[{"intvolume":"        45","date_updated":"2023-01-06T12:21:07Z","publication_status":"published","author":[{"full_name":"Caruso, Carina","last_name":"Caruso","first_name":"Carina","id":"23123"},{"full_name":"Seifert, Andreas","last_name":"Seifert","first_name":"Andreas"}],"publication_identifier":{"issn":["2750 - 3941"]},"year":"2022","title":"Pädagogische Kompetenz als Ausgangspunkt beruflichen Könnens!? Ergebnisse der Kompetenzmessung angehender Lehrkräfte unter Berücksichtigung individueller Voraussetzungen","doi":"10.20377/rpb-101","language":[{"iso":"ger"}],"abstract":[{"lang":"ger","text":"Im Zentrum dieses Beitrags stehen Ergebnisse der Messung pädagogischer Kompetenzen Studierender. Dabei werden sowohl das bildungswissenschaftliche Wissen als auch die Entwicklung der Kompe­tenzselbsteinschätzungen in den Bereichen Unterrichten, Erziehen, Beurteilen und Innovieren unter Berücksichtigung individueller Voraussetzungen (Alter, Geschlecht, Abiturnote, Bachelornote, Konfession) betrachtet. Um die Ergeb­nisse hinsichtlich ihrer Bedeutung für die Professionalisierung angehender Lehrkräfte diskutieren zu können, wird, den empirischen Erkenntnissen voranstehend, die Bedeutung von Wissen für berufliches Können herausgearbeitet. Daran anschließend werden Hypothesen hergeleitet, die Anlage der Studie sowie die Testinstrumente vorgestellt, die Ergebnisse präsentiert und diskutiert. Die Ergebnisse zeigen, dass die Abitur- und Bachelornote die Varianz hinsichtlich des pädagogischen Wissens aufklären, sich eine signifikante Entwicklung der Kompetenzselbsteinschätzungen angehender Lehrkräfte feststellen lässt, aber sich angehende Religionslehrkräfte kaum von anderen Studierenden unterscheiden. Die Diskussion nimmt u. a. Rückbezug auf die Denkfiguren zur Entwicklung berufli­chen Könnens und benennt Limitationen, die mit der Studie und Kompetenzmessungen verbunden sind. Daran schließt die Formulierung eines Ausblicks an. Der Beitrag zielt insbesondere darauf, repräsentative Ergebnisse der Kompetenzmessung zu präsentieren und dabei potenzielle Einflussfaktoren auf die studentische Kompetenzent­wicklung zu beleuchten. Ein dadurch angereichertes Konglomerat belastbarer Erkenntnisse zielt darauf, langfristig zur Ableitung lehrerbildungsdidaktischer Überlegungen herangezogen werden zu können, die die studentische Professionalisierung unterstützen."},{"text":"This paper focuses on the results of the measurement of pedagogical competences of students. In doing so,  both  the  knowledge  of  the  educational  sciences  and  the  development  of  competence  self-assessments  in  the  fields of teaching, education, assessment andinnovating are taken into account. The study makes use of the following individual requirements: age, sex, Abitur grade, Bachelor grade, Confession. In order to be able to discuss the re-sults regarding their importance for the professionalization of prospective teachers, the importance of knowledge for  professional  skills  is  highlighted,  preceded  by  empirical  findings.  Subsequently,  hypotheses  are  derived,  the  plan  of  the  study  as  well  as  the  test  instruments  are  presented,  the  results  presented  and  discussed.  The  results  show that the Abitur and Bachelor grades clarify the variance in pedagogical knowledge, that there is a significant development in the competence self-assessments of prospective teachers, and that prospective religious teachers are not different from other students. The discussion takes into account, among other things, the ideas for the devel-opment of professional skills and identifies limitations associated with the study. This is followed by the formula-tion of an outlook. The main aim of the paper is to present representative results of the competence measurement and  to  examine  potential  influencing  factors  on  student  competence  development.  A  conglomerate  of  resilient  knowledge enriched by this aims to be used in the long term to derive teacher training didactic considerations that support student professionalization.","lang":"eng"}],"issue":"1","publication":"Religionspädagogische Beiträge. Journal for Religion in Education ","keyword":["Bildungswissenschaftliches Wissen","Kompetenzmessung","Kompetenzselbsteinschätzung","Praxissemester","Professionalisierung / competence measurement","competence self-assessment","educational knowledge","internship","professionalization"],"type":"journal_article","date_created":"2023-01-03T12:45:09Z","status":"public","volume":45,"user_id":"86519","publisher":"University of Bamberg Press","_id":"35137","page":"3-15","citation":{"ieee":"C. Caruso and A. Seifert, “Pädagogische Kompetenz als Ausgangspunkt beruflichen Könnens!? Ergebnisse der Kompetenzmessung angehender Lehrkräfte unter Berücksichtigung individueller Voraussetzungen,” <i>Religionspädagogische Beiträge. Journal for Religion in Education </i>, vol. 45, no. 1, pp. 3–15, 2022, doi: <a href=\"https://doi.org/10.20377/rpb-101\">10.20377/rpb-101</a>.","apa":"Caruso, C., &#38; Seifert, A. (2022). Pädagogische Kompetenz als Ausgangspunkt beruflichen Könnens!? Ergebnisse der Kompetenzmessung angehender Lehrkräfte unter Berücksichtigung individueller Voraussetzungen. <i>Religionspädagogische Beiträge. Journal for Religion in Education </i>, <i>45</i>(1), 3–15. <a href=\"https://doi.org/10.20377/rpb-101\">https://doi.org/10.20377/rpb-101</a>","chicago":"Caruso, Carina, and Andreas Seifert. “Pädagogische Kompetenz als Ausgangspunkt beruflichen Könnens!? Ergebnisse der Kompetenzmessung angehender Lehrkräfte unter Berücksichtigung individueller Voraussetzungen.” <i>Religionspädagogische Beiträge. Journal for Religion in Education </i> 45, no. 1 (2022): 3–15. <a href=\"https://doi.org/10.20377/rpb-101\">https://doi.org/10.20377/rpb-101</a>.","short":"C. Caruso, A. Seifert, Religionspädagogische Beiträge. Journal for Religion in Education  45 (2022) 3–15.","mla":"Caruso, Carina, and Andreas Seifert. “Pädagogische Kompetenz als Ausgangspunkt beruflichen Könnens!? Ergebnisse der Kompetenzmessung angehender Lehrkräfte unter Berücksichtigung individueller Voraussetzungen.” <i>Religionspädagogische Beiträge. Journal for Religion in Education </i>, vol. 45, no. 1, University of Bamberg Press, 2022, pp. 3–15, doi:<a href=\"https://doi.org/10.20377/rpb-101\">10.20377/rpb-101</a>.","bibtex":"@article{Caruso_Seifert_2022, title={Pädagogische Kompetenz als Ausgangspunkt beruflichen Könnens!? Ergebnisse der Kompetenzmessung angehender Lehrkräfte unter Berücksichtigung individueller Voraussetzungen}, volume={45}, DOI={<a href=\"https://doi.org/10.20377/rpb-101\">10.20377/rpb-101</a>}, number={1}, journal={Religionspädagogische Beiträge. Journal for Religion in Education }, publisher={University of Bamberg Press}, author={Caruso, Carina and Seifert, Andreas}, year={2022}, pages={3–15} }","ama":"Caruso C, Seifert A. Pädagogische Kompetenz als Ausgangspunkt beruflichen Könnens!? Ergebnisse der Kompetenzmessung angehender Lehrkräfte unter Berücksichtigung individueller Voraussetzungen. <i>Religionspädagogische Beiträge Journal for Religion in Education </i>. 2022;45(1):3-15. doi:<a href=\"https://doi.org/10.20377/rpb-101\">10.20377/rpb-101</a>"}},{"status":"public","publisher":"Springer International Publishing","_id":"48882","page":"192–206","editor":[{"full_name":"Rudolph, Günter","first_name":"Günter","last_name":"Rudolph"},{"full_name":"Kononova, Anna V.","first_name":"Anna V.","last_name":"Kononova"},{"last_name":"Aguirre","first_name":"Hernán","full_name":"Aguirre, Hernán"},{"last_name":"Kerschke","first_name":"Pascal","full_name":"Kerschke, Pascal"},{"first_name":"Gabriela","last_name":"Ochoa","full_name":"Ochoa, Gabriela"},{"first_name":"Tea","last_name":"Tusar","full_name":"Tusar, Tea"}],"user_id":"102979","citation":{"mla":"Heins, Jonathan, et al. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 192–206, doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">10.1007/978-3-031-14714-2_14</a>.","ama":"Heins J, Rook J, Schäpermeier L, Kerschke P, Bossek J, Trautmann H. BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tusar T, eds. <i>Parallel Problem Solving from Nature (PPSN XVII)</i>. Lecture Notes in Computer Science. Springer International Publishing; 2022:192–206. doi:<a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">10.1007/978-3-031-14714-2_14</a>","bibtex":"@inproceedings{Heins_Rook_Schäpermeier_Kerschke_Bossek_Trautmann_2022, place={Cham}, series={Lecture Notes in Computer Science}, title={BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">10.1007/978-3-031-14714-2_14</a>}, booktitle={Parallel Problem Solving from Nature (PPSN XVII)}, publisher={Springer International Publishing}, author={Heins, Jonathan and Rook, Jeroen and Schäpermeier, Lennart and Kerschke, Pascal and Bossek, Jakob and Trautmann, Heike}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tusar, Tea}, year={2022}, pages={192–206}, collection={Lecture Notes in Computer Science} }","apa":"Heins, J., Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J., &#38; Trautmann, H. (2022). BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, &#38; T. Tusar (Eds.), <i>Parallel Problem Solving from Nature (PPSN XVII)</i> (pp. 192–206). Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">https://doi.org/10.1007/978-3-031-14714-2_14</a>","ieee":"J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, and H. Trautmann, “BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems,” in <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, 2022, pp. 192–206, doi: <a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">10.1007/978-3-031-14714-2_14</a>.","short":"J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, H. Trautmann, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tusar (Eds.), Parallel Problem Solving from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 192–206.","chicago":"Heins, Jonathan, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, and Heike Trautmann. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” In <i>Parallel Problem Solving from Nature (PPSN XVII)</i>, edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tusar, 192–206. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. <a href=\"https://doi.org/10.1007/978-3-031-14714-2_14\">https://doi.org/10.1007/978-3-031-14714-2_14</a>."},"place":"Cham","author":[{"last_name":"Heins","first_name":"Jonathan","full_name":"Heins, Jonathan"},{"first_name":"Jeroen","last_name":"Rook","full_name":"Rook, Jeroen"},{"full_name":"Schäpermeier, Lennart","first_name":"Lennart","last_name":"Schäpermeier"},{"full_name":"Kerschke, Pascal","first_name":"Pascal","last_name":"Kerschke"},{"id":"102979","last_name":"Bossek","first_name":"Jakob","orcid":"0000-0002-4121-4668","full_name":"Bossek, Jakob"},{"full_name":"Trautmann, Heike","last_name":"Trautmann","first_name":"Heike"}],"publication_identifier":{"isbn":["978-3-031-14714-2"]},"year":"2022","title":"BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems","date_updated":"2023-12-13T10:47:50Z","series_title":"Lecture Notes in Computer Science","language":[{"iso":"eng"}],"doi":"10.1007/978-3-031-14714-2_14","publication":"Parallel Problem Solving from Nature (PPSN XVII)","abstract":[{"lang":"eng","text":"In multimodal multi-objective optimization (MMMOO), the focus is not solely on convergence in objective space, but rather also on explicitly ensuring diversity in decision space. We illustrate why commonly used diversity measures are not entirely appropriate for this task and propose a sophisticated basin-based evaluation (BBE) method. Also, BBE variants are developed, capturing the anytime behavior of algorithms. The set of BBE measures is tested by means of an algorithm configuration study. We show that these new measures also transfer properties of the well-established hypervolume (HV) indicator to the domain of MMMOO, thus also accounting for objective space convergence. Moreover, we advance MMMOO research by providing insights into the multimodal performance of the considered algorithms. Specifically, algorithms exploiting local structures are shown to outperform classical evolutionary multi-objective optimizers regarding the BBE variants and respective trade-off with HV."}],"extern":"1","date_created":"2023-11-14T15:58:58Z","department":[{"_id":"819"}],"keyword":["Anytime behavior","Benchmarking","Continuous optimization","Multi-objective optimization","Multimodality","Performance metric"],"type":"conference"},{"place":"New York, NY, USA","citation":{"bibtex":"@inproceedings{Rook_Trautmann_Bossek_Grimme_2022, place={New York, NY, USA}, series={GECCO’22}, title={On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems}, DOI={<a href=\"https://doi.org/10.1145/3520304.3528998\">10.1145/3520304.3528998</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion}, publisher={Association for Computing Machinery}, author={Rook, Jeroen and Trautmann, Heike and Bossek, Jakob and Grimme, Christian}, year={2022}, pages={356–359}, collection={GECCO’22} }","ama":"Rook J, Trautmann H, Bossek J, Grimme C. On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>. GECCO’22. Association for Computing Machinery; 2022:356–359. doi:<a href=\"https://doi.org/10.1145/3520304.3528998\">10.1145/3520304.3528998</a>","mla":"Rook, Jeroen, et al. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, Association for Computing Machinery, 2022, pp. 356–359, doi:<a href=\"https://doi.org/10.1145/3520304.3528998\">10.1145/3520304.3528998</a>.","short":"J. Rook, H. Trautmann, J. Bossek, C. Grimme, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2022, pp. 356–359.","chicago":"Rook, Jeroen, Heike Trautmann, Jakob Bossek, and Christian Grimme. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, 356–359. GECCO’22. New York, NY, USA: Association for Computing Machinery, 2022. <a href=\"https://doi.org/10.1145/3520304.3528998\">https://doi.org/10.1145/3520304.3528998</a>.","ieee":"J. Rook, H. Trautmann, J. Bossek, and C. Grimme, “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, 2022, pp. 356–359, doi: <a href=\"https://doi.org/10.1145/3520304.3528998\">10.1145/3520304.3528998</a>.","apa":"Rook, J., Trautmann, H., Bossek, J., &#38; Grimme, C. (2022). On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i>, 356–359. <a href=\"https://doi.org/10.1145/3520304.3528998\">https://doi.org/10.1145/3520304.3528998</a>"},"page":"356–359","_id":"48896","publisher":"Association for Computing Machinery","user_id":"102979","status":"public","date_created":"2023-11-14T15:59:00Z","keyword":["configuration","multi-modality","multi-objective optimization"],"type":"conference","department":[{"_id":"819"}],"publication":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","abstract":[{"text":"Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.","lang":"eng"}],"extern":"1","language":[{"iso":"eng"}],"series_title":"GECCO’22","doi":"10.1145/3520304.3528998","year":"2022","title":"On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems","author":[{"first_name":"Jeroen","last_name":"Rook","full_name":"Rook, Jeroen"},{"full_name":"Trautmann, Heike","last_name":"Trautmann","first_name":"Heike"},{"full_name":"Bossek, Jakob","last_name":"Bossek","first_name":"Jakob","orcid":"0000-0002-4121-4668","id":"102979"},{"full_name":"Grimme, Christian","last_name":"Grimme","first_name":"Christian"}],"publication_identifier":{"isbn":["978-1-4503-9268-6"]},"date_updated":"2023-12-13T10:50:24Z"},{"volume":"0","user_id":"95394","doi":"10.3934/mcrf.2022052","publisher":"American Institute of Mathematical Sciences (AIMS)","_id":"35206","language":[{"iso":"eng"}],"page":"0-0","publication_status":"published","date_updated":"2023-01-16T12:07:51Z","author":[{"last_name":"Bonnard","first_name":"Bernard","full_name":"Bonnard, Bernard"},{"first_name":"Jérémy","last_name":"Rouot","full_name":"Rouot, Jérémy"},{"id":"95394","first_name":"Boris Edgar","last_name":"Wembe Moafo","full_name":"Wembe Moafo, Boris Edgar"}],"publication_identifier":{"issn":["2156-8472","2156-8499"]},"status":"public","year":"2022","title":"Accessibility properties of abnormal geodesics in optimal control illustrated by two case studies","type":"journal_article","keyword":["Applied Mathematics","Control and Optimization","General Medicine"],"date_created":"2023-01-04T10:26:56Z","citation":{"ama":"Bonnard B, Rouot J, Wembe Moafo BE. Accessibility properties of abnormal geodesics in optimal control illustrated by two case studies. <i>Mathematical Control and Related Fields</i>. 2022;0(0):0-0. doi:<a href=\"https://doi.org/10.3934/mcrf.2022052\">10.3934/mcrf.2022052</a>","short":"B. Bonnard, J. Rouot, B.E. Wembe Moafo, Mathematical Control and Related Fields 0 (2022) 0–0.","chicago":"Bonnard, Bernard, Jérémy Rouot, and Boris Edgar Wembe Moafo. “Accessibility Properties of Abnormal Geodesics in Optimal Control Illustrated by Two Case Studies.” <i>Mathematical Control and Related Fields</i> 0, no. 0 (2022): 0–0. <a href=\"https://doi.org/10.3934/mcrf.2022052\">https://doi.org/10.3934/mcrf.2022052</a>.","bibtex":"@article{Bonnard_Rouot_Wembe Moafo_2022, title={Accessibility properties of abnormal geodesics in optimal control illustrated by two case studies}, volume={0}, DOI={<a href=\"https://doi.org/10.3934/mcrf.2022052\">10.3934/mcrf.2022052</a>}, number={0}, journal={Mathematical Control and Related Fields}, publisher={American Institute of Mathematical Sciences (AIMS)}, author={Bonnard, Bernard and Rouot, Jérémy and Wembe Moafo, Boris Edgar}, year={2022}, pages={0–0} }","mla":"Bonnard, Bernard, et al. “Accessibility Properties of Abnormal Geodesics in Optimal Control Illustrated by Two Case Studies.” <i>Mathematical Control and Related Fields</i>, vol. 0, no. 0, American Institute of Mathematical Sciences (AIMS), 2022, pp. 0–0, doi:<a href=\"https://doi.org/10.3934/mcrf.2022052\">10.3934/mcrf.2022052</a>.","apa":"Bonnard, B., Rouot, J., &#38; Wembe Moafo, B. E. (2022). Accessibility properties of abnormal geodesics in optimal control illustrated by two case studies. <i>Mathematical Control and Related Fields</i>, <i>0</i>(0), 0–0. <a href=\"https://doi.org/10.3934/mcrf.2022052\">https://doi.org/10.3934/mcrf.2022052</a>","ieee":"B. Bonnard, J. Rouot, and B. E. Wembe Moafo, “Accessibility properties of abnormal geodesics in optimal control illustrated by two case studies,” <i>Mathematical Control and Related Fields</i>, vol. 0, no. 0, pp. 0–0, 2022, doi: <a href=\"https://doi.org/10.3934/mcrf.2022052\">10.3934/mcrf.2022052</a>."},"issue":"0","publication":"Mathematical Control and Related Fields"},{"quality_controlled":"1","citation":{"mla":"Schröer, Franz, and Claudia Tenberge. “How to Enable Pre-Service Teachers to Design Technological Teaching and Learning Inclusively? – On the Nature and Consideration of Basic Needs in Teacher Training.” <i>PATT39 - PATT on the Edge Technology, Innovation and Education</i>, edited by David Gill et al., 2022, pp. 49–57.","ama":"Schröer F, Tenberge C. How to enable pre-service teachers to design technological teaching and learning inclusively? – On the nature and consideration of basic needs in teacher training. In: Gill D, Tuff J, Kennedy T, Pendergast S, Jamil S, eds. <i>PATT39 - PATT on the Edge Technology, Innovation and Education</i>. PATT Proceedings. ; 2022:49-57.","bibtex":"@inproceedings{Schröer_Tenberge_2022, place={St. John’s, Newfoundland and Labrador, Canada}, series={PATT Proceedings}, title={How to enable pre-service teachers to design technological teaching and learning inclusively? – On the nature and consideration of basic needs in teacher training}, booktitle={PATT39 - PATT on the Edge Technology, Innovation and Education}, author={Schröer, Franz and Tenberge, Claudia}, editor={Gill, David and Tuff, Jim and Kennedy, Thomas and Pendergast, Shawn and Jamil, Sana}, year={2022}, pages={49–57}, collection={PATT Proceedings} }","apa":"Schröer, F., &#38; Tenberge, C. (2022). How to enable pre-service teachers to design technological teaching and learning inclusively? – On the nature and consideration of basic needs in teacher training. In D. Gill, J. Tuff, T. Kennedy, S. Pendergast, &#38; S. Jamil (Eds.), <i>PATT39 - PATT on the Edge Technology, Innovation and Education</i> (pp. 49–57).","ieee":"F. Schröer and C. Tenberge, “How to enable pre-service teachers to design technological teaching and learning inclusively? – On the nature and consideration of basic needs in teacher training,” in <i>PATT39 - PATT on the Edge Technology, Innovation and Education</i>, St. John’s, Newfoundland and Labrador, Canada, 2022, pp. 49–57.","chicago":"Schröer, Franz, and Claudia Tenberge. “How to Enable Pre-Service Teachers to Design Technological Teaching and Learning Inclusively? – On the Nature and Consideration of Basic Needs in Teacher Training.” In <i>PATT39 - PATT on the Edge Technology, Innovation and Education</i>, edited by David Gill, Jim Tuff, Thomas Kennedy, Shawn Pendergast, and Sana Jamil, 49–57. PATT Proceedings. St. John’s, Newfoundland and Labrador, Canada, 2022.","short":"F. Schröer, C. Tenberge, in: D. Gill, J. Tuff, T. Kennedy, S. Pendergast, S. Jamil (Eds.), PATT39 - PATT on the Edge Technology, Innovation and Education, St. John’s, Newfoundland and Labrador, Canada, 2022, pp. 49–57."},"place":"St. John’s, Newfoundland and Labrador, Canada","status":"public","conference":{"name":"PATT39 - PATT on the Edge Technology, Innovation and Education","start_date":"2022-06-21","location":"St. John’s, Newfoundland and Labrador, Canada","end_date":"2022-06-24"},"user_id":"71764","editor":[{"full_name":"Gill, David","first_name":"David","last_name":"Gill"},{"full_name":"Tuff, Jim","first_name":"Jim","last_name":"Tuff"},{"first_name":"Thomas","last_name":"Kennedy","full_name":"Kennedy, Thomas"},{"full_name":"Pendergast, Shawn","last_name":"Pendergast","first_name":"Shawn"},{"first_name":"Sana","last_name":"Jamil","full_name":"Jamil, Sana"}],"page":"49-57","_id":"40046","abstract":[{"text":"Theoretical approaches to the transformation towards an inclusive educational system in Germany mostly agree on the involvement of developmental tasks in subject related research (Hinz, 2011). The common understanding of inclusion as a process geared towards equal participation of all children (Booth, 2012) requires a reflexive questioning of established values, attitudes and practices in order to develop inclusive subject related research, teacher training and teaching and learning (Pech & Schomaker, 2013). Among other things, this results in consequences for the design of pre- service teacher training. To a large extent, teacher education is driven by the promotion of central competencies, interests and self-efficacy (Baumert & Kunter, 2011). It aims towards the development and realisation of inclusive interdisciplinary science and social studies (‘Sachunterricht’) in primary education (Moser, 2018). In conjunction with largely acknowledged constructivist approaches to teaching and learning (Möller, 2001), the development of personality, the consideration of basic needs (Deci & Ryan, 1993) and promotion of individual potentials are repeatedly fundamentally represented in subject related and pedagogical considerations (Feuser, 1989; GDSU, 2013). Therefore, the aforementioned constructivist approach is connected to several certain key paradigms for teaching and learning processes (e.g., Vygotskij, 1978; Posner et al., 1982; van de Pol et al., 2010). In this regard, the nature of primary school students’ basic needs have empirically not been sufficiently studied yet. Theoretical frameworks from motivational psychology (Deci & Ryan, 1993) do not explicitly address how individual needs differ and how the diversity of needs can be included in joint-learning, multi-perspective technology education classes. The research project the present paper is part of aims to develop a research-based concept for the professionalisation of pre-service teachers in a seminar course. Therefore, the promotion of the pre- service teachers’ interests and self-efficacy expectations have been assessed in a pre-post research design with a control group visiting another course not related to technology education and inclusion. The present paper describes and discusses first results of the project and will give an outlook on subsequent developmental tasks.","lang":"eng"}],"publication":"PATT39 - PATT on the Edge Technology, Innovation and Education","type":"conference","keyword":["Inclusion","basic needs","pre-service teacher training","interest","self-efficacy"],"department":[{"_id":"588"}],"date_created":"2023-01-25T15:13:45Z","publication_status":"published","date_updated":"2023-01-25T15:13:57Z","title":"How to enable pre-service teachers to design technological teaching and learning inclusively? – On the nature and consideration of basic needs in teacher training","year":"2022","author":[{"id":"71764","full_name":"Schröer, Franz","last_name":"Schröer","first_name":"Franz"},{"full_name":"Tenberge, Claudia","last_name":"Tenberge","first_name":"Claudia","id":"67302"}],"publication_identifier":{"unknown":["https://research.edgehill.ac.uk/ws/portalfiles/portal/50821651/patt39_proceedings_june_17_2022.pdf"]},"main_file_link":[{"url":"https://research.edgehill.ac.uk/ws/portalfiles/portal/50821651/patt39_proceedings_june_17_2022.pdf"}],"language":[{"iso":"eng"}],"series_title":"PATT Proceedings"},{"status":"public","title":"Engaging with self-tracking applications: how do users respond to their performance data?","year":"2022","author":[{"first_name":"Ioanna","last_name":"Constantiou","full_name":"Constantiou, Ioanna"},{"last_name":"Mukkamala","first_name":"Alivelu","full_name":"Mukkamala, Alivelu"},{"full_name":"Sjöklint, Mimmi","last_name":"Sjöklint","first_name":"Mimmi"},{"id":"72744","first_name":"Matthias","last_name":"Trier","full_name":"Trier, Matthias"}],"publication_identifier":{"issn":["0960-085X","1476-9344"]},"date_updated":"2023-01-29T23:05:59Z","publication_status":"published","page":"1-21","_id":"36083","publisher":"Informa UK Limited","language":[{"iso":"eng"}],"doi":"10.1080/0960085x.2022.2081096","user_id":"14931","publication":"European Journal of Information Systems","citation":{"chicago":"Constantiou, Ioanna, Alivelu Mukkamala, Mimmi Sjöklint, and Matthias Trier. “Engaging with Self-Tracking Applications: How Do Users Respond to Their Performance Data?” <i>European Journal of Information Systems</i>, 2022, 1–21. <a href=\"https://doi.org/10.1080/0960085x.2022.2081096\">https://doi.org/10.1080/0960085x.2022.2081096</a>.","ama":"Constantiou I, Mukkamala A, Sjöklint M, Trier M. Engaging with self-tracking applications: how do users respond to their performance data? <i>European Journal of Information Systems</i>. Published online 2022:1-21. doi:<a href=\"https://doi.org/10.1080/0960085x.2022.2081096\">10.1080/0960085x.2022.2081096</a>","short":"I. Constantiou, A. Mukkamala, M. Sjöklint, M. Trier, European Journal of Information Systems (2022) 1–21.","bibtex":"@article{Constantiou_Mukkamala_Sjöklint_Trier_2022, title={Engaging with self-tracking applications: how do users respond to their performance data?}, DOI={<a href=\"https://doi.org/10.1080/0960085x.2022.2081096\">10.1080/0960085x.2022.2081096</a>}, journal={European Journal of Information Systems}, publisher={Informa UK Limited}, author={Constantiou, Ioanna and Mukkamala, Alivelu and Sjöklint, Mimmi and Trier, Matthias}, year={2022}, pages={1–21} }","apa":"Constantiou, I., Mukkamala, A., Sjöklint, M., &#38; Trier, M. (2022). Engaging with self-tracking applications: how do users respond to their performance data? <i>European Journal of Information Systems</i>, 1–21. <a href=\"https://doi.org/10.1080/0960085x.2022.2081096\">https://doi.org/10.1080/0960085x.2022.2081096</a>","mla":"Constantiou, Ioanna, et al. “Engaging with Self-Tracking Applications: How Do Users Respond to Their Performance Data?” <i>European Journal of Information Systems</i>, Informa UK Limited, 2022, pp. 1–21, doi:<a href=\"https://doi.org/10.1080/0960085x.2022.2081096\">10.1080/0960085x.2022.2081096</a>.","ieee":"I. Constantiou, A. Mukkamala, M. Sjöklint, and M. Trier, “Engaging with self-tracking applications: how do users respond to their performance data?,” <i>European Journal of Information Systems</i>, pp. 1–21, 2022, doi: <a href=\"https://doi.org/10.1080/0960085x.2022.2081096\">10.1080/0960085x.2022.2081096</a>."},"date_created":"2023-01-11T12:13:54Z","keyword":["Library and Information Sciences","Information Systems","Self-Tracking","User Behaviour","Discontinuance"],"type":"journal_article","department":[{"_id":"195"}]},{"citation":{"mla":"Philipo, Godiana Hagile, et al. “Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping.” <i>Energies</i>, vol. 15, no. 14, 5215, MDPI AG, 2022, doi:<a href=\"https://doi.org/10.3390/en15145215\">10.3390/en15145215</a>.","ama":"Philipo GH, Kakande JN, Krauter S. Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping. <i>Energies</i>. 2022;15(14). doi:<a href=\"https://doi.org/10.3390/en15145215\">10.3390/en15145215</a>","bibtex":"@article{Philipo_Kakande_Krauter_2022, title={Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping}, volume={15}, DOI={<a href=\"https://doi.org/10.3390/en15145215\">10.3390/en15145215</a>}, number={145215}, journal={Energies}, publisher={MDPI AG}, author={Philipo, Godiana Hagile and Kakande, Josephine Nakato and Krauter, Stefan}, year={2022} }","apa":"Philipo, G. H., Kakande, J. N., &#38; Krauter, S. (2022). Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping. <i>Energies</i>, <i>15</i>(14), Article 5215. <a href=\"https://doi.org/10.3390/en15145215\">https://doi.org/10.3390/en15145215</a>","ieee":"G. H. Philipo, J. N. Kakande, and S. Krauter, “Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping,” <i>Energies</i>, vol. 15, no. 14, Art. no. 5215, 2022, doi: <a href=\"https://doi.org/10.3390/en15145215\">10.3390/en15145215</a>.","chicago":"Philipo, Godiana Hagile, Josephine Nakato Kakande, and Stefan Krauter. “Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping.” <i>Energies</i> 15, no. 14 (2022). <a href=\"https://doi.org/10.3390/en15145215\">https://doi.org/10.3390/en15145215</a>.","short":"G.H. Philipo, J.N. Kakande, S. Krauter, Energies 15 (2022)."},"user_id":"16148","volume":15,"_id":"47961","publisher":"MDPI AG","status":"public","type":"journal_article","keyword":["Energy (miscellaneous)","Energy Engineering and Power Technology","Renewable Energy","Sustainability and the Environment","Electrical and Electronic Engineering","Control and Optimization","Engineering (miscellaneous)","Building and Construction"],"department":[{"_id":"53"}],"date_created":"2023-10-11T08:13:13Z","abstract":[{"lang":"eng","text":"<jats:p>Due to failures or even the absence of an electricity grid, microgrid systems are becoming popular solutions for electrifying African rural communities. However, they are heavily stressed and complex to control due to their intermittency and demand growth. Demand side management (DSM) serves as an option to increase the level of flexibility on the demand side by scheduling users’ consumption patterns profiles in response to supply. This paper proposes a demand-side management strategy based on load shifting and peak clipping. The proposed approach was modelled in a MATLAB/Simulink R2021a environment and was optimized using the artificial neural network (ANN) algorithm. Simulations were carried out to test the model’s efficacy in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces the peak demand, smoothing the load profile to the desired level, and improves the system’s peak to average ratio (PAR). The presence of deferrable loads has been considered to bring more flexible demand-side management. Results promise decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through peak clipping. In addition, load shifting promises more flexibility to customers.</jats:p>"}],"issue":"14","publication":"Energies","doi":"10.3390/en15145215","article_number":"5215","language":[{"iso":"eng"}],"date_updated":"2024-10-17T08:46:23Z","publication_status":"published","intvolume":"        15","year":"2022","title":"Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping","publication_identifier":{"issn":["1996-1073"]},"author":[{"full_name":"Philipo, Godiana Hagile","last_name":"Philipo","first_name":"Godiana Hagile","id":"88505"},{"id":"88649","full_name":"Kakande, Josephine Nakato","last_name":"Kakande","first_name":"Josephine Nakato"},{"id":"28836","full_name":"Krauter, Stefan","orcid":"0000-0002-3594-260X","last_name":"Krauter","first_name":"Stefan"}]},{"abstract":[{"lang":"eng","text":"While trade-offs between modeling effort and model accuracy remain a major concern with system identification, resorting to data-driven methods often leads to a complete disregard for physical plausibility. To address this issue, we propose a physics-guided hybrid approach for modeling non-autonomous systems under control. Starting from a traditional physics-based model, this is extended by a recurrent neural network and trained using a sophisticated multi-objective strategy yielding physically plausible models. While purely data-driven methods fail to produce satisfying results, experiments conducted on real data reveal substantial accuracy improvements by our approach compared to a physics-based model. "}],"issue":"12","publication":"14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)","department":[{"_id":"153"},{"_id":"880"}],"keyword":["neural networks","physics-guided","data-driven","multi-objective optimization","system identification","machine learning","dynamical systems"],"type":"conference","date_created":"2022-05-05T06:22:55Z","intvolume":"        55","date_updated":"2024-11-13T08:43:16Z","author":[{"first_name":"Oliver","last_name":"Schön","full_name":"Schön, Oliver"},{"id":"43992","full_name":"Götte, Ricarda-Samantha","last_name":"Götte","first_name":"Ricarda-Samantha"},{"full_name":"Timmermann, Julia","last_name":"Timmermann","first_name":"Julia","id":"15402"}],"title":"Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems","year":"2022","doi":"https://doi.org/10.1016/j.ifacol.2022.07.282","language":[{"iso":"eng"}],"quality_controlled":"1","citation":{"apa":"Schön, O., Götte, R.-S., &#38; Timmermann, J. (2022). Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. <i>14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)</i>, <i>55</i>(12), 19–24. <a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>","ieee":"O. Schön, R.-S. Götte, and J. Timmermann, “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems,” in <i>14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)</i>, Casablanca, Morocco, 2022, vol. 55, no. 12, pp. 19–24, doi: <a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>.","short":"O. Schön, R.-S. Götte, J. Timmermann, in: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 2022, pp. 19–24.","chicago":"Schön, Oliver, Ricarda-Samantha Götte, and Julia Timmermann. “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems.” In <i>14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)</i>, 55:19–24, 2022. <a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>.","mla":"Schön, Oliver, et al. “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems.” <i>14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)</i>, vol. 55, no. 12, 2022, pp. 19–24, doi:<a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>.","ama":"Schön O, Götte R-S, Timmermann J. Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. In: <i>14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)</i>. Vol 55. ; 2022:19-24. doi:<a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>","bibtex":"@inproceedings{Schön_Götte_Timmermann_2022, title={Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems}, volume={55}, DOI={<a href=\"https://doi.org/10.1016/j.ifacol.2022.07.282\">https://doi.org/10.1016/j.ifacol.2022.07.282</a>}, number={12}, booktitle={14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)}, author={Schön, Oliver and Götte, Ricarda-Samantha and Timmermann, Julia}, year={2022}, pages={19–24} }"},"conference":{"location":"Casablanca, Morocco","start_date":"2022-06-29","name":"14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)","end_date":"2022-07-01"},"status":"public","volume":55,"user_id":"43992","_id":"31066","page":"19-24"},{"date_updated":"2024-11-13T08:44:17Z","title":"Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design","status":"public","year":"2022","publication_identifier":{"isbn":["978-989-758-549-4"]},"author":[{"first_name":"Michael","last_name":"Hesse","full_name":"Hesse, Michael","id":"29222"},{"first_name":"Matthias","last_name":"Hunstig","full_name":"Hunstig, Matthias"},{"id":"15402","last_name":"Timmermann","first_name":"Julia","full_name":"Timmermann, Julia"},{"id":"552","full_name":"Trächtler, Ansgar","first_name":"Ansgar","last_name":"Trächtler"}],"conference":{"name":"11th International Conference on Pattern Recognition Applications and Methods","start_date":"2022-02-03","location":"Online","end_date":"2022-02-05"},"user_id":"82875","page":"383-394","_id":"29803","language":[{"iso":"eng"}],"quality_controlled":"1","abstract":[{"text":"Ultrasonic wire bonding is a solid-state joining process used to form electrical interconnections in micro and\r\npower electronics and batteries. A high frequency oscillation causes a metallurgical bond deformation in\r\nthe contact area. Due to the numerous physical influencing factors, it is very difficult to accurately capture\r\nthis process in a model. Therefore, our goal is to determine a suitable feed-forward control strategy for the\r\nbonding process even without detailed model knowledge. We propose the use of batch constrained Bayesian\r\noptimization for the control design. Hence, Bayesian optimization is precisely adapted to the application of\r\nbonding: the constraint is used to check one quality feature of the process and the use of batches leads to\r\nmore efficient experiments. Our approach is suitable to determine a feed-forward control for the bonding\r\nprocess that provides very high quality bonds without using a physical model. We also show that the quality\r\nof the Bayesian optimization based control outperforms random search as well as manual search by a user.\r\nUsing a simple prior knowledge model derived from data further improves the quality of the connection.\r\nThe Bayesian optimization approach offers the possibility to perform a sensitivity analysis of the control\r\nparameters, which allows to evaluate the influence of each control parameter on the bond quality. In summary,\r\nBayesian optimization applied to the bonding process provides an excellent opportunity to develop a feedforward\r\ncontrol without full modeling of the underlying physical processes.","lang":"eng"}],"publication":"Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM)","citation":{"short":"M. Hesse, M. Hunstig, J. Timmermann, A. Trächtler, in: Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM), 2022, pp. 383–394.","chicago":"Hesse, Michael, Matthias Hunstig, Julia Timmermann, and Ansgar Trächtler. “Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-Forward Control Design.” In <i>Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM)</i>, 383–94, 2022.","apa":"Hesse, M., Hunstig, M., Timmermann, J., &#38; Trächtler, A. (2022). Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design. <i>Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM)</i>, 383–394.","ieee":"M. Hesse, M. Hunstig, J. Timmermann, and A. Trächtler, “Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design,” in <i>Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM)</i>, Online, 2022, pp. 383–394.","ama":"Hesse M, Hunstig M, Timmermann J, Trächtler A. Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design. In: <i>Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM)</i>. ; 2022:383-394.","bibtex":"@inproceedings{Hesse_Hunstig_Timmermann_Trächtler_2022, title={Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-forward Control Design}, booktitle={Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM)}, author={Hesse, Michael and Hunstig, Matthias and Timmermann, Julia and Trächtler, Ansgar}, year={2022}, pages={383–394} }","mla":"Hesse, Michael, et al. “Batch Constrained Bayesian Optimization for UltrasonicWire Bonding Feed-Forward Control Design.” <i>Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods (ICPRAM)</i>, 2022, pp. 383–94."},"type":"conference","keyword":["Bayesian optimization","Wire bonding","Feed-forward control","model-free design"],"department":[{"_id":"153"},{"_id":"880"}],"date_created":"2022-02-09T12:50:25Z"},{"doi":"10.25969/MEDIAREP/18238","language":[{"iso":"ger"}],"publication_status":"published","date_updated":"2024-11-22T10:09:55Z","article_type":"original","intvolume":"         6","year":"2022","title":"‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker","author":[{"id":"33185","full_name":"Schloots, Franziska Margarete","first_name":"Franziska Margarete","last_name":"Schloots","orcid":"0009-0008-9673-2615"}],"keyword":["self-tracking","Selbsttechnologien","Wearable","Bullet Journal","Personenwaage","Selbstvermessung"],"type":"journal_article","department":[{"_id":"574"}],"file":[{"date_updated":"2022-12-20T14:23:57Z","relation":"main_file","access_level":"closed","file_size":530069,"file_name":"ffk_journal_07_74-91_Schloots_Selbstkontrolle_.pdf","content_type":"application/pdf","success":1,"file_id":"34616","creator":"fms","date_created":"2022-12-20T14:23:57Z"}],"date_created":"2022-12-20T14:20:56Z","abstract":[{"text":"Mit steigenden Optimierungsanforderungen an das Individuum wächst auch das indivi-\r\nduelle Bedürfnis nach Kontrolle. Dieses kann u. a. durch self tracking-Technologien erfüllt werden.\r\nAnhand von drei Fallbeispielen – der Personenwaage, dem Wearable und dem habit tracker – zeigt\r\ndieser Aufsatz, wie sich medienbasierte Selbsttechnologien im historischen Verlauf intensiviert und\r\nstärker in den Alltag integriert haben. Ein besonderer Fokus liegt dabei auf der Ambivalenz dieser\r\nMedien: Ermöglichen sie auf der einen Seite zwar eine Selbstkontrolle und stellen so potenziell sta-\r\nbilisierende Ressourcen für das Individuum dar, schaffen sie auf der anderen Seite auch neue\r\nAnforderungen, die es zu erfüllen gilt.","lang":"ger"}],"issue":"7","publication":"ffk Journal","user_id":"33185","ddc":["040"],"volume":6,"page":"74-91","_id":"34614","has_accepted_license":"1","status":"public","file_date_updated":"2022-12-20T14:23:57Z","citation":{"apa":"Schloots, F. M. (2022). ‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker. <i>ffk Journal</i>, <i>6</i>(7), 74–91. <a href=\"https://doi.org/10.25969/MEDIAREP/18238\">https://doi.org/10.25969/MEDIAREP/18238</a>","ieee":"F. M. Schloots, “‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker,” <i>ffk Journal</i>, vol. 6, no. 7, pp. 74–91, 2022, doi: <a href=\"https://doi.org/10.25969/MEDIAREP/18238\">10.25969/MEDIAREP/18238</a>.","chicago":"Schloots, Franziska Margarete. “‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker.” <i>ffk Journal</i> 6, no. 7 (2022): 74–91. <a href=\"https://doi.org/10.25969/MEDIAREP/18238\">https://doi.org/10.25969/MEDIAREP/18238</a>.","short":"F.M. Schloots, ffk Journal 6 (2022) 74–91.","mla":"Schloots, Franziska Margarete. “‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker.” <i>ffk Journal</i>, vol. 6, no. 7, 2022, pp. 74–91, doi:<a href=\"https://doi.org/10.25969/MEDIAREP/18238\">10.25969/MEDIAREP/18238</a>.","ama":"Schloots FM. ‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker. <i>ffk Journal</i>. 2022;6(7):74-91. doi:<a href=\"https://doi.org/10.25969/MEDIAREP/18238\">10.25969/MEDIAREP/18238</a>","bibtex":"@article{Schloots_2022, title={‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker}, volume={6}, DOI={<a href=\"https://doi.org/10.25969/MEDIAREP/18238\">10.25969/MEDIAREP/18238</a>}, number={7}, journal={ffk Journal}, author={Schloots, Franziska Margarete}, year={2022}, pages={74–91} }"}},{"page":"1-1","language":[{"iso":"eng"}],"_id":"21004","user_id":"5786","doi":"10.1109/tpami.2021.3051276","year":"2021","title":"AutoML for Multi-Label Classification: Overview and Empirical Evaluation","status":"public","publication_identifier":{"issn":["0162-8828","2160-9292","1939-3539"]},"author":[{"id":"33176","last_name":"Wever","orcid":" https://orcid.org/0000-0001-9782-6818","first_name":"Marcel Dominik","full_name":"Wever, Marcel Dominik"},{"first_name":"Alexander","last_name":"Tornede","full_name":"Tornede, Alexander","id":"38209"},{"first_name":"Felix","last_name":"Mohr","full_name":"Mohr, Felix"},{"id":"48129","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","first_name":"Eyke"}],"publication_status":"published","date_updated":"2022-01-06T06:54:42Z","date_created":"2021-01-16T14:48:13Z","keyword":["Automated Machine Learning","Multi Label Classification","Hierarchical Planning","Bayesian Optimization"],"type":"journal_article","department":[{"_id":"34"},{"_id":"355"},{"_id":"26"}],"publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","citation":{"ama":"Wever MD, Tornede A, Mohr F, Hüllermeier E. AutoML for Multi-Label Classification: Overview and Empirical Evaluation. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. Published online 2021:1-1. doi:<a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>","short":"M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) 1–1.","chicago":"Wever, Marcel Dominik, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, 2021, 1–1. <a href=\"https://doi.org/10.1109/tpami.2021.3051276\">https://doi.org/10.1109/tpami.2021.3051276</a>.","bibtex":"@article{Wever_Tornede_Mohr_Hüllermeier_2021, title={AutoML for Multi-Label Classification: Overview and Empirical Evaluation}, DOI={<a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, author={Wever, Marcel Dominik and Tornede, Alexander and Mohr, Felix and Hüllermeier, Eyke}, year={2021}, pages={1–1} }","apa":"Wever, M. D., Tornede, A., Mohr, F., &#38; Hüllermeier, E. (2021). AutoML for Multi-Label Classification: Overview and Empirical Evaluation. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, 1–1. <a href=\"https://doi.org/10.1109/tpami.2021.3051276\">https://doi.org/10.1109/tpami.2021.3051276</a>","mla":"Wever, Marcel Dominik, et al. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, 2021, pp. 1–1, doi:<a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>.","ieee":"M. D. Wever, A. Tornede, F. Mohr, and E. Hüllermeier, “AutoML for Multi-Label Classification: Overview and Empirical Evaluation,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, pp. 1–1, 2021, doi: <a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>."},"abstract":[{"lang":"eng","text":"Automated machine learning (AutoML) supports the algorithmic construction and data-specific customization of machine learning pipelines, including the selection, combination, and parametrization of machine learning algorithms as main constituents. Generally speaking, AutoML approaches comprise two major components: a search space model and an optimizer for traversing the space. Recent approaches have shown impressive results in the realm of supervised learning, most notably (single-label) classification (SLC). Moreover, first attempts at extending these approaches towards multi-label classification (MLC) have been made. While the space of candidate pipelines is already huge in SLC, the complexity of the search space is raised to an even higher power in MLC. One may wonder, therefore, whether and to what extent optimizers established for SLC can scale to this increased complexity, and how they compare to each other. This paper makes the following contributions: First, we survey existing approaches to AutoML for MLC. Second, we augment these approaches with optimizers not previously tried for MLC. Third, we propose a benchmarking framework that supports a fair and systematic comparison. Fourth, we conduct an extensive experimental study, evaluating the methods on a suite of MLC problems. We find a grammar-based best-first search to compare favorably to other optimizers."}],"project":[{"name":"SFB 901","_id":"1"},{"_id":"3","name":"SFB 901 - Project Area B"},{"name":"SFB 901 - Subproject B2","_id":"10"},{"_id":"52","name":"Computing Resources Provided by the Paderborn Center for Parallel Computing"}]},{"publication":"Transactions on Network and Service Management","abstract":[{"text":"Modern services consist of interconnected components,e.g., microservices in a service mesh or machine learning functions in a pipeline. These services can scale and run across multiple network nodes on demand. To process incoming traffic, service components have to be instantiated and traffic assigned to these instances, taking capacities, changing demands, and Quality of Service (QoS) requirements into account. This challenge is usually solved with custom approaches designed by experts. While this typically works well for the considered scenario, the models often rely on unrealistic assumptions or on knowledge that is not available in practice (e.g., a priori knowledge).\r\n\r\nWe propose DeepCoord, a novel deep reinforcement learning approach that learns how to best coordinate services and is geared towards realistic assumptions. It interacts with the network and relies on available, possibly delayed monitoring information. Rather than defining a complex model or an algorithm on how to achieve an objective, our model-free approach adapts to various objectives and traffic patterns. An agent is trained offline without expert knowledge and then applied online with minimal overhead. Compared to a state-of-the-art heuristic, DeepCoord significantly improves flow throughput (up to 76%) and overall network utility (more than 2x) on realworld network topologies and traffic traces. It also supports optimizing multiple, possibly competing objectives, learns to respect QoS requirements, generalizes to scenarios with unseen, stochastic traffic, and scales to large real-world networks. For reproducibility and reuse, our code is publicly available.","lang":"eng"}],"file":[{"relation":"main_file","date_updated":"2021-04-27T08:01:26Z","file_name":"ris-accepted-version.pdf","access_level":"open_access","file_size":4172270,"file_id":"21809","content_type":"application/pdf","creator":"stschn","description":"Author version of the accepted paper","date_created":"2021-04-27T08:01:26Z"}],"date_created":"2021-04-27T08:04:16Z","type":"journal_article","keyword":["network management","service management","coordination","reinforcement learning","self-learning","self-adaptation","multi-objective"],"department":[{"_id":"75"}],"year":"2021","title":"Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning","author":[{"id":"35343","full_name":"Schneider, Stefan Balthasar","first_name":"Stefan Balthasar","orcid":"0000-0001-8210-4011","last_name":"Schneider"},{"full_name":"Khalili, Ramin","last_name":"Khalili","first_name":"Ramin"},{"full_name":"Manzoor, Adnan","last_name":"Manzoor","first_name":"Adnan"},{"full_name":"Qarawlus, Haydar","first_name":"Haydar","last_name":"Qarawlus"},{"full_name":"Schellenberg, Rafael","first_name":"Rafael","last_name":"Schellenberg"},{"last_name":"Karl","first_name":"Holger","full_name":"Karl, Holger","id":"126"},{"full_name":"Hecker, Artur","first_name":"Artur","last_name":"Hecker"}],"date_updated":"2022-01-06T06:55:15Z","article_type":"original","language":[{"iso":"eng"}],"doi":"10.1109/TNSM.2021.3076503","file_date_updated":"2021-04-27T08:01:26Z","citation":{"bibtex":"@article{Schneider_Khalili_Manzoor_Qarawlus_Schellenberg_Karl_Hecker_2021, title={Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning}, DOI={<a href=\"https://doi.org/10.1109/TNSM.2021.3076503\">10.1109/TNSM.2021.3076503</a>}, journal={Transactions on Network and Service Management}, publisher={IEEE}, author={Schneider, Stefan Balthasar and Khalili, Ramin and Manzoor, Adnan and Qarawlus, Haydar and Schellenberg, Rafael and Karl, Holger and Hecker, Artur}, year={2021} }","ama":"Schneider SB, Khalili R, Manzoor A, et al. Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning. <i>Transactions on Network and Service Management</i>. 2021. doi:<a href=\"https://doi.org/10.1109/TNSM.2021.3076503\">10.1109/TNSM.2021.3076503</a>","mla":"Schneider, Stefan Balthasar, et al. “Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning.” <i>Transactions on Network and Service Management</i>, IEEE, 2021, doi:<a href=\"https://doi.org/10.1109/TNSM.2021.3076503\">10.1109/TNSM.2021.3076503</a>.","short":"S.B. Schneider, R. Khalili, A. Manzoor, H. Qarawlus, R. Schellenberg, H. Karl, A. Hecker, Transactions on Network and Service Management (2021).","chicago":"Schneider, Stefan Balthasar, Ramin Khalili, Adnan Manzoor, Haydar Qarawlus, Rafael Schellenberg, Holger Karl, and Artur Hecker. “Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning.” <i>Transactions on Network and Service Management</i>, 2021. <a href=\"https://doi.org/10.1109/TNSM.2021.3076503\">https://doi.org/10.1109/TNSM.2021.3076503</a>.","ieee":"S. B. Schneider <i>et al.</i>, “Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning,” <i>Transactions on Network and Service Management</i>, 2021.","apa":"Schneider, S. B., Khalili, R., Manzoor, A., Qarawlus, H., Schellenberg, R., Karl, H., &#38; Hecker, A. (2021). Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning. <i>Transactions on Network and Service Management</i>. <a href=\"https://doi.org/10.1109/TNSM.2021.3076503\">https://doi.org/10.1109/TNSM.2021.3076503</a>"},"project":[{"name":"SFB 901","_id":"1"},{"_id":"4","name":"SFB 901 - Project Area C"},{"name":"SFB 901 - Subproject C4","_id":"16"}],"oa":"1","status":"public","has_accepted_license":"1","publisher":"IEEE","_id":"21808","ddc":["000"],"user_id":"35343"},{"keyword":["mobility management","coordinated multipoint","CoMP","cell selection","resource management","reinforcement learning","multi agent","MARL","self-learning","self-adaptation","QoE"],"type":"working_paper","department":[{"_id":"75"}],"oa":"1","file":[{"date_created":"2022-10-20T16:41:10Z","creator":"stschn","content_type":"application/pdf","file_id":"33855","date_updated":"2022-10-20T16:41:10Z","relation":"main_file","file_size":2521656,"access_level":"open_access","file_name":"preprint.pdf"}],"date_created":"2022-10-20T16:44:19Z","abstract":[{"text":"Macrodiversity is a key technique to increase the capacity of mobile networks. It can be realized using coordinated multipoint (CoMP), simultaneously connecting users to multiple overlapping cells. Selecting which users to serve by how many and which cells is NP-hard but needs to happen continuously in real time as users move and channel state changes. Existing approaches often require strict assumptions about or perfect knowledge of the underlying radio system, its resource allocation scheme, or user movements, none of which is readily available in practice.\r\n\r\nInstead, we propose three novel self-learning and self-adapting approaches using model-free deep reinforcement learning (DRL): DeepCoMP, DD-CoMP, and D3-CoMP. DeepCoMP leverages central observations and control of all users to select cells almost optimally. DD-CoMP and D3-CoMP use multi-agent DRL, which allows distributed, robust, and highly scalable coordination. All three approaches learn from experience and self-adapt to varying scenarios, reaching 2x higher Quality of Experience than other approaches. They have very few built-in assumptions and do not need prior system knowledge, making them more robust to change and better applicable in practice than existing approaches.","lang":"eng"}],"project":[{"_id":"4","name":"SFB 901 - C: SFB 901 - Project Area C"},{"_id":"16","name":"SFB 901 - C4: SFB 901 - Subproject C4"},{"_id":"1","name":"SFB 901: SFB 901"}],"file_date_updated":"2022-10-20T16:41:10Z","citation":{"chicago":"Schneider, Stefan Balthasar, Holger Karl, Ramin Khalili, and Artur Hecker. <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>, 2021.","short":"S.B. Schneider, H. Karl, R. Khalili, A. Hecker, DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning, 2021.","ieee":"S. B. Schneider, H. Karl, R. Khalili, and A. Hecker, <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>. 2021.","apa":"Schneider, S. B., Karl, H., Khalili, R., &#38; Hecker, A. (2021). <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>.","bibtex":"@book{Schneider_Karl_Khalili_Hecker_2021, title={DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning}, author={Schneider, Stefan Balthasar and Karl, Holger and Khalili, Ramin and Hecker, Artur}, year={2021} }","ama":"Schneider SB, Karl H, Khalili R, Hecker A. <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>.; 2021.","mla":"Schneider, Stefan Balthasar, et al. <i>DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning</i>. 2021."},"user_id":"477","ddc":["004"],"language":[{"iso":"eng"}],"_id":"33854","date_updated":"2022-11-18T09:59:27Z","has_accepted_license":"1","year":"2021","status":"public","title":"DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning","author":[{"id":"35343","full_name":"Schneider, Stefan Balthasar","orcid":"0000-0001-8210-4011","last_name":"Schneider","first_name":"Stefan Balthasar"},{"last_name":"Karl","first_name":"Holger","full_name":"Karl, Holger","id":"126"},{"first_name":"Ramin","last_name":"Khalili","full_name":"Khalili, Ramin"},{"full_name":"Hecker, Artur","last_name":"Hecker","first_name":"Artur"}]},{"page":"105489","language":[{"iso":"eng"}],"_id":"46318","user_id":"15504","doi":"https://doi.org/10.1016/j.cor.2021.105489","volume":136,"status":"public","year":"2021","title":"Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization","publication_identifier":{"issn":["0305-0548"]},"author":[{"last_name":"Grimme","first_name":"Christian","full_name":"Grimme, Christian"},{"first_name":"Pascal","last_name":"Kerschke","full_name":"Kerschke, Pascal"},{"full_name":"Aspar, Pelin","last_name":"Aspar","first_name":"Pelin"},{"id":"100740","first_name":"Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann","full_name":"Trautmann, Heike"},{"full_name":"Preuss, Mike","first_name":"Mike","last_name":"Preuss"},{"last_name":"Deutz","first_name":"André H.","full_name":"Deutz, André H."},{"first_name":"Hao","last_name":"Wang","full_name":"Wang, Hao"},{"last_name":"Emmerich","first_name":"Michael","full_name":"Emmerich, Michael"}],"date_updated":"2023-10-16T12:58:42Z","intvolume":"       136","date_created":"2023-08-04T07:28:34Z","keyword":["Multimodal optimization","Multi-objective continuous optimization","Landscape analysis","Visualization","Benchmarking","Theory","Algorithms"],"type":"journal_article","department":[{"_id":"34"},{"_id":"819"}],"publication":"Computers & Operations Research","citation":{"mla":"Grimme, Christian, et al. “Peeking beyond Peaks: Challenges and Research Potentials of Continuous Multimodal Multi-Objective Optimization.” <i>Computers &#38; Operations Research</i>, vol. 136, 2021, p. 105489, doi:<a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>.","bibtex":"@article{Grimme_Kerschke_Aspar_Trautmann_Preuss_Deutz_Wang_Emmerich_2021, title={Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization}, volume={136}, DOI={<a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>}, journal={Computers &#38; Operations Research}, author={Grimme, Christian and Kerschke, Pascal and Aspar, Pelin and Trautmann, Heike and Preuss, Mike and Deutz, André H. and Wang, Hao and Emmerich, Michael}, year={2021}, pages={105489} }","ama":"Grimme C, Kerschke P, Aspar P, et al. Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. <i>Computers &#38; Operations Research</i>. 2021;136:105489. doi:<a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>","ieee":"C. Grimme <i>et al.</i>, “Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization,” <i>Computers &#38; Operations Research</i>, vol. 136, p. 105489, 2021, doi: <a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>.","apa":"Grimme, C., Kerschke, P., Aspar, P., Trautmann, H., Preuss, M., Deutz, A. H., Wang, H., &#38; Emmerich, M. (2021). Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. <i>Computers &#38; Operations Research</i>, <i>136</i>, 105489. <a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>","chicago":"Grimme, Christian, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, and Michael Emmerich. “Peeking beyond Peaks: Challenges and Research Potentials of Continuous Multimodal Multi-Objective Optimization.” <i>Computers &#38; Operations Research</i> 136 (2021): 105489. <a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>.","short":"C. Grimme, P. Kerschke, P. Aspar, H. Trautmann, M. Preuss, A.H. Deutz, H. Wang, M. Emmerich, Computers &#38; Operations Research 136 (2021) 105489."},"abstract":[{"lang":"eng","text":"Multi-objective (MO) optimization, i.e., the simultaneous optimization of multiple conflicting objectives, is gaining more and more attention in various research areas, such as evolutionary computation, machine learning (e.g., (hyper-)parameter optimization), or logistics (e.g., vehicle routing). Many works in this domain mention the structural problem property of multimodality as a challenge from two classical perspectives: (1) finding all globally optimal solution sets, and (2) avoiding to get trapped in local optima. Interestingly, these streams seem to transfer many traditional concepts of single-objective (SO) optimization into claims, assumptions, or even terminology regarding the MO domain, but mostly neglect the understanding of the structural properties as well as the algorithmic search behavior on a problem’s landscape. However, some recent works counteract this trend, by investigating the fundamentals and characteristics of MO problems using new visualization techniques and gaining surprising insights. Using these visual insights, this work proposes a step towards a unified terminology to capture multimodality and locality in a broader way than it is usually done. This enables us to investigate current research activities in multimodal continuous MO optimization and to highlight new implications and promising research directions for the design of benchmark suites, the discovery of MO landscape features, the development of new MO (or even SO) optimization algorithms, and performance indicators. For all these topics, we provide a review of ideas and methods but also an outlook on future challenges, research potential and perspectives that result from recent developments."}]},{"citation":{"mla":"Bossek, Jakob, et al. “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms.” <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, Association for Computing Machinery, 2021, pp. 556–564, doi:<a href=\"https://doi.org/10.1145/3449639.3459364\">10.1145/3449639.3459364</a>.","bibtex":"@inproceedings{Bossek_Neumann_Neumann_2021, place={New York, NY, USA}, series={GECCO ’21}, title={Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms}, DOI={<a href=\"https://doi.org/10.1145/3449639.3459364\">10.1145/3449639.3459364</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Bossek, Jakob and Neumann, Aneta and Neumann, Frank}, year={2021}, pages={556–564}, collection={GECCO ’21} }","ama":"Bossek J, Neumann A, Neumann F. Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. GECCO ’21. Association for Computing Machinery; 2021:556–564. doi:<a href=\"https://doi.org/10.1145/3449639.3459364\">10.1145/3449639.3459364</a>","ieee":"J. Bossek, A. Neumann, and F. Neumann, “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2021, pp. 556–564, doi: <a href=\"https://doi.org/10.1145/3449639.3459364\">10.1145/3449639.3459364</a>.","apa":"Bossek, J., Neumann, A., &#38; Neumann, F. (2021). Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms. <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 556–564. <a href=\"https://doi.org/10.1145/3449639.3459364\">https://doi.org/10.1145/3449639.3459364</a>","short":"J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 556–564.","chicago":"Bossek, Jakob, Aneta Neumann, and Frank Neumann. “Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 556–564. GECCO ’21. New York, NY, USA: Association for Computing Machinery, 2021. <a href=\"https://doi.org/10.1145/3449639.3459364\">https://doi.org/10.1145/3449639.3459364</a>."},"place":"New York, NY, USA","status":"public","page":"556–564","_id":"48853","publisher":"Association for Computing Machinery","user_id":"102979","publication":"Proceedings of the Genetic and Evolutionary Computation Conference","extern":"1","abstract":[{"lang":"eng","text":"In practise, it is often desirable to provide the decision-maker with a rich set of diverse solutions of decent quality instead of just a single solution. In this paper we study evolutionary diversity optimization for the knapsack problem (KP). Our goal is to evolve a population of solutions that all have a profit of at least (1 - {$ϵ$}) {$\\cdot$} OPT, where OPT is the value of an optimal solution. Furthermore, they should differ in structure with respect to an entropy-based diversity measure. To this end we propose a simple ({$\\mu$} + 1)-EA with initial approximate solutions calculated by a well-known FPTAS for the KP. We investigate the effect of different standard mutation operators and introduce biased mutation and crossover which puts strong probability on flipping bits of low and/or high frequency within the population. An experimental study on different instances and settings shows that the proposed mutation operators in most cases perform slightly inferior in the long term, but show strong benefits if the number of function evaluations is severely limited."}],"date_created":"2023-11-14T15:58:54Z","keyword":["evolutionary algorithms","evolutionary diversity optimization","knapsack problem","tailored operators"],"type":"conference","department":[{"_id":"819"}],"title":"Breeding Diverse Packings for the Knapsack Problem by Means of Diversity-Tailored Evolutionary Algorithms","year":"2021","publication_identifier":{"isbn":["978-1-4503-8350-9"]},"author":[{"first_name":"Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","full_name":"Bossek, Jakob","id":"102979"},{"full_name":"Neumann, Aneta","last_name":"Neumann","first_name":"Aneta"},{"full_name":"Neumann, Frank","first_name":"Frank","last_name":"Neumann"}],"publication_status":"published","date_updated":"2023-12-13T10:45:22Z","series_title":"GECCO ’21","language":[{"iso":"eng"}],"doi":"10.1145/3449639.3459364"},{"type":"conference","keyword":["evolutionary algorithms","evolutionary diversity optimization","minimum spanning tree","runtime analysis"],"department":[{"_id":"819"}],"date_created":"2023-11-14T15:58:55Z","extern":"1","abstract":[{"lang":"eng","text":"In the area of evolutionary computation the calculation of diverse sets of high-quality solutions to a given optimization problem has gained momentum in recent years under the term evolutionary diversity optimization. Theoretical insights into the working principles of baseline evolutionary algorithms for diversity optimization are still rare. In this paper we study the well-known Minimum Spanning Tree problem (MST) in the context of diversity optimization where population diversity is measured by the sum of pairwise edge overlaps. Theoretical results provide insights into the fitness landscape of the MST diversity optimization problem pointing out that even for a population of {$\\mu$} = 2 fitness plateaus (of constant length) can be reached, but nevertheless diverse sets can be calculated in polynomial time. We supplement our theoretical results with a series of experiments for the unconstrained and constraint case where all solutions need to fulfill a minimal quality threshold. Our results show that a simple ({$\\mu$} + 1)-EA can effectively compute a diversified population of spanning trees of high quality."}],"publication":"Proceedings of the Genetic and Evolutionary Computation Conference","doi":"10.1145/3449639.3459363","series_title":"GECCO ’21","language":[{"iso":"eng"}],"publication_status":"published","date_updated":"2023-12-13T10:45:37Z","year":"2021","title":"Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem","publication_identifier":{"isbn":["978-1-4503-8350-9"]},"author":[{"id":"102979","first_name":"Jakob","orcid":"0000-0002-4121-4668","last_name":"Bossek","full_name":"Bossek, Jakob"},{"first_name":"Frank","last_name":"Neumann","full_name":"Neumann, Frank"}],"place":"New York, NY, USA","citation":{"mla":"Bossek, Jakob, and Frank Neumann. “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem.” <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, Association for Computing Machinery, 2021, pp. 198–206, doi:<a href=\"https://doi.org/10.1145/3449639.3459363\">10.1145/3449639.3459363</a>.","bibtex":"@inproceedings{Bossek_Neumann_2021, place={New York, NY, USA}, series={GECCO ’21}, title={Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem}, DOI={<a href=\"https://doi.org/10.1145/3449639.3459363\">10.1145/3449639.3459363</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Bossek, Jakob and Neumann, Frank}, year={2021}, pages={198–206}, collection={GECCO ’21} }","ama":"Bossek J, Neumann F. Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. GECCO ’21. Association for Computing Machinery; 2021:198–206. doi:<a href=\"https://doi.org/10.1145/3449639.3459363\">10.1145/3449639.3459363</a>","ieee":"J. Bossek and F. Neumann, “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2021, pp. 198–206, doi: <a href=\"https://doi.org/10.1145/3449639.3459363\">10.1145/3449639.3459363</a>.","apa":"Bossek, J., &#38; Neumann, F. (2021). Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem. <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 198–206. <a href=\"https://doi.org/10.1145/3449639.3459363\">https://doi.org/10.1145/3449639.3459363</a>","short":"J. Bossek, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2021, pp. 198–206.","chicago":"Bossek, Jakob, and Frank Neumann. “Evolutionary Diversity Optimization and the Minimum Spanning Tree Problem.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 198–206. GECCO ’21. New York, NY, USA: Association for Computing Machinery, 2021. <a href=\"https://doi.org/10.1145/3449639.3459363\">https://doi.org/10.1145/3449639.3459363</a>."},"user_id":"102979","page":"198–206","_id":"48860","publisher":"Association for Computing Machinery","status":"public"},{"status":"public","user_id":"102979","volume":83,"page":"3148–3179","_id":"48854","citation":{"mla":"Bossek, Jakob, et al. “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.” <i>Algorithmica</i>, vol. 83, no. 10, 2021, pp. 3148–3179, doi:<a href=\"https://doi.org/10.1007/s00453-021-00838-3\">10.1007/s00453-021-00838-3</a>.","bibtex":"@article{Bossek_Neumann_Peng_Sudholt_2021, title={Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem}, volume={83}, DOI={<a href=\"https://doi.org/10.1007/s00453-021-00838-3\">10.1007/s00453-021-00838-3</a>}, number={10}, journal={Algorithmica}, author={Bossek, Jakob and Neumann, Frank and Peng, Pan and Sudholt, Dirk}, year={2021}, pages={3148–3179} }","ama":"Bossek J, Neumann F, Peng P, Sudholt D. Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. <i>Algorithmica</i>. 2021;83(10):3148–3179. doi:<a href=\"https://doi.org/10.1007/s00453-021-00838-3\">10.1007/s00453-021-00838-3</a>","ieee":"J. Bossek, F. Neumann, P. Peng, and D. Sudholt, “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem,” <i>Algorithmica</i>, vol. 83, no. 10, pp. 3148–3179, 2021, doi: <a href=\"https://doi.org/10.1007/s00453-021-00838-3\">10.1007/s00453-021-00838-3</a>.","apa":"Bossek, J., Neumann, F., Peng, P., &#38; Sudholt, D. (2021). Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem. <i>Algorithmica</i>, <i>83</i>(10), 3148–3179. <a href=\"https://doi.org/10.1007/s00453-021-00838-3\">https://doi.org/10.1007/s00453-021-00838-3</a>","short":"J. Bossek, F. Neumann, P. Peng, D. Sudholt, Algorithmica 83 (2021) 3148–3179.","chicago":"Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem.” <i>Algorithmica</i> 83, no. 10 (2021): 3148–3179. <a href=\"https://doi.org/10.1007/s00453-021-00838-3\">https://doi.org/10.1007/s00453-021-00838-3</a>."},"date_updated":"2023-12-13T10:51:34Z","intvolume":"        83","year":"2021","title":"Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem","author":[{"id":"102979","full_name":"Bossek, Jakob","last_name":"Bossek","first_name":"Jakob","orcid":"0000-0002-4121-4668"},{"full_name":"Neumann, Frank","first_name":"Frank","last_name":"Neumann"},{"full_name":"Peng, Pan","first_name":"Pan","last_name":"Peng"},{"last_name":"Sudholt","first_name":"Dirk","full_name":"Sudholt, Dirk"}],"publication_identifier":{"issn":["0178-4617"]},"doi":"10.1007/s00453-021-00838-3","language":[{"iso":"eng"}],"abstract":[{"text":"We contribute to the theoretical understanding of randomized search heuristics for dynamic problems. We consider the classical vertex coloring problem on graphs and investigate the dynamic setting where edges are added to the current graph. We then analyze the expected time for randomized search heuristics to recompute high quality solutions. The (1+1) Evolutionary Algorithm and RLS operate in a setting where the number of colors is bounded and we are minimizing the number of conflicts. Iterated local search algorithms use an unbounded color palette and aim to use the smallest colors and, consequently, the smallest number of colors. We identify classes of bipartite graphs where reoptimization is as hard as or even harder than optimization from scratch, i.e., starting with a random initialization. Even adding a single edge can lead to hard symmetry problems. However, graph classes that are hard for one algorithm turn out to be easy for others. In most cases our bounds show that reoptimization is faster than optimizing from scratch. We further show that tailoring mutation operators to parts of the graph where changes have occurred can significantly reduce the expected reoptimization time. In most settings the expected reoptimization time for such tailored algorithms is linear in the number of added edges. However, tailored algorithms cannot prevent exponential times in settings where the original algorithm is inefficient.","lang":"eng"}],"issue":"10","publication":"Algorithmica","keyword":["Dynamic optimization","Evolutionary algorithms","Running time analysis"],"type":"journal_article","department":[{"_id":"819"}],"date_created":"2023-11-14T15:58:54Z"},{"doi":"https://doi.org/10.1016/j.microrel.2021.114077","language":[{"iso":"eng"}],"intvolume":"       119","date_updated":"2023-09-21T14:15:33Z","publication_status":"published","publication_identifier":{"issn":["0026-2714"]},"author":[{"full_name":"Schemmel, Reinhard","first_name":"Reinhard","last_name":"Schemmel","id":"28647"},{"first_name":"Viktor","last_name":"Krieger","full_name":"Krieger, Viktor"},{"full_name":"Hemsel, Tobias","first_name":"Tobias","last_name":"Hemsel","id":"210"},{"id":"21220","full_name":"Sextro, Walter","last_name":"Sextro","first_name":"Walter"}],"year":"2021","title":"Co-simulation of MATLAB and ANSYS for ultrasonic wire bonding process optimization","department":[{"_id":"151"}],"type":"journal_article","keyword":["Ultrasonic heavy wire bonding","Co-simulation","ANSYS","MATLAB","Process optimization","Friction coefficient","Copper-copper","Aluminium-copper"],"date_created":"2021-03-10T09:37:02Z","abstract":[{"text":"Ultrasonic wire bonding is a solid-state joining process, used in the electronics industry to form electrical connections, e.g. to connect electrical terminals within semiconductor modules. Many process parameters affect the bond strength, such like the bond normal force, ultrasonic power, wire material and bonding frequency. Today, process design, development, and optimization is most likely based on the knowledge of process engineers and is mainly performed by experimental testing. In this contribution, a newly developed simulation tool is presented, to reduce time and costs and efficiently determine optimized process parameter. Based on a co-simulation of MATLAB and ANSYS, the different physical phenomena of the wire bonding process are considered using finite element simulation for the complex plastic deformation of the wire and reduced order models for the transient dynamics of the transducer, wire, substrate and bond formation. The model parameters such as the coefficients of friction between bond tool and wire and between wire and substrate were determined for aluminium and copper wire in experiments with a test rig specially developed for the requirements of heavy wire bonding. To reduce simulation time, for the finite element simulation a restart analysis and high performance computing is utilized. Detailed analysis of the bond formation showed, that the normal pressure distribution in the contact between wire and substrate has high impact on bond formation and distribution of welded areas in the contact area.","lang":"eng"}],"publication":"Microelectronics Reliability","volume":119,"user_id":"210","_id":"21436","page":"114077","status":"public","quality_controlled":"1","citation":{"ieee":"R. Schemmel, V. Krieger, T. Hemsel, and W. Sextro, “Co-simulation of MATLAB and ANSYS for ultrasonic wire bonding process optimization,” <i>Microelectronics Reliability</i>, vol. 119, p. 114077, 2021, doi: <a href=\"https://doi.org/10.1016/j.microrel.2021.114077\">https://doi.org/10.1016/j.microrel.2021.114077</a>.","apa":"Schemmel, R., Krieger, V., Hemsel, T., &#38; Sextro, W. (2021). Co-simulation of MATLAB and ANSYS for ultrasonic wire bonding process optimization. <i>Microelectronics Reliability</i>, <i>119</i>, 114077. <a href=\"https://doi.org/10.1016/j.microrel.2021.114077\">https://doi.org/10.1016/j.microrel.2021.114077</a>","short":"R. Schemmel, V. Krieger, T. Hemsel, W. Sextro, Microelectronics Reliability 119 (2021) 114077.","chicago":"Schemmel, Reinhard, Viktor Krieger, Tobias Hemsel, and Walter Sextro. “Co-Simulation of MATLAB and ANSYS for Ultrasonic Wire Bonding Process Optimization.” <i>Microelectronics Reliability</i> 119 (2021): 114077. <a href=\"https://doi.org/10.1016/j.microrel.2021.114077\">https://doi.org/10.1016/j.microrel.2021.114077</a>.","mla":"Schemmel, Reinhard, et al. “Co-Simulation of MATLAB and ANSYS for Ultrasonic Wire Bonding Process Optimization.” <i>Microelectronics Reliability</i>, vol. 119, 2021, p. 114077, doi:<a href=\"https://doi.org/10.1016/j.microrel.2021.114077\">https://doi.org/10.1016/j.microrel.2021.114077</a>.","bibtex":"@article{Schemmel_Krieger_Hemsel_Sextro_2021, title={Co-simulation of MATLAB and ANSYS for ultrasonic wire bonding process optimization}, volume={119}, DOI={<a href=\"https://doi.org/10.1016/j.microrel.2021.114077\">https://doi.org/10.1016/j.microrel.2021.114077</a>}, journal={Microelectronics Reliability}, author={Schemmel, Reinhard and Krieger, Viktor and Hemsel, Tobias and Sextro, Walter}, year={2021}, pages={114077} }","ama":"Schemmel R, Krieger V, Hemsel T, Sextro W. Co-simulation of MATLAB and ANSYS for ultrasonic wire bonding process optimization. <i>Microelectronics Reliability</i>. 2021;119:114077. doi:<a href=\"https://doi.org/10.1016/j.microrel.2021.114077\">https://doi.org/10.1016/j.microrel.2021.114077</a>"}},{"language":[{"iso":"eng"}],"doi":"10.1007/978-3-030-75381-8_124","author":[{"last_name":"Uhe","first_name":"Benedikt","full_name":"Uhe, Benedikt","id":"38131"},{"last_name":"Kuball","first_name":"Clara-Maria","full_name":"Kuball, Clara-Maria"},{"full_name":"Merklein, Marion","first_name":"Marion","last_name":"Merklein"},{"orcid":"0000-0002-2763-1246","first_name":"Gerson","last_name":"Meschut","full_name":"Meschut, Gerson","id":"32056"}],"year":"2021","title":"Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening","date_updated":"2026-02-27T10:40:39Z","publication_status":"published","date_created":"2021-08-04T14:02:32Z","department":[{"_id":"157"}],"keyword":["Self-piercing riveting","Lightweight design","Deformation behaviour","Stainless steel","High nitrogen steel"],"type":"book_chapter","publication":"Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals & Materials Series.","abstract":[{"text":"Self-piercing riveting is an established technique for joining multi-material structures in car body manufacturing. Rivets for self-piercing riveting differ in their geometry, the material used, the condition of the material and their surface condition. To shorten the manufacturing process by omitting the heat treatment and the coating process, the authors have elaborated a concept for the use of stainless steel with high strain hardening as a rivet material. The focus of the present investigation is on the evaluation of the influences of the rivet’s geometry and material on its deformation behaviour. Conventional rivets of types P and HD2, a rivet with an improved geometry made of treatable steel 38B2, and rivets made of the stainless steels 1.3815 and 1.4541 are examined. The analysis is conducted by means of multi-step joining tests for two material combinations comprising high-strength steel HCT70X and aluminium EN AW-5083. The joints are cut to provide a cross-section and the deformation behaviour of the different rivets is analysed on the basis of the measured changes in geometry and hardness. In parallel, an examination of the force-stroke curves provides further insights. It can be demonstrated that, besides the geometry, the material strength, in particular, has a significant influence on the deformation behaviour of the rivet. The strength of steel 1.4541 is seen to be too low for the joining task, while the strength of steel 1.3815 is sufficient, and hence the investigation confirms the capability of rivets made of 1.3815 for joining even challenging material combinations.","lang":"eng"}],"publisher":"Springer","_id":"22930","page":"1495-1506","editor":[{"first_name":"Glenn","last_name":"Daehn","full_name":"Daehn, Glenn"},{"full_name":"Cao, Jian","first_name":"Jian","last_name":"Cao"},{"last_name":"Kinsey","first_name":"Brad","full_name":"Kinsey, Brad"},{"full_name":"Tekkaya, Erman","last_name":"Tekkaya","first_name":"Erman"},{"first_name":"Anupam","last_name":"Vivek","full_name":"Vivek, Anupam"},{"last_name":"Yoshida","first_name":"Yoshinori","full_name":"Yoshida, Yoshinori"}],"user_id":"53912","status":"public","place":"Cham","citation":{"mla":"Uhe, Benedikt, et al. “Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening.” <i>Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals &#38; Materials Series.</i>, edited by Glenn Daehn et al., Springer, 2021, pp. 1495–506, doi:<a href=\"https://doi.org/10.1007/978-3-030-75381-8_124\">10.1007/978-3-030-75381-8_124</a>.","ama":"Uhe B, Kuball C-M, Merklein M, Meschut G. Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening. In: Daehn G, Cao J, Kinsey B, Tekkaya E, Vivek A, Yoshida Y, eds. <i>Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals &#38; Materials Series.</i> Springer; 2021:1495-1506. doi:<a href=\"https://doi.org/10.1007/978-3-030-75381-8_124\">10.1007/978-3-030-75381-8_124</a>","bibtex":"@inbook{Uhe_Kuball_Merklein_Meschut_2021, place={Cham}, title={Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening}, DOI={<a href=\"https://doi.org/10.1007/978-3-030-75381-8_124\">10.1007/978-3-030-75381-8_124</a>}, booktitle={Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals &#38; Materials Series.}, publisher={Springer}, author={Uhe, Benedikt and Kuball, Clara-Maria and Merklein, Marion and Meschut, Gerson}, editor={Daehn, Glenn and Cao, Jian and Kinsey, Brad and Tekkaya, Erman and Vivek, Anupam and Yoshida, Yoshinori}, year={2021}, pages={1495–1506} }","apa":"Uhe, B., Kuball, C.-M., Merklein, M., &#38; Meschut, G. (2021). Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening. In G. Daehn, J. Cao, B. Kinsey, E. Tekkaya, A. Vivek, &#38; Y. Yoshida (Eds.), <i>Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals &#38; Materials Series.</i> (pp. 1495–1506). Springer. <a href=\"https://doi.org/10.1007/978-3-030-75381-8_124\">https://doi.org/10.1007/978-3-030-75381-8_124</a>","ieee":"B. Uhe, C.-M. Kuball, M. Merklein, and G. Meschut, “Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening,” in <i>Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals &#38; Materials Series.</i>, G. Daehn, J. Cao, B. Kinsey, E. Tekkaya, A. Vivek, and Y. Yoshida, Eds. Cham: Springer, 2021, pp. 1495–1506.","chicago":"Uhe, Benedikt, Clara-Maria Kuball, Marion Merklein, and Gerson Meschut. “Self-Piercing Riveting Using Rivets Made of Stainless Steel with High Strain Hardening.” In <i>Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals &#38; Materials Series.</i>, edited by Glenn Daehn, Jian Cao, Brad Kinsey, Erman Tekkaya, Anupam Vivek, and Yoshinori Yoshida, 1495–1506. Cham: Springer, 2021. <a href=\"https://doi.org/10.1007/978-3-030-75381-8_124\">https://doi.org/10.1007/978-3-030-75381-8_124</a>.","short":"B. Uhe, C.-M. Kuball, M. Merklein, G. Meschut, in: G. Daehn, J. Cao, B. Kinsey, E. Tekkaya, A. Vivek, Y. Yoshida (Eds.), Forming the Future - Proceedings of the 13th International Conference on the Technology of Plasticity. The Minerals, Metals &#38; Materials Series., Springer, Cham, 2021, pp. 1495–1506."},"quality_controlled":"1"},{"citation":{"bibtex":"@inproceedings{Uhe_Kuball_Merklein_Meschut_2021, title={Strength of self-piercing riveted Joints with conventional Rivets and Rivets made of High Nitrogen Steel}, DOI={<a href=\"https://doi.org/10.25518/esaform21.1911\">10.25518/esaform21.1911</a>}, author={Uhe, Benedikt and Kuball, Clara-Maria and Merklein, Marion and Meschut, Gerson}, year={2021} }","short":"B. Uhe, C.-M. Kuball, M. Merklein, G. Meschut, in: 2021.","ama":"Uhe B, Kuball C-M, Merklein M, Meschut G. Strength of self-piercing riveted Joints with conventional Rivets and Rivets made of High Nitrogen Steel. In: ; 2021. doi:<a href=\"https://doi.org/10.25518/esaform21.1911\">10.25518/esaform21.1911</a>","chicago":"Uhe, Benedikt, Clara-Maria Kuball, Marion Merklein, and Gerson Meschut. “Strength of Self-Piercing Riveted Joints with Conventional Rivets and Rivets Made of High Nitrogen Steel,” 2021. <a href=\"https://doi.org/10.25518/esaform21.1911\">https://doi.org/10.25518/esaform21.1911</a>.","ieee":"B. Uhe, C.-M. Kuball, M. Merklein, and G. Meschut, “Strength of self-piercing riveted Joints with conventional Rivets and Rivets made of High Nitrogen Steel,” presented at the 24th International Conference on Material Forming (ESAFORM), Liège, Belgien, 2021, doi: <a href=\"https://doi.org/10.25518/esaform21.1911\">10.25518/esaform21.1911</a>.","apa":"Uhe, B., Kuball, C.-M., Merklein, M., &#38; Meschut, G. (2021). <i>Strength of self-piercing riveted Joints with conventional Rivets and Rivets made of High Nitrogen Steel</i>. 24th International Conference on Material Forming (ESAFORM), Liège, Belgien. <a href=\"https://doi.org/10.25518/esaform21.1911\">https://doi.org/10.25518/esaform21.1911</a>","mla":"Uhe, Benedikt, et al. <i>Strength of Self-Piercing Riveted Joints with Conventional Rivets and Rivets Made of High Nitrogen Steel</i>. 2021, doi:<a href=\"https://doi.org/10.25518/esaform21.1911\">10.25518/esaform21.1911</a>."},"abstract":[{"lang":"eng","text":"The use of high-strength steel and aluminium is rising due to the intensified efforts being made in lightweight design, and self-piercing riveting is becoming increasingly important. Conventional rivets for self-piercing riveting differ in their geometry, the material used, the condition of the material and the coating. To shorten the manufacturing process, the use of stainless steel with high strain hardening as the rivet material represents a promising approach. This allows the coating of the rivets to be omitted due to the corrosion resistance of the material and, since the strength of the stainless steel is achieved by cold forming, heat treatment is no longer required. In addition, it is possible to adjust the local strength within the rivet. Because of that, the authors have elaborated a concept for using high nitrogen steel 1.3815 as the rivet material. The present investigation focusses on the joint strength in order to evaluate the capability of rivets in high nitrogen steel by comparison to conventional rivets made of treatable steel. Due to certain challenges in the forming process of the high nitrogen steel rivets, deviations result from the targeted rivet geometry. Mainly these deviations cause a lower joint strength with these rivets, which is, however, adequate. All in all, the capability of the new rivet is proven by the results of this investigation. "}],"quality_controlled":"1","date_created":"2021-05-31T10:17:37Z","department":[{"_id":"157"}],"type":"conference","keyword":["Self-piercing Riveting","Joining Technology","Rivet Geometry","Rivet Material","High Nitrogen Steel","Joint Strength"],"conference":{"end_date":"2021-04-16","location":"Liège, Belgien","name":"24th International Conference on Material Forming (ESAFORM)","start_date":"2021-04-14"},"author":[{"full_name":"Uhe, Benedikt","last_name":"Uhe","first_name":"Benedikt","id":"38131"},{"last_name":"Kuball","first_name":"Clara-Maria","full_name":"Kuball, Clara-Maria"},{"full_name":"Merklein, Marion","last_name":"Merklein","first_name":"Marion"},{"id":"32056","full_name":"Meschut, Gerson","orcid":"0000-0002-2763-1246","first_name":"Gerson","last_name":"Meschut"}],"title":"Strength of self-piercing riveted Joints with conventional Rivets and Rivets made of High Nitrogen Steel","year":"2021","status":"public","date_updated":"2026-02-27T10:25:13Z","language":[{"iso":"eng"}],"_id":"22274","doi":"10.25518/esaform21.1911","user_id":"53912"}]
