[{"date_updated":"2023-01-25T11:50:56Z","_id":"39976","year":"2023","type":"journal_article","citation":{"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.","short":"N. Janicki, C. Tenberge, Australasian Journal of Technology Education (n.d.).","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.","bibtex":"@article{Janicki_Tenberge, title={Technology education in elementary school using the example of “learning robots” – development and evaluation of an in-service teacher training concept}, journal={Australasian Journal of Technology Education}, author={Janicki, Nicole and Tenberge, Claudia} }","apa":"Janicki, N., & Tenberge, C. (n.d.). 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.","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.","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, n.d."},"language":[{"iso":"eng"}],"title":"Technology education in elementary school using the example of 'learning robots' – development and evaluation of an in-service teacher training concept","user_id":"50915","author":[{"last_name":"Janicki","id":"50915","first_name":"Nicole","full_name":"Janicki, Nicole"},{"last_name":"Tenberge","full_name":"Tenberge, Claudia","first_name":"Claudia"}],"publication":"Australasian Journal of Technology Education","department":[{"_id":"588"}],"keyword":["technology education","teacher professionalisation","Computational Thinking","digitalization","learning robots"],"publication_status":"accepted","status":"public","date_created":"2023-01-25T11:50:07Z"},{"title":"Student Teachers ’ Knowledge of Congruence before a University Course on Geometry","place":"Hannover","publication_status":"published","editor":[{"last_name":"Trigueros","first_name":"Marı́a","full_name":"Trigueros, Marı́a"},{"full_name":"Barquero, Berta","first_name":"Berta","last_name":"Barquero"},{"last_name":"Hochmuth","first_name":"Reinhard","full_name":"Hochmuth, Reinhard"},{"first_name":"Jana","full_name":"Peters, Jana","last_name":"Peters"}],"department":[{"_id":"97"}],"oa":"1","date_updated":"2023-03-25T10:11:35Z","language":[{"iso":"eng"}],"ddc":["370","510"],"user_id":"32202","date_created":"2022-06-12T11:07:34Z","has_accepted_license":"1","status":"public","keyword":["Teaching and learning of specific topics in university mathematics","Transition to","across and from university mathematics","Student Teachers","Geometry","Congruence","Double Discontinuity."],"publication":"Proceedings of the Fourth Conference of the International Network for Didactic Research in University Mathematics (INDRUM 2022, 19-22 October 2022)","file_date_updated":"2023-03-25T10:01:03Z","quality_controlled":"1","author":[{"first_name":"Max","full_name":"Hoffmann, Max","orcid":"0000-0002-6964-7123","last_name":"Hoffmann","id":"32202"},{"id":"16274","last_name":"Biehler","full_name":"Biehler, Rolf","first_name":"Rolf"}],"publisher":"University of Hannover and INDRUM.","file":[{"file_size":201942,"file_id":"43096","creator":"maxh","date_updated":"2023-03-25T10:01:03Z","content_type":"application/pdf","relation":"main_file","success":1,"date_created":"2023-03-25T10:01:03Z","file_name":"HoffmannBiehler2022_indrum_congruence.pdf","access_level":"closed"}],"_id":"31849","year":"2023","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.","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.","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} }","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.","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."},"type":"conference","main_file_link":[{"open_access":"1","url":"https://hal.univ-reims.fr/INDRUM2022/"}]},{"language":[{"iso":"eng"}],"doi":"10.1080/12460125.2023.2207268","date_updated":"2023-05-26T05:08:36Z","publication_status":"published","publication_identifier":{"issn":["1246-0125","2116-7052"]},"department":[{"_id":"195"},{"_id":"196"}],"title":"HIEF: a holistic interpretability and explainability framework","page":"1-41","year":"2023","type":"journal_article","citation":{"short":"J.-P. Kucklick, Journal of Decision Systems (2023) 1–41.","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.","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","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","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.","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.","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} }"},"main_file_link":[{"url":"https://www.tandfonline.com/doi/full/10.1080/12460125.2023.2207268"}],"_id":"45299","date_created":"2023-05-26T05:04:45Z","status":"public","publication":"Journal of Decision Systems","keyword":["Explainable AI (XAI)","machine learning","interpretability","real estate appraisal","framework","taxonomy"],"publisher":"Taylor & Francis","author":[{"full_name":"Kucklick, Jan-Peter","first_name":"Jan-Peter","id":"77066","last_name":"Kucklick"}],"user_id":"77066","abstract":[{"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.","lang":"eng"}]},{"date_updated":"2023-07-02T18:10:02Z","doi":"https://doi.org/10.1007/978-3-031-33455-9_13","oa":"1","language":[{"iso":"eng"}],"external_id":{"unknown":["https://link.springer.com/chapter/10.1007/978-3-031-33455-9_13"]},"title":"Neural Class Expression Synthesis","department":[{"_id":"574"},{"_id":"760"}],"publication_status":"published","publication_identifier":{"unknown":["978-3-031-33455-9"]},"editor":[{"full_name":"Pesquita, Catia","first_name":"Catia","last_name":"Pesquita"},{"full_name":"Jimenez-Ruiz, Ernesto","first_name":"Ernesto","last_name":"Jimenez-Ruiz"},{"last_name":"McCusker","first_name":"Jamie","full_name":"McCusker, Jamie"},{"last_name":"Faria","first_name":"Daniel","full_name":"Faria, Daniel"},{"full_name":"Dragoni, Mauro","first_name":"Mauro","last_name":"Dragoni"},{"last_name":"Dimou","full_name":"Dimou, Anastasia","first_name":"Anastasia"},{"full_name":"Troncy, Raphael","first_name":"Raphael","last_name":"Troncy"},{"full_name":"Hertling, Sven","first_name":"Sven","last_name":"Hertling"}],"project":[{"name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale","_id":"410"},{"_id":"407","grant_number":"101070305","name":"ENEXA: Efficient Explainable Learning on Knowledge Graphs"},{"name":"SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems","grant_number":"NW21-059D","_id":"285"}],"conference":{"end_date":"2023-06-01","location":"Hersonissos, Crete, Greece","name":"20th Extended Semantic Web Conference","start_date":"2023-05-28"},"_id":"33734","intvolume":" 13870","main_file_link":[{"open_access":"1","url":"https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Kouagou_2023_Neural.pdf"}],"page":"209 - 226","year":"2023","type":"conference","citation":{"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.","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} }","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","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","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.","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."},"abstract":[{"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","lang":"eng"}],"user_id":"11871","keyword":["Neural network","Concept learning","Description logics"],"publication":"The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)","author":[{"id":"87189","last_name":"KOUAGOU","full_name":"KOUAGOU, N'Dah Jean","first_name":"N'Dah Jean"},{"first_name":"Stefan","full_name":"Heindorf, Stefan","orcid":"0000-0002-4525-6865","last_name":"Heindorf","id":"11871"},{"last_name":"Demir","id":"43817","first_name":"Caglar","full_name":"Demir, Caglar"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo"}],"publisher":"Springer International Publishing","volume":13870,"date_created":"2022-10-15T19:20:11Z","status":"public"},{"_id":"29240","intvolume":" 421","citation":{"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","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","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.","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} }","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.","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."},"type":"journal_article","year":"2023","page":"114780","article_type":"original","abstract":[{"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.","lang":"eng"}],"user_id":"85279","ddc":["510"],"file":[{"date_updated":"2022-06-28T15:25:50Z","content_type":"application/pdf","description":"The principle of least action is one of the most fundamental physical principle. It says that among all possible motions\nconnecting two points in a phase space, the system will exhibit those motions which extremise an action functional.\nMany qualitative features of dynamical systems, such as the presence of conservation laws and energy balance equa-\ntions, are related to the existence of an action functional. Incorporating variational structure into learning algorithms\nfor dynamical systems is, therefore, crucial in order to make sure that the learned model shares important features\nwith the exact physical system. In this paper we show how to incorporate variational principles into trajectory predic-\ntions of learned dynamical systems. The novelty of this work is that (1) our technique relies only on discrete position\ndata of observed trajectories. Velocities or conjugate momenta do not need to be observed or approximated and no\nprior knowledge about the form of the variational principle is assumed. Instead, they are recovered using backward\nerror analysis. (2) Moreover, our technique compensates discretisation errors when trajectories are computed from the\nlearned system. This is important when moderate to large step-sizes are used and high accuracy is required. For this,\nwe introduce and rigorously analyse the concept of inverse modified Lagrangians by developing an inverse version of\nvariational backward error analysis. (3) Finally, we introduce a method to perform system identification from position\nobservations only, based on variational backward error analysis.","relation":"main_file","file_id":"32274","creator":"coffen","access_level":"open_access","date_created":"2022-06-28T15:25:50Z","file_name":"ShadowLagrangian_revision1_journal_style_arxiv.pdf","file_size":3640770,"title":"Variational Learning of Euler–Lagrange Dynamics from Data"}],"publisher":"Elsevier","author":[{"full_name":"Ober-Blöbaum, Sina","first_name":"Sina","id":"16494","last_name":"Ober-Blöbaum"},{"first_name":"Christian","full_name":"Offen, Christian","orcid":"0000-0002-5940-8057","last_name":"Offen","id":"85279"}],"quality_controlled":"1","file_date_updated":"2022-06-28T15:25:50Z","keyword":["Lagrangian learning","variational backward error analysis","modified Lagrangian","variational integrators","physics informed learning"],"publication":"Journal of Computational and Applied Mathematics","has_accepted_license":"1","status":"public","date_created":"2022-01-11T13:24:00Z","volume":421,"date_updated":"2023-08-10T08:42:39Z","oa":"1","doi":"10.1016/j.cam.2022.114780","language":[{"iso":"eng"}],"external_id":{"arxiv":["2112.12619"]},"related_material":{"link":[{"relation":"software","url":"https://github.com/Christian-Offen/LagrangianShadowIntegration"}]},"title":"Variational Learning of Euler–Lagrange Dynamics from Data","department":[{"_id":"636"}],"publication_identifier":{"issn":["0377-0427"]},"publication_status":"epub_ahead"},{"type":"conference","citation":{"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.","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} }","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.","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.","short":"H. Halimeh, M. Caron, O. Müller, in: Hawaii International Conference on System Sciences, 2023."},"year":"2023","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://scholarspace.manoa.hawaii.edu/items/2ddab486-5d2f-4302-8de3-a8b24017da3d"}],"oa":"1","conference":{"end_date":"2023-01-06","start_date":"2023-01-03","name":"Hawaii International Conference on System Sciences"},"_id":"45270","date_updated":"2024-01-10T15:16:37Z","publication_status":"published","date_created":"2023-05-25T10:25:21Z","status":"public","keyword":["Social Media and Healthcare Technology","early depression detection","liwc","mental health","transfer learning","transformer architectures"],"publication":"Hawaii International Conference on System Sciences","department":[{"_id":"195"},{"_id":"196"}],"author":[{"full_name":"Halimeh, Haya","first_name":"Haya","id":"87673","last_name":"Halimeh"},{"full_name":"Caron, Matthew","first_name":"Matthew","id":"60721","last_name":"Caron"},{"id":"72849","last_name":"Müller","full_name":"Müller, Oliver","first_name":"Oliver"}],"title":"Early Depression Detection with Transformer Models: Analyzing the Relationship between Linguistic and Psychology-Based Features","related_material":{"link":[{"relation":"confirmation","url":"https://hdl.handle.net/10125/103046"}]},"user_id":"60721","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."}]},{"doi":"10.1007/978-3-031-47240-4_25","date_updated":"2024-01-13T11:48:28Z","language":[{"iso":"eng"}],"series_title":" Lecture Notes in Computer Science","title":"TemporalFC: A Temporal Fact Checking Approach over Knowledge Graphs","place":"Cham","publication_status":"published","publication_identifier":{"issn":["0302-9743","1611-3349"],"isbn":["9783031472398","9783031472404"]},"editor":[{"last_name":"R. Payne","first_name":"Terry","full_name":"R. Payne, Terry"},{"last_name":"Presutti","full_name":"Presutti, Valentina","first_name":"Valentina"},{"full_name":"Qi, Guilin","first_name":"Guilin","last_name":"Qi"},{"first_name":"María","full_name":"Poveda-Villalón, María","last_name":"Poveda-Villalón"},{"full_name":"Stoilos, Giorgos","first_name":"Giorgos","last_name":"Stoilos"},{"last_name":"Hollink","first_name":"Laura","full_name":"Hollink, Laura"},{"first_name":"Zoi","full_name":"Kaoudi, Zoi","last_name":"Kaoudi"},{"last_name":"Cheng","first_name":"Gong","full_name":"Cheng, Gong"},{"first_name":"Juanzi","full_name":"Li, Juanzi","last_name":"Li"}],"project":[{"grant_number":"860801","name":"KnowGraphs: KnowGraphs: Knowledge Graphs at Scale","_id":"410"}],"department":[{"_id":"34"}],"conference":{"end_date":"2023-11-10","name":"The Semantic Web – ISWC 2023","start_date":"2023-11-06","location":"Athens, Greece"},"intvolume":" 14265","_id":"50479","page":"465–483","year":"2023","citation":{"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.","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.","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} }","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.","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","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","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."},"type":"conference","ddc":["006"],"user_id":"83392","abstract":[{"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.","lang":"eng"}],"volume":14265,"jel":["C"],"date_created":"2024-01-13T11:22:15Z","has_accepted_license":"1","status":"public","publication":"The Semantic Web – ISWC 2023","keyword":["temporal fact checking · ensemble learning · transfer learning · time-point prediction · temporal knowledge graphs"],"file_date_updated":"2024-01-13T11:25:48Z","publisher":"Springer, Cham","author":[{"full_name":"Qudus, Umair","first_name":"Umair","last_name":"Qudus"},{"full_name":"Röder, Michael","first_name":"Michael","last_name":"Röder"},{"last_name":"Kirrane","full_name":"Kirrane, Sabrina","first_name":"Sabrina"},{"last_name":"Ngomo","first_name":"Axel-Cyrille Ngonga","full_name":"Ngomo, Axel-Cyrille Ngonga"}],"file":[{"access_level":"closed","date_created":"2024-01-13T11:25:48Z","file_name":"ISWC 2023 TemporalFC-A Temporal Fact Checking approach over Knowledge Graphs.pdf","success":1,"relation":"main_file","content_type":"application/pdf","date_updated":"2024-01-13T11:25:48Z","creator":"uqudus","file_id":"50480","file_size":1944818}]},{"title":"Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing","publication_status":"published","department":[{"_id":"152"}],"doi":"10.5162/smsi2023/d7.4","date_updated":"2024-03-25T11:05:53Z","language":[{"iso":"eng"}],"user_id":"5905","abstract":[{"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.","lang":"eng"}],"date_created":"2024-03-25T10:16:24Z","status":"public","publication":"Lectures","keyword":["synthetic training data","machine vision quality gates","deep learning","automated inspection and quality control","production control"],"author":[{"first_name":"Iris","full_name":"Gräßler, Iris","orcid":"0000-0001-5765-971X","last_name":"Gräßler","id":"47565"},{"id":"72252","last_name":"Hieb","full_name":"Hieb, Michael","first_name":"Michael"}],"quality_controlled":"1","publisher":"AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany","conference":{"name":"SMSI 2023. Sensor and Measurement Science International","start_date":"2023-05-08","location":"Nuremberg","end_date":"2023-05-11"},"_id":"52816","page":"253-524","year":"2023","citation":{"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.","short":"I. Gräßler, M. Hieb, in: Lectures, AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 2023, pp. 253–524.","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.","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.","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"},"type":"conference"},{"year":"2023","type":"journal_article","citation":{"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} }","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.","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","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","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.","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)."},"language":[{"iso":"eng"}],"intvolume":" 5","_id":"49434","date_updated":"2024-03-27T11:27:33Z","doi":"10.11576/DIMAWE-6699","issue":"4","keyword":["Rollenspiel","mulitprofessionelle Kooperation","inklusionssensible Lehrerbildung","Hochschuldidaktik","Blended Learning"],"publication":"Zeitschrift für Konzepte Und Arbeitsmaterialien für Lehrer*innenbildung Und Unterricht","department":[{"_id":"479"}],"author":[{"full_name":"Schuldt, Alessa ","first_name":"Alessa ","last_name":"Schuldt"},{"last_name":"Palm","full_name":"Palm, Manfred","first_name":"Manfred"},{"id":"95559","last_name":"Neumann","full_name":"Neumann, Phillip","first_name":"Phillip"},{"first_name":"Oliver","full_name":"Böhm-Kasper, Oliver","last_name":"Böhm-Kasper"},{"last_name":"Demmer","first_name":"Christine","full_name":"Demmer, Christine"},{"first_name":"Birgit","full_name":"Lütje-Klose, Birgit","last_name":"Lütje-Klose"}],"volume":5,"date_created":"2023-12-04T10:11:17Z","status":"public","abstract":[{"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.","lang":"ger"}],"title":"„Jede*r von uns sieht die Situation eben unterschiedlich – das ist zwar eine Schwierigkeit, aber auch eine Bereicherung“","user_id":"77750"},{"date_created":"2022-03-10T18:28:14Z","has_accepted_license":"1","status":"public","publication":"IEEE/IFIP Network Operations and Management Symposium (NOMS)","file_date_updated":"2022-03-10T18:25:41Z","keyword":["wireless mobile networks","network management","continuous control","cognitive networks","autonomous coordination","reinforcement learning","gym environment","simulation","open source"],"author":[{"id":"35343","last_name":"Schneider","full_name":"Schneider, Stefan Balthasar","orcid":"0000-0001-8210-4011","first_name":"Stefan Balthasar"},{"last_name":"Werner","first_name":"Stefan","full_name":"Werner, Stefan"},{"last_name":"Khalili","full_name":"Khalili, Ramin","first_name":"Ramin"},{"last_name":"Hecker","first_name":"Artur","full_name":"Hecker, Artur"},{"id":"126","last_name":"Karl","full_name":"Karl, Holger","first_name":"Holger"}],"quality_controlled":"1","publisher":"IEEE","file":[{"access_level":"open_access","date_created":"2022-03-10T18:25:41Z","file_name":"author_version.pdf","relation":"main_file","date_updated":"2022-03-10T18:25:41Z","content_type":"application/pdf","file_id":"30237","creator":"stschn","file_size":223412}],"ddc":["004"],"user_id":"35343","abstract":[{"text":"Recent reinforcement learning approaches for continuous control in wireless mobile networks have shown impressive\r\nresults. But due to the lack of open and compatible simulators, authors typically create their own simulation environments for training and evaluation. This is cumbersome and time-consuming for authors and limits reproducibility and comparability, ultimately impeding progress in the field.\r\n\r\nTo this end, we propose mobile-env, a simple and open platform for training, evaluating, and comparing reinforcement learning and conventional approaches for continuous control in mobile wireless networks. mobile-env is lightweight and implements the common OpenAI Gym interface and additional wrappers, which allows connecting virtually any single-agent or multi-agent reinforcement learning framework to the environment. While mobile-env provides sensible default values and can be used out of the box, it also has many configuration options and is easy to extend. We therefore believe mobile-env to be a valuable platform for driving meaningful progress in autonomous coordination of\r\nwireless mobile networks.","lang":"eng"}],"year":"2022","type":"conference","citation":{"short":"S.B. Schneider, S. Werner, R. Khalili, A. Hecker, H. Karl, in: IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, 2022.","ieee":"S. B. Schneider, S. Werner, R. Khalili, A. Hecker, and H. Karl, “mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks,” presented at the IEEE/IFIP Network Operations and Management Symposium (NOMS), Budapest, 2022.","ama":"Schneider SB, Werner S, Khalili R, Hecker A, Karl H. mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks. In: IEEE/IFIP Network Operations and Management Symposium (NOMS). IEEE; 2022.","apa":"Schneider, S. B., Werner, S., Khalili, R., Hecker, A., & Karl, H. (2022). mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks. IEEE/IFIP Network Operations and Management Symposium (NOMS). IEEE/IFIP Network Operations and Management Symposium (NOMS), Budapest.","chicago":"Schneider, Stefan Balthasar, Stefan Werner, Ramin Khalili, Artur Hecker, and Holger Karl. “Mobile-Env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks.” In IEEE/IFIP Network Operations and Management Symposium (NOMS). IEEE, 2022.","mla":"Schneider, Stefan Balthasar, et al. “Mobile-Env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks.” IEEE/IFIP Network Operations and Management Symposium (NOMS), IEEE, 2022.","bibtex":"@inproceedings{Schneider_Werner_Khalili_Hecker_Karl_2022, title={mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks}, booktitle={IEEE/IFIP Network Operations and Management Symposium (NOMS)}, publisher={IEEE}, author={Schneider, Stefan Balthasar and Werner, Stefan and Khalili, Ramin and Hecker, Artur and Karl, Holger}, year={2022} }"},"conference":{"end_date":"2022-04-29","start_date":"2022-04-25","name":"IEEE/IFIP Network Operations and Management Symposium (NOMS)","location":"Budapest"},"_id":"30236","project":[{"name":"SFB 901: SFB 901","_id":"1"},{"_id":"4","name":"SFB 901 - C: SFB 901 - Project Area C"},{"name":"SFB 901 - C4: SFB 901 - Subproject C4","_id":"16"}],"department":[{"_id":"75"}],"title":"mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks","language":[{"iso":"eng"}],"oa":"1","date_updated":"2022-03-10T18:28:19Z"}]