[{"quality_controlled":"1","citation":{"bibtex":"@inproceedings{Osnabrügge_Tenberge_Fechner, title={Artificial Intelligence in primary science and technology education with a focus on implementation of AI in learning context – Results of a Scoping Review}, author={Osnabrügge, Malin and Tenberge, Claudia and Fechner, Sabine} }","ama":"Osnabrügge M, Tenberge C, Fechner S. Artificial Intelligence in primary science and technology education with a focus on implementation of AI in learning context – Results of a Scoping Review.","mla":"Osnabrügge, Malin, et al. <i>Artificial Intelligence in Primary Science and Technology Education with a Focus on Implementation of AI in Learning Context – Results of a Scoping Review</i>.","chicago":"Osnabrügge, Malin, Claudia Tenberge, and Sabine Fechner. “Artificial Intelligence in Primary Science and Technology Education with a Focus on Implementation of AI in Learning Context – Results of a Scoping Review,” n.d.","short":"M. Osnabrügge, C. Tenberge, S. Fechner, in: n.d.","ieee":"M. Osnabrügge, C. Tenberge, and S. Fechner, “Artificial Intelligence in primary science and technology education with a focus on implementation of AI in learning context – Results of a Scoping Review,” presented at the Pupils’ Attitudes Towards Technology (PATT), Norrköping, Sweden.","apa":"Osnabrügge, M., Tenberge, C., &#38; Fechner, S. (n.d.). <i>Artificial Intelligence in primary science and technology education with a focus on implementation of AI in learning context – Results of a Scoping Review</i>. Pupils’ Attitudes Towards Technology (PATT), Norrköping, Sweden."},"department":[{"_id":"386"},{"_id":"588"},{"_id":"33"}],"keyword":["Artificial intelligence","primary education","science and technology education"],"type":"conference","date_created":"2025-12-04T14:12:38Z","publication_status":"draft","date_updated":"2025-12-13T23:56:03Z","author":[{"id":"79748","full_name":"Osnabrügge, Malin","last_name":"Osnabrügge","first_name":"Malin"},{"first_name":"Claudia","last_name":"Tenberge","full_name":"Tenberge, Claudia","id":"67302"},{"id":"54823","full_name":"Fechner, Sabine","orcid":"0000-0001-5645-5870","first_name":"Sabine","last_name":"Fechner"}],"conference":{"start_date":"2026-06-15","name":"Pupils' Attitudes Towards Technology (PATT)","location":"Norrköping, Sweden","end_date":"2026-06-18"},"year":"2026","status":"public","title":"Artificial Intelligence in primary science and technology education with a focus on implementation of AI in learning context – Results of a Scoping Review","user_id":"54823","language":[{"iso":"eng"}],"_id":"62885"},{"department":[{"_id":"152"}],"type":"conference","keyword":["Tacit knowledge","Sustainability","Product Engineering","Artificial Intelligence"],"date_created":"2026-07-20T13:16:49Z","abstract":[{"text":"Tacit knowledge is particularly valuable in product engineering. Experiences reside in minds of employees and are not systematically documented but could have a significant influence on sustainable product engineering. Existing approaches do not offer sufficient support for harnessing technical tacit knowledge regarding sustainable product engineering. In this paper a three-step method is presented: The method contains knowledge acquisition, requirements extraction und requirements validation for quality assurance. Acquisition is performed by support artifacts like interview guidelines. Extraction is supported by Artificial Intelligence, converting statements into requirements. These requirements are validated using a specific questionnaire. The developed approach is applied in a funded project of the European Union (EU) with automotive industry partners. The method supports product engineers to collect tacit knowledge from experienced employees, transform unsystematic knowledge into standardized technical requirements and validate them. Application of this method enables creation of validated requirements that can be applied throughout the company and are not exclusively dependent on a single employee.","lang":"eng"}],"publication":"1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University","doi":"10.17619/UNIPB/1-2639","language":[{"iso":"eng"}],"series_title":"International Symposium on Hybrid Intelligence in Product and Production Engineering","intvolume":"         1","date_updated":"2026-08-13T09:02:56Z","publication_status":"published","author":[{"id":"98210","full_name":"Mansheim, Johanna","first_name":"Johanna","last_name":"Mansheim"},{"first_name":"Iris","last_name":"Gräßler","orcid":"0000-0001-5765-971X","full_name":"Gräßler, Iris","id":"47565"},{"id":"62841","last_name":"Pfeifer","first_name":"Jan Niklas","full_name":"Pfeifer, Jan Niklas"}],"year":"2026","title":"Harnessing tacit Knowledge from Sustainable Product Engineering through Artificial Intelligence","place":"Paderborn","quality_controlled":"1","citation":{"mla":"Mansheim, Johanna, et al. “Harnessing Tacit Knowledge from Sustainable Product Engineering through Artificial Intelligence.” <i>1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>, edited by Iris Graessler, vol. 1, Universitätsbibliothek, 2026, pp. 229–38, doi:<a href=\"https://doi.org/10.17619/UNIPB/1-2639\">10.17619/UNIPB/1-2639</a>.","ama":"Mansheim J, Gräßler I, Pfeifer JN. Harnessing tacit Knowledge from Sustainable Product Engineering through Artificial Intelligence. In: Graessler I, ed. <i>1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>. Vol 1. International Symposium on Hybrid Intelligence in Product and Production Engineering. Universitätsbibliothek; 2026:229-238. doi:<a href=\"https://doi.org/10.17619/UNIPB/1-2639\">10.17619/UNIPB/1-2639</a>","bibtex":"@inproceedings{Mansheim_Gräßler_Pfeifer_2026, place={Paderborn}, series={International Symposium on Hybrid Intelligence in Product and Production Engineering}, title={Harnessing tacit Knowledge from Sustainable Product Engineering through Artificial Intelligence}, volume={1}, DOI={<a href=\"https://doi.org/10.17619/UNIPB/1-2639\">10.17619/UNIPB/1-2639</a>}, booktitle={1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University}, publisher={Universitätsbibliothek}, author={Mansheim, Johanna and Gräßler, Iris and Pfeifer, Jan Niklas}, editor={Graessler, Iris}, year={2026}, pages={229–238}, collection={International Symposium on Hybrid Intelligence in Product and Production Engineering} }","apa":"Mansheim, J., Gräßler, I., &#38; Pfeifer, J. N. (2026). Harnessing tacit Knowledge from Sustainable Product Engineering through Artificial Intelligence. In I. Graessler (Ed.), <i>1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i> (Vol. 1, pp. 229–238). Universitätsbibliothek. <a href=\"https://doi.org/10.17619/UNIPB/1-2639\">https://doi.org/10.17619/UNIPB/1-2639</a>","ieee":"J. Mansheim, I. Gräßler, and J. N. Pfeifer, “Harnessing tacit Knowledge from Sustainable Product Engineering through Artificial Intelligence,” in <i>1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>, Paderborn, 2026, vol. 1, pp. 229–238, doi: <a href=\"https://doi.org/10.17619/UNIPB/1-2639\">10.17619/UNIPB/1-2639</a>.","short":"J. Mansheim, I. Gräßler, J.N. Pfeifer, in: I. Graessler (Ed.), 1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University, Universitätsbibliothek, Paderborn, 2026, pp. 229–238.","chicago":"Mansheim, Johanna, Iris Gräßler, and Jan Niklas Pfeifer. “Harnessing Tacit Knowledge from Sustainable Product Engineering through Artificial Intelligence.” In <i>1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>, edited by Iris Graessler, 1:229–38. International Symposium on Hybrid Intelligence in Product and Production Engineering. Paderborn: Universitätsbibliothek, 2026. <a href=\"https://doi.org/10.17619/UNIPB/1-2639\">https://doi.org/10.17619/UNIPB/1-2639</a>."},"editor":[{"last_name":"Graessler","first_name":"Iris","full_name":"Graessler, Iris"}],"volume":1,"user_id":"98210","_id":"66547","publisher":"Universitätsbibliothek","page":"229-238","conference":{"end_date":"2026-03-26","start_date":"2026-03-24","name":"International Symposium on Hybrid Intelligence in Product and Production Engineering 1. 2026 Paderborn","location":"Paderborn"},"status":"public"},{"date_created":"2026-08-24T14:31:30Z","type":"conference","keyword":["Requirements Engineering","Artificial Intelligence","Large Language Models","Generative AI"],"citation":{"apa":"Gräßler, I., &#38; Pfeifer, J. N. (2026). Performance evaluation of large language models in extracting requirements sets from technical documents. In I. Graessler (Ed.), <i>1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>. Universitätsbibliothek. <a href=\"https://doi.org/10.17619/UNIPB/1-2646\">https://doi.org/10.17619/UNIPB/1-2646</a>","ieee":"I. Gräßler and J. N. Pfeifer, “Performance evaluation of large language models in extracting requirements sets from technical documents,” in <i>1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>, Paderborn, 2026, doi: <a href=\"https://doi.org/10.17619/UNIPB/1-2646\">10.17619/UNIPB/1-2646</a>.","chicago":"Gräßler, Iris, and Jan Niklas Pfeifer. “Performance Evaluation of Large Language Models in Extracting Requirements Sets from Technical Documents.” In <i>1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>, edited by Iris Graessler. Universitätsbibliothek, 2026. <a href=\"https://doi.org/10.17619/UNIPB/1-2646\">https://doi.org/10.17619/UNIPB/1-2646</a>.","short":"I. Gräßler, J.N. Pfeifer, in: I. Graessler (Ed.), 1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University, Universitätsbibliothek, 2026.","mla":"Gräßler, Iris, and Jan Niklas Pfeifer. “Performance Evaluation of Large Language Models in Extracting Requirements Sets from Technical Documents.” <i>1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>, edited by Iris Graessler, Universitätsbibliothek, 2026, doi:<a href=\"https://doi.org/10.17619/UNIPB/1-2646\">10.17619/UNIPB/1-2646</a>.","ama":"Gräßler I, Pfeifer JN. Performance evaluation of large language models in extracting requirements sets from technical documents. In: Graessler I, ed. <i>1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University</i>. Universitätsbibliothek; 2026. doi:<a href=\"https://doi.org/10.17619/UNIPB/1-2646\">10.17619/UNIPB/1-2646</a>","bibtex":"@inproceedings{Gräßler_Pfeifer_2026, title={Performance evaluation of large language models in extracting requirements sets from technical documents}, DOI={<a href=\"https://doi.org/10.17619/UNIPB/1-2646\">10.17619/UNIPB/1-2646</a>}, booktitle={1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University}, publisher={Universitätsbibliothek}, author={Gräßler, Iris and Pfeifer, Jan Niklas}, editor={Graessler, Iris}, year={2026} }"},"publication":"1st International Symposium: March 24 – 26, 2026, Heinz Nixdorf Institute, Paderborn University","abstract":[{"text":"Manufacturers operate under dynamic regulatory conditions, leading to frequently changing requirements that must be managed with high effort. AI-based requirements extraction using Large Language Models (LLMs) has the potential to support engineers in this task by analyzing large documents, for example. Existing evaluation approaches in AI-supported requirements engineering mainly assess individual requirements and their consistency with source documents, while quality criteria of requirements sets are largely neglected. This paper presents a five-step approach to evaluate the performance of current LLMs in generating requirements sets: a systematic literature review to identify quality criteria of requirements sets (1), exemplary generation of requirements sets from the Machinery Directive 2006/42/EC using LLMs (2), examination (3), evaluation (4) and comparison (5) of the generated requirements sets. The results support engineers in selecting LLMs for creating requirement sets and in evaluating future LLMs.","lang":"eng"}],"quality_controlled":"1","_id":"66837","publisher":"Universitätsbibliothek","language":[{"iso":"eng"}],"editor":[{"first_name":"Iris","last_name":"Graessler","full_name":"Graessler, Iris"}],"user_id":"62841","doi":"10.17619/UNIPB/1-2646","author":[{"id":"47565","full_name":"Gräßler, Iris","first_name":"Iris","last_name":"Gräßler","orcid":"0000-0001-5765-971X"},{"last_name":"Pfeifer","first_name":"Jan Niklas","full_name":"Pfeifer, Jan Niklas","id":"62841"}],"conference":{"end_date":"26.03.2026","location":"Paderborn","name":"International Symposium on Hybrid Intelligence in Product and Production Engineering 1. 2026 Paderborn","start_date":"24.03.2026"},"title":"Performance evaluation of large language models in extracting requirements sets from technical documents","status":"public","year":"2026","has_accepted_license":"1","date_updated":"2026-08-24T14:41:41Z"},{"user_id":"54823","_id":"62920","language":[{"iso":"eng"}],"date_updated":"2025-12-05T13:05:59Z","conference":{"end_date":"2025-09-11","start_date":"2025-09-08","name":"GDCP Jahrestagung","location":"Frankfurt"},"author":[{"id":"80773","first_name":"Marvin Lee","last_name":"Fox","full_name":"Fox, Marvin Lee"},{"orcid":"https://orcid.org/ 0000-0002-7143-3781","last_name":"Peeters","first_name":"Hendrik","full_name":"Peeters, Hendrik","id":"49942"},{"id":"54823","last_name":"Fechner","first_name":"Sabine","orcid":"0000-0001-5645-5870","full_name":"Fechner, Sabine"}],"year":"2025","title":"KI-Einsatz durch Lernende im Erkenntnisgewinnungsprozess - ein Review","status":"public","department":[{"_id":"386"},{"_id":"33"}],"type":"conference_abstract","keyword":["Artificial intelligence","education","chemistry"],"date_created":"2025-12-05T12:53:09Z","citation":{"ieee":"M. L. Fox, H. Peeters, and S. Fechner, “KI-Einsatz durch Lernende im Erkenntnisgewinnungsprozess - ein Review,” presented at the GDCP Jahrestagung, Frankfurt, 2025.","apa":"Fox, M. L., Peeters, H., &#38; Fechner, S. (2025). KI-Einsatz durch Lernende im Erkenntnisgewinnungsprozess - ein Review. <i>GDCP Jahrestagung</i>. GDCP Jahrestagung, Frankfurt.","short":"M.L. Fox, H. Peeters, S. Fechner, in: GDCP Jahrestagung, 2025.","chicago":"Fox, Marvin Lee, Hendrik Peeters, and Sabine Fechner. “KI-Einsatz Durch Lernende Im Erkenntnisgewinnungsprozess - Ein Review.” In <i>GDCP Jahrestagung</i>, 2025.","mla":"Fox, Marvin Lee, et al. “KI-Einsatz Durch Lernende Im Erkenntnisgewinnungsprozess - Ein Review.” <i>GDCP Jahrestagung</i>, 2025.","bibtex":"@inproceedings{Fox_Peeters_Fechner_2025, title={KI-Einsatz durch Lernende im Erkenntnisgewinnungsprozess - ein Review}, booktitle={GDCP Jahrestagung}, author={Fox, Marvin Lee and Peeters, Hendrik and Fechner, Sabine}, year={2025} }","ama":"Fox ML, Peeters H, Fechner S. KI-Einsatz durch Lernende im Erkenntnisgewinnungsprozess - ein Review. In: <i>GDCP Jahrestagung</i>. ; 2025."},"publication":"GDCP Jahrestagung"},{"date_updated":"2025-12-12T06:13:51Z","year":"2025","status":"public","title":"An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization","author":[{"last_name":"Hernández","first_name":"Carlos","full_name":"Hernández, Carlos"},{"first_name":"Angel E.","last_name":"Rodriguez-Fernandez","full_name":"Rodriguez-Fernandez, Angel E."},{"last_name":"Schäpermeier","first_name":"Lennart","full_name":"Schäpermeier, Lennart"},{"full_name":"Cuate, Oliver","last_name":"Cuate","first_name":"Oliver"},{"id":"100740","orcid":"0000-0002-9788-8282","first_name":"Heike","last_name":"Trautmann","full_name":"Trautmann, Heike"},{"first_name":"Oliver","last_name":"Schütze","full_name":"Schütze, Oliver"}],"doi":"10.1109/TEVC.2025.3637276","user_id":"15504","page":"1-1","language":[{"iso":"eng"}],"_id":"63053","publication":"IEEE Transactions on Evolutionary Computation","citation":{"chicago":"Hernández, Carlos, Angel E. Rodriguez-Fernandez, Lennart Schäpermeier, Oliver Cuate, Heike Trautmann, and Oliver Schütze. “An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.” <i>IEEE Transactions on Evolutionary Computation</i>, 2025, 1–1. <a href=\"https://doi.org/10.1109/TEVC.2025.3637276\">https://doi.org/10.1109/TEVC.2025.3637276</a>.","short":"C. Hernández, A.E. Rodriguez-Fernandez, L. Schäpermeier, O. Cuate, H. Trautmann, O. Schütze, IEEE Transactions on Evolutionary Computation (2025) 1–1.","apa":"Hernández, C., Rodriguez-Fernandez, A. E., Schäpermeier, L., Cuate, O., Trautmann, H., &#38; Schütze, O. (2025). An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. <i>IEEE Transactions on Evolutionary Computation</i>, 1–1. <a href=\"https://doi.org/10.1109/TEVC.2025.3637276\">https://doi.org/10.1109/TEVC.2025.3637276</a>","ieee":"C. Hernández, A. E. Rodriguez-Fernandez, L. Schäpermeier, O. Cuate, H. Trautmann, and O. Schütze, “An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization,” <i>IEEE Transactions on Evolutionary Computation</i>, pp. 1–1, 2025, doi: <a href=\"https://doi.org/10.1109/TEVC.2025.3637276\">10.1109/TEVC.2025.3637276</a>.","ama":"Hernández C, Rodriguez-Fernandez AE, Schäpermeier L, Cuate O, Trautmann H, Schütze O. An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. <i>IEEE Transactions on Evolutionary Computation</i>. Published online 2025:1-1. doi:<a href=\"https://doi.org/10.1109/TEVC.2025.3637276\">10.1109/TEVC.2025.3637276</a>","bibtex":"@article{Hernández_Rodriguez-Fernandez_Schäpermeier_Cuate_Trautmann_Schütze_2025, title={An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization}, DOI={<a href=\"https://doi.org/10.1109/TEVC.2025.3637276\">10.1109/TEVC.2025.3637276</a>}, journal={IEEE Transactions on Evolutionary Computation}, author={Hernández, Carlos and Rodriguez-Fernandez, Angel E. and Schäpermeier, Lennart and Cuate, Oliver and Trautmann, Heike and Schütze, Oliver}, year={2025}, pages={1–1} }","mla":"Hernández, Carlos, et al. “An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.” <i>IEEE Transactions on Evolutionary Computation</i>, 2025, pp. 1–1, doi:<a href=\"https://doi.org/10.1109/TEVC.2025.3637276\">10.1109/TEVC.2025.3637276</a>."},"keyword":["Optimization","Evolutionary computation","Hands","Proposals","Convergence","Computational efficiency","Artificial intelligence","Accuracy","Approximation algorithms","Aerospace electronics","Multi-objective optimization","evolutionary algorithms","nearly optimal solutions","multimodal optimization","archiving","continuation"],"type":"journal_article","department":[{"_id":"819"}],"date_created":"2025-12-12T06:13:06Z"},{"citation":{"mla":"Fox, Marvin Lee, et al. “How Can Students Be Supported by ChatGPT as a Tutor in Hands-on Chemistry Education?” <i>Conference of The European Science Education Research Association (ESERA)</i>, 2025.","bibtex":"@inproceedings{Fox_Peeters_Fechner_2025, title={How can students be supported by ChatGPT as a tutor in hands-on chemistry education?}, booktitle={Conference of The European Science Education Research Association (ESERA)}, author={Fox, Marvin Lee and Peeters, Hendrik and Fechner, Sabine}, year={2025} }","ama":"Fox ML, Peeters H, Fechner S. How can students be supported by ChatGPT as a tutor in hands-on chemistry education? In: <i>Conference of The European Science Education Research Association (ESERA)</i>. ; 2025.","ieee":"M. L. Fox, H. Peeters, and S. Fechner, “How can students be supported by ChatGPT as a tutor in hands-on chemistry education?,” presented at the ESERA conference, Copenhagen, Denmark, 2025.","apa":"Fox, M. L., Peeters, H., &#38; Fechner, S. (2025). How can students be supported by ChatGPT as a tutor in hands-on chemistry education? <i>Conference of The European Science Education Research Association (ESERA)</i>. ESERA conference, Copenhagen, Denmark.","short":"M.L. Fox, H. Peeters, S. Fechner, in: Conference of The European Science Education Research Association (ESERA), 2025.","chicago":"Fox, Marvin Lee, Hendrik Peeters, and Sabine Fechner. “How Can Students Be Supported by ChatGPT as a Tutor in Hands-on Chemistry Education?” In <i>Conference of The European Science Education Research Association (ESERA)</i>, 2025."},"publication":"Conference of The European Science Education Research Association (ESERA)","quality_controlled":"1","date_created":"2025-12-05T12:57:51Z","department":[{"_id":"386"},{"_id":"33"}],"keyword":["Artificial intelligence","education","chemistry"],"type":"conference_abstract","conference":{"location":"Copenhagen, Denmark","name":"ESERA conference","start_date":"2025-09-25","end_date":"2025-09-29"},"author":[{"id":"80773","first_name":"Marvin Lee","last_name":"Fox","full_name":"Fox, Marvin Lee"},{"full_name":"Peeters, Hendrik","first_name":"Hendrik","orcid":"https://orcid.org/ 0000-0002-7143-3781","last_name":"Peeters","id":"49942"},{"id":"54823","full_name":"Fechner, Sabine","first_name":"Sabine","last_name":"Fechner","orcid":"0000-0001-5645-5870"}],"year":"2025","title":"How can students be supported by ChatGPT as a tutor in hands-on chemistry education?","status":"public","date_updated":"2025-12-13T23:54:59Z","_id":"62921","language":[{"iso":"eng"}],"user_id":"54823"},{"publication":"at - Automatisierungstechnik","issue":"1","abstract":[{"text":"This paper presents the concept of Information Circularity Assistance, which provides decision support in the early stages of product creation for Circular Economy. Engineers in strategic product planning need to proactively predict the quantity, quality, and timing of secondary materials and returned components. For example, products with high recycled content will only be economically sustainable if the material is actually available in the future product life. Our assumption is that Information Circularity Assistance enables decision makers to incorporate insights from extreme data – high-volume, high-velocity, heterogeneous and distributed data from the product life – into product creation through intelligent Digital Twins. Artificial Intelligence can help to derive sustainable actions in favor of circular products by processing extreme data and enriching it with expert knowledge. The research contributes in three key dimensions. First, a comprehensive literature review is conducted. This review covers concepts of intelligence in Scenario-Technique for strategic product planning, Digital Twin-based analysis of extreme data and relevant technologies from Data Science and Artificial Intelligence. In all areas, the state of the art and emerging trends are identified. Secondly, the study identifies information needs along the steps of the Scenario-Technique and information offerings based on Digital Twins. The concept of Information Circularity Assistance results from the coupling of these demands and offerings, extending the Scenario-Technique beyond traditional expert-based methods. Third, we extend existing Digital Twin methods used in circularity and discuss the deployment of Data Science and Artificial Intelligence algorithms within the product creation process. Our approach uses extreme data to provide a strategic advantage in optimizing product life cycle planning, which is illustrated by two sample applications. The aim is to provide Information Circularity Assistance that will support experienced product planners, developers, and decision makers in the future.","lang":"eng"}],"date_created":"2025-01-07T13:30:45Z","keyword":["Scenario-Technique","Artificial Intelligence","Digital Twin","Large Language Models"],"type":"journal_article","department":[{"_id":"152"}],"year":"2025","title":"Information Circularity Assistance based on extreme data","publication_identifier":{"issn":["0178-2312","2196-677X"]},"author":[{"first_name":"Iris","orcid":"0000-0001-5765-971X","last_name":"Gräßler","full_name":"Gräßler, Iris","id":"47565"},{"full_name":"Weyrich, Michael","last_name":"Weyrich","first_name":"Michael"},{"id":"405","last_name":"Pottebaum","first_name":"Jens","orcid":"http://orcid.org/0000-0001-8778-2989","full_name":"Pottebaum, Jens"},{"full_name":"Kamm, Simon","last_name":"Kamm","first_name":"Simon"}],"publication_status":"published","date_updated":"2025-02-15T09:41:54Z","article_type":"original","intvolume":"        73","main_file_link":[{"open_access":"1"}],"language":[{"iso":"eng"}],"doi":"10.1515/auto-2024-0039","alternative_title":["Utilizing Artificial Intelligence, Scenario-Technique and Digital Twins to solve challenges of product creation for Circular Economy"],"citation":{"ieee":"I. Gräßler, M. Weyrich, J. Pottebaum, and S. Kamm, “Information Circularity Assistance based on extreme data,” <i>at - Automatisierungstechnik</i>, vol. 73, no. 1, pp. 3–21, 2025, doi: <a href=\"https://doi.org/10.1515/auto-2024-0039\">10.1515/auto-2024-0039</a>.","mla":"Gräßler, Iris, et al. “Information Circularity Assistance Based on Extreme Data.” <i>At - Automatisierungstechnik</i>, vol. 73, no. 1, Walter de Gruyter GmbH, 2025, pp. 3–21, doi:<a href=\"https://doi.org/10.1515/auto-2024-0039\">10.1515/auto-2024-0039</a>.","apa":"Gräßler, I., Weyrich, M., Pottebaum, J., &#38; Kamm, S. (2025). Information Circularity Assistance based on extreme data. <i>At - Automatisierungstechnik</i>, <i>73</i>(1), 3–21. <a href=\"https://doi.org/10.1515/auto-2024-0039\">https://doi.org/10.1515/auto-2024-0039</a>","bibtex":"@article{Gräßler_Weyrich_Pottebaum_Kamm_2025, title={Information Circularity Assistance based on extreme data}, volume={73}, DOI={<a href=\"https://doi.org/10.1515/auto-2024-0039\">10.1515/auto-2024-0039</a>}, number={1}, journal={at - Automatisierungstechnik}, publisher={Walter de Gruyter GmbH}, author={Gräßler, Iris and Weyrich, Michael and Pottebaum, Jens and Kamm, Simon}, year={2025}, pages={3–21} }","short":"I. Gräßler, M. Weyrich, J. Pottebaum, S. Kamm, At - Automatisierungstechnik 73 (2025) 3–21.","ama":"Gräßler I, Weyrich M, Pottebaum J, Kamm S. Information Circularity Assistance based on extreme data. <i>at - Automatisierungstechnik</i>. 2025;73(1):3-21. doi:<a href=\"https://doi.org/10.1515/auto-2024-0039\">10.1515/auto-2024-0039</a>","chicago":"Gräßler, Iris, Michael Weyrich, Jens Pottebaum, and Simon Kamm. “Information Circularity Assistance Based on Extreme Data.” <i>At - Automatisierungstechnik</i> 73, no. 1 (2025): 3–21. <a href=\"https://doi.org/10.1515/auto-2024-0039\">https://doi.org/10.1515/auto-2024-0039</a>."},"quality_controlled":"1","oa":"1","status":"public","page":"3-21","publisher":"Walter de Gruyter GmbH","_id":"58076","user_id":"405","volume":73},{"publication":"Industry 4.0 Science","issue":"1","abstract":[{"text":"Technical systems are characterized by increasing interdisciplinarity, complexity and networking. A product and its corresponding production systems require interdisciplinary multi-objective optimization. Sustainability and recyclability demands increase said complexity. The efficiency of previously established engineering methods is reaching its limits, which can only be overcome by systematic integration of extreme data. The aim of \"hybrid decision support\" is as follows: Data science and artificial intelligence should be used to supplement human capabilities in conjunction with existing heuristics, methods, modeling and simulation to increase the efficiency of product creation.","lang":"eng"}],"date_created":"2025-02-15T09:31:30Z","keyword":["AI","artificial intelligence","Data Science","decision support","extreme data","Künstliche Intelligenz","product creation","product development"],"type":"journal_article","department":[{"_id":"152"}],"title":"Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence","year":"2025","publication_identifier":{"issn":["2942-6170"]},"author":[{"id":"47565","full_name":"Gräßler, Iris","orcid":"0000-0001-5765-971X","last_name":"Gräßler","first_name":"Iris"},{"last_name":"Pottebaum","orcid":"http://orcid.org/0000-0001-8778-2989","first_name":"Jens","full_name":"Pottebaum, Jens","id":"405"},{"first_name":"Peter","last_name":"Nyhuis","full_name":"Nyhuis, Peter"},{"full_name":"Stark, Rainer","last_name":"Stark","first_name":"Rainer"},{"full_name":"Thoben, Klaus-Dieter","last_name":"Thoben","first_name":"Klaus-Dieter"},{"full_name":"Wiederkehr, Petra","first_name":"Petra","last_name":"Wiederkehr"}],"publication_status":"published","date_updated":"2025-02-15T09:40:52Z","article_type":"original","intvolume":"      2025","main_file_link":[{"open_access":"1"}],"language":[{"iso":"eng"}],"doi":"10.30844/i4sd.25.1.18","alternative_title":["Hybride Entscheidungsunterstützung in der Produktentstehung - Mit Data Science und Künstlicher Intelligenz die Leistungsfähigkeit erhöhen"],"citation":{"ieee":"I. Gräßler, J. Pottebaum, P. Nyhuis, R. Stark, K.-D. Thoben, and P. Wiederkehr, “Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence,” <i>Industry 4.0 Science</i>, vol. 2025, no. 1, 2025, doi: <a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>.","apa":"Gräßler, I., Pottebaum, J., Nyhuis, P., Stark, R., Thoben, K.-D., &#38; Wiederkehr, P. (2025). Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence. <i>Industry 4.0 Science</i>, <i>2025</i>(1). <a href=\"https://doi.org/10.30844/i4sd.25.1.18\">https://doi.org/10.30844/i4sd.25.1.18</a>","chicago":"Gräßler, Iris, Jens Pottebaum, Peter Nyhuis, Rainer Stark, Klaus-Dieter Thoben, and Petra Wiederkehr. “Hybrid Decision Support in Product Creation - Improving Performance with Data Science and Artificial Intelligence.” <i>Industry 4.0 Science</i> 2025, no. 1 (2025). <a href=\"https://doi.org/10.30844/i4sd.25.1.18\">https://doi.org/10.30844/i4sd.25.1.18</a>.","short":"I. Gräßler, J. Pottebaum, P. Nyhuis, R. Stark, K.-D. Thoben, P. Wiederkehr, Industry 4.0 Science 2025 (2025).","mla":"Gräßler, Iris, et al. “Hybrid Decision Support in Product Creation - Improving Performance with Data Science and Artificial Intelligence.” <i>Industry 4.0 Science</i>, vol. 2025, no. 1, GITO mbH Verlag, 2025, doi:<a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>.","bibtex":"@article{Gräßler_Pottebaum_Nyhuis_Stark_Thoben_Wiederkehr_2025, title={Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence}, volume={2025}, DOI={<a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>}, number={1}, journal={Industry 4.0 Science}, publisher={GITO mbH Verlag}, author={Gräßler, Iris and Pottebaum, Jens and Nyhuis, Peter and Stark, Rainer and Thoben, Klaus-Dieter and Wiederkehr, Petra}, year={2025} }","ama":"Gräßler I, Pottebaum J, Nyhuis P, Stark R, Thoben K-D, Wiederkehr P. Hybrid Decision Support in Product Creation - Improving performance with data science and artificial intelligence. <i>Industry 40 Science</i>. 2025;2025(1). doi:<a href=\"https://doi.org/10.30844/i4sd.25.1.18\">10.30844/i4sd.25.1.18</a>"},"quality_controlled":"1","oa":"1","status":"public","_id":"58650","publisher":"GITO mbH Verlag","user_id":"405","volume":2025},{"citation":{"ieee":"A. Amiri, M. Tavana, and H. Arman, “An Integrated Fuzzy Analytic Network Process and Fuzzy Regression Method for Bitcoin Price Prediction,” <i>Internet of Things</i>, vol. 25, Art. no. 101027, 2024, doi: <a href=\"https://doi.org/10.1016/j.iot.2023.101027\">10.1016/j.iot.2023.101027</a>.","apa":"Amiri, A., Tavana, M., &#38; Arman, H. (2024). An Integrated Fuzzy Analytic Network Process and Fuzzy Regression Method for Bitcoin Price Prediction. <i>Internet of Things</i>, <i>25</i>, Article 101027. <a href=\"https://doi.org/10.1016/j.iot.2023.101027\">https://doi.org/10.1016/j.iot.2023.101027</a>","short":"A. Amiri, M. Tavana, H. Arman, Internet of Things 25 (2024).","chicago":"Amiri, Arman, Madjid Tavana, and Hosein Arman. “An Integrated Fuzzy Analytic Network Process and Fuzzy Regression Method for Bitcoin Price Prediction.” <i>Internet of Things</i> 25 (2024). <a href=\"https://doi.org/10.1016/j.iot.2023.101027\">https://doi.org/10.1016/j.iot.2023.101027</a>.","mla":"Amiri, Arman, et al. “An Integrated Fuzzy Analytic Network Process and Fuzzy Regression Method for Bitcoin Price Prediction.” <i>Internet of Things</i>, vol. 25, 101027, Elsevier BV, 2024, doi:<a href=\"https://doi.org/10.1016/j.iot.2023.101027\">10.1016/j.iot.2023.101027</a>.","bibtex":"@article{Amiri_Tavana_Arman_2024, title={An Integrated Fuzzy Analytic Network Process and Fuzzy Regression Method for Bitcoin Price Prediction}, volume={25}, DOI={<a href=\"https://doi.org/10.1016/j.iot.2023.101027\">10.1016/j.iot.2023.101027</a>}, number={101027}, journal={Internet of Things}, publisher={Elsevier BV}, author={Amiri, Arman and Tavana, Madjid and Arman, Hosein}, year={2024} }","ama":"Amiri A, Tavana M, Arman H. An Integrated Fuzzy Analytic Network Process and Fuzzy Regression Method for Bitcoin Price Prediction. <i>Internet of Things</i>. 2024;25. doi:<a href=\"https://doi.org/10.1016/j.iot.2023.101027\">10.1016/j.iot.2023.101027</a>"},"status":"public","volume":25,"user_id":"51811","_id":"53213","publisher":"Elsevier BV","publication":"Internet of Things","department":[{"_id":"277"}],"type":"journal_article","keyword":["Management of Technology and Innovation","Artificial Intelligence","Computer Science Applications","Hardware and Architecture","Engineering (miscellaneous)","Information Systems","Computer Science (miscellaneous)","Software"],"date_created":"2024-04-04T13:34:26Z","intvolume":"        25","date_updated":"2024-04-15T13:08:17Z","publication_status":"published","publication_identifier":{"issn":["2542-6605"]},"author":[{"last_name":"Amiri","first_name":"Arman","full_name":"Amiri, Arman"},{"id":"31858","full_name":"Tavana, Madjid","first_name":"Madjid","last_name":"Tavana"},{"full_name":"Arman, Hosein","last_name":"Arman","first_name":"Hosein"}],"year":"2024","title":"An Integrated Fuzzy Analytic Network Process and Fuzzy Regression Method for Bitcoin Price Prediction","doi":"10.1016/j.iot.2023.101027","language":[{"iso":"eng"}],"article_number":"101027"},{"date_created":"2024-09-17T09:56:43Z","keyword":["Data Driven Design","Design Automation","Systems Engineering (SE)","Artificial Intelligence (AI)"],"type":"conference","publication":"DS 130: Proceedings of NordDesign 2024","abstract":[{"text":"Developing Intelligent Technical Systems (ITS) involves a complex process encompassing planning, analysis, design, production, and maintenance. Model-Based Systems Engineering (MBSE) is a key methodology for systematic systems engineering. Designing models for ITS requires harmonious interaction of various elements, posing a challenge in MBSE. Leveraging Generative Artificial Intelligence, we generated a dataset for modeling, using prompt engineering on large language models. The generated artifacts can aid engineers in MBSE design or serve as synthetic training data for AI assistants.","lang":"eng"}],"related_material":{"link":[{"relation":"confirmation","url":"https://www.designsociety.org/publication/47658/Towards+Automated+Design%3A+Automatically+Generating+Modeling+Elements+with+Prompt+Engineering+and+Generative+Artificial+Intelligence"}]},"language":[{"iso":"eng"}],"doi":"10.35199/NORDDESIGN2024.66","publication_identifier":{"unknown":["978-1-912254-21-7"]},"author":[{"id":"86782","full_name":"Kulkarni, Pranav Jayant","last_name":"Kulkarni","first_name":"Pranav Jayant"},{"id":"44458","full_name":"Tissen, Denis","first_name":"Denis","last_name":"Tissen"},{"id":"36312","first_name":"Ruslan","last_name":"Bernijazov","full_name":"Bernijazov, Ruslan"},{"id":"16190","full_name":"Dumitrescu, Roman","last_name":"Dumitrescu","first_name":"Roman"}],"title":"Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence","year":"2024","publication_status":"epub_ahead","date_updated":"2024-09-17T09:57:07Z","citation":{"apa":"Kulkarni, P. J., Tissen, D., Bernijazov, R., &#38; Dumitrescu, R. (2024). Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence. In J. Malmqvist, M. Candi, R. Saemundsson, F. Bystrom, &#38; O. Isaksson (Eds.), <i>DS 130: Proceedings of NordDesign 2024</i> (pp. 617–625). <a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">https://doi.org/10.35199/NORDDESIGN2024.66</a>","mla":"Kulkarni, Pranav Jayant, et al. “Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence.” <i>DS 130: Proceedings of NordDesign 2024</i>, edited by J. Malmqvist et al., 2024, pp. 617–25, doi:<a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>.","ieee":"P. J. Kulkarni, D. Tissen, R. Bernijazov, and R. Dumitrescu, “Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence,” in <i>DS 130: Proceedings of NordDesign 2024</i>, Reykjavik, 2024, pp. 617–625, doi: <a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>.","short":"P.J. Kulkarni, D. Tissen, R. Bernijazov, R. Dumitrescu, in: J. Malmqvist, M. Candi, R. Saemundsson, F. Bystrom, O. Isaksson (Eds.), DS 130: Proceedings of NordDesign 2024, 2024, pp. 617–625.","ama":"Kulkarni PJ, Tissen D, Bernijazov R, Dumitrescu R. Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence. In: Malmqvist J, Candi M, Saemundsson R, Bystrom F, Isaksson O, eds. <i>DS 130: Proceedings of NordDesign 2024</i>. ; 2024:617-625. doi:<a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>","chicago":"Kulkarni, Pranav Jayant, Denis Tissen, Ruslan Bernijazov, and Roman Dumitrescu. “Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence.” In <i>DS 130: Proceedings of NordDesign 2024</i>, edited by J. Malmqvist, M. Candi, R. Saemundsson, F. Bystrom, and O. Isaksson, 617–25, 2024. <a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">https://doi.org/10.35199/NORDDESIGN2024.66</a>.","bibtex":"@inproceedings{Kulkarni_Tissen_Bernijazov_Dumitrescu_2024, title={Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence}, DOI={<a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>}, booktitle={DS 130: Proceedings of NordDesign 2024}, author={Kulkarni, Pranav Jayant and Tissen, Denis and Bernijazov, Ruslan and Dumitrescu, Roman}, editor={Malmqvist, J. and Candi, M. and Saemundsson, R. and Bystrom, F. and Isaksson, O.}, year={2024}, pages={617–625} }"},"_id":"56166","page":"617-625","editor":[{"full_name":"Malmqvist, J.","first_name":"J.","last_name":"Malmqvist"},{"last_name":"Candi","first_name":"M.","full_name":"Candi, M."},{"full_name":"Saemundsson, R.","first_name":"R.","last_name":"Saemundsson"},{"first_name":"F.","last_name":"Bystrom","full_name":"Bystrom, F."},{"first_name":"O.","last_name":"Isaksson","full_name":"Isaksson, O."}],"user_id":"86782","conference":{"name":"NordDesign Conference 2024","start_date":"2024-08-12","location":"Reykjavik","end_date":"2024-08-14"},"status":"public"},{"page":"14388-14396","_id":"53073","user_id":"93420","volume":38,"status":"public","citation":{"short":"M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024, pp. 14388–14396.","chicago":"Muschalik, Maximilian, Fabian Fumagalli, Barbara Hammer, and Eyke Huellermeier. “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles.” In <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>, 38:14388–96, 2024. <a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">https://doi.org/10.1609/aaai.v38i13.29352</a>.","apa":"Muschalik, M., Fumagalli, F., Hammer, B., &#38; Huellermeier, E. (2024). Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>, <i>38</i>(13), 14388–14396. <a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">https://doi.org/10.1609/aaai.v38i13.29352</a>","ieee":"M. Muschalik, F. Fumagalli, B. Hammer, and E. Huellermeier, “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles,” in <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>, 2024, vol. 38, no. 13, pp. 14388–14396, doi: <a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">10.1609/aaai.v38i13.29352</a>.","ama":"Muschalik M, Fumagalli F, Hammer B, Huellermeier E. Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. In: <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>. Vol 38. ; 2024:14388-14396. doi:<a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">10.1609/aaai.v38i13.29352</a>","bibtex":"@inproceedings{Muschalik_Fumagalli_Hammer_Huellermeier_2024, title={Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles}, volume={38}, DOI={<a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">10.1609/aaai.v38i13.29352</a>}, number={13}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)}, author={Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara and Huellermeier, Eyke}, year={2024}, pages={14388–14396} }","mla":"Muschalik, Maximilian, et al. “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles.” <i>Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)</i>, vol. 38, no. 13, 2024, pp. 14388–96, doi:<a href=\"https://doi.org/10.1609/aaai.v38i13.29352\">10.1609/aaai.v38i13.29352</a>."},"project":[{"_id":"126","name":"TRR 318 - C3: TRR 318 - Subproject C3"},{"name":"TRR 318: TRR 318 - Erklärbarkeit konstruieren","_id":"109"},{"name":"TRR 318 - C: TRR 318 - Project Area C","_id":"117"}],"language":[{"iso":"eng"}],"doi":"10.1609/aaai.v38i13.29352","title":"Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles","year":"2024","author":[{"last_name":"Muschalik","first_name":"Maximilian","full_name":"Muschalik, Maximilian"},{"first_name":"Fabian","last_name":"Fumagalli","full_name":"Fumagalli, Fabian","id":"93420"},{"full_name":"Hammer, Barbara","last_name":"Hammer","first_name":"Barbara"},{"first_name":"Eyke","last_name":"Huellermeier","full_name":"Huellermeier, Eyke","id":"48129"}],"publication_identifier":{"issn":["2374-3468","2159-5399"]},"date_updated":"2025-09-11T16:20:11Z","publication_status":"published","intvolume":"        38","date_created":"2024-03-27T14:50:04Z","type":"conference","keyword":["Explainable Artificial Intelligence"],"department":[{"_id":"660"}],"publication":"Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)","issue":"13","abstract":[{"text":"While shallow decision trees may be interpretable, larger ensemble models like gradient-boosted trees, which often set the state of the art in machine learning problems involving tabular data, still remain black box models. As a remedy, the Shapley value (SV) is a well-known concept in explainable artificial intelligence (XAI) research for quantifying additive feature attributions of predictions. The model-specific TreeSHAP methodology solves the exponential complexity for retrieving exact SVs from tree-based models. Expanding beyond individual feature attribution, Shapley interactions reveal the impact of intricate feature interactions of any order. In this work, we present TreeSHAP-IQ, an efficient method to compute any-order additive Shapley interactions for predictions of tree-based models. TreeSHAP-IQ is supported by a mathematical framework that exploits polynomial arithmetic to compute the interaction scores in a single recursive traversal of the tree, akin to Linear TreeSHAP. We apply TreeSHAP-IQ on state-of-the-art tree ensembles and explore interactions on well-established benchmark datasets.","lang":"eng"}]},{"date_created":"2023-10-19T08:23:39Z","department":[{"_id":"34"},{"_id":"820"}],"type":"journal_article","keyword":["Law","Artificial Intelligence"],"citation":{"mla":"Habernal, Ivan, et al. “Mining Legal Arguments in Court Decisions.” <i>Artificial Intelligence and Law</i>, Springer Science and Business Media LLC, 2023, doi:<a href=\"https://doi.org/10.1007/s10506-023-09361-y\">10.1007/s10506-023-09361-y</a>.","ama":"Habernal I, Faber D, Recchia N, et al. Mining legal arguments in court decisions. <i>Artificial Intelligence and Law</i>. Published online 2023. doi:<a href=\"https://doi.org/10.1007/s10506-023-09361-y\">10.1007/s10506-023-09361-y</a>","bibtex":"@article{Habernal_Faber_Recchia_Bretthauer_Gurevych_Spiecker genannt Döhmann_Burchard_2023, title={Mining legal arguments in court decisions}, DOI={<a href=\"https://doi.org/10.1007/s10506-023-09361-y\">10.1007/s10506-023-09361-y</a>}, journal={Artificial Intelligence and Law}, publisher={Springer Science and Business Media LLC}, author={Habernal, Ivan and Faber, Daniel and Recchia, Nicola and Bretthauer, Sebastian and Gurevych, Iryna and Spiecker genannt Döhmann, Indra and Burchard, Christoph}, year={2023} }","apa":"Habernal, I., Faber, D., Recchia, N., Bretthauer, S., Gurevych, I., Spiecker genannt Döhmann, I., &#38; Burchard, C. (2023). Mining legal arguments in court decisions. <i>Artificial Intelligence and Law</i>. <a href=\"https://doi.org/10.1007/s10506-023-09361-y\">https://doi.org/10.1007/s10506-023-09361-y</a>","ieee":"I. Habernal <i>et al.</i>, “Mining legal arguments in court decisions,” <i>Artificial Intelligence and Law</i>, 2023, doi: <a href=\"https://doi.org/10.1007/s10506-023-09361-y\">10.1007/s10506-023-09361-y</a>.","chicago":"Habernal, Ivan, Daniel Faber, Nicola Recchia, Sebastian Bretthauer, Iryna Gurevych, Indra Spiecker genannt Döhmann, and Christoph Burchard. “Mining Legal Arguments in Court Decisions.” <i>Artificial Intelligence and Law</i>, 2023. <a href=\"https://doi.org/10.1007/s10506-023-09361-y\">https://doi.org/10.1007/s10506-023-09361-y</a>.","short":"I. Habernal, D. Faber, N. Recchia, S. Bretthauer, I. Gurevych, I. Spiecker genannt Döhmann, C. Burchard, Artificial Intelligence and Law (2023)."},"publication":"Artificial Intelligence and Law","abstract":[{"lang":"eng","text":"<jats:title>Abstract</jats:title><jats:p>Identifying, classifying, and analyzing arguments in legal discourse has been a prominent area of research since the inception of the argument mining field. However, there has been a major discrepancy between the way natural language processing (NLP) researchers model and annotate arguments in court decisions and the way legal experts understand and analyze legal argumentation. While computational approaches typically simplify arguments into generic premises and claims, arguments in legal research usually exhibit a rich typology that is important for gaining insights into the particular case and applications of law in general. We address this problem and make several substantial contributions to move the field forward. First, we design a new annotation scheme for legal arguments in proceedings of the European Court of Human Rights (ECHR) that is deeply rooted in the theory and practice of legal argumentation research. Second, we compile and annotate a large corpus of 373 court decisions (2.3M tokens and 15k annotated argument spans). Finally, we train an argument mining model that outperforms state-of-the-art models in the legal NLP domain and provide a thorough expert-based evaluation. All datasets and source codes are available under open lincenses at <jats:ext-link xmlns:xlink=\"http://www.w3.org/1999/xlink\" ext-link-type=\"uri\" xlink:href=\"https://github.com/trusthlt/mining-legal-arguments\">https://github.com/trusthlt/mining-legal-arguments</jats:ext-link>.</jats:p>"}],"_id":"48290","language":[{"iso":"eng"}],"publisher":"Springer Science and Business Media LLC","user_id":"15504","doi":"10.1007/s10506-023-09361-y","author":[{"id":"101881","last_name":"Habernal","first_name":"Ivan","full_name":"Habernal, Ivan"},{"full_name":"Faber, Daniel","last_name":"Faber","first_name":"Daniel"},{"full_name":"Recchia, Nicola","last_name":"Recchia","first_name":"Nicola"},{"first_name":"Sebastian","last_name":"Bretthauer","full_name":"Bretthauer, Sebastian"},{"full_name":"Gurevych, Iryna","last_name":"Gurevych","first_name":"Iryna"},{"first_name":"Indra","last_name":"Spiecker genannt Döhmann","full_name":"Spiecker genannt Döhmann, Indra"},{"last_name":"Burchard","first_name":"Christoph","full_name":"Burchard, Christoph"}],"publication_identifier":{"issn":["0924-8463","1572-8382"]},"status":"public","title":"Mining legal arguments in court decisions","year":"2023","publication_status":"published","date_updated":"2023-10-19T12:10:02Z"},{"publication_status":"published","date_updated":"2023-11-10T14:24:27Z","publication_identifier":{"issn":["0885-6125","1573-0565"]},"author":[{"full_name":"Fumagalli, Fabian","first_name":"Fabian","last_name":"Fumagalli"},{"last_name":"Muschalik","first_name":"Maximilian","full_name":"Muschalik, Maximilian"},{"first_name":"Eyke","last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke"},{"full_name":"Hammer, Barbara","last_name":"Hammer","first_name":"Barbara"}],"year":"2023","status":"public","title":"Incremental permutation feature importance (iPFI): towards online explanations on data streams","user_id":"55908","doi":"10.1007/s10994-023-06385-y","_id":"48777","language":[{"iso":"eng"}],"publisher":"Springer Science and Business Media LLC","abstract":[{"text":"<jats:title>Abstract</jats:title><jats:p>Explainable artificial intelligence has mainly focused on static learning scenarios so far. We are interested in dynamic scenarios where data is sampled progressively, and learning is done in an incremental rather than a batch mode. We seek efficient incremental algorithms for computing feature importance (FI). Permutation feature importance (PFI) is a well-established model-agnostic measure to obtain global FI based on feature marginalization of absent features. We propose an efficient, model-agnostic algorithm called iPFI to estimate this measure incrementally and under dynamic modeling conditions including concept drift. We prove theoretical guarantees on the approximation quality in terms of expectation and variance. To validate our theoretical findings and the efficacy of our approaches in incremental scenarios dealing with streaming data rather than traditional batch settings, we conduct multiple experimental studies on benchmark data with and without concept drift.</jats:p>","lang":"eng"}],"citation":{"bibtex":"@article{Fumagalli_Muschalik_Hüllermeier_Hammer_2023, title={Incremental permutation feature importance (iPFI): towards online explanations on data streams}, DOI={<a href=\"https://doi.org/10.1007/s10994-023-06385-y\">10.1007/s10994-023-06385-y</a>}, journal={Machine Learning}, publisher={Springer Science and Business Media LLC}, author={Fumagalli, Fabian and Muschalik, Maximilian and Hüllermeier, Eyke and Hammer, Barbara}, year={2023} }","chicago":"Fumagalli, Fabian, Maximilian Muschalik, Eyke Hüllermeier, and Barbara Hammer. “Incremental Permutation Feature Importance (IPFI): Towards Online Explanations on Data Streams.” <i>Machine Learning</i>, 2023. <a href=\"https://doi.org/10.1007/s10994-023-06385-y\">https://doi.org/10.1007/s10994-023-06385-y</a>.","short":"F. Fumagalli, M. Muschalik, E. Hüllermeier, B. Hammer, Machine Learning (2023).","ama":"Fumagalli F, Muschalik M, Hüllermeier E, Hammer B. Incremental permutation feature importance (iPFI): towards online explanations on data streams. <i>Machine Learning</i>. Published online 2023. doi:<a href=\"https://doi.org/10.1007/s10994-023-06385-y\">10.1007/s10994-023-06385-y</a>","ieee":"F. Fumagalli, M. Muschalik, E. Hüllermeier, and B. Hammer, “Incremental permutation feature importance (iPFI): towards online explanations on data streams,” <i>Machine Learning</i>, 2023, doi: <a href=\"https://doi.org/10.1007/s10994-023-06385-y\">10.1007/s10994-023-06385-y</a>.","mla":"Fumagalli, Fabian, et al. “Incremental Permutation Feature Importance (IPFI): Towards Online Explanations on Data Streams.” <i>Machine Learning</i>, Springer Science and Business Media LLC, 2023, doi:<a href=\"https://doi.org/10.1007/s10994-023-06385-y\">10.1007/s10994-023-06385-y</a>.","apa":"Fumagalli, F., Muschalik, M., Hüllermeier, E., &#38; Hammer, B. (2023). Incremental permutation feature importance (iPFI): towards online explanations on data streams. <i>Machine Learning</i>. <a href=\"https://doi.org/10.1007/s10994-023-06385-y\">https://doi.org/10.1007/s10994-023-06385-y</a>"},"publication":"Machine Learning","department":[{"_id":"424"},{"_id":"660"}],"type":"journal_article","keyword":["Artificial Intelligence","Software"],"date_created":"2023-11-10T14:15:36Z"},{"_id":"44639","publisher":"Elsevier BV","user_id":"42933","volume":9,"status":"public","citation":{"ama":"Hoppe JA, Tuisku O, Johansson-Pajala R-M, et al. When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty. <i>Computers in Human Behavior Reports</i>. 2023;9. doi:<a href=\"https://doi.org/10.1016/j.chbr.2022.100258\">10.1016/j.chbr.2022.100258</a>","bibtex":"@article{Hoppe_Tuisku_Johansson-Pajala_Pekkarinen_Hennala_Gustafsson_Melkas_Thommes_2023, title={When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty}, volume={9}, DOI={<a href=\"https://doi.org/10.1016/j.chbr.2022.100258\">10.1016/j.chbr.2022.100258</a>}, number={100258}, journal={Computers in Human Behavior Reports}, publisher={Elsevier BV}, author={Hoppe, Julia Amelie and Tuisku, Outi and Johansson-Pajala, Rose-Marie and Pekkarinen, Satu and Hennala, Lea and Gustafsson, Christine and Melkas, Helinä and Thommes, Kirsten}, year={2023} }","mla":"Hoppe, Julia Amelie, et al. “When Do Individuals Choose Care Robots over a Human Caregiver? Insights from a Laboratory Experiment on Choices under Uncertainty.” <i>Computers in Human Behavior Reports</i>, vol. 9, 100258, Elsevier BV, 2023, doi:<a href=\"https://doi.org/10.1016/j.chbr.2022.100258\">10.1016/j.chbr.2022.100258</a>.","short":"J.A. Hoppe, O. Tuisku, R.-M. Johansson-Pajala, S. Pekkarinen, L. Hennala, C. Gustafsson, H. Melkas, K. Thommes, Computers in Human Behavior Reports 9 (2023).","chicago":"Hoppe, Julia Amelie, Outi Tuisku, Rose-Marie Johansson-Pajala, Satu Pekkarinen, Lea Hennala, Christine Gustafsson, Helinä Melkas, and Kirsten Thommes. “When Do Individuals Choose Care Robots over a Human Caregiver? Insights from a Laboratory Experiment on Choices under Uncertainty.” <i>Computers in Human Behavior Reports</i> 9 (2023). <a href=\"https://doi.org/10.1016/j.chbr.2022.100258\">https://doi.org/10.1016/j.chbr.2022.100258</a>.","apa":"Hoppe, J. A., Tuisku, O., Johansson-Pajala, R.-M., Pekkarinen, S., Hennala, L., Gustafsson, C., Melkas, H., &#38; Thommes, K. (2023). When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty. <i>Computers in Human Behavior Reports</i>, <i>9</i>, Article 100258. <a href=\"https://doi.org/10.1016/j.chbr.2022.100258\">https://doi.org/10.1016/j.chbr.2022.100258</a>","ieee":"J. A. Hoppe <i>et al.</i>, “When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty,” <i>Computers in Human Behavior Reports</i>, vol. 9, Art. no. 100258, 2023, doi: <a href=\"https://doi.org/10.1016/j.chbr.2022.100258\">10.1016/j.chbr.2022.100258</a>."},"project":[{"name":"ORIENT: Use of care robots in welfare services: New models for effective orientation","grant_number":"16SV7954","_id":"46"}],"article_number":"100258","language":[{"iso":"eng"}],"doi":"10.1016/j.chbr.2022.100258","title":"When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty","year":"2023","author":[{"id":"73093","last_name":"Hoppe","first_name":"Julia Amelie","full_name":"Hoppe, Julia Amelie"},{"full_name":"Tuisku, Outi","first_name":"Outi","last_name":"Tuisku"},{"first_name":"Rose-Marie","last_name":"Johansson-Pajala","full_name":"Johansson-Pajala, Rose-Marie"},{"full_name":"Pekkarinen, Satu","first_name":"Satu","last_name":"Pekkarinen"},{"full_name":"Hennala, Lea","last_name":"Hennala","first_name":"Lea"},{"last_name":"Gustafsson","first_name":"Christine","full_name":"Gustafsson, Christine"},{"first_name":"Helinä","last_name":"Melkas","full_name":"Melkas, Helinä"},{"id":"72497","full_name":"Thommes, Kirsten","first_name":"Kirsten","last_name":"Thommes"}],"publication_identifier":{"issn":["2451-9588"]},"publication_status":"published","date_updated":"2023-12-06T09:16:42Z","intvolume":"         9","date_created":"2023-05-08T12:29:18Z","keyword":["Artificial Intelligence","Cognitive Neuroscience","Computer Science Applications","Human-Computer Interaction","Applied Psychology","Neuroscience (miscellaneous)"],"type":"journal_article","department":[{"_id":"178"},{"_id":"184"}],"publication":"Computers in Human Behavior Reports"},{"file_date_updated":"2023-12-07T09:18:55Z","citation":{"ama":"Groß A, Schütze C, Brandt M, Wrede B, Richter B. RISE: an open-source architecture for interdisciplinary and reproducible human–robot interaction research. <i>Frontiers in Robotics and AI</i>. 2023;10. doi:<a href=\"https://doi.org/10.3389/frobt.2023.1245501\">10.3389/frobt.2023.1245501</a>","bibtex":"@article{Groß_Schütze_Brandt_Wrede_Richter_2023, title={RISE: an open-source architecture for interdisciplinary and reproducible human–robot interaction research}, volume={10}, DOI={<a href=\"https://doi.org/10.3389/frobt.2023.1245501\">10.3389/frobt.2023.1245501</a>}, journal={Frontiers in Robotics and AI}, publisher={Frontiers Media SA}, author={Groß, André and Schütze, Christian and Brandt, Mara and Wrede, Britta and Richter, Birte}, year={2023} }","mla":"Groß, André, et al. “RISE: An Open-Source Architecture for Interdisciplinary and Reproducible Human–Robot Interaction Research.” <i>Frontiers in Robotics and AI</i>, vol. 10, Frontiers Media SA, 2023, doi:<a href=\"https://doi.org/10.3389/frobt.2023.1245501\">10.3389/frobt.2023.1245501</a>.","short":"A. Groß, C. Schütze, M. Brandt, B. Wrede, B. Richter, Frontiers in Robotics and AI 10 (2023).","chicago":"Groß, André, Christian Schütze, Mara Brandt, Britta Wrede, and Birte Richter. “RISE: An Open-Source Architecture for Interdisciplinary and Reproducible Human–Robot Interaction Research.” <i>Frontiers in Robotics and AI</i> 10 (2023). <a href=\"https://doi.org/10.3389/frobt.2023.1245501\">https://doi.org/10.3389/frobt.2023.1245501</a>.","apa":"Groß, A., Schütze, C., Brandt, M., Wrede, B., &#38; Richter, B. (2023). RISE: an open-source architecture for interdisciplinary and reproducible human–robot interaction research. <i>Frontiers in Robotics and AI</i>, <i>10</i>. <a href=\"https://doi.org/10.3389/frobt.2023.1245501\">https://doi.org/10.3389/frobt.2023.1245501</a>","ieee":"A. Groß, C. Schütze, M. Brandt, B. Wrede, and B. Richter, “RISE: an open-source architecture for interdisciplinary and reproducible human–robot interaction research,” <i>Frontiers in Robotics and AI</i>, vol. 10, 2023, doi: <a href=\"https://doi.org/10.3389/frobt.2023.1245501\">10.3389/frobt.2023.1245501</a>."},"project":[{"grant_number":"438445824","_id":"109","name":"TRR 318: TRR 318 - Erklärbarkeit konstruieren"},{"_id":"113","name":"TRR 318 - A3: TRR 318 - Subproject A3"},{"_id":"115","grant_number":"438445824","name":"TRR 318 - A05: TRR 318 - Echtzeitmessung der Aufmerksamkeit im Mensch-Roboter-Erklärdialog (Teilprojekt A05)"}],"_id":"49516","publisher":"Frontiers Media SA","user_id":"93405","ddc":["000"],"volume":10,"status":"public","has_accepted_license":"1","file":[{"date_created":"2023-12-07T09:18:55Z","creator":"angross","file_id":"49517","success":1,"content_type":"application/pdf","file_name":"frobt-10-1245501.pdf","access_level":"closed","file_size":40679118,"relation":"main_file","date_updated":"2023-12-07T09:18:55Z"}],"date_created":"2023-12-07T09:17:09Z","keyword":["Artificial Intelligence","Computer Science Applications"],"type":"journal_article","publication":"Frontiers in Robotics and AI","abstract":[{"text":"<jats:p>In this article, we present RISE—a <jats:bold>R</jats:bold>obotics <jats:bold>I</jats:bold>ntegration and <jats:bold>S</jats:bold>cenario-Management <jats:bold>E</jats:bold>xtensible-Architecture—for designing human–robot dialogs and conducting <jats:italic>Human–Robot Interaction</jats:italic> (HRI) studies. In current HRI research, interdisciplinarity in the creation and implementation of interaction studies is becoming increasingly important. In addition, there is a lack of reproducibility of the research results. With the presented open-source architecture, we aim to address these two topics. Therefore, we discuss the advantages and disadvantages of various existing tools from different sub-fields within robotics. Requirements for an architecture can be derived from this overview of the literature, which 1) supports interdisciplinary research, 2) allows reproducibility of the research, and 3) is accessible to other researchers in the field of HRI. With our architecture, we tackle these requirements by providing a <jats:italic>Graphical User Interface</jats:italic> which explains the robot behavior and allows introspection into the current state of the dialog. Additionally, it offers controlling possibilities to easily conduct <jats:italic>Wizard of Oz</jats:italic> studies. To achieve transparency, the dialog is modeled explicitly, and the robot behavior can be configured. Furthermore, the modular architecture offers an interface for external features and sensors and is expandable to new robots and modalities.</jats:p>","lang":"eng"}],"language":[{"iso":"eng"}],"doi":"10.3389/frobt.2023.1245501","title":"RISE: an open-source architecture for interdisciplinary and reproducible human–robot interaction research","year":"2023","publication_identifier":{"issn":["2296-9144"]},"author":[{"full_name":"Groß, André","last_name":"Groß","first_name":"André"},{"full_name":"Schütze, Christian","last_name":"Schütze","first_name":"Christian"},{"last_name":"Brandt","first_name":"Mara","full_name":"Brandt, Mara"},{"full_name":"Wrede, Britta","first_name":"Britta","last_name":"Wrede"},{"first_name":"Birte","last_name":"Richter","full_name":"Richter, Birte"}],"publication_status":"published","date_updated":"2023-12-07T12:09:41Z","article_type":"original","intvolume":"        10"},{"date_created":"2024-01-03T09:54:00Z","type":"conference","keyword":["Artificial Intelligence","Algorithm Appreciation","Framing","Advice-taking","Expertise"],"department":[{"_id":"196"}],"issue":"10","publication":"International Conference on Information Systems","citation":{"ieee":"D. Leffrang, “AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization,” in <i>International Conference on Information Systems</i>, Hyderabad, India, 2023, no. 10.","apa":"Leffrang, D. (2023). AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization. <i>International Conference on Information Systems</i>, <i>10</i>.","mla":"Leffrang, Dirk. “AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization.” <i>International Conference on Information Systems</i>, no. 10, 2023.","bibtex":"@inproceedings{Leffrang_2023, title={AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization}, number={10}, booktitle={International Conference on Information Systems}, author={Leffrang, Dirk}, year={2023} }","short":"D. Leffrang, in: International Conference on Information Systems, 2023.","ama":"Leffrang D. AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization. In: <i>International Conference on Information Systems</i>. ; 2023.","chicago":"Leffrang, Dirk. “AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization.” In <i>International Conference on Information Systems</i>, 2023."},"abstract":[{"text":"Many researchers and practitioners see artificial intelligence as a game changer compared to classical statistical models. However, some software providers engage in “AI washing”, relabeling solutions that use simple statistical models as AI systems. By contrast, research on algorithm aversion unsystematically varied the labels for advisors and treated labels such as \"artificial intelligence\" and \"statistical model\" synonymously. This study investigates the effect of individual labels on users' actual advice utilization behavior. Through two incentivized online within-subjects experiments on regression tasks, we find that labeling human advisors with labels that suggest higher expertise leads to an increase in advice-taking, even though the content of the advice remains the same. In contrast, our results do not suggest such an expert effect for advice-taking from algorithms, despite differences in self-reported perception. These findings challenge the effectiveness of framing intelligent systems as AI-based systems and have important implications for both research and practice.","lang":"eng"}],"main_file_link":[{"url":"https://aisel.aisnet.org/icis2023/aiinbus/aiinbus/10"}],"language":[{"iso":"eng"}],"_id":"50121","user_id":"51271","year":"2023","title":"AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization","status":"public","author":[{"first_name":"Dirk","orcid":"0000-0001-9004-2391","last_name":"Leffrang","full_name":"Leffrang, Dirk","id":"51271"}],"conference":{"name":"International Conference on Information Systems (ICIS)","location":"Hyderabad, India"},"date_updated":"2024-01-10T09:53:41Z"},{"publication_identifier":{"issn":["0957-4174"]},"author":[{"last_name":"Vieluf","first_name":"Solveig","full_name":"Vieluf, Solveig"},{"last_name":"Hasija","first_name":"Tanuj","full_name":"Hasija, Tanuj","id":"43497"},{"last_name":"Kuschel","first_name":"Maurice","full_name":"Kuschel, Maurice","id":"56070"},{"id":"48978","full_name":"Reinsberger, Claus","last_name":"Reinsberger","first_name":"Claus"},{"last_name":"Loddenkemper","first_name":"Tobias","full_name":"Loddenkemper, Tobias"}],"year":"2023","title":"Developing a deep canonical correlation-based technique for seizure prediction","intvolume":"       234","date_updated":"2024-04-05T14:49:56Z","publication_status":"published","language":[{"iso":"eng"}],"article_number":"120986","doi":"10.1016/j.eswa.2023.120986","publication":"Expert Systems with Applications","date_created":"2024-04-05T14:37:06Z","department":[{"_id":"263"}],"keyword":["Artificial Intelligence","Computer Science Applications","General Engineering"],"type":"journal_article","status":"public","_id":"53301","publisher":"Elsevier BV","volume":234,"user_id":"56070","citation":{"bibtex":"@article{Vieluf_Hasija_Kuschel_Reinsberger_Loddenkemper_2023, title={Developing a deep canonical correlation-based technique for seizure prediction}, volume={234}, DOI={<a href=\"https://doi.org/10.1016/j.eswa.2023.120986\">10.1016/j.eswa.2023.120986</a>}, number={120986}, journal={Expert Systems with Applications}, publisher={Elsevier BV}, author={Vieluf, Solveig and Hasija, Tanuj and Kuschel, Maurice and Reinsberger, Claus and Loddenkemper, Tobias}, year={2023} }","ama":"Vieluf S, Hasija T, Kuschel M, Reinsberger C, Loddenkemper T. Developing a deep canonical correlation-based technique for seizure prediction. <i>Expert Systems with Applications</i>. 2023;234. doi:<a href=\"https://doi.org/10.1016/j.eswa.2023.120986\">10.1016/j.eswa.2023.120986</a>","mla":"Vieluf, Solveig, et al. “Developing a Deep Canonical Correlation-Based Technique for Seizure Prediction.” <i>Expert Systems with Applications</i>, vol. 234, 120986, Elsevier BV, 2023, doi:<a href=\"https://doi.org/10.1016/j.eswa.2023.120986\">10.1016/j.eswa.2023.120986</a>.","short":"S. Vieluf, T. Hasija, M. Kuschel, C. Reinsberger, T. Loddenkemper, Expert Systems with Applications 234 (2023).","chicago":"Vieluf, Solveig, Tanuj Hasija, Maurice Kuschel, Claus Reinsberger, and Tobias Loddenkemper. “Developing a Deep Canonical Correlation-Based Technique for Seizure Prediction.” <i>Expert Systems with Applications</i> 234 (2023). <a href=\"https://doi.org/10.1016/j.eswa.2023.120986\">https://doi.org/10.1016/j.eswa.2023.120986</a>.","ieee":"S. Vieluf, T. Hasija, M. Kuschel, C. Reinsberger, and T. Loddenkemper, “Developing a deep canonical correlation-based technique for seizure prediction,” <i>Expert Systems with Applications</i>, vol. 234, Art. no. 120986, 2023, doi: <a href=\"https://doi.org/10.1016/j.eswa.2023.120986\">10.1016/j.eswa.2023.120986</a>.","apa":"Vieluf, S., Hasija, T., Kuschel, M., Reinsberger, C., &#38; Loddenkemper, T. (2023). Developing a deep canonical correlation-based technique for seizure prediction. <i>Expert Systems with Applications</i>, <i>234</i>, Article 120986. <a href=\"https://doi.org/10.1016/j.eswa.2023.120986\">https://doi.org/10.1016/j.eswa.2023.120986</a>"}},{"user_id":"51811","volume":22,"_id":"53220","publisher":"Elsevier BV","status":"public","citation":{"mla":"Tavana, Madjid, et al. “An Interval Multi-Criteria Decision-Making Model for Evaluating Blockchain-IoT Technology in Supply Chain Networks.” <i>Internet of Things</i>, vol. 22, 100786, Elsevier BV, 2023, doi:<a href=\"https://doi.org/10.1016/j.iot.2023.100786\">10.1016/j.iot.2023.100786</a>.","ama":"Tavana M, Khalili Nasr A, Ahmadabadi AB, Amiri AS, Mina H. An interval multi-criteria decision-making model for evaluating blockchain-IoT technology in supply chain networks. <i>Internet of Things</i>. 2023;22. doi:<a href=\"https://doi.org/10.1016/j.iot.2023.100786\">10.1016/j.iot.2023.100786</a>","bibtex":"@article{Tavana_Khalili Nasr_Ahmadabadi_Amiri_Mina_2023, title={An interval multi-criteria decision-making model for evaluating blockchain-IoT technology in supply chain networks}, volume={22}, DOI={<a href=\"https://doi.org/10.1016/j.iot.2023.100786\">10.1016/j.iot.2023.100786</a>}, number={100786}, journal={Internet of Things}, publisher={Elsevier BV}, author={Tavana, Madjid and Khalili Nasr, Arash and Ahmadabadi, Alireza Barati and Amiri, Alireza Shamekhi and Mina, Hassan}, year={2023} }","apa":"Tavana, M., Khalili Nasr, A., Ahmadabadi, A. B., Amiri, A. S., &#38; Mina, H. (2023). An interval multi-criteria decision-making model for evaluating blockchain-IoT technology in supply chain networks. <i>Internet of Things</i>, <i>22</i>, Article 100786. <a href=\"https://doi.org/10.1016/j.iot.2023.100786\">https://doi.org/10.1016/j.iot.2023.100786</a>","ieee":"M. Tavana, A. Khalili Nasr, A. B. Ahmadabadi, A. S. Amiri, and H. Mina, “An interval multi-criteria decision-making model for evaluating blockchain-IoT technology in supply chain networks,” <i>Internet of Things</i>, vol. 22, Art. no. 100786, 2023, doi: <a href=\"https://doi.org/10.1016/j.iot.2023.100786\">10.1016/j.iot.2023.100786</a>.","short":"M. Tavana, A. Khalili Nasr, A.B. Ahmadabadi, A.S. Amiri, H. Mina, Internet of Things 22 (2023).","chicago":"Tavana, Madjid, Arash Khalili Nasr, Alireza Barati Ahmadabadi, Alireza Shamekhi Amiri, and Hassan Mina. “An Interval Multi-Criteria Decision-Making Model for Evaluating Blockchain-IoT Technology in Supply Chain Networks.” <i>Internet of Things</i> 22 (2023). <a href=\"https://doi.org/10.1016/j.iot.2023.100786\">https://doi.org/10.1016/j.iot.2023.100786</a>."},"doi":"10.1016/j.iot.2023.100786","article_number":"100786","language":[{"iso":"eng"}],"date_updated":"2024-04-15T13:10:41Z","publication_status":"published","intvolume":"        22","title":"An interval multi-criteria decision-making model for evaluating blockchain-IoT technology in supply chain networks","year":"2023","author":[{"last_name":"Tavana","first_name":"Madjid","full_name":"Tavana, Madjid","id":"31858"},{"full_name":"Khalili Nasr, Arash","first_name":"Arash","last_name":"Khalili Nasr"},{"full_name":"Ahmadabadi, Alireza Barati","first_name":"Alireza Barati","last_name":"Ahmadabadi"},{"last_name":"Amiri","first_name":"Alireza Shamekhi","full_name":"Amiri, Alireza Shamekhi"},{"last_name":"Mina","first_name":"Hassan","full_name":"Mina, Hassan"}],"publication_identifier":{"issn":["2542-6605"]},"type":"journal_article","keyword":["Management of Technology and Innovation","Artificial Intelligence","Computer Science Applications","Hardware and Architecture","Engineering (miscellaneous)","Information Systems","Computer Science (miscellaneous)","Software"],"department":[{"_id":"277"}],"date_created":"2024-04-04T13:49:53Z","publication":"Internet of Things"},{"publication":"Expert Systems with Applications","date_created":"2024-04-04T13:47:25Z","department":[{"_id":"277"}],"keyword":["Artificial Intelligence","Computer Science Applications","General Engineering"],"type":"journal_article","author":[{"first_name":"Madjid","last_name":"Tavana","full_name":"Tavana, Madjid","id":"31858"},{"full_name":"Soltanifar, Mehdi","last_name":"Soltanifar","first_name":"Mehdi"},{"full_name":"Santos-Arteaga, Francisco J.","first_name":"Francisco J.","last_name":"Santos-Arteaga"},{"first_name":"Hamid","last_name":"Sharafi","full_name":"Sharafi, Hamid"}],"publication_identifier":{"issn":["0957-4174"]},"year":"2023","title":"Analytic hierarchy process and data envelopment analysis: A match made in heaven","intvolume":"       223","publication_status":"published","date_updated":"2024-04-15T13:08:50Z","language":[{"iso":"eng"}],"article_number":"119902","doi":"10.1016/j.eswa.2023.119902","citation":{"mla":"Tavana, Madjid, et al. “Analytic Hierarchy Process and Data Envelopment Analysis: A Match Made in Heaven.” <i>Expert Systems with Applications</i>, vol. 223, 119902, Elsevier BV, 2023, doi:<a href=\"https://doi.org/10.1016/j.eswa.2023.119902\">10.1016/j.eswa.2023.119902</a>.","ama":"Tavana M, Soltanifar M, Santos-Arteaga FJ, Sharafi H. Analytic hierarchy process and data envelopment analysis: A match made in heaven. <i>Expert Systems with Applications</i>. 2023;223. doi:<a href=\"https://doi.org/10.1016/j.eswa.2023.119902\">10.1016/j.eswa.2023.119902</a>","bibtex":"@article{Tavana_Soltanifar_Santos-Arteaga_Sharafi_2023, title={Analytic hierarchy process and data envelopment analysis: A match made in heaven}, volume={223}, DOI={<a href=\"https://doi.org/10.1016/j.eswa.2023.119902\">10.1016/j.eswa.2023.119902</a>}, number={119902}, journal={Expert Systems with Applications}, publisher={Elsevier BV}, author={Tavana, Madjid and Soltanifar, Mehdi and Santos-Arteaga, Francisco J. and Sharafi, Hamid}, year={2023} }","apa":"Tavana, M., Soltanifar, M., Santos-Arteaga, F. J., &#38; Sharafi, H. (2023). Analytic hierarchy process and data envelopment analysis: A match made in heaven. <i>Expert Systems with Applications</i>, <i>223</i>, Article 119902. <a href=\"https://doi.org/10.1016/j.eswa.2023.119902\">https://doi.org/10.1016/j.eswa.2023.119902</a>","ieee":"M. Tavana, M. Soltanifar, F. J. Santos-Arteaga, and H. Sharafi, “Analytic hierarchy process and data envelopment analysis: A match made in heaven,” <i>Expert Systems with Applications</i>, vol. 223, Art. no. 119902, 2023, doi: <a href=\"https://doi.org/10.1016/j.eswa.2023.119902\">10.1016/j.eswa.2023.119902</a>.","chicago":"Tavana, Madjid, Mehdi Soltanifar, Francisco J. Santos-Arteaga, and Hamid Sharafi. “Analytic Hierarchy Process and Data Envelopment Analysis: A Match Made in Heaven.” <i>Expert Systems with Applications</i> 223 (2023). <a href=\"https://doi.org/10.1016/j.eswa.2023.119902\">https://doi.org/10.1016/j.eswa.2023.119902</a>.","short":"M. Tavana, M. Soltanifar, F.J. Santos-Arteaga, H. 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