[{"date_updated":"2022-08-19T06:27:55Z","publisher":"IEEE","date_created":"2022-08-11T08:46:36Z","author":[{"orcid":"0000-0002-8480-7295","last_name":"Böcker","id":"66","full_name":"Böcker, Joachim","first_name":"Joachim"}],"title":"Concept Study of an LLC Converter with Magnetically Resonant Inductor","doi":"10.1109/speedam53979.2022.9842047","conference":{"location":"Sorrento, Italy","start_date":"2022-06","name":"SPEEDAM"},"publication_status":"published","year":"2022","citation":{"bibtex":"@inproceedings{Böcker_2022, title={Concept Study of an LLC Converter with Magnetically Resonant Inductor}, DOI={<a href=\"https://doi.org/10.1109/speedam53979.2022.9842047\">10.1109/speedam53979.2022.9842047</a>}, booktitle={2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)}, publisher={IEEE}, author={Böcker, Joachim}, year={2022} }","short":"J. Böcker, in: 2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM), IEEE, 2022.","mla":"Böcker, Joachim. “Concept Study of an LLC Converter with Magnetically Resonant Inductor.” <i>2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)</i>, IEEE, 2022, doi:<a href=\"https://doi.org/10.1109/speedam53979.2022.9842047\">10.1109/speedam53979.2022.9842047</a>.","apa":"Böcker, J. (2022). Concept Study of an LLC Converter with Magnetically Resonant Inductor. <i>2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)</i>. SPEEDAM, Sorrento, Italy. <a href=\"https://doi.org/10.1109/speedam53979.2022.9842047\">https://doi.org/10.1109/speedam53979.2022.9842047</a>","ama":"Böcker J. Concept Study of an LLC Converter with Magnetically Resonant Inductor. In: <i>2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)</i>. IEEE; 2022. doi:<a href=\"https://doi.org/10.1109/speedam53979.2022.9842047\">10.1109/speedam53979.2022.9842047</a>","chicago":"Böcker, Joachim. “Concept Study of an LLC Converter with Magnetically Resonant Inductor.” In <i>2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)</i>. IEEE, 2022. <a href=\"https://doi.org/10.1109/speedam53979.2022.9842047\">https://doi.org/10.1109/speedam53979.2022.9842047</a>.","ieee":"J. Böcker, “Concept Study of an LLC Converter with Magnetically Resonant Inductor,” presented at the SPEEDAM, Sorrento, Italy, 2022, doi: <a href=\"https://doi.org/10.1109/speedam53979.2022.9842047\">10.1109/speedam53979.2022.9842047</a>."},"_id":"32796","department":[{"_id":"52"}],"user_id":"66","language":[{"iso":"eng"}],"publication":"2022 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)","type":"conference","status":"public"},{"ddc":["006"],"language":[{"iso":"eng"}],"file_date_updated":"2022-08-19T09:39:57Z","project":[{"name":"SFB 901: SFB 901","_id":"1"},{"name":"SFB 901 - B: SFB 901 - Project Area B","_id":"3"},{"_id":"10","name":"SFB 901 - B2: SFB 901 - Subproject B2"}],"_id":"33033","user_id":"38209","department":[{"_id":"34"},{"_id":"7"},{"_id":"26"}],"file":[{"file_name":"Final Bachelor Thesis.pdf","access_level":"open_access","file_id":"33034","file_size":24830795,"creator":"ahetzer","date_created":"2022-08-19T09:39:57Z","date_updated":"2022-08-19T09:39:57Z","relation":"main_file","content_type":"application/pdf"}],"status":"public","type":"bachelorsthesis","title":"Combined Ranking and Regression Trees for Algorithm Selection","oa":"1","date_updated":"2022-08-20T07:02:04Z","date_created":"2022-08-19T09:41:14Z","author":[{"last_name":"Fehring","id":"75695","full_name":"Fehring, Lukas","first_name":"Lukas"}],"place":"Paderborn","year":"2022","citation":{"short":"L. Fehring, Combined Ranking and Regression Trees for Algorithm Selection, Paderborn, 2022.","mla":"Fehring, Lukas. <i>Combined Ranking and Regression Trees for Algorithm Selection</i>. 2022.","bibtex":"@book{Fehring_2022, place={Paderborn}, title={Combined Ranking and Regression Trees for Algorithm Selection}, author={Fehring, Lukas}, year={2022} }","apa":"Fehring, L. (2022). <i>Combined Ranking and Regression Trees for Algorithm Selection</i>.","chicago":"Fehring, Lukas. <i>Combined Ranking and Regression Trees for Algorithm Selection</i>. Paderborn, 2022.","ieee":"L. Fehring, <i>Combined Ranking and Regression Trees for Algorithm Selection</i>. Paderborn, 2022.","ama":"Fehring L. <i>Combined Ranking and Regression Trees for Algorithm Selection</i>.; 2022."},"has_accepted_license":"1"},{"language":[{"iso":"eng"}],"_id":"33041","user_id":"44323","status":"public","type":"bachelorsthesis","title":"Untersuchung der physikalische Absorptionsmethoden zur Bestimmung von gasseitigen Stoffübergangskoeffizienten für strukturierte Packungen basierend auf hydrodynamischen Analogien","date_updated":"2022-08-19T14:17:48Z","supervisor":[{"first_name":"Luz Alejandra","id":"44323","full_name":"Mapura Ramirez, Luz Alejandra","last_name":"Mapura Ramirez"}],"author":[{"last_name":"Luan","full_name":"Luan, Yunhao","first_name":"Yunhao"}],"date_created":"2022-08-19T14:13:15Z","year":"2022","citation":{"mla":"Luan, Yunhao. <i>Untersuchung Der Physikalische Absorptionsmethoden Zur Bestimmung von Gasseitigen Stoffübergangskoeffizienten Für Strukturierte Packungen Basierend Auf Hydrodynamischen Analogien</i>. 2022.","bibtex":"@book{Luan_2022, title={Untersuchung der physikalische Absorptionsmethoden zur Bestimmung von gasseitigen Stoffübergangskoeffizienten für strukturierte Packungen basierend auf hydrodynamischen Analogien}, author={Luan, Yunhao}, year={2022} }","short":"Y. Luan, Untersuchung Der Physikalische Absorptionsmethoden Zur Bestimmung von Gasseitigen Stoffübergangskoeffizienten Für Strukturierte Packungen Basierend Auf Hydrodynamischen Analogien, 2022.","apa":"Luan, Y. (2022). <i>Untersuchung der physikalische Absorptionsmethoden zur Bestimmung von gasseitigen Stoffübergangskoeffizienten für strukturierte Packungen basierend auf hydrodynamischen Analogien</i>.","ama":"Luan Y. <i>Untersuchung Der Physikalische Absorptionsmethoden Zur Bestimmung von Gasseitigen Stoffübergangskoeffizienten Für Strukturierte Packungen Basierend Auf Hydrodynamischen Analogien</i>.; 2022.","chicago":"Luan, Yunhao. <i>Untersuchung Der Physikalische Absorptionsmethoden Zur Bestimmung von Gasseitigen Stoffübergangskoeffizienten Für Strukturierte Packungen Basierend Auf Hydrodynamischen Analogien</i>, 2022.","ieee":"Y. Luan, <i>Untersuchung der physikalische Absorptionsmethoden zur Bestimmung von gasseitigen Stoffübergangskoeffizienten für strukturierte Packungen basierend auf hydrodynamischen Analogien</i>. 2022."}},{"language":[{"iso":"ger"}],"user_id":"14932","department":[{"_id":"115"}],"_id":"32756","status":"public","type":"review","publication":"Zeitschrift für Angewandte Linguistik","title":"Hexenverhörprotokolle als sprachhistorisches Korpus. Fallstudien zur Erschließung der frühneuzeitlichen Schriftsprache","author":[{"first_name":"Friedrich","full_name":"Markewitz, Friedrich","id":"67227","last_name":"Markewitz"}],"date_created":"2022-08-09T19:39:59Z","volume":76,"date_updated":"2022-08-22T09:26:35Z","citation":{"ama":"Markewitz F. Hexenverhörprotokolle als sprachhistorisches Korpus. Fallstudien zur Erschließung der frühneuzeitlichen Schriftsprache. <i>Zeitschrift für Angewandte Linguistik</i>. 2022;76:130-138.","chicago":"Markewitz, Friedrich. “Hexenverhörprotokolle als sprachhistorisches Korpus. Fallstudien zur Erschließung der frühneuzeitlichen Schriftsprache.” <i>Zeitschrift für Angewandte Linguistik</i>, 2022.","ieee":"F. Markewitz, “Hexenverhörprotokolle als sprachhistorisches Korpus. Fallstudien zur Erschließung der frühneuzeitlichen Schriftsprache,” <i>Zeitschrift für Angewandte Linguistik</i>, vol. 76. pp. 130–138, 2022.","apa":"Markewitz, F. (2022). Hexenverhörprotokolle als sprachhistorisches Korpus. Fallstudien zur Erschließung der frühneuzeitlichen Schriftsprache. In <i>Zeitschrift für Angewandte Linguistik</i> (Vol. 76, pp. 130–138).","mla":"Markewitz, Friedrich. “Hexenverhörprotokolle als sprachhistorisches Korpus. Fallstudien zur Erschließung der frühneuzeitlichen Schriftsprache.” <i>Zeitschrift für Angewandte Linguistik</i>, vol. 76, 2022, pp. 130–38.","bibtex":"@article{Markewitz_2022, title={Hexenverhörprotokolle als sprachhistorisches Korpus. Fallstudien zur Erschließung der frühneuzeitlichen Schriftsprache}, volume={76}, journal={Zeitschrift für Angewandte Linguistik}, author={Markewitz, Friedrich}, year={2022}, pages={130–138} }","short":"F. Markewitz, Zeitschrift für Angewandte Linguistik 76 (2022) 130–138."},"page":"130-138","intvolume":"        76","year":"2022","publication_status":"published"},{"_id":"29934","department":[{"_id":"151"}],"series_title":"Lecture Notes in Mechanical Engineering","user_id":"77313","editor":[{"last_name":"Orlova","full_name":"Orlova, Anna","first_name":"Anna"},{"first_name":"David","full_name":"Cole, David","last_name":"Cole"}],"status":"public","type":"conference","conference":{"start_date":"2021-08-17","name":"27th IAVSD Symposium on Dynamics of Vehicles on Roads and Tracks, IAVSD 2021","location":"Saint Petersburg, Russia","end_date":"2021-08-19"},"doi":"10.1007/978-3-031-07305-2_92","main_file_link":[{"url":"https://link.springer.com/chapter/10.1007/978-3-031-07305-2_92"}],"date_updated":"2022-08-23T11:55:07Z","author":[{"first_name":"Lars","full_name":"Muth, Lars","id":"77313","last_name":"Muth","orcid":"0000-0002-2938-5616"},{"first_name":"Christian","last_name":"Noll","full_name":"Noll, Christian"},{"first_name":"Walter","last_name":"Sextro","full_name":"Sextro, Walter","id":"21220"}],"place":"Cham","citation":{"ama":"Muth L, Noll C, Sextro W. Generation of a Reduced, Representative, Virtual Test Drive for Fast Evaluation of Tire Wear by Clustering of Driving Data. In: Orlova A, Cole D, eds. <i>Advances in Dynamics of Vehicles on Roads and Tracks II - Proceedings of the 27th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2021</i>. Lecture Notes in Mechanical Engineering. Springer; 2022. doi:<a href=\"https://doi.org/10.1007/978-3-031-07305-2_92\">10.1007/978-3-031-07305-2_92</a>","chicago":"Muth, Lars, Christian Noll, and Walter Sextro. “Generation of a Reduced, Representative, Virtual Test Drive for Fast Evaluation of Tire Wear by Clustering of Driving Data.” In <i>Advances in Dynamics of Vehicles on Roads and Tracks II - Proceedings of the 27th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2021</i>, edited by Anna Orlova and David Cole. Lecture Notes in Mechanical Engineering. Cham: Springer, 2022. <a href=\"https://doi.org/10.1007/978-3-031-07305-2_92\">https://doi.org/10.1007/978-3-031-07305-2_92</a>.","ieee":"L. Muth, C. Noll, and W. Sextro, “Generation of a Reduced, Representative, Virtual Test Drive for Fast Evaluation of Tire Wear by Clustering of Driving Data,” in <i>Advances in Dynamics of Vehicles on Roads and Tracks II - Proceedings of the 27th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2021</i>, Saint Petersburg, Russia, 2022, doi: <a href=\"https://doi.org/10.1007/978-3-031-07305-2_92\">10.1007/978-3-031-07305-2_92</a>.","apa":"Muth, L., Noll, C., &#38; Sextro, W. (2022). Generation of a Reduced, Representative, Virtual Test Drive for Fast Evaluation of Tire Wear by Clustering of Driving Data. In A. Orlova &#38; D. Cole (Eds.), <i>Advances in Dynamics of Vehicles on Roads and Tracks II - Proceedings of the 27th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2021</i>. Springer. <a href=\"https://doi.org/10.1007/978-3-031-07305-2_92\">https://doi.org/10.1007/978-3-031-07305-2_92</a>","short":"L. Muth, C. Noll, W. Sextro, in: A. Orlova, D. Cole (Eds.), Advances in Dynamics of Vehicles on Roads and Tracks II - Proceedings of the 27th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2021, Springer, Cham, 2022.","bibtex":"@inproceedings{Muth_Noll_Sextro_2022, place={Cham}, series={Lecture Notes in Mechanical Engineering}, title={Generation of a Reduced, Representative, Virtual Test Drive for Fast Evaluation of Tire Wear by Clustering of Driving Data}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-07305-2_92\">10.1007/978-3-031-07305-2_92</a>}, booktitle={Advances in Dynamics of Vehicles on Roads and Tracks II - Proceedings of the 27th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2021}, publisher={Springer}, author={Muth, Lars and Noll, Christian and Sextro, Walter}, editor={Orlova, Anna and Cole, David}, year={2022}, collection={Lecture Notes in Mechanical Engineering} }","mla":"Muth, Lars, et al. “Generation of a Reduced, Representative, Virtual Test Drive for Fast Evaluation of Tire Wear by Clustering of Driving Data.” <i>Advances in Dynamics of Vehicles on Roads and Tracks II - Proceedings of the 27th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2021</i>, edited by Anna Orlova and David Cole, Springer, 2022, doi:<a href=\"https://doi.org/10.1007/978-3-031-07305-2_92\">10.1007/978-3-031-07305-2_92</a>."},"publication_identifier":{"eisbn":["978-3-031-07305-2"],"isbn":["978-3-031-07304-5"]},"publication_status":"published","keyword":["Tire Wear","Vehicle Dynamics","Clustering","Virtual Test"],"language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Tire and road wear are a major source of emissions of nonexhaust particulate matter (PM) and make up the largest share of microplastics in the environment. To reduce tire wear through numerical optimization of a vehicle's suspension system, fast simulations of the representative usage of a vehicle are needed. Therefore, this contribution evaluates if instead of a full simulation of a representative test drive, only specific driving maneuvers resulting from a clustering of the driving data can be used to predict tire wear. As a measure for tire wear, the friction work between tire and road is calculated. It is shown that enough clusters result in negligible deviations between the total friction work of the full simulation and the cluster simulations as well as between the distributions of the friction work over the tire width. The calculation time can be reduced to about 1% of the full simulation."}],"publication":"Advances in Dynamics of Vehicles on Roads and Tracks II - Proceedings of the 27th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2021","title":"Generation of a Reduced, Representative, Virtual Test Drive for Fast Evaluation of Tire Wear by Clustering of Driving Data","publisher":"Springer","date_created":"2022-02-21T14:14:11Z","year":"2022","quality_controlled":"1"},{"language":[{"iso":"eng"}],"department":[{"_id":"34"},{"_id":"7"},{"_id":"26"}],"user_id":"38209","_id":"30867","external_id":{"arxiv":["2109.06234"]},"project":[{"_id":"1","name":"SFB 901: SFB 901"},{"_id":"3","name":"SFB 901 - B: SFB 901 - Project Area B"},{"name":"SFB 901 - B2: SFB 901 - Subproject B2","_id":"10"}],"status":"public","abstract":[{"lang":"eng","text":"In online algorithm selection (OAS), instances of an algorithmic problem\r\nclass are presented to an agent one after another, and the agent has to quickly\r\nselect a presumably best algorithm from a fixed set of candidate algorithms.\r\nFor decision problems such as satisfiability (SAT), quality typically refers to\r\nthe algorithm's runtime. As the latter is known to exhibit a heavy-tail\r\ndistribution, an algorithm is normally stopped when exceeding a predefined\r\nupper time limit. As a consequence, machine learning methods used to optimize\r\nan algorithm selection strategy in a data-driven manner need to deal with\r\nright-censored samples, a problem that has received little attention in the\r\nliterature so far. In this work, we revisit multi-armed bandit algorithms for\r\nOAS and discuss their capability of dealing with the problem. Moreover, we\r\nadapt them towards runtime-oriented losses, allowing for partially censored\r\ndata while keeping a space- and time-complexity independent of the time\r\nhorizon. In an extensive experimental evaluation on an adapted version of the\r\nASlib benchmark, we demonstrate that theoretically well-founded methods based\r\non Thompson sampling perform specifically strong and improve in comparison to\r\nexisting methods."}],"publication":"Proceedings of the 36th AAAI Conference on Artificial Intelligence","type":"preprint","title":"Machine Learning for Online Algorithm Selection under Censored Feedback","author":[{"last_name":"Tornede","id":"38209","full_name":"Tornede, Alexander","first_name":"Alexander"},{"first_name":"Viktor","full_name":"Bengs, Viktor","id":"76599","last_name":"Bengs"},{"id":"48129","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","first_name":"Eyke"}],"date_created":"2022-04-12T11:58:56Z","date_updated":"2022-08-24T12:44:27Z","publisher":"AAAI","citation":{"mla":"Tornede, Alexander, et al. “Machine Learning for Online Algorithm Selection under Censored Feedback.” <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence</i>, AAAI, 2022.","short":"A. Tornede, V. Bengs, E. Hüllermeier, Proceedings of the 36th AAAI Conference on Artificial Intelligence (2022).","bibtex":"@article{Tornede_Bengs_Hüllermeier_2022, title={Machine Learning for Online Algorithm Selection under Censored Feedback}, journal={Proceedings of the 36th AAAI Conference on Artificial Intelligence}, publisher={AAAI}, author={Tornede, Alexander and Bengs, Viktor and Hüllermeier, Eyke}, year={2022} }","apa":"Tornede, A., Bengs, V., &#38; Hüllermeier, E. (2022). Machine Learning for Online Algorithm Selection under Censored Feedback. In <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence</i>. AAAI.","chicago":"Tornede, Alexander, Viktor Bengs, and Eyke Hüllermeier. “Machine Learning for Online Algorithm Selection under Censored Feedback.” <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence</i>. AAAI, 2022.","ieee":"A. Tornede, V. Bengs, and E. Hüllermeier, “Machine Learning for Online Algorithm Selection under Censored Feedback,” <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence</i>. AAAI, 2022.","ama":"Tornede A, Bengs V, Hüllermeier E. Machine Learning for Online Algorithm Selection under Censored Feedback. <i>Proceedings of the 36th AAAI Conference on Artificial Intelligence</i>. Published online 2022."},"year":"2022"},{"language":[{"iso":"eng"}],"department":[{"_id":"34"},{"_id":"7"},{"_id":"26"}],"user_id":"38209","_id":"30865","external_id":{"arxiv":["2107.09414"]},"project":[{"name":"SFB 901: SFB 901","_id":"1"},{"_id":"3","name":"SFB 901 - B: SFB 901 - Project Area B"},{"_id":"10","name":"SFB 901 - B2: SFB 901 - Subproject B2"}],"status":"public","abstract":[{"lang":"eng","text":"The problem of selecting an algorithm that appears most suitable for a\r\nspecific instance of an algorithmic problem class, such as the Boolean\r\nsatisfiability problem, is called instance-specific algorithm selection. Over\r\nthe past decade, the problem has received considerable attention, resulting in\r\na number of different methods for algorithm selection. Although most of these\r\nmethods are based on machine learning, surprisingly little work has been done\r\non meta learning, that is, on taking advantage of the complementarity of\r\nexisting algorithm selection methods in order to combine them into a single\r\nsuperior algorithm selector. In this paper, we introduce the problem of meta\r\nalgorithm selection, which essentially asks for the best way to combine a given\r\nset of algorithm selectors. We present a general methodological framework for\r\nmeta algorithm selection as well as several concrete learning methods as\r\ninstantiations of this framework, essentially combining ideas of meta learning\r\nand ensemble learning. In an extensive experimental evaluation, we demonstrate\r\nthat ensembles of algorithm selectors can significantly outperform single\r\nalgorithm selectors and have the potential to form the new state of the art in\r\nalgorithm selection."}],"publication":"Machine Learning","type":"preprint","title":"Algorithm Selection on a Meta Level","author":[{"full_name":"Tornede, Alexander","id":"38209","last_name":"Tornede","first_name":"Alexander"},{"last_name":"Gehring","full_name":"Gehring, Lukas","first_name":"Lukas"},{"last_name":"Tornede","id":"40795","full_name":"Tornede, Tanja","first_name":"Tanja"},{"full_name":"Wever, Marcel Dominik","id":"33176","orcid":" https://orcid.org/0000-0001-9782-6818","last_name":"Wever","first_name":"Marcel Dominik"},{"first_name":"Eyke","full_name":"Hüllermeier, Eyke","id":"48129","last_name":"Hüllermeier"}],"date_created":"2022-04-12T11:55:18Z","date_updated":"2022-08-24T12:45:39Z","citation":{"mla":"Tornede, Alexander, et al. “Algorithm Selection on a Meta Level.” <i>Machine Learning</i>, 2022.","short":"A. Tornede, L. Gehring, T. Tornede, M.D. Wever, E. Hüllermeier, Machine Learning (2022).","bibtex":"@article{Tornede_Gehring_Tornede_Wever_Hüllermeier_2022, title={Algorithm Selection on a Meta Level}, journal={Machine Learning}, author={Tornede, Alexander and Gehring, Lukas and Tornede, Tanja and Wever, Marcel Dominik and Hüllermeier, Eyke}, year={2022} }","apa":"Tornede, A., Gehring, L., Tornede, T., Wever, M. D., &#38; Hüllermeier, E. (2022). Algorithm Selection on a Meta Level. In <i>Machine Learning</i>.","ama":"Tornede A, Gehring L, Tornede T, Wever MD, Hüllermeier E. Algorithm Selection on a Meta Level. <i>Machine Learning</i>. Published online 2022.","chicago":"Tornede, Alexander, Lukas Gehring, Tanja Tornede, Marcel Dominik Wever, and Eyke Hüllermeier. “Algorithm Selection on a Meta Level.” <i>Machine Learning</i>, 2022.","ieee":"A. Tornede, L. Gehring, T. Tornede, M. D. Wever, and E. Hüllermeier, “Algorithm Selection on a Meta Level,” <i>Machine Learning</i>. 2022."},"year":"2022"},{"publication_identifier":{"unknown":["9783844086676 "]},"year":"2022","citation":{"apa":"Fuhrmann, A., Schoch, R., Rusam, A., Bosse, M., Flachmann, F., Moritzer, E., Hochrein, T., &#38; Bastian, M. (2022). <i>Verbessertes Füllverhalten im Spritzgießprozess durch Schäumen von WPC: Bewertung des Fließverhaltens treibmittelbeladener Polymerschmelzen</i>. Shaker.","bibtex":"@book{Fuhrmann_Schoch_Rusam_Bosse_Flachmann_Moritzer_Hochrein_Bastian_2022, title={Verbessertes Füllverhalten im Spritzgießprozess durch Schäumen von WPC: Bewertung des Fließverhaltens treibmittelbeladener Polymerschmelzen}, publisher={Shaker}, author={Fuhrmann, Anika and Schoch, Rebecca  and Rusam, Alexander and Bosse, Michael and Flachmann, Felix and Moritzer, Elmar and Hochrein, Thomas and Bastian, Martin}, year={2022} }","mla":"Fuhrmann, Anika, et al. <i>Verbessertes Füllverhalten Im Spritzgießprozess Durch Schäumen von WPC: Bewertung Des Fließverhaltens Treibmittelbeladener Polymerschmelzen</i>. Shaker, 2022.","short":"A. Fuhrmann, R. Schoch, A. Rusam, M. Bosse, F. Flachmann, E. Moritzer, T. Hochrein, M. Bastian, Verbessertes Füllverhalten Im Spritzgießprozess Durch Schäumen von WPC: Bewertung Des Fließverhaltens Treibmittelbeladener Polymerschmelzen, Shaker, 2022.","chicago":"Fuhrmann, Anika, Rebecca  Schoch, Alexander Rusam, Michael Bosse, Felix Flachmann, Elmar Moritzer, Thomas Hochrein, and Martin Bastian. <i>Verbessertes Füllverhalten Im Spritzgießprozess Durch Schäumen von WPC: Bewertung Des Fließverhaltens Treibmittelbeladener Polymerschmelzen</i>. Shaker, 2022.","ieee":"A. Fuhrmann <i>et al.</i>, <i>Verbessertes Füllverhalten im Spritzgießprozess durch Schäumen von WPC: Bewertung des Fließverhaltens treibmittelbeladener Polymerschmelzen</i>. Shaker, 2022.","ama":"Fuhrmann A, Schoch R, Rusam A, et al. <i>Verbessertes Füllverhalten Im Spritzgießprozess Durch Schäumen von WPC: Bewertung Des Fließverhaltens Treibmittelbeladener Polymerschmelzen</i>. Shaker; 2022."},"date_updated":"2022-08-24T07:16:33Z","publisher":"Shaker","date_created":"2022-08-22T11:51:59Z","author":[{"full_name":"Fuhrmann, Anika","last_name":"Fuhrmann","first_name":"Anika"},{"full_name":"Schoch, Rebecca ","last_name":"Schoch","first_name":"Rebecca "},{"full_name":"Rusam, Alexander","last_name":"Rusam","first_name":"Alexander"},{"last_name":"Bosse","full_name":"Bosse, Michael","first_name":"Michael"},{"first_name":"Felix","id":"38212","full_name":"Flachmann, Felix","orcid":"0000-0002-7651-7028","last_name":"Flachmann"},{"last_name":"Moritzer","id":"20531","full_name":"Moritzer, Elmar","first_name":"Elmar"},{"last_name":"Hochrein","full_name":"Hochrein, Thomas","first_name":"Thomas"},{"first_name":"Martin","last_name":"Bastian","full_name":"Bastian, Martin"}],"title":"Verbessertes Füllverhalten im Spritzgießprozess durch Schäumen von WPC: Bewertung des Fließverhaltens treibmittelbeladener Polymerschmelzen","type":"report","status":"public","_id":"33070","department":[{"_id":"321"},{"_id":"9"},{"_id":"367"},{"_id":"147"}],"user_id":"38212","language":[{"iso":"eng"}]},{"date_created":"2022-08-24T12:51:07Z","author":[{"last_name":"Gevers","full_name":"Gevers, Karina","id":"83151","first_name":"Karina"},{"last_name":"Tornede","id":"38209","full_name":"Tornede, Alexander","first_name":"Alexander"},{"first_name":"Marcel Dominik","id":"33176","full_name":"Wever, Marcel Dominik","orcid":" https://orcid.org/0000-0001-9782-6818","last_name":"Wever"},{"first_name":"Volker","full_name":"Schöppner, Volker","id":"20530","last_name":"Schöppner"},{"id":"48129","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","first_name":"Eyke"}],"publisher":"Springer Science and Business Media LLC","date_updated":"2022-08-24T12:52:06Z","doi":"10.1007/s40194-022-01339-9","title":"A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials","publication_identifier":{"issn":["0043-2288","1878-6669"]},"publication_status":"published","citation":{"short":"K. Gevers, A. Tornede, M.D. Wever, V. Schöppner, E. Hüllermeier, Welding in the World (2022).","mla":"Gevers, Karina, et al. “A Comparison of Heuristic, Statistical, and Machine Learning Methods for Heated Tool Butt Welding of Two Different Materials.” <i>Welding in the World</i>, Springer Science and Business Media LLC, 2022, doi:<a href=\"https://doi.org/10.1007/s40194-022-01339-9\">10.1007/s40194-022-01339-9</a>.","bibtex":"@article{Gevers_Tornede_Wever_Schöppner_Hüllermeier_2022, title={A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials}, DOI={<a href=\"https://doi.org/10.1007/s40194-022-01339-9\">10.1007/s40194-022-01339-9</a>}, journal={Welding in the World}, publisher={Springer Science and Business Media LLC}, author={Gevers, Karina and Tornede, Alexander and Wever, Marcel Dominik and Schöppner, Volker and Hüllermeier, Eyke}, year={2022} }","apa":"Gevers, K., Tornede, A., Wever, M. D., Schöppner, V., &#38; Hüllermeier, E. (2022). A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials. <i>Welding in the World</i>. <a href=\"https://doi.org/10.1007/s40194-022-01339-9\">https://doi.org/10.1007/s40194-022-01339-9</a>","ama":"Gevers K, Tornede A, Wever MD, Schöppner V, Hüllermeier E. A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials. <i>Welding in the World</i>. Published online 2022. doi:<a href=\"https://doi.org/10.1007/s40194-022-01339-9\">10.1007/s40194-022-01339-9</a>","ieee":"K. Gevers, A. Tornede, M. D. Wever, V. Schöppner, and E. Hüllermeier, “A comparison of heuristic, statistical, and machine learning methods for heated tool butt welding of two different materials,” <i>Welding in the World</i>, 2022, doi: <a href=\"https://doi.org/10.1007/s40194-022-01339-9\">10.1007/s40194-022-01339-9</a>.","chicago":"Gevers, Karina, Alexander Tornede, Marcel Dominik Wever, Volker Schöppner, and Eyke Hüllermeier. “A Comparison of Heuristic, Statistical, and Machine Learning Methods for Heated Tool Butt Welding of Two Different Materials.” <i>Welding in the World</i>, 2022. <a href=\"https://doi.org/10.1007/s40194-022-01339-9\">https://doi.org/10.1007/s40194-022-01339-9</a>."},"year":"2022","user_id":"38209","_id":"33090","project":[{"name":"SFB 901: SFB 901","_id":"1"},{"_id":"3","name":"SFB 901 - B: SFB 901 - Project Area B"},{"_id":"10","name":"SFB 901 - B2: SFB 901 - Subproject B2"}],"language":[{"iso":"eng"}],"keyword":["Metals and Alloys","Mechanical Engineering","Mechanics of Materials"],"publication":"Welding in the World","type":"journal_article","status":"public","abstract":[{"text":"<jats:title>Abstract</jats:title><jats:p>Heated tool butt welding is a method often used for joining thermoplastics, especially when the components are made out of different materials. The quality of the connection between the components crucially depends on a suitable choice of the parameters of the welding process, such as heating time, temperature, and the precise way how the parts are then welded. Moreover, when different materials are to be joined, the parameter values need to be tailored to the specifics of the respective material. To this end, in this paper, three approaches to tailor the parameter values to optimize the quality of the connection are compared: a heuristic by Potente, statistical experimental design, and Bayesian optimization. With the suitability for practice in mind, a series of experiments are carried out with these approaches, and their capabilities of proposing well-performing parameter values are investigated. As a result, Bayesian optimization is found to yield peak performance, but the costs for optimization are substantial. In contrast, the Potente heuristic does not require any experimentation and recommends parameter values with competitive quality.</jats:p>","lang":"eng"}]},{"language":[{"iso":"eng"}],"_id":"33150","external_id":{"arxiv":["2208.12094"]},"department":[{"_id":"101"},{"_id":"655"}],"user_id":"47427","abstract":[{"text":"In this article, we build on previous work to present an optimization algorithm for nonlinearly constrained multi-objective optimization problems. The algorithm combines a surrogate-assisted derivative-free trust-region approach with the filter method known from single-objective optimization. Instead of the true objective and constraint functions, so-called fully linear models are employed and we show how to deal with the gradient inexactness in the composite step setting, adapted from single-objective optimization as well. Under standard assumptions, we prove convergence of a subset of iterates to a quasi-stationary point and if constraint qualifications hold, then the limit point is also a KKT-point of the multi-objective problem.","lang":"eng"}],"status":"public","publication":"arXiv:2208.12094","type":"preprint","title":"Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients","main_file_link":[{"open_access":"1","url":"https://arxiv.org/pdf/2208.12094"}],"oa":"1","date_updated":"2022-08-26T06:12:10Z","author":[{"first_name":"Manuel Bastian","last_name":"Berkemeier","full_name":"Berkemeier, Manuel Bastian","id":"51701"},{"orcid":"0000-0002-3389-793X","last_name":"Peitz","full_name":"Peitz, Sebastian","id":"47427","first_name":"Sebastian"}],"date_created":"2022-08-26T06:08:06Z","year":"2022","citation":{"mla":"Berkemeier, Manuel Bastian, and Sebastian Peitz. “Multi-Objective Trust-Region Filter Method for Nonlinear Constraints Using Inexact Gradients.” <i>ArXiv:2208.12094</i>, 2022.","short":"M.B. Berkemeier, S. Peitz, ArXiv:2208.12094 (2022).","bibtex":"@article{Berkemeier_Peitz_2022, title={Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients}, journal={arXiv:2208.12094}, author={Berkemeier, Manuel Bastian and Peitz, Sebastian}, year={2022} }","apa":"Berkemeier, M. B., &#38; Peitz, S. (2022). Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. In <i>arXiv:2208.12094</i>.","ama":"Berkemeier MB, Peitz S. Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. <i>arXiv:220812094</i>. Published online 2022.","ieee":"M. B. Berkemeier and S. Peitz, “Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients,” <i>arXiv:2208.12094</i>. 2022.","chicago":"Berkemeier, Manuel Bastian, and Sebastian Peitz. “Multi-Objective Trust-Region Filter Method for Nonlinear Constraints Using Inexact Gradients.” <i>ArXiv:2208.12094</i>, 2022."}},{"language":[{"iso":"eng"}],"keyword":["Economics and Econometrics"],"department":[{"_id":"475"},{"_id":"200"},{"_id":"202"}],"user_id":"14931","_id":"33221","status":"public","abstract":[{"lang":"eng","text":"<jats:title>Abstract</jats:title><jats:p>Non-pharmaceutical interventions are an effective strategy to prevent and control COVID-19 transmission in the community. However, the timing and stringency to which these measures have been implemented varied between countries and regions. The differences in stringency can only to a limited extent be explained by the number of infections and the prevailing vaccination strategies. Our study aims to shed more light on the lockdown strategies and to identify the determinants underlying the differences between countries on regional, economic, institutional, and political level. Based on daily panel data for 173 countries and the period from January 2020 to October 2021 we find significant regional differences in lockdown strategies. Further, more prosperous countries implemented milder restrictions but responded more quickly, while poorer countries introduced more stringent measures but had a longer response time. Finally, democratic regimes and stronger manifested institutions alleviated and slowed down the introduction of lockdown measures.</jats:p>"}],"publication":"Journal of Regulatory Economics","type":"journal_article","doi":"10.1007/s11149-022-09452-9","title":"Differences in NPI strategies against COVID-19","author":[{"first_name":"Margarete","id":"135","full_name":"Redlin, Margarete","last_name":"Redlin"}],"date_created":"2022-08-29T06:49:33Z","date_updated":"2022-08-29T08:38:12Z","publisher":"Springer Science and Business Media LLC","citation":{"chicago":"Redlin, Margarete. “Differences in NPI Strategies against COVID-19.” <i>Journal of Regulatory Economics</i>, 2022. <a href=\"https://doi.org/10.1007/s11149-022-09452-9\">https://doi.org/10.1007/s11149-022-09452-9</a>.","ieee":"M. Redlin, “Differences in NPI strategies against COVID-19,” <i>Journal of Regulatory Economics</i>, 2022, doi: <a href=\"https://doi.org/10.1007/s11149-022-09452-9\">10.1007/s11149-022-09452-9</a>.","ama":"Redlin M. Differences in NPI strategies against COVID-19. <i>Journal of Regulatory Economics</i>. Published online 2022. doi:<a href=\"https://doi.org/10.1007/s11149-022-09452-9\">10.1007/s11149-022-09452-9</a>","apa":"Redlin, M. (2022). Differences in NPI strategies against COVID-19. <i>Journal of Regulatory Economics</i>. <a href=\"https://doi.org/10.1007/s11149-022-09452-9\">https://doi.org/10.1007/s11149-022-09452-9</a>","short":"M. Redlin, Journal of Regulatory Economics (2022).","mla":"Redlin, Margarete. “Differences in NPI Strategies against COVID-19.” <i>Journal of Regulatory Economics</i>, Springer Science and Business Media LLC, 2022, doi:<a href=\"https://doi.org/10.1007/s11149-022-09452-9\">10.1007/s11149-022-09452-9</a>.","bibtex":"@article{Redlin_2022, title={Differences in NPI strategies against COVID-19}, DOI={<a href=\"https://doi.org/10.1007/s11149-022-09452-9\">10.1007/s11149-022-09452-9</a>}, journal={Journal of Regulatory Economics}, publisher={Springer Science and Business Media LLC}, author={Redlin, Margarete}, year={2022} }"},"year":"2022","publication_identifier":{"issn":["0922-680X","1573-0468"]},"publication_status":"published"},{"year":"2022","intvolume":"        56","citation":{"short":"T. Gries, W. Naudé, Journal for Labour Market Research 56 (2022).","mla":"Gries, Thomas, and Wim Naudé. “Modelling Artificial Intelligence in Economics.” <i>Journal for Labour Market Research</i>, vol. 56, no. 1, 12, Springer Science and Business Media LLC, 2022, doi:<a href=\"https://doi.org/10.1186/s12651-022-00319-2\">10.1186/s12651-022-00319-2</a>.","bibtex":"@article{Gries_Naudé_2022, title={Modelling artificial intelligence in economics}, volume={56}, DOI={<a href=\"https://doi.org/10.1186/s12651-022-00319-2\">10.1186/s12651-022-00319-2</a>}, number={112}, journal={Journal for Labour Market Research}, publisher={Springer Science and Business Media LLC}, author={Gries, Thomas and Naudé, Wim}, year={2022} }","apa":"Gries, T., &#38; Naudé, W. (2022). Modelling artificial intelligence in economics. <i>Journal for Labour Market Research</i>, <i>56</i>(1), Article 12. <a href=\"https://doi.org/10.1186/s12651-022-00319-2\">https://doi.org/10.1186/s12651-022-00319-2</a>","ama":"Gries T, Naudé W. Modelling artificial intelligence in economics. <i>Journal for Labour Market Research</i>. 2022;56(1). doi:<a href=\"https://doi.org/10.1186/s12651-022-00319-2\">10.1186/s12651-022-00319-2</a>","ieee":"T. Gries and W. Naudé, “Modelling artificial intelligence in economics,” <i>Journal for Labour Market Research</i>, vol. 56, no. 1, Art. no. 12, 2022, doi: <a href=\"https://doi.org/10.1186/s12651-022-00319-2\">10.1186/s12651-022-00319-2</a>.","chicago":"Gries, Thomas, and Wim Naudé. “Modelling Artificial Intelligence in Economics.” <i>Journal for Labour Market Research</i> 56, no. 1 (2022). <a href=\"https://doi.org/10.1186/s12651-022-00319-2\">https://doi.org/10.1186/s12651-022-00319-2</a>."},"publication_identifier":{"issn":["2510-5019","2510-5027"]},"publication_status":"published","issue":"1","title":"Modelling artificial intelligence in economics","doi":"10.1186/s12651-022-00319-2","publisher":"Springer Science and Business Media LLC","date_updated":"2022-08-30T07:37:57Z","volume":56,"author":[{"full_name":"Gries, Thomas","id":"186","last_name":"Gries","first_name":"Thomas"},{"first_name":"Wim","full_name":"Naudé, Wim","last_name":"Naudé"}],"date_created":"2022-08-29T06:43:37Z","abstract":[{"lang":"eng","text":"<jats:title>Abstract</jats:title><jats:p>We provide a partial equilibrium model wherein AI provides abilities combined with human skills to provide an aggregate intermediate service good. We use the model to find that the extent of automation through AI will be greater if (a) the economy is relatively abundant in sophisticated programs and machine abilities compared to human skills; (b) the economy hosts a relatively large number of AI-providing firms and experts; and (c) the task-specific productivity of AI services is relatively high compared to the task-specific productivity of general labor and labor skills. We also illustrate that the contribution of AI to aggregate productive labor service depends not only on the amount of AI services available but on the endogenous number of automated tasks, the relative productivity of standard and IT-related labor, and the substitutability of tasks. These determinants also affect the income distribution between the two kinds of labor. We derive several empirical implications and identify possible future extensions.</jats:p>"}],"status":"public","publication":"Journal for Labour Market Research","type":"journal_article","keyword":["General Medicine"],"article_number":"12","language":[{"iso":"eng"}],"_id":"33220","department":[{"_id":"475"},{"_id":"200"},{"_id":"202"}],"user_id":"135"},{"editor":[{"first_name":"James","full_name":"Aspnes, James","last_name":"Aspnes"},{"last_name":"Michail","full_name":"Michail, Othon","first_name":"Othon"}],"status":"public","publication":"1st Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2022, March 28-30, 2022, Virtual Conference","type":"conference","language":[{"iso":"eng"}],"_id":"33230","project":[{"name":"SFB 901: SFB 901","_id":"1"},{"name":"SFB 901 - A: SFB 901 - Project Area A","_id":"2"},{"_id":"5","name":"SFB 901 - A1: SFB 901 - Subproject A1"}],"department":[{"_id":"79"}],"user_id":"15504","series_title":"LIPIcs","year":"2022","intvolume":"       221","page":"12:1–12:19","citation":{"bibtex":"@inproceedings{Daymude_Richa_Scheideler_2022, series={LIPIcs}, title={Local Mutual Exclusion for Dynamic, Anonymous, Bounded Memory Message Passing Systems}, volume={221}, DOI={<a href=\"https://doi.org/10.4230/LIPIcs.SAND.2022.12\">10.4230/LIPIcs.SAND.2022.12</a>}, booktitle={1st Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2022, March 28-30, 2022, Virtual Conference}, publisher={Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, author={Daymude, Joshua J. and Richa, Andréa W. and Scheideler, Christian}, editor={Aspnes, James and Michail, Othon}, year={2022}, pages={12:1–12:19}, collection={LIPIcs} }","mla":"Daymude, Joshua J., et al. “Local Mutual Exclusion for Dynamic, Anonymous, Bounded Memory Message Passing Systems.” <i>1st Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2022, March 28-30, 2022, Virtual Conference</i>, edited by James Aspnes and Othon Michail, vol. 221, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 12:1–12:19, doi:<a href=\"https://doi.org/10.4230/LIPIcs.SAND.2022.12\">10.4230/LIPIcs.SAND.2022.12</a>.","short":"J.J. Daymude, A.W. Richa, C. Scheideler, in: J. Aspnes, O. Michail (Eds.), 1st Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2022, March 28-30, 2022, Virtual Conference, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 12:1–12:19.","apa":"Daymude, J. J., Richa, A. W., &#38; Scheideler, C. (2022). Local Mutual Exclusion for Dynamic, Anonymous, Bounded Memory Message Passing Systems. In J. Aspnes &#38; O. Michail (Eds.), <i>1st Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2022, March 28-30, 2022, Virtual Conference</i> (Vol. 221, p. 12:1–12:19). Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href=\"https://doi.org/10.4230/LIPIcs.SAND.2022.12\">https://doi.org/10.4230/LIPIcs.SAND.2022.12</a>","ieee":"J. J. Daymude, A. W. Richa, and C. Scheideler, “Local Mutual Exclusion for Dynamic, Anonymous, Bounded Memory Message Passing Systems,” in <i>1st Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2022, March 28-30, 2022, Virtual Conference</i>, 2022, vol. 221, p. 12:1–12:19, doi: <a href=\"https://doi.org/10.4230/LIPIcs.SAND.2022.12\">10.4230/LIPIcs.SAND.2022.12</a>.","chicago":"Daymude, Joshua J., Andréa W. Richa, and Christian Scheideler. “Local Mutual Exclusion for Dynamic, Anonymous, Bounded Memory Message Passing Systems.” In <i>1st Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2022, March 28-30, 2022, Virtual Conference</i>, edited by James Aspnes and Othon Michail, 221:12:1–12:19. LIPIcs. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. <a href=\"https://doi.org/10.4230/LIPIcs.SAND.2022.12\">https://doi.org/10.4230/LIPIcs.SAND.2022.12</a>.","ama":"Daymude JJ, Richa AW, Scheideler C. Local Mutual Exclusion for Dynamic, Anonymous, Bounded Memory Message Passing Systems. In: Aspnes J, Michail O, eds. <i>1st Symposium on Algorithmic Foundations of Dynamic Networks, SAND 2022, March 28-30, 2022, Virtual Conference</i>. Vol 221. LIPIcs. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:12:1–12:19. doi:<a href=\"https://doi.org/10.4230/LIPIcs.SAND.2022.12\">10.4230/LIPIcs.SAND.2022.12</a>"},"title":"Local Mutual Exclusion for Dynamic, Anonymous, Bounded Memory Message Passing Systems","doi":"10.4230/LIPIcs.SAND.2022.12","publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","date_updated":"2022-08-30T06:33:44Z","volume":221,"date_created":"2022-08-30T06:31:21Z","author":[{"first_name":"Joshua J.","last_name":"Daymude","full_name":"Daymude, Joshua J."},{"full_name":"Richa, Andréa W.","last_name":"Richa","first_name":"Andréa W."},{"id":"20792","full_name":"Scheideler, Christian","last_name":"Scheideler","first_name":"Christian"}]},{"date_updated":"2022-08-30T07:35:51Z","publisher":"Informa UK Limited","volume":33,"date_created":"2022-08-29T06:41:11Z","author":[{"full_name":"Gries, Thomas","id":"186","last_name":"Gries","first_name":"Thomas"},{"first_name":"Veronika","last_name":"Müller","full_name":"Müller, Veronika"},{"first_name":"John T.","full_name":"Jost, John T.","last_name":"Jost"}],"title":"The Market for Belief Systems: A Formal Model of Ideological Choice","doi":"10.1080/1047840x.2022.2065128","publication_identifier":{"issn":["1047-840X","1532-7965"]},"publication_status":"published","issue":"2","year":"2022","intvolume":"        33","page":"65-83","citation":{"short":"T. Gries, V. Müller, J.T. Jost, Psychological Inquiry 33 (2022) 65–83.","mla":"Gries, Thomas, et al. “The Market for Belief Systems: A Formal Model of Ideological Choice.” <i>Psychological Inquiry</i>, vol. 33, no. 2, Informa UK Limited, 2022, pp. 65–83, doi:<a href=\"https://doi.org/10.1080/1047840x.2022.2065128\">10.1080/1047840x.2022.2065128</a>.","bibtex":"@article{Gries_Müller_Jost_2022, title={The Market for Belief Systems: A Formal Model of Ideological Choice}, volume={33}, DOI={<a href=\"https://doi.org/10.1080/1047840x.2022.2065128\">10.1080/1047840x.2022.2065128</a>}, number={2}, journal={Psychological Inquiry}, publisher={Informa UK Limited}, author={Gries, Thomas and Müller, Veronika and Jost, John T.}, year={2022}, pages={65–83} }","apa":"Gries, T., Müller, V., &#38; Jost, J. T. (2022). The Market for Belief Systems: A Formal Model of Ideological Choice. <i>Psychological Inquiry</i>, <i>33</i>(2), 65–83. <a href=\"https://doi.org/10.1080/1047840x.2022.2065128\">https://doi.org/10.1080/1047840x.2022.2065128</a>","ama":"Gries T, Müller V, Jost JT. The Market for Belief Systems: A Formal Model of Ideological Choice. <i>Psychological Inquiry</i>. 2022;33(2):65-83. doi:<a href=\"https://doi.org/10.1080/1047840x.2022.2065128\">10.1080/1047840x.2022.2065128</a>","ieee":"T. Gries, V. Müller, and J. T. Jost, “The Market for Belief Systems: A Formal Model of Ideological Choice,” <i>Psychological Inquiry</i>, vol. 33, no. 2, pp. 65–83, 2022, doi: <a href=\"https://doi.org/10.1080/1047840x.2022.2065128\">10.1080/1047840x.2022.2065128</a>.","chicago":"Gries, Thomas, Veronika Müller, and John T. Jost. “The Market for Belief Systems: A Formal Model of Ideological Choice.” <i>Psychological Inquiry</i> 33, no. 2 (2022): 65–83. <a href=\"https://doi.org/10.1080/1047840x.2022.2065128\">https://doi.org/10.1080/1047840x.2022.2065128</a>."},"_id":"33219","department":[{"_id":"202"},{"_id":"200"},{"_id":"475"}],"user_id":"135","keyword":["General Psychology"],"language":[{"iso":"eng"}],"publication":"Psychological Inquiry","type":"journal_article","status":"public"},{"year":"2022","citation":{"short":"T. Götte, C. Scheideler, in: K. Agrawal, I.-T.A. 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