberge, Australasian Journal of Technology Education 9 (2023). date_created: 2023-01-25T11:50:07Z date_updated: 2024-05-31T09:22:58Z department: - _id: '588' doi: https://doi.org/10.15663/ajte.v9.i0.103 intvolume: ' 9' keyword: - technology education - teacher professionalisation - Computational Thinking - digitalization - learning robots language: - iso: eng publication: Australasian Journal of Technology Education publication_status: published status: public title: Technology education in elementary school using the example of 'learning robots' – development and evaluation of an in-service teacher training concept type: journal_article user_id: '50915' volume: 9 year: '2023' ... --- _id: '31849' author: - first_name: Max full_name: Hoffmann, Max id: '32202' last_name: Hoffmann orcid: 0000-0002-6964-7123 - first_name: Rolf full_name: Biehler, Rolf id: '16274' last_name: Biehler citation: ama: 'Hoffmann M, Biehler R. Student Teachers ’ Knowledge of Congruence before a University Course on Geometry. In: Trigueros M, Barquero B, Hochmuth R, Peters J, eds. Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022). University of Hannover and INDRUM.; 2023.' apa: Hoffmann, M., & Biehler, R. (2023). Student Teachers ’ Knowledge of Congruence before a University Course on Geometry. In M. Trigueros, B. Barquero, R. Hochmuth, & J. Peters (Eds.), Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022). University of Hannover and INDRUM. bibtex: '@inproceedings{Hoffmann_Biehler_2023, place={Hannover}, title={Student Teachers ’ Knowledge of Congruence before a University Course on Geometry}, booktitle={Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022)}, publisher={University of Hannover and INDRUM.}, author={Hoffmann, Max and Biehler, Rolf}, editor={Trigueros, Marı́a and Barquero, Berta and Hochmuth, Reinhard and Peters, Jana}, year={2023} }' chicago: 'Hoffmann, Max, and Rolf Biehler. “Student Teachers ’ Knowledge of Congruence before a University Course on Geometry.” In Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022), edited by Marı́a Trigueros, Berta Barquero, Reinhard Hochmuth, and Jana Peters. Hannover: University of Hannover and INDRUM., 2023.' ieee: M. Hoffmann and R. Biehler, “Student Teachers ’ Knowledge of Congruence before a University Course on Geometry,” in Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022), 2023. mla: Hoffmann, Max, and Rolf Biehler. “Student Teachers ’ Knowledge of Congruence before a University Course on Geometry.” Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022), edited by Marı́a Trigueros et al., University of Hannover and INDRUM., 2023. short: 'M. Hoffmann, R. Biehler, in: M. Trigueros, B. Barquero, R. Hochmuth, J. Peters (Eds.), Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022), University of Hannover and INDRUM., Hannover, 2023.' date_created: 2022-06-12T11:07:34Z date_updated: 2023-03-25T10:11:35Z ddc: - '370' - '510' department: - _id: '97' editor: - first_name: Marı́a full_name: Trigueros, Marı́a last_name: Trigueros - first_name: Berta full_name: Barquero, Berta last_name: Barquero - first_name: Reinhard full_name: Hochmuth, Reinhard last_name: Hochmuth - first_name: Jana full_name: Peters, Jana last_name: Peters file: - access_level: closed content_type: application/pdf creator: maxh date_created: 2023-03-25T10:01:03Z date_updated: 2023-03-25T10:01:03Z file_id: '43096' file_name: HoffmannBiehler2022_indrum_congruence.pdf file_size: 201942 relation: main_file success: 1 file_date_updated: 2023-03-25T10:01:03Z has_accepted_license: '1' keyword: - Teaching and learning of specific topics in university mathematics - Transition to - across and from university mathematics - Student Teachers - Geometry - Congruence - Double Discontinuity. language: - iso: eng main_file_link: - open_access: '1' url: https://hal.univ-reims.fr/INDRUM2022/ oa: '1' place: Hannover publication: Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022) publication_status: published publisher: University of Hannover and INDRUM. quality_controlled: '1' status: public title: Student Teachers ’ Knowledge of Congruence before a University Course on Geometry type: conference user_id: '32202' year: '2023' ... --- _id: '45299' abstract: - lang: eng text: Many applications are driven by Machine Learning (ML) today. While complex ML models lead to an accurate prediction, their inner decision-making is obfuscated. However, especially for high-stakes decisions, interpretability and explainability of the model are necessary. Therefore, we develop a holistic interpretability and explainability framework (HIEF) to objectively describe and evaluate an intelligent system’s explainable AI (XAI) capacities. This guides data scientists to create more transparent models. To evaluate our framework, we analyse 50 real estate appraisal papers to ensure the robustness of HIEF. Additionally, we identify six typical types of intelligent systems, so-called archetypes, which range from explanatory to predictive, and demonstrate how researchers can use the framework to identify blind-spot topics in their domain. Finally, regarding comprehensiveness, we used a random sample of six intelligent systems and conducted an applicability check to provide external validity. author: - first_name: Jan-Peter full_name: Kucklick, Jan-Peter id: '77066' last_name: Kucklick citation: ama: 'Kucklick J-P. HIEF: a holistic interpretability and explainability framework. Journal of Decision Systems. Published online 2023:1-41. doi:10.1080/12460125.2023.2207268' apa: 'Kucklick, J.-P. (2023). HIEF: a holistic interpretability and explainability framework. Journal of Decision Systems, 1–41. https://doi.org/10.1080/12460125.2023.2207268' bibtex: '@article{Kucklick_2023, title={HIEF: a holistic interpretability and explainability framework}, DOI={10.1080/12460125.2023.2207268}, journal={Journal of Decision Systems}, publisher={Taylor & Francis}, author={Kucklick, Jan-Peter}, year={2023}, pages={1–41} }' chicago: 'Kucklick, Jan-Peter. “HIEF: A Holistic Interpretability and Explainability Framework.” Journal of Decision Systems, 2023, 1–41. https://doi.org/10.1080/12460125.2023.2207268.' ieee: 'J.-P. Kucklick, “HIEF: a holistic interpretability and explainability framework,” Journal of Decision Systems, pp. 1–41, 2023, doi: 10.1080/12460125.2023.2207268.' mla: 'Kucklick, Jan-Peter. “HIEF: A Holistic Interpretability and Explainability Framework.” Journal of Decision Systems, Taylor & Francis, 2023, pp. 1–41, doi:10.1080/12460125.2023.2207268.' short: J.-P. Kucklick, Journal of Decision Systems (2023) 1–41. date_created: 2023-05-26T05:04:45Z date_updated: 2023-05-26T05:08:36Z department: - _id: '195' - _id: '196' doi: 10.1080/12460125.2023.2207268 keyword: - Explainable AI (XAI) - machine learning - interpretability - real estate appraisal - framework - taxonomy language: - iso: eng main_file_link: - url: https://www.tandfonline.com/doi/full/10.1080/12460125.2023.2207268 page: 1-41 publication: Journal of Decision Systems publication_identifier: issn: - 1246-0125 - 2116-7052 publication_status: published publisher: Taylor & Francis status: public title: 'HIEF: a holistic interpretability and explainability framework' type: journal_article user_id: '77066' year: '2023' ... --- _id: '33734' abstract: - lang: eng text: 'Many applications require explainable node classification in knowledge graphs. Towards this end, a popular ``white-box'''' approach is class expression learning: Given sets of positive and negative nodes, class expressions in description logics are learned that separate positive from negative nodes. Most existing approaches are search-based approaches generating many candidate class expressions and selecting the best one. However, they often take a long time to find suitable class expressions. In this paper, we cast class expression learning as a translation problem and propose a new family of class expression learning approaches which we dub neural class expression synthesizers. Training examples are ``translated'''' into class expressions in a fashion akin to machine translation. Consequently, our synthesizers are not subject to the runtime limitations of search-based approaches. We study three instances of this novel family of approaches based on LSTMs, GRUs, and set transformers, respectively. An evaluation of our approach on four benchmark datasets suggests that it can effectively synthesize high-quality class expressions with respect to the input examples in approximately one second on average. Moreover, a comparison to state-of-the-art approaches suggests that we achieve better F-measures on large datasets. For reproducibility purposes, we provide our implementation as well as pretrained models in our public GitHub repository at https://github.com/dice-group/NeuralClassExpressionSynthesis' author: - first_name: N'Dah Jean full_name: KOUAGOU, N'Dah Jean id: '87189' last_name: KOUAGOU - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Caglar full_name: Demir, Caglar id: '43817' last_name: Demir - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: ama: 'KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression Synthesis. In: Pesquita C, Jimenez-Ruiz E, McCusker J, et al., eds. The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023). Vol 13870. Springer International Publishing; 2023:209-226. doi:https://doi.org/10.1007/978-3-031-33455-9_13' apa: KOUAGOU, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2023). Neural Class Expression Synthesis. In C. Pesquita, E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, & S. Hertling (Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023) (Vol. 13870, pp. 209–226). Springer International Publishing. https://doi.org/10.1007/978-3-031-33455-9_13 bibtex: '@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2023, title={Neural Class Expression Synthesis}, volume={13870}, DOI={https://doi.org/10.1007/978-3-031-33455-9_13}, booktitle={The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)}, publisher={Springer International Publishing}, author={KOUAGOU, N’Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, editor={Pesquita, Catia and Jimenez-Ruiz, Ernesto and McCusker, Jamie and Faria, Daniel and Dragoni, Mauro and Dimou, Anastasia and Troncy, Raphael and Hertling, Sven}, year={2023}, pages={209–226} }' chicago: KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Neural Class Expression Synthesis.” In The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), edited by Catia Pesquita, Ernesto Jimenez-Ruiz, Jamie McCusker, Daniel Faria, Mauro Dragoni, Anastasia Dimou, Raphael Troncy, and Sven Hertling, 13870:209–26. Springer International Publishing, 2023. https://doi.org/10.1007/978-3-031-33455-9_13. ieee: 'N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class Expression Synthesis,” in The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), Hersonissos, Crete, Greece, 2023, vol. 13870, pp. 209–226, doi: https://doi.org/10.1007/978-3-031-33455-9_13.' mla: KOUAGOU, N’Dah Jean, et al. “Neural Class Expression Synthesis.” The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), edited by Catia Pesquita et al., vol. 13870, Springer International Publishing, 2023, pp. 209–26, doi:https://doi.org/10.1007/978-3-031-33455-9_13. short: 'N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: C. Pesquita, E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, S. Hertling (Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), Springer International Publishing, 2023, pp. 209–226.' conference: end_date: 2023-06-01 location: Hersonissos, Crete, Greece name: 20th Extended Semantic Web Conference start_date: 2023-05-28 date_created: 2022-10-15T19:20:11Z date_updated: 2023-07-02T18:10:02Z department: - _id: '574' - _id: '760' doi: https://doi.org/10.1007/978-3-031-33455-9_13 editor: - first_name: Catia full_name: Pesquita, Catia last_name: Pesquita - first_name: Ernesto full_name: Jimenez-Ruiz, Ernesto last_name: Jimenez-Ruiz - first_name: Jamie full_name: McCusker, Jamie last_name: McCusker - first_name: Daniel full_name: Faria, Daniel last_name: Faria - first_name: Mauro full_name: Dragoni, Mauro last_name: Dragoni - first_name: Anastasia full_name: Dimou, Anastasia last_name: Dimou - first_name: Raphael full_name: Troncy, Raphael last_name: Troncy - first_name: Sven full_name: Hertling, Sven last_name: Hertling external_id: unknown: - https://link.springer.com/chapter/10.1007/978-3-031-33455-9_13 intvolume: ' 13870' keyword: - Neural network - Concept learning - Description logics language: - iso: eng main_file_link: - open_access: '1' url: https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Kouagou_2023_Neural.pdf oa: '1' page: 209 - 226 project: - _id: '410' name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale' - _id: '407' grant_number: '101070305' name: 'ENEXA: Efficient Explainable Learning on Knowledge Graphs' - _id: '285' grant_number: NW21-059D name: 'SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems' publication: The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023) publication_identifier: unknown: - 978-3-031-33455-9 publication_status: published publisher: Springer International Publishing status: public title: Neural Class Expression Synthesis type: conference user_id: '11871' volume: 13870 year: '2023' ... --- _id: '29240' abstract: - lang: eng text: "The principle of least action is one of the most fundamental physical principle. It says that among all possible motions connecting two points in a phase space, the system will exhibit those motions which extremise an action functional. Many qualitative features of dynamical systems, such as the presence of conservation laws and energy balance equations, are related to the existence of an action functional. Incorporating variational structure into learning algorithms for dynamical systems is, therefore, crucial in order to make sure that the learned model shares important features with the exact physical system. In this paper we show how to incorporate variational principles into trajectory predictions of learned dynamical systems. The novelty of this work is that (1) our technique relies only on discrete position data of observed trajectories. Velocities or conjugate momenta do not need to be observed or approximated and no prior knowledge about the form of the variational principle is assumed. Instead, they are recovered using backward error analysis. (2) Moreover, our technique compensates discretisation errors when trajectories are computed from the learned system. This is important when moderate to large step-sizes are used and high accuracy is required. For this,\r\nwe introduce and rigorously analyse the concept of inverse modified Lagrangians by developing an inverse version of variational backward error analysis. (3) Finally, we introduce a method to perform system identification from position observations only, based on variational backward error analysis." article_type: original author: - first_name: Sina full_name: Ober-Blöbaum, Sina id: '16494' last_name: Ober-Blöbaum - first_name: Christian full_name: Offen, Christian id: '85279' last_name: Offen orcid: 0000-0002-5940-8057 citation: ama: Ober-Blöbaum S, Offen C. Variational Learning of Euler–Lagrange Dynamics from Data. Journal of Computational and Applied Mathematics. 2023;421:114780. doi:10.1016/j.cam.2022.114780 apa: Ober-Blöbaum, S., & Offen, C. (2023). Variational Learning of Euler–Lagrange Dynamics from Data. Journal of Computational and Applied Mathematics, 421, 114780. https://doi.org/10.1016/j.cam.2022.114780 bibtex: '@article{Ober-Blöbaum_Offen_2023, title={Variational Learning of Euler–Lagrange Dynamics from Data}, volume={421}, DOI={10.1016/j.cam.2022.114780}, journal={Journal of Computational and Applied Mathematics}, publisher={Elsevier}, author={Ober-Blöbaum, Sina and Offen, Christian}, year={2023}, pages={114780} }' chicago: 'Ober-Blöbaum, Sina, and Christian Offen. “Variational Learning of Euler–Lagrange Dynamics from Data.” Journal of Computational and Applied Mathematics 421 (2023): 114780. https://doi.org/10.1016/j.cam.2022.114780.' ieee: 'S. Ober-Blöbaum and C. Offen, “Variational Learning of Euler–Lagrange Dynamics from Data,” Journal of Computational and Applied Mathematics, vol. 421, p. 114780, 2023, doi: 10.1016/j.cam.2022.114780.' mla: Ober-Blöbaum, Sina, and Christian Offen. “Variational Learning of Euler–Lagrange Dynamics from Data.” Journal of Computational and Applied Mathematics, vol. 421, Elsevier, 2023, p. 114780, doi:10.1016/j.cam.2022.114780. short: S. Ober-Blöbaum, C. Offen, Journal of Computational and Applied Mathematics 421 (2023) 114780. date_created: 2022-01-11T13:24:00Z date_updated: 2023-08-10T08:42:39Z ddc: - '510' department: - _id: '636' doi: 10.1016/j.cam.2022.114780 external_id: arxiv: - '2112.12619' file: - access_level: open_access content_type: application/pdf creator: coffen date_created: 2022-06-28T15:25:50Z date_updated: 2022-06-28T15:25:50Z description: |- The principle of least action is one of the most fundamental physical principle. It says that among all possible motions connecting two points in a phase space, the system will exhibit those motions which extremise an action functional. Many qualitative features of dynamical systems, such as the presence of conservation laws and energy balance equa- tions, are related to the existence of an action functional. Incorporating variational structure into learning algorithms for dynamical systems is, therefore, crucial in order to make sure that the learned model shares important features with the exact physical system. In this paper we show how to incorporate variational principles into trajectory predic- tions of learned dynamical systems. The novelty of this work is that (1) our technique relies only on discrete position data of observed trajectories. Velocities or conjugate momenta do not need to be observed or approximated and no prior knowledge about the form of the variational principle is assumed. Instead, they are recovered using backward error analysis. (2) Moreover, our technique compensates discretisation errors when trajectories are computed from the learned system. This is important when moderate to large step-sizes are used and high accuracy is required. For this, we introduce and rigorously analyse the concept of inverse modified Lagrangians by developing an inverse version of variational backward error analysis. (3) Finally, we introduce a method to perform system identification from position observations only, based on variational backward error analysis. file_id: '32274' file_name: ShadowLagrangian_revision1_journal_style_arxiv.pdf file_size: 3640770 relation: main_file title: Variational Learning of Euler–Lagrange Dynamics from Data file_date_updated: 2022-06-28T15:25:50Z has_accepted_license: '1' intvolume: ' 421' keyword: - Lagrangian learning - variational backward error analysis - modified Lagrangian - variational integrators - physics informed learning language: - iso: eng oa: '1' page: '114780' publication: Journal of Computational and Applied Mathematics publication_identifier: issn: - 0377-0427 publication_status: epub_ahead publisher: Elsevier quality_controlled: '1' related_material: link: - relation: software url: https://github.com/Christian-Offen/LagrangianShadowIntegration status: public title: Variational Learning of Euler–Lagrange Dynamics from Data type: journal_article user_id: '85279' volume: 421 year: '2023' ... --- _id: '60304' abstract: - lang: eng text: The focus towards multi-material and lightweight assemblies, driven by legal requirements on reducing emissions and energy consumptions, reveals important drawbacks and disadvantages of established joining processes, such as welding. In this context, mechanical joining technologies, such as clinching, are becoming more and more relevant especially in the automotive industry. However, the availability of only few standards and almost none systematic design methods causes a still very time- and cost-intensive assembly development process considering mainly expert knowledge and a considerable amount of experimental studies. Motivated by this, the presented work introduces a novel approach for the methodical design and dimensioning of mechanically clinched assemblies. Therefore, the utilization of regression models, such as machine learning algorithms, combined with manufacturing knowledge ensures a reliable estimation of individual clinched joint characteristics. In addition, the implementation of an engineering workbench enables the following data-driven and knowledge-based generation of high-quality initial assembly designs already in early product development phases. In a subsequent analysis and adjustment, these designs are being improved while guaranteeing joining safety and loading conformity. The presented results indicate that the methodological approach can pave the way to a more systematic design process of mechanical joining assemblies, which can significantly shorten the required number of iteration loops and therefore the product development time. author: - first_name: Christoph full_name: Zirngibl, Christoph last_name: Zirngibl - first_name: Sven full_name: Martin, Sven last_name: Martin - first_name: Christian full_name: Steinfelder, Christian last_name: Steinfelder - first_name: Benjamin full_name: Schleich, Benjamin last_name: Schleich - first_name: Thomas full_name: Tröster, Thomas last_name: Tröster - first_name: Alexander full_name: Brosius, Alexander last_name: Brosius - first_name: Sandro full_name: Wartzack, Sandro last_name: Wartzack citation: ama: 'Zirngibl C, Martin S, Steinfelder C, et al. Methodical approach for the design and dimensioning of mechanical clinched assemblies. In: Materials Research Proceedings. Vol 25. Materials Research Forum LLC; 2023. doi:10.21741/9781644902417-23' apa: Zirngibl, C., Martin, S., Steinfelder, C., Schleich, B., Tröster, T., Brosius, A., & Wartzack, S. (2023). Methodical approach for the design and dimensioning of mechanical clinched assemblies. Materials Research Proceedings, 25. https://doi.org/10.21741/9781644902417-23 bibtex: '@inproceedings{Zirngibl_Martin_Steinfelder_Schleich_Tröster_Brosius_Wartzack_2023, title={Methodical approach for the design and dimensioning of mechanical clinched assemblies}, volume={25}, DOI={10.21741/9781644902417-23}, booktitle={Materials Research Proceedings}, publisher={Materials Research Forum LLC}, author={Zirngibl, Christoph and Martin, Sven and Steinfelder, Christian and Schleich, Benjamin and Tröster, Thomas and Brosius, Alexander and Wartzack, Sandro}, year={2023} }' chicago: Zirngibl, Christoph, Sven Martin, Christian Steinfelder, Benjamin Schleich, Thomas Tröster, Alexander Brosius, and Sandro Wartzack. “Methodical Approach for the Design and Dimensioning of Mechanical Clinched Assemblies.” In Materials Research Proceedings, Vol. 25. Materials Research Forum LLC, 2023. https://doi.org/10.21741/9781644902417-23. ieee: 'C. Zirngibl et al., “Methodical approach for the design and dimensioning of mechanical clinched assemblies,” in Materials Research Proceedings, Erlangen-Nürnberg, 2023, vol. 25, doi: 10.21741/9781644902417-23.' mla: Zirngibl, Christoph, et al. “Methodical Approach for the Design and Dimensioning of Mechanical Clinched Assemblies.” Materials Research Proceedings, vol. 25, Materials Research Forum LLC, 2023, doi:10.21741/9781644902417-23. short: 'C. Zirngibl, S. Martin, C. Steinfelder, B. Schleich, T. Tröster, A. Brosius, S. Wartzack, in: Materials Research Proceedings, Materials Research Forum LLC, 2023.' conference: end_date: 2023-04-05 location: Erlangen-Nürnberg name: 20th International Conference on Sheet Metal start_date: 2023-04-02 date_created: 2025-06-23T08:08:23Z date_updated: 2025-06-23T08:15:07Z department: - _id: '630' doi: 10.21741/9781644902417-23 intvolume: ' 25' keyword: - Joining - Structural Analysis - Machine Learning language: - iso: eng project: - _id: '130' grant_number: '418701707' name: 'TRR 285: TRR 285: Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen Prozessketten' - _id: '132' name: 'TRR 285 - B: TRR 285 - Project Area B' - _id: '140' name: 'TRR 285 – B01: TRR 285 - Subproject B01' - _id: '144' name: 'TRR 285 – B05: TRR 285 - Subproject B05' publication: Materials Research Proceedings publication_identifier: issn: - 2474-395X publication_status: published publisher: Materials Research Forum LLC status: public title: Methodical approach for the design and dimensioning of mechanical clinched assemblies type: conference user_id: '104464' volume: 25 year: '2023' ...