[{"citation":{"mla":"Lugovtsova, Yevgeniya, et al. “К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН.” <i>МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская Школа-Конференция</i>, 2021.","ama":"Lugovtsova Y, Zeipert H, Johannesmann S, Nicolai M, Prager J, Henning B. К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН. In: <i>МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская Школа-Конференция</i>. ; 2021.","bibtex":"@inproceedings{Lugovtsova_Zeipert_Johannesmann_Nicolai_Prager_Henning_2021, place={Perm}, title={К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН}, booktitle={МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция}, author={Lugovtsova, Yevgeniya and Zeipert, Henning and Johannesmann, Sarah and Nicolai, Marcel and Prager, Jens and Henning, Bernd}, year={2021} }","apa":"Lugovtsova, Y., Zeipert, H., Johannesmann, S., Nicolai, M., Prager, J., &#38; Henning, B. (2021). К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН. <i>МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская Школа-Конференция</i>. МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция, Perm.","ieee":"Y. Lugovtsova, H. Zeipert, S. Johannesmann, M. Nicolai, J. Prager, and B. Henning, “К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН,” presented at the МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция, Perm, 2021.","chicago":"Lugovtsova, Yevgeniya, Henning Zeipert, Sarah Johannesmann, Marcel Nicolai, Jens Prager, and Bernd Henning. “К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН.” In <i>МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская Школа-Конференция</i>. Perm, 2021.","short":"Y. Lugovtsova, H. Zeipert, S. Johannesmann, M. Nicolai, J. Prager, B. Henning, in: МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская Школа-Конференция, Perm, 2021."},"file_date_updated":"2021-11-26T07:53:21Z","project":[{"name":"Vermiedene Kreuzungen von Lamb-Wellenmoden in mehrlagigen Strukturen","_id":"105","grant_number":"449607253"}],"place":"Perm","oa":"1","conference":{"start_date":"2021-10-06","name":"МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция","location":"Perm","end_date":"2021-10-09"},"status":"public","has_accepted_license":"1","_id":"27847","user_id":"11829","ddc":["620"],"publication":"МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция","date_created":"2021-11-25T14:58:13Z","file":[{"file_id":"27848","content_type":"application/pdf","relation":"main_file","date_updated":"2021-11-26T07:53:21Z","file_name":"Paper - Mode Repulsion - 2021 MMEN (Perm).pdf","file_size":450749,"access_level":"open_access","date_created":"2021-11-25T14:57:25Z","creator":"leanderc"}],"department":[{"_id":"49"}],"type":"conference","author":[{"full_name":"Lugovtsova, Yevgeniya","first_name":"Yevgeniya","last_name":"Lugovtsova"},{"id":"32580","last_name":"Zeipert","first_name":"Henning","full_name":"Zeipert, Henning"},{"id":"29190","full_name":"Johannesmann, Sarah","first_name":"Sarah","last_name":"Johannesmann"},{"full_name":"Nicolai, Marcel","last_name":"Nicolai","first_name":"Marcel"},{"full_name":"Prager, Jens","last_name":"Prager","first_name":"Jens"},{"last_name":"Henning","first_name":"Bernd","full_name":"Henning, Bernd","id":"213"}],"year":"2021","title":"К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН","date_updated":"2022-01-06T06:57:47Z","language":[{"iso":"eng"}],"alternative_title":["Über die Bestimmung der Festigkeit der Klebeschicht in mehrschichtigen Materialien durch Untersuchung des modalen Abstands von geführten elastischen Wellen"]},{"_id":"21004","language":[{"iso":"eng"}],"page":"1-1","user_id":"5786","doi":"10.1109/tpami.2021.3051276","author":[{"full_name":"Wever, Marcel Dominik","orcid":" https://orcid.org/0000-0001-9782-6818","last_name":"Wever","first_name":"Marcel Dominik","id":"33176"},{"id":"38209","last_name":"Tornede","first_name":"Alexander","full_name":"Tornede, Alexander"},{"full_name":"Mohr, Felix","first_name":"Felix","last_name":"Mohr"},{"id":"48129","last_name":"Hüllermeier","first_name":"Eyke","full_name":"Hüllermeier, Eyke"}],"publication_identifier":{"issn":["0162-8828","2160-9292","1939-3539"]},"title":"AutoML for Multi-Label Classification: Overview and Empirical Evaluation","year":"2021","status":"public","publication_status":"published","date_updated":"2022-01-06T06:54:42Z","date_created":"2021-01-16T14:48:13Z","department":[{"_id":"34"},{"_id":"355"},{"_id":"26"}],"keyword":["Automated Machine Learning","Multi Label Classification","Hierarchical Planning","Bayesian Optimization"],"type":"journal_article","citation":{"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} }","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>.","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>.","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>."},"publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Project Area B","_id":"3"},{"_id":"10","name":"SFB 901 - Subproject B2"},{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"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."}]},{"conference":{"start_date":"2021-05-10","name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","location":"Vancouver BC Canada","end_date":"2021-05-13"},"status":"public","user_id":"63288","ddc":["000"],"publisher":"IEEE Communications Society","_id":"21005","project":[{"name":"SFB 901 - Subproject C4","_id":"16"},{"_id":"4","name":"SFB 901 - Project Area C"},{"_id":"1","name":"SFB 901"}],"citation":{"ama":"Hasnain A, Karl H. Learning Coflow Admissions. In: <i>IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)</i>. IEEE Communications Society. doi:<a href=\"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599\">10.1109/INFOCOMWKSHPS51825.2021.9484599</a>","bibtex":"@inproceedings{Hasnain_Karl, title={Learning Coflow Admissions}, DOI={<a href=\"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599\">10.1109/INFOCOMWKSHPS51825.2021.9484599</a>}, booktitle={IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)}, publisher={IEEE Communications Society}, author={Hasnain, Asif and Karl, Holger} }","mla":"Hasnain, Asif, and Holger Karl. “Learning Coflow Admissions.” <i>IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)</i>, IEEE Communications Society, doi:<a href=\"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599\">10.1109/INFOCOMWKSHPS51825.2021.9484599</a>.","chicago":"Hasnain, Asif, and Holger Karl. “Learning Coflow Admissions.” In <i>IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)</i>. IEEE Communications Society, n.d. <a href=\"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599\">https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599</a>.","short":"A. Hasnain, H. Karl, in: IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE Communications Society, n.d.","apa":"Hasnain, A., &#38; Karl, H. (n.d.). Learning Coflow Admissions. In <i>IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)</i>. Vancouver BC Canada: IEEE Communications Society. <a href=\"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599\">https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599</a>","ieee":"A. Hasnain and H. Karl, “Learning Coflow Admissions,” in <i>IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)</i>, Vancouver BC Canada."},"publication_status":"accepted","date_updated":"2022-01-06T06:54:42Z","author":[{"full_name":"Hasnain, Asif","first_name":"Asif","last_name":"Hasnain","id":"63288"},{"full_name":"Karl, Holger","first_name":"Holger","last_name":"Karl","id":"126"}],"year":"2021","title":"Learning Coflow Admissions","doi":"10.1109/INFOCOMWKSHPS51825.2021.9484599","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://ieeexplore.ieee.org/document/9484599"}],"related_material":{"link":[{"relation":"confirmation","url":"https://ieeexplore.ieee.org/document/9484599"}]},"abstract":[{"lang":"eng","text":"Data-parallel applications are developed using different data programming models, e.g., MapReduce, partition/aggregate. These models represent diverse resource requirements of application in a datacenter network, which can be represented by the coflow abstraction. The conventional method of creating hand-crafted coflow heuristics for admission or scheduling for different workloads is practically infeasible. In this paper, we propose a deep reinforcement learning (DRL)-based coflow admission scheme -- LCS -- that can learn an admission policy for a higher-level performance objective, i.e., maximize successful coflow admissions, without manual feature engineering.  LCS is trained on a production trace, which has online coflow arrivals. The evaluation results show that LCS is able to learn a reasonable admission policy that admits more coflows than state-of-the-art Varys heuristic while meeting their deadlines."}],"publication":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","department":[{"_id":"75"}],"keyword":["Coflow scheduling","Reinforcement learning","Deadlines"],"type":"conference","date_created":"2021-01-16T18:24:19Z"},{"file":[{"date_created":"2021-01-25T08:17:23Z","creator":"huesera","content_type":"application/pdf","file_id":"21066","file_size":4173988,"access_level":"open_access","file_name":"proceedings_2021_haebumbach_Paper.pdf","date_updated":"2021-01-25T08:17:23Z","relation":"main_file"}],"date_created":"2021-01-25T08:15:27Z","type":"journal_article","department":[{"_id":"54"}],"issue":"2","publication":"Proceedings of the IEEE","abstract":[{"text":"The machine recognition of speech spoken at a distance from the microphones, known as far-field automatic speech recognition (ASR), has received a significant increase of attention in science and industry, which caused or was caused by an equally significant improvement in recognition accuracy. Meanwhile it has entered the consumer market with digital home assistants with a spoken language interface being its most prominent application. Speech recorded at a distance is affected by various acoustic distortions and, consequently, quite different processing pipelines have emerged compared to ASR for close-talk speech. A signal enhancement front-end for dereverberation, source separation and acoustic beamforming is employed to clean up the speech, and the back-end ASR engine is robustified by multi-condition training and adaptation. We will also describe the so-called end-to-end approach to ASR, which is a new promising architecture that has recently been extended to the far-field scenario. This tutorial article gives an account of the algorithms used to enable accurate speech recognition from a distance, and it will be seen that, although deep learning has a significant share in the technological breakthroughs, a clever combination with traditional signal processing can lead to surprisingly effective solutions.","lang":"eng"}],"language":[{"iso":"eng"}],"doi":"10.1109/JPROC.2020.3018668","title":"Far-Field Automatic Speech Recognition","year":"2021","author":[{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"},{"first_name":"Jahn","last_name":"Heymann","full_name":"Heymann, Jahn"},{"first_name":"Lukas","last_name":"Drude","full_name":"Drude, Lukas"},{"first_name":"Shinji","last_name":"Watanabe","full_name":"Watanabe, Shinji"},{"full_name":"Delcroix, Marc","last_name":"Delcroix","first_name":"Marc"},{"last_name":"Nakatani","first_name":"Tomohiro","full_name":"Nakatani, Tomohiro"}],"date_updated":"2022-01-06T06:54:44Z","intvolume":"       109","oa":"1","file_date_updated":"2021-01-25T08:17:23Z","citation":{"apa":"Haeb-Umbach, R., Heymann, J., Drude, L., Watanabe, S., Delcroix, M., &#38; Nakatani, T. (2021). Far-Field Automatic Speech Recognition. <i>Proceedings of the IEEE</i>, <i>109</i>(2), 124–148. <a href=\"https://doi.org/10.1109/JPROC.2020.3018668\">https://doi.org/10.1109/JPROC.2020.3018668</a>","ieee":"R. Haeb-Umbach, J. Heymann, L. Drude, S. Watanabe, M. Delcroix, and T. Nakatani, “Far-Field Automatic Speech Recognition,” <i>Proceedings of the IEEE</i>, vol. 109, no. 2, pp. 124–148, 2021.","chicago":"Haeb-Umbach, Reinhold, Jahn Heymann, Lukas Drude, Shinji Watanabe, Marc Delcroix, and Tomohiro Nakatani. “Far-Field Automatic Speech Recognition.” <i>Proceedings of the IEEE</i> 109, no. 2 (2021): 124–48. <a href=\"https://doi.org/10.1109/JPROC.2020.3018668\">https://doi.org/10.1109/JPROC.2020.3018668</a>.","short":"R. Haeb-Umbach, J. Heymann, L. Drude, S. Watanabe, M. Delcroix, T. Nakatani, Proceedings of the IEEE 109 (2021) 124–148.","mla":"Haeb-Umbach, Reinhold, et al. “Far-Field Automatic Speech Recognition.” <i>Proceedings of the IEEE</i>, vol. 109, no. 2, 2021, pp. 124–48, doi:<a href=\"https://doi.org/10.1109/JPROC.2020.3018668\">10.1109/JPROC.2020.3018668</a>.","ama":"Haeb-Umbach R, Heymann J, Drude L, Watanabe S, Delcroix M, Nakatani T. Far-Field Automatic Speech Recognition. <i>Proceedings of the IEEE</i>. 2021;109(2):124-148. doi:<a href=\"https://doi.org/10.1109/JPROC.2020.3018668\">10.1109/JPROC.2020.3018668</a>","bibtex":"@article{Haeb-Umbach_Heymann_Drude_Watanabe_Delcroix_Nakatani_2021, title={Far-Field Automatic Speech Recognition}, volume={109}, DOI={<a href=\"https://doi.org/10.1109/JPROC.2020.3018668\">10.1109/JPROC.2020.3018668</a>}, number={2}, journal={Proceedings of the IEEE}, author={Haeb-Umbach, Reinhold and Heymann, Jahn and Drude, Lukas and Watanabe, Shinji and Delcroix, Marc and Nakatani, Tomohiro}, year={2021}, pages={124–148} }"},"project":[{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"page":"124-148","_id":"21065","ddc":["000"],"user_id":"59789","volume":109,"status":"public","has_accepted_license":"1"},{"user_id":"11829","volume":88,"page":"147-155","_id":"21067","status":"public","project":[{"_id":"105","grant_number":"449607253","name":"Vermiedene Kreuzungen von Lamb-Wellenmoden in mehrlagigen Strukturen"}],"citation":{"mla":"Claes, Leander, et al. “Investigating Peculiarities of Piezoelectric Detection Methods for Acoustic Plate Waves in Material Characterisation Applications.” <i>Tm - Technisches Messen</i>, vol. 88, no. 3, 2021, pp. 147–55, doi:<a href=\"https://doi.org/10.1515/teme-2020-0098\">10.1515/teme-2020-0098</a>.","bibtex":"@article{Claes_Schmiegel_Grünsteidl_Johannesmann_Webersen_Henning_2021, title={Investigating peculiarities of piezoelectric detection methods for acoustic plate waves in material characterisation applications}, volume={88}, DOI={<a href=\"https://doi.org/10.1515/teme-2020-0098\">10.1515/teme-2020-0098</a>}, number={3}, journal={tm - Technisches Messen}, author={Claes, Leander and Schmiegel, Hanna and Grünsteidl, Clemens and Johannesmann, Sarah and Webersen, Manuel and Henning, Bernd}, year={2021}, pages={147–155} }","ama":"Claes L, Schmiegel H, Grünsteidl C, Johannesmann S, Webersen M, Henning B. Investigating peculiarities of piezoelectric detection methods for acoustic plate waves in material characterisation applications. <i>tm - Technisches Messen</i>. 2021;88(3):147-155. doi:<a href=\"https://doi.org/10.1515/teme-2020-0098\">10.1515/teme-2020-0098</a>","ieee":"L. Claes, H. Schmiegel, C. Grünsteidl, S. Johannesmann, M. Webersen, and B. Henning, “Investigating peculiarities of piezoelectric detection methods for acoustic plate waves in material characterisation applications,” <i>tm - Technisches Messen</i>, vol. 88, no. 3, pp. 147–155, 2021.","apa":"Claes, L., Schmiegel, H., Grünsteidl, C., Johannesmann, S., Webersen, M., &#38; Henning, B. (2021). Investigating peculiarities of piezoelectric detection methods for acoustic plate waves in material characterisation applications. <i>Tm - Technisches Messen</i>, <i>88</i>(3), 147–155. <a href=\"https://doi.org/10.1515/teme-2020-0098\">https://doi.org/10.1515/teme-2020-0098</a>","chicago":"Claes, Leander, Hanna Schmiegel, Clemens Grünsteidl, Sarah Johannesmann, Manuel Webersen, and Bernd Henning. “Investigating Peculiarities of Piezoelectric Detection Methods for Acoustic Plate Waves in Material Characterisation Applications.” <i>Tm - Technisches Messen</i> 88, no. 3 (2021): 147–55. <a href=\"https://doi.org/10.1515/teme-2020-0098\">https://doi.org/10.1515/teme-2020-0098</a>.","short":"L. Claes, H. Schmiegel, C. Grünsteidl, S. Johannesmann, M. Webersen, B. Henning, Tm - Technisches Messen 88 (2021) 147–155."},"doi":"10.1515/teme-2020-0098","alternative_title":["Untersuchung von Eigenheiten piezoelektrischer Detektionsmethoden für akustische Plattenwellen zur Materialcharakterisierung"],"language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:54:44Z","publication_status":"published","intvolume":"        88","title":"Investigating peculiarities of piezoelectric detection methods for acoustic plate waves in material characterisation applications","year":"2021","publication_identifier":{"issn":["2196-7113","0171-8096"]},"author":[{"full_name":"Claes, Leander","orcid":"0000-0002-4393-268X","last_name":"Claes","first_name":"Leander","id":"11829"},{"full_name":"Schmiegel, Hanna","last_name":"Schmiegel","first_name":"Hanna"},{"full_name":"Grünsteidl, Clemens","first_name":"Clemens","last_name":"Grünsteidl"},{"last_name":"Johannesmann","first_name":"Sarah","full_name":"Johannesmann, Sarah","id":"29190"},{"id":"11289","full_name":"Webersen, Manuel","last_name":"Webersen","first_name":"Manuel","orcid":"0000-0001-6411-4232"},{"last_name":"Henning","first_name":"Bernd","full_name":"Henning, Bernd","id":"213"}],"type":"journal_article","department":[{"_id":"49"}],"date_created":"2021-01-25T09:38:58Z","abstract":[{"text":"Acoustic waves in plates have proven a viable tool for testing and material characterisation purposes. There are a multitude of options for excitation and detection of theses waves, such as optical and piezoelectric systems. While optical systems, with thermoelastic excitation and interferometric detection, have the benefit of being contactless, they usually require rather complex and expensive experimental setups. Piezoelectric systems are more easily realised but require direct contact with the specimen and usually have a limited bandwidth, especially in case of piezoelectric excitation. In this work, the authors compare the properties of piezoelectric and optical detection methods for broad-band acoustic signals. The shape (e. g. the displacement) of a propagating plate wave is given by its frequency and wave number, allowing to investigate correlations between mode shapes and received signal strengths. This is aided by evaluations in normalised frequency and wavenumber space, facilitating comparisons of different specimens. Further, the authors explore possibilities to utilise the specific properties of the detection methods to determine acoustic material parameters.","lang":"eng"}],"publication":"tm - Technisches Messen","issue":"3"},{"citation":{"ama":"Itner D, Gravenkamp H, Dreiling D, Feldmann N, Henning B. Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization. <i>PAMM</i>. 2021. doi:<a href=\"https://doi.org/10.1002/pamm.202000232\">10.1002/pamm.202000232</a>","bibtex":"@article{Itner_Gravenkamp_Dreiling_Feldmann_Henning_2021, title={Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization}, DOI={<a href=\"https://doi.org/10.1002/pamm.202000232\">10.1002/pamm.202000232</a>}, journal={PAMM}, author={Itner, Dominik and Gravenkamp, Hauke and Dreiling, Dmitrij and Feldmann, Nadine and Henning, Bernd}, year={2021} }","mla":"Itner, Dominik, et al. “Simulation of Guided Waves in Cylinders Subject to Arbitrary Boundary Conditions for Applications in Material Characterization.” <i>PAMM</i>, 2021, doi:<a href=\"https://doi.org/10.1002/pamm.202000232\">10.1002/pamm.202000232</a>.","chicago":"Itner, Dominik, Hauke Gravenkamp, Dmitrij Dreiling, Nadine Feldmann, and Bernd Henning. “Simulation of Guided Waves in Cylinders Subject to Arbitrary Boundary Conditions for Applications in Material Characterization.” <i>PAMM</i>, 2021. <a href=\"https://doi.org/10.1002/pamm.202000232\">https://doi.org/10.1002/pamm.202000232</a>.","short":"D. Itner, H. Gravenkamp, D. Dreiling, N. Feldmann, B. Henning, PAMM (2021).","apa":"Itner, D., Gravenkamp, H., Dreiling, D., Feldmann, N., &#38; Henning, B. (2021). Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization. <i>PAMM</i>. <a href=\"https://doi.org/10.1002/pamm.202000232\">https://doi.org/10.1002/pamm.202000232</a>","ieee":"D. Itner, H. Gravenkamp, D. Dreiling, N. Feldmann, and B. Henning, “Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization,” <i>PAMM</i>, 2021."},"publication":"PAMM","project":[{"name":"Vollständige Bestimmung der akustischen Materialparameter von Polymeren","grant_number":"409779252","_id":"89"}],"date_created":"2021-01-26T13:52:47Z","department":[{"_id":"49"}],"type":"journal_article","publication_identifier":{"issn":["1617-7061","1617-7061"]},"author":[{"last_name":"Itner","first_name":"Dominik","full_name":"Itner, Dominik"},{"full_name":"Gravenkamp, Hauke","last_name":"Gravenkamp","first_name":"Hauke"},{"last_name":"Dreiling","first_name":"Dmitrij","full_name":"Dreiling, Dmitrij","id":"32616"},{"last_name":"Feldmann","first_name":"Nadine","full_name":"Feldmann, Nadine","id":"23082"},{"first_name":"Bernd","last_name":"Henning","full_name":"Henning, Bernd","id":"213"}],"status":"public","title":"Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization","year":"2021","publication_status":"published","date_updated":"2022-01-06T06:54:44Z","language":[{"iso":"eng"}],"_id":"21082","user_id":"23082","doi":"10.1002/pamm.202000232"},{"type":"mastersthesis","department":[{"_id":"79"}],"date_created":"2021-01-26T13:58:14Z","project":[{"_id":"1","name":"SFB 901"},{"_id":"2","name":"SFB 901 - Project Area A"},{"_id":"5","name":"SFB 901 - Subproject A1"}],"supervisor":[{"id":"20792","full_name":"Scheideler, Christian","first_name":"Christian","last_name":"Scheideler"}],"citation":{"chicago":"Werthmann, Julian. <i>Derandomization and Local Graph Problems in the Node-Capacitated Clique</i>, 2021.","short":"J. Werthmann, Derandomization and Local Graph Problems in the Node-Capacitated Clique, 2021.","apa":"Werthmann, J. (2021). <i>Derandomization and Local Graph Problems in the Node-Capacitated Clique</i>.","ieee":"J. Werthmann, <i>Derandomization and Local Graph Problems in the Node-Capacitated Clique</i>. 2021.","ama":"Werthmann J. <i>Derandomization and Local Graph Problems in the Node-Capacitated Clique</i>.; 2021.","bibtex":"@book{Werthmann_2021, title={Derandomization and Local Graph Problems in the Node-Capacitated Clique}, author={Werthmann, Julian}, year={2021} }","mla":"Werthmann, Julian. <i>Derandomization and Local Graph Problems in the Node-Capacitated Clique</i>. 2021."},"user_id":"15504","_id":"21084","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:54:44Z","title":"Derandomization and Local Graph Problems in the Node-Capacitated Clique","year":"2021","status":"public","author":[{"last_name":"Werthmann","first_name":"Julian","full_name":"Werthmann, Julian","id":"50024"}]},{"user_id":"5786","_id":"21092","language":[{"iso":"eng"}],"publisher":"IEEE","date_updated":"2022-01-06T06:54:45Z","publication_status":"accepted","title":"Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning","year":"2021","status":"public","author":[{"first_name":"Felix","last_name":"Mohr","full_name":"Mohr, Felix"},{"orcid":" https://orcid.org/0000-0001-9782-6818","last_name":"Wever","first_name":"Marcel Dominik","full_name":"Wever, Marcel Dominik","id":"33176"},{"id":"38209","last_name":"Tornede","first_name":"Alexander","full_name":"Tornede, Alexander"},{"id":"48129","last_name":"Hüllermeier","first_name":"Eyke","full_name":"Hüllermeier, Eyke"}],"type":"journal_article","department":[{"_id":"34"},{"_id":"355"},{"_id":"26"}],"date_created":"2021-01-27T13:45:52Z","abstract":[{"text":"Automated Machine Learning (AutoML) seeks to automatically find so-called machine learning pipelines that maximize the prediction performance when being used to train a model on a given dataset. One of the main and yet open challenges in AutoML is an effective use of computational resources: An AutoML process involves the evaluation of many candidate pipelines, which   are costly but often ineffective because they are canceled due to a timeout.\r\nIn this paper, we present an approach to predict the runtime of two-step machine learning pipelines with up to one pre-processor, which can be used to anticipate whether or not a pipeline will time out. Separate runtime models are trained offline for each algorithm that may be used in a pipeline, and an overall prediction is derived from these models. We empirically show that the approach increases successful evaluations made by an AutoML tool while preserving or even improving on the previously best solutions.","lang":"eng"}],"project":[{"_id":"1","name":"SFB 901"},{"_id":"3","name":"SFB 901 - Project Area B"},{"name":"SFB 901 - Subproject B2","_id":"10"},{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","citation":{"apa":"Mohr, F., Wever, M. D., Tornede, A., &#38; Hüllermeier, E. (n.d.). Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>.","ieee":"F. Mohr, M. D. Wever, A. Tornede, and E. Hüllermeier, “Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>.","chicago":"Mohr, Felix, Marcel Dominik Wever, Alexander Tornede, and Eyke Hüllermeier. “Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, n.d.","short":"F. Mohr, M.D. Wever, A. Tornede, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (n.d.).","mla":"Mohr, Felix, et al. “Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, IEEE.","ama":"Mohr F, Wever MD, Tornede A, Hüllermeier E. Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>.","bibtex":"@article{Mohr_Wever_Tornede_Hüllermeier, title={Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, publisher={IEEE}, author={Mohr, Felix and Wever, Marcel Dominik and Tornede, Alexander and Hüllermeier, Eyke} }"}},{"publication_status":"published","date_updated":"2022-01-06T06:54:49Z","author":[{"full_name":"Webersen, Manuel","first_name":"Manuel","orcid":"0000-0001-6411-4232","last_name":"Webersen","id":"11289"}],"title":"Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall","year":"2021","status":"public","user_id":"11289","doi":"10.17619/UNIPB/1-1088","_id":"21183","language":[{"iso":"ger"}],"publisher":"Universitätsbibliothek Paderborn","abstract":[{"lang":"ger","text":"Die präzise Kenntnis der Eigenschaften verwendeter Materialien hat große Bedeutung für den Entwurf technischer Systeme aller Art, aber auch für die Überwachung solcher Systeme im Betrieb. Für verschiedene physikalische Eigenschaften, Betriebsbedingungen und Materialklassen werden daher geeignete messtechnische Verfahren zur Materialcharakterisierung benötigt. In der vorliegenden Arbeit wird ein Verfahren zur ultraschallbasierten Charakterisierung der mechanischen Eigenschaften von homogenen und faserverstärkten thermoplastischen Polymeren unter Berücksichtigung der Richtungsabhängigkeit vorgestellt. Plattenförmige Probekörper werden dazu mittels Laser-Pulsen hoher Energie breitbandig angeregt und die resultierenden akustischen Lamb-Wellen aufgezeichnet. Auf Basis der dispersiven Eigenschaften der detektierten Wellenleitermoden werden in einem inversen Verfahren die Parameter eines linear-elastischen Materialmodells identifiziert. Darüber hinaus wird ein Verfahren zur vollständigen Charakterisierung der Richtungsabhängigkeit in orthotropen Materialien wie Faserverbundwerkstoffen unter Verwendung eines zweidimensionalen Simulationsmodells vorgestellt. Das Messverfahren wird anhand einer Untersuchungsreihe an künstlich gealterten Polymer- und Faserverbundwerkstoffen verifiziert und die Übertragbarkeit der Ergebnisse auf den quasistatischen Fall betrachtet. Im Vergleich mit den Ergebnissen mechanischer Zugversuche werden die Voraussetzungen und Einschränkungen, insbesondere durch die Annahme eines ideal-elastischen Materialmodells, diskutiert."},{"lang":"eng","text":"Precise knowledge of material properties is a great concern in the design of technical systems, and in the monitoring of such systems during operation. Therefore, metrological processes are required for materials characterisation with respect to specific physical properties, operational conditions and classes of materials. In the work presented herein, a measurement procedure for the ultrasonic characterization of mechanical properties of homogeneous and fiber-reinforced thermoplastic polymer materials is presented, considering the different degrees of anisotropy. For this, acoustic Lamb waves are excited in a plate-shaped specimen using high-energy laser pulses, and then recorded.Based on the dispersive characteristics of the detected waveguide modes, an inverse procedure is applied to identify the parameters of a linear-elastic material model. Further, a procedure for completely characterising the orthotropy of materials like fiber-reinforced composites using a two-dimensional simulation model is presented. The measurement procedure is verified by examining artificially aged homogeneous polymers and composites, also considering the applicability of results to the quasistatic case. Comparing to the results of corresponding mechanical tensile tests, preconditions and limitations of the procedure are discussed, specifically regarding the assumption of an ideal-elastic material model."}],"citation":{"bibtex":"@book{Webersen_2021, title={Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall}, DOI={<a href=\"https://doi.org/10.17619/UNIPB/1-1088\">10.17619/UNIPB/1-1088</a>}, publisher={Universitätsbibliothek Paderborn}, author={Webersen, Manuel}, year={2021} }","ama":"Webersen M. <i>Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall</i>. Universitätsbibliothek Paderborn; 2021. doi:<a href=\"https://doi.org/10.17619/UNIPB/1-1088\">10.17619/UNIPB/1-1088</a>","mla":"Webersen, Manuel. <i>Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall</i>. Universitätsbibliothek Paderborn, 2021, doi:<a href=\"https://doi.org/10.17619/UNIPB/1-1088\">10.17619/UNIPB/1-1088</a>.","short":"M. Webersen, Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall, Universitätsbibliothek Paderborn, 2021.","chicago":"Webersen, Manuel. <i>Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall</i>. Universitätsbibliothek Paderborn, 2021. <a href=\"https://doi.org/10.17619/UNIPB/1-1088\">https://doi.org/10.17619/UNIPB/1-1088</a>.","ieee":"M. Webersen, <i>Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall</i>. Universitätsbibliothek Paderborn, 2021.","apa":"Webersen, M. (2021). <i>Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall</i>. Universitätsbibliothek Paderborn. <a href=\"https://doi.org/10.17619/UNIPB/1-1088\">https://doi.org/10.17619/UNIPB/1-1088</a>"},"department":[{"_id":"49"}],"type":"dissertation","date_created":"2021-02-05T11:47:28Z"},{"main_file_link":[{"url":"https://link.springer.com/content/pdf/10.1007/s11571-020-09656-9.pdf"}],"language":[{"iso":"eng"}],"_id":"21195","user_id":"32643","doi":"10.1007/s11571-020-09656-9","status":"public","year":"2021","title":"Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults","author":[{"last_name":"Goelz","first_name":"Christian","full_name":"Goelz, Christian"},{"first_name":"Karin","last_name":"Mora","full_name":"Mora, Karin"},{"last_name":"Stroehlein","first_name":"Julia Kristin","full_name":"Stroehlein, Julia Kristin"},{"full_name":"Haase, Franziska Katharina","first_name":"Franziska Katharina","last_name":"Haase"},{"last_name":"Dellnitz","first_name":"Michael","full_name":"Dellnitz, Michael"},{"first_name":"Claus","last_name":"Reinsberger","full_name":"Reinsberger, Claus"},{"last_name":"Vieluf","first_name":"Solveig","full_name":"Vieluf, Solveig"}],"date_updated":"2022-01-06T06:54:49Z","date_created":"2021-02-08T13:16:07Z","type":"journal_article","department":[{"_id":"101"}],"publication":"Cognitive Neurodynamics","citation":{"apa":"Goelz, C., Mora, K., Stroehlein, J. K., Haase, F. K., Dellnitz, M., Reinsberger, C., &#38; Vieluf, S. (2021). Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults. <i>Cognitive Neurodynamics</i>. <a href=\"https://doi.org/10.1007/s11571-020-09656-9\">https://doi.org/10.1007/s11571-020-09656-9</a>","ieee":"C. Goelz <i>et al.</i>, “Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults,” <i>Cognitive Neurodynamics</i>, 2021.","short":"C. Goelz, K. Mora, J.K. Stroehlein, F.K. Haase, M. Dellnitz, C. Reinsberger, S. Vieluf, Cognitive Neurodynamics (2021).","chicago":"Goelz, Christian, Karin Mora, Julia Kristin Stroehlein, Franziska Katharina Haase, Michael Dellnitz, Claus Reinsberger, and Solveig Vieluf. “Electrophysiological Signatures of Dedifferentiation Differ between Fit and Less Fit Older Adults.” <i>Cognitive Neurodynamics</i>, 2021. <a href=\"https://doi.org/10.1007/s11571-020-09656-9\">https://doi.org/10.1007/s11571-020-09656-9</a>.","mla":"Goelz, Christian, et al. “Electrophysiological Signatures of Dedifferentiation Differ between Fit and Less Fit Older Adults.” <i>Cognitive Neurodynamics</i>, 2021, doi:<a href=\"https://doi.org/10.1007/s11571-020-09656-9\">10.1007/s11571-020-09656-9</a>.","ama":"Goelz C, Mora K, Stroehlein JK, et al. Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults. <i>Cognitive Neurodynamics</i>. 2021. doi:<a href=\"https://doi.org/10.1007/s11571-020-09656-9\">10.1007/s11571-020-09656-9</a>","bibtex":"@article{Goelz_Mora_Stroehlein_Haase_Dellnitz_Reinsberger_Vieluf_2021, title={Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults}, DOI={<a href=\"https://doi.org/10.1007/s11571-020-09656-9\">10.1007/s11571-020-09656-9</a>}, journal={Cognitive Neurodynamics}, author={Goelz, Christian and Mora, Karin and Stroehlein, Julia Kristin and Haase, Franziska Katharina and Dellnitz, Michael and Reinsberger, Claus and Vieluf, Solveig}, year={2021} }"}},{"project":[{"_id":"1","name":"SFB 901"},{"_id":"2","name":"SFB 901 - Project Area A"},{"name":"SFB 901 - Project Area C","_id":"4"},{"name":"SFB 901 - Subproject A1","_id":"5"},{"name":"SFB 901 - Subproject C1","_id":"13"}],"supervisor":[{"id":"20792","full_name":"Scheideler, Christian","last_name":"Scheideler","first_name":"Christian"}],"citation":{"apa":"Mengshi, M. (2021). <i>Self-stabilizing Arrow Protocol on Spanning Trees with a Low Diameter</i>.","ieee":"M. Mengshi, <i>Self-stabilizing Arrow Protocol on Spanning Trees with a Low Diameter</i>. 2021.","short":"M. Mengshi, Self-Stabilizing Arrow Protocol on Spanning Trees with a Low Diameter, 2021.","chicago":"Mengshi, Ma. <i>Self-Stabilizing Arrow Protocol on Spanning Trees with a Low Diameter</i>, 2021.","mla":"Mengshi, Ma. <i>Self-Stabilizing Arrow Protocol on Spanning Trees with a Low Diameter</i>. 2021.","ama":"Mengshi M. <i>Self-Stabilizing Arrow Protocol on Spanning Trees with a Low Diameter</i>.; 2021.","bibtex":"@book{Mengshi_2021, title={Self-stabilizing Arrow Protocol on Spanning Trees with a Low Diameter}, author={Mengshi, Ma}, year={2021} }"},"department":[{"_id":"79"}],"type":"bachelorsthesis","date_created":"2021-02-09T07:09:22Z","date_updated":"2022-01-06T06:54:49Z","author":[{"first_name":"Ma","last_name":"Mengshi","full_name":"Mengshi, Ma"}],"status":"public","title":"Self-stabilizing Arrow Protocol on Spanning Trees with a Low Diameter","year":"2021","user_id":"15504","language":[{"iso":"eng"}],"_id":"21197"},{"intvolume":"        26","publication_status":"published","date_updated":"2022-01-06T06:54:55Z","author":[{"id":"51701","last_name":"Berkemeier","first_name":"Manuel Bastian","full_name":"Berkemeier, Manuel Bastian"},{"id":"47427","full_name":"Peitz, Sebastian","last_name":"Peitz","orcid":"0000-0002-3389-793X","first_name":"Sebastian"}],"publication_identifier":{"eissn":["2297-8747"]},"title":"Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models","year":"2021","doi":"10.3390/mca26020031","language":[{"iso":"eng"}],"article_number":"31","main_file_link":[{"open_access":"1","url":"https://www.mdpi.com/2297-8747/26/2/31/pdf"}],"abstract":[{"text":"We present a flexible trust region descend algorithm for unconstrained and\r\nconvexly constrained multiobjective optimization problems. It is targeted at\r\nheterogeneous and expensive problems, i.e., problems that have at least one\r\nobjective function that is computationally expensive. The method is\r\nderivative-free in the sense that neither need derivative information be\r\navailable for the expensive objectives nor are gradients approximated using\r\nrepeated function evaluations as is the case in finite-difference methods.\r\nInstead, a multiobjective trust region approach is used that works similarly to\r\nits well-known scalar pendants. Local surrogate models constructed from\r\nevaluation data of the true objective functions are employed to compute\r\npossible descent directions. In contrast to existing multiobjective trust\r\nregion algorithms, these surrogates are not polynomial but carefully\r\nconstructed radial basis function networks. This has the important advantage\r\nthat the number of data points scales linearly with the parameter space\r\ndimension. The local models qualify as fully linear and the corresponding\r\ngeneral scalar framework is adapted for problems with multiple objectives.\r\nConvergence to Pareto critical points is proven and numerical examples\r\nillustrate our findings.","lang":"eng"}],"issue":"2","publication":"Mathematical and Computational Applications","department":[{"_id":"101"},{"_id":"655"}],"type":"journal_article","date_created":"2021-03-01T10:46:48Z","status":"public","volume":26,"user_id":"47427","_id":"21337","citation":{"ama":"Berkemeier MB, Peitz S. Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. <i>Mathematical and Computational Applications</i>. 2021;26(2). doi:<a href=\"https://doi.org/10.3390/mca26020031\">10.3390/mca26020031</a>","bibtex":"@article{Berkemeier_Peitz_2021, title={Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models}, volume={26}, DOI={<a href=\"https://doi.org/10.3390/mca26020031\">10.3390/mca26020031</a>}, number={231}, journal={Mathematical and Computational Applications}, author={Berkemeier, Manuel Bastian and Peitz, Sebastian}, year={2021} }","mla":"Berkemeier, Manuel Bastian, and Sebastian Peitz. “Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models.” <i>Mathematical and Computational Applications</i>, vol. 26, no. 2, 31, 2021, doi:<a href=\"https://doi.org/10.3390/mca26020031\">10.3390/mca26020031</a>.","short":"M.B. Berkemeier, S. Peitz, Mathematical and Computational Applications 26 (2021).","chicago":"Berkemeier, Manuel Bastian, and Sebastian Peitz. “Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models.” <i>Mathematical and Computational Applications</i> 26, no. 2 (2021). <a href=\"https://doi.org/10.3390/mca26020031\">https://doi.org/10.3390/mca26020031</a>.","apa":"Berkemeier, M. B., &#38; Peitz, S. (2021). Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. <i>Mathematical and Computational Applications</i>, <i>26</i>(2). <a href=\"https://doi.org/10.3390/mca26020031\">https://doi.org/10.3390/mca26020031</a>","ieee":"M. B. Berkemeier and S. Peitz, “Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models,” <i>Mathematical and Computational Applications</i>, vol. 26, no. 2, 2021."},"oa":"1"},{"user_id":"14961","doi":"10.1007/978-3-030-68780-9_19","language":[{"iso":"eng"}],"_id":"21378","publication_status":"published","date_updated":"2022-01-06T06:54:57Z","title":"An OCR Pipeline and Semantic Text Analysis for Comics","year":"2021","status":"public","publication_identifier":{"issn":["0302-9743","1611-3349"],"isbn":["9783030687793","9783030687809"]},"author":[{"id":"14961","first_name":"Rita","last_name":"Hartel","full_name":"Hartel, Rita"},{"full_name":"Dunst, Alexander","last_name":"Dunst","first_name":"Alexander"}],"type":"conference","department":[{"_id":"69"}],"date_created":"2021-03-04T12:35:22Z","place":"Cham","publication":"MANPU 2020: The 4th International Workshop on coMics ANalysis, Processing and Understanding@Pattern Recognition. ICPR International Workshops and Challenges","citation":{"ieee":"R. Hartel and A. Dunst, “An OCR Pipeline and Semantic Text Analysis for Comics,” in <i>MANPU 2020: The 4th International Workshop on coMics ANalysis, Processing and Understanding@Pattern Recognition. ICPR International Workshops and Challenges</i>, 2021.","apa":"Hartel, R., &#38; Dunst, A. (2021). An OCR Pipeline and Semantic Text Analysis for Comics. In <i>MANPU 2020: The 4th International Workshop on coMics ANalysis, Processing and Understanding@Pattern Recognition. ICPR International Workshops and Challenges</i>. Cham. <a href=\"https://doi.org/10.1007/978-3-030-68780-9_19\">https://doi.org/10.1007/978-3-030-68780-9_19</a>","short":"R. Hartel, A. Dunst, in: MANPU 2020: The 4th International Workshop on CoMics ANalysis, Processing and Understanding@Pattern Recognition. ICPR International Workshops and Challenges, Cham, 2021.","chicago":"Hartel, Rita, and Alexander Dunst. “An OCR Pipeline and Semantic Text Analysis for Comics.” In <i>MANPU 2020: The 4th International Workshop on CoMics ANalysis, Processing and Understanding@Pattern Recognition. ICPR International Workshops and Challenges</i>. Cham, 2021. <a href=\"https://doi.org/10.1007/978-3-030-68780-9_19\">https://doi.org/10.1007/978-3-030-68780-9_19</a>.","mla":"Hartel, Rita, and Alexander Dunst. “An OCR Pipeline and Semantic Text Analysis for Comics.” <i>MANPU 2020: The 4th International Workshop on CoMics ANalysis, Processing and Understanding@Pattern Recognition. ICPR International Workshops and Challenges</i>, 2021, doi:<a href=\"https://doi.org/10.1007/978-3-030-68780-9_19\">10.1007/978-3-030-68780-9_19</a>.","bibtex":"@inproceedings{Hartel_Dunst_2021, place={Cham}, title={An OCR Pipeline and Semantic Text Analysis for Comics}, DOI={<a href=\"https://doi.org/10.1007/978-3-030-68780-9_19\">10.1007/978-3-030-68780-9_19</a>}, booktitle={MANPU 2020: The 4th International Workshop on coMics ANalysis, Processing and Understanding@Pattern Recognition. ICPR International Workshops and Challenges}, author={Hartel, Rita and Dunst, Alexander}, year={2021} }","ama":"Hartel R, Dunst A. An OCR Pipeline and Semantic Text Analysis for Comics. In: <i>MANPU 2020: The 4th International Workshop on CoMics ANalysis, Processing and Understanding@Pattern Recognition. ICPR International Workshops and Challenges</i>. Cham; 2021. doi:<a href=\"https://doi.org/10.1007/978-3-030-68780-9_19\">10.1007/978-3-030-68780-9_19</a>"}},{"department":[{"_id":"34"},{"_id":"7"},{"_id":"355"}],"type":"journal_article","date_created":"2021-03-18T11:15:38Z","quality_controlled":"1","citation":{"ama":"Bengs V, Busa-Fekete R, El Mesaoudi-Paul A, Hüllermeier E. Preference-based Online Learning with Dueling Bandits: A Survey. <i>Journal of Machine Learning Research</i>. 2021;22(7):1-108.","bibtex":"@article{Bengs_Busa-Fekete_El Mesaoudi-Paul_Hüllermeier_2021, title={Preference-based Online Learning with Dueling Bandits: A Survey}, volume={22}, number={7}, journal={Journal of Machine Learning Research}, author={Bengs, Viktor and Busa-Fekete, Róbert and El Mesaoudi-Paul, Adil and Hüllermeier, Eyke}, year={2021}, pages={1–108} }","mla":"Bengs, Viktor, et al. “Preference-Based Online Learning with Dueling Bandits: A Survey.” <i>Journal of Machine Learning Research</i>, vol. 22, no. 7, 2021, pp. 1–108.","chicago":"Bengs, Viktor, Róbert Busa-Fekete, Adil El Mesaoudi-Paul, and Eyke Hüllermeier. “Preference-Based Online Learning with Dueling Bandits: A Survey.” <i>Journal of Machine Learning Research</i> 22, no. 7 (2021): 1–108.","short":"V. Bengs, R. Busa-Fekete, A. El Mesaoudi-Paul, E. Hüllermeier, Journal of Machine Learning Research 22 (2021) 1–108.","apa":"Bengs, V., Busa-Fekete, R., El Mesaoudi-Paul, A., &#38; Hüllermeier, E. (2021). Preference-based Online Learning with Dueling Bandits: A Survey. <i>Journal of Machine Learning Research</i>, <i>22</i>(7), 1–108.","ieee":"V. Bengs, R. Busa-Fekete, A. El Mesaoudi-Paul, and E. Hüllermeier, “Preference-based Online Learning with Dueling Bandits: A Survey,” <i>Journal of Machine Learning Research</i>, vol. 22, no. 7, pp. 1–108, 2021."},"publication":"Journal of Machine Learning Research","issue":"7","volume":22,"user_id":"76599","_id":"21535","language":[{"iso":"eng"}],"page":"1-108","intvolume":"        22","date_updated":"2022-01-06T06:55:03Z","author":[{"last_name":"Bengs","first_name":"Viktor","full_name":"Bengs, Viktor"},{"full_name":"Busa-Fekete, Róbert","first_name":"Róbert","last_name":"Busa-Fekete"},{"full_name":"El Mesaoudi-Paul, Adil","last_name":"El Mesaoudi-Paul","first_name":"Adil"},{"last_name":"Hüllermeier","first_name":"Eyke","full_name":"Hüllermeier, Eyke"}],"title":"Preference-based Online Learning with Dueling Bandits: A Survey","year":"2021","status":"public"},{"author":[{"id":"35343","full_name":"Schneider, Stefan Balthasar","first_name":"Stefan Balthasar","last_name":"Schneider","orcid":"0000-0001-8210-4011"},{"full_name":"Qarawlus, Haydar","first_name":"Haydar","last_name":"Qarawlus"},{"id":"126","first_name":"Holger","last_name":"Karl","full_name":"Karl, Holger"}],"title":"Distributed Online Service Coordination Using Deep Reinforcement Learning","year":"2021","date_updated":"2022-01-06T06:55:04Z","language":[{"iso":"eng"}],"publication":"IEEE International Conference on Distributed Computing Systems (ICDCS)","abstract":[{"lang":"eng","text":"Services often consist of multiple chained components such as microservices in a service mesh, or machine learning functions in a pipeline. Providing these services requires online coordination including scaling the service, placing instance of all components in the network, scheduling traffic to these instances, and routing traffic through the network. Optimized service coordination is still a hard problem due to many influencing factors such as rapidly arriving user demands and limited node and link capacity. Existing approaches to solve the problem are often built on rigid models and assumptions, tailored to specific scenarios. If the scenario changes and the assumptions no longer hold, they easily break and require manual adjustments by experts. Novel self-learning approaches using deep reinforcement learning (DRL) are promising but still have limitations as they only address simplified versions of the problem and are typically centralized and thus do not scale to practical large-scale networks.\r\n\r\nTo address these issues, we propose a distributed self-learning service coordination approach using DRL. After centralized training, we deploy a distributed DRL agent at each node in the network, making fast coordination decisions locally in parallel with the other nodes. Each agent only observes its direct neighbors and does not need global knowledge. Hence, our approach scales independently from the size of the network. In our extensive evaluation using real-world network topologies and traffic traces, we show that our proposed approach outperforms a state-of-the-art conventional heuristic as well as a centralized DRL approach (60% higher throughput on average) while requiring less time per online decision (1 ms)."}],"related_material":{"link":[{"relation":"software","url":"https://github.com/ RealVNF/distributed-drl-coordination"}]},"date_created":"2021-03-18T17:15:47Z","file":[{"title":"Distributed Online Service Coordination Using Deep Reinforcement Learning","file_id":"21544","content_type":"application/pdf","relation":"main_file","date_updated":"2021-03-18T17:12:56Z","file_name":"public_author_version.pdf","file_size":606321,"access_level":"open_access","date_created":"2021-03-18T17:12:56Z","creator":"stschn"}],"department":[{"_id":"75"}],"keyword":["network management","service management","coordination","reinforcement learning","distributed"],"type":"conference","conference":{"name":"IEEE International Conference on Distributed Computing Systems (ICDCS)","location":"Washington, DC, USA"},"status":"public","has_accepted_license":"1","_id":"21543","publisher":"IEEE","user_id":"35343","ddc":["000"],"citation":{"mla":"Schneider, Stefan Balthasar, et al. “Distributed Online Service Coordination Using Deep Reinforcement Learning.” <i>IEEE International Conference on Distributed Computing Systems (ICDCS)</i>, IEEE, 2021.","ama":"Schneider SB, Qarawlus H, Karl H. Distributed Online Service Coordination Using Deep Reinforcement Learning. In: <i>IEEE International Conference on Distributed Computing Systems (ICDCS)</i>. IEEE; 2021.","bibtex":"@inproceedings{Schneider_Qarawlus_Karl_2021, title={Distributed Online Service Coordination Using Deep Reinforcement Learning}, booktitle={IEEE International Conference on Distributed Computing Systems (ICDCS)}, publisher={IEEE}, author={Schneider, Stefan Balthasar and Qarawlus, Haydar and Karl, Holger}, year={2021} }","apa":"Schneider, S. B., Qarawlus, H., &#38; Karl, H. (2021). Distributed Online Service Coordination Using Deep Reinforcement Learning. In <i>IEEE International Conference on Distributed Computing Systems (ICDCS)</i>. Washington, DC, USA: IEEE.","ieee":"S. B. Schneider, H. Qarawlus, and H. Karl, “Distributed Online Service Coordination Using Deep Reinforcement Learning,” in <i>IEEE International Conference on Distributed Computing Systems (ICDCS)</i>, Washington, DC, USA, 2021.","chicago":"Schneider, Stefan Balthasar, Haydar Qarawlus, and Holger Karl. “Distributed Online Service Coordination Using Deep Reinforcement Learning.” In <i>IEEE International Conference on Distributed Computing Systems (ICDCS)</i>. IEEE, 2021.","short":"S.B. Schneider, H. Qarawlus, H. Karl, in: IEEE International Conference on Distributed Computing Systems (ICDCS), IEEE, 2021."},"file_date_updated":"2021-03-18T17:12:56Z","project":[{"_id":"1","name":"SFB 901"},{"_id":"4","name":"SFB 901 - Project Area C"},{"_id":"16","name":"SFB 901 - Subproject C4"}],"oa":"1"},{"_id":"21564","language":[{"iso":"eng"}],"user_id":"11829","status":"public","title":"On the forward simulation and cost functions for the ultrasonic material characterization of polymers ","year":"2021","author":[{"full_name":"Itner, Dominik","first_name":"Dominik","last_name":"Itner"},{"last_name":"Gravenkamp","first_name":"Hauke","full_name":"Gravenkamp, Hauke"},{"last_name":"Dreiling","first_name":"Dmitrij","full_name":"Dreiling, Dmitrij","id":"32616"},{"last_name":"Feldmann","first_name":"Nadine","full_name":"Feldmann, Nadine","id":"23082"},{"id":"213","full_name":"Henning, Bernd","last_name":"Henning","first_name":"Bernd"}],"date_updated":"2022-01-06T06:55:06Z","date_created":"2021-03-24T13:37:38Z","place":"GAMM Annual Meeting, Kassel","type":"misc","department":[{"_id":"49"}],"citation":{"ama":"Itner D, Gravenkamp H, Dreiling D, Feldmann N, Henning B. <i>On the Forward Simulation and Cost Functions for the Ultrasonic Material Characterization of Polymers </i>. GAMM Annual Meeting, Kassel; 2021.","bibtex":"@book{Itner_Gravenkamp_Dreiling_Feldmann_Henning_2021, place={GAMM Annual Meeting, Kassel}, title={On the forward simulation and cost functions for the ultrasonic material characterization of polymers }, author={Itner, Dominik and Gravenkamp, Hauke and Dreiling, Dmitrij and Feldmann, Nadine and Henning, Bernd}, year={2021} }","mla":"Itner, Dominik, et al. <i>On the Forward Simulation and Cost Functions for the Ultrasonic Material Characterization of Polymers </i>. 2021.","chicago":"Itner, Dominik, Hauke Gravenkamp, Dmitrij Dreiling, Nadine Feldmann, and Bernd Henning. <i>On the Forward Simulation and Cost Functions for the Ultrasonic Material Characterization of Polymers </i>. GAMM Annual Meeting, Kassel, 2021.","short":"D. Itner, H. Gravenkamp, D. Dreiling, N. Feldmann, B. Henning, On the Forward Simulation and Cost Functions for the Ultrasonic Material Characterization of Polymers , GAMM Annual Meeting, Kassel, 2021.","apa":"Itner, D., Gravenkamp, H., Dreiling, D., Feldmann, N., &#38; Henning, B. (2021). <i>On the forward simulation and cost functions for the ultrasonic material characterization of polymers </i>. GAMM Annual Meeting, Kassel.","ieee":"D. Itner, H. Gravenkamp, D. Dreiling, N. Feldmann, and B. Henning, <i>On the forward simulation and cost functions for the ultrasonic material characterization of polymers </i>. GAMM Annual Meeting, Kassel, 2021."},"project":[{"grant_number":"409779252","_id":"89","name":"Vollständige Bestimmung der akustischen Materialparameter von Polymeren"}]},{"oa":"1","citation":{"ieee":"S. Gottschalk and E. Yigitbas, <i>Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools  und deren Datennutzung</i>, vol. 1. Gesellschaft für Informatik, 2021.","apa":"Gottschalk, S., &#38; Yigitbas, E. (2021). <i>Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools  und deren Datennutzung</i> (Vol. 1). Gesellschaft für Informatik.","chicago":"Gottschalk, Sebastian, and Enes Yigitbas. <i>Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools  und deren Datennutzung</i>. Vol. 1. WI-MAW-Rundbrief. Gesellschaft für Informatik, 2021.","short":"S. Gottschalk, E. Yigitbas, Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools  und deren Datennutzung, Gesellschaft für Informatik, 2021.","mla":"Gottschalk, Sebastian, and Enes Yigitbas. <i>Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools  und deren Datennutzung</i>. Vol. 1, Gesellschaft für Informatik, 2021.","bibtex":"@book{Gottschalk_Yigitbas_2021, series={WI-MAW-Rundbrief}, title={Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools  und deren Datennutzung}, volume={1}, publisher={Gesellschaft für Informatik}, author={Gottschalk, Sebastian and Yigitbas, Enes}, year={2021}, collection={WI-MAW-Rundbrief} }","ama":"Gottschalk S, Yigitbas E. <i>Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools  und deren Datennutzung</i>. Vol 1. Gesellschaft für Informatik; 2021."},"project":[{"_id":"1","name":"SFB 901"},{"_id":"4","name":"SFB 901 - Project Area C"},{"name":"SFB 901 - Subproject C5","_id":"17"}],"_id":"21569","publisher":"Gesellschaft für Informatik","user_id":"47208","volume":1,"status":"public","date_created":"2021-03-25T10:02:18Z","type":"report","department":[{"_id":"66"},{"_id":"534"}],"abstract":[{"lang":"eng","text":"Die kontinuierliche Weiterentwicklung des eigenen Geschäftsmodells ist für eine Organisation von entscheidender Bedeutung, um wettbewerbsfähig und somit nachhaltig erfolgreich zu bleiben. Während für die Entwicklung neuer Geschäftsmodelle häufig Workshops und einfache Software-Tools zur Visualisierung genutzt werden, wurden in der Forschung bereits erste Ansätze von datengetriebener Geschäftsmodellentwicklung (GME) vorgestellt. Diese Ansätze nutzen dabei Daten, Informationen oder auch Wissen aus internen und externen Unternehmensquellen, um den GME-Prozess zu unterstützen. Innerhalb dieses Beitrags zeigen wir einige Ansätze aus der aktuellen Literatur und analysieren wie ihre Datennutzung den GME-Prozess unterstützt. Weiterhin stellen wir mit dem BMDL Feature Modeler ein Tool vor, welches den GME-Prozess mit Expertenwissen unterstützt."}],"main_file_link":[{"url":"https://fa-wi-maw.gi.de/fileadmin/FA/WI-MAW/Rundbriefe/3037624_GI_45_Rundbrief_JG27.pdf","open_access":"1"}],"series_title":"WI-MAW-Rundbrief","language":[{"iso":"ger"}],"year":"2021","title":"Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools  und deren Datennutzung","author":[{"id":"47208","full_name":"Gottschalk, Sebastian","first_name":"Sebastian","last_name":"Gottschalk"},{"last_name":"Yigitbas","first_name":"Enes","orcid":"0000-0002-5967-833X","full_name":"Yigitbas, Enes","id":"8447"}],"publication_identifier":{"unknown":["1610-5753"]},"date_updated":"2022-01-06T06:55:06Z","intvolume":"         1"},{"user_id":"5786","_id":"21570","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:55:06Z","conference":{"name":"Genetic and Evolutionary Computation Conference","start_date":"2021-07-10","end_date":"2021-07-14"},"author":[{"full_name":"Tornede, Tanja","first_name":"Tanja","last_name":"Tornede","id":"40795"},{"full_name":"Tornede, Alexander","first_name":"Alexander","last_name":"Tornede","id":"38209"},{"orcid":" https://orcid.org/0000-0001-9782-6818","first_name":"Marcel Dominik","last_name":"Wever","full_name":"Wever, Marcel Dominik","id":"33176"},{"id":"48129","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","first_name":"Eyke"}],"title":"Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance","status":"public","year":"2021","department":[{"_id":"34"},{"_id":"355"},{"_id":"26"}],"type":"conference","date_created":"2021-03-26T09:14:19Z","project":[{"_id":"1","name":"SFB 901"},{"_id":"3","name":"SFB 901 - Project Area B"},{"_id":"10","name":"SFB 901 - Subproject B2"},{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"citation":{"ama":"Tornede T, Tornede A, Wever MD, Hüllermeier E. Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. ; 2021.","bibtex":"@inproceedings{Tornede_Tornede_Wever_Hüllermeier_2021, title={Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, author={Tornede, Tanja and Tornede, Alexander and Wever, Marcel Dominik and Hüllermeier, Eyke}, year={2021} }","mla":"Tornede, Tanja, et al. “Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance.” <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2021.","short":"T. Tornede, A. Tornede, M.D. Wever, E. Hüllermeier, in: Proceedings of the Genetic and Evolutionary Computation Conference, 2021.","chicago":"Tornede, Tanja, Alexander Tornede, Marcel Dominik Wever, and Eyke Hüllermeier. “Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2021.","apa":"Tornede, T., Tornede, A., Wever, M. D., &#38; Hüllermeier, E. (2021). Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance. <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. Genetic and Evolutionary Computation Conference.","ieee":"T. Tornede, A. Tornede, M. D. Wever, and E. Hüllermeier, “Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance,” presented at the Genetic and Evolutionary Computation Conference, 2021."},"publication":"Proceedings of the Genetic and Evolutionary Computation Conference"},{"department":[{"_id":"76"}],"type":"journal_article","date_created":"2021-04-08T11:21:32Z","citation":{"bibtex":"@article{Stockmann_Laux_Bodden_2021, title={Using Architectural Runtime Verification for Offline Data Analysis}, DOI={<a href=\"https://doi.org/10.2991/jase.d.210205.001\">10.2991/jase.d.210205.001</a>}, journal={Journal of Automotive Software Engineering}, author={Stockmann, Lars and Laux, Sven and Bodden, Eric}, year={2021} }","ama":"Stockmann L, Laux S, Bodden E. Using Architectural Runtime Verification for Offline Data Analysis. <i>Journal of Automotive Software Engineering</i>. Published online 2021. doi:<a href=\"https://doi.org/10.2991/jase.d.210205.001\">10.2991/jase.d.210205.001</a>","mla":"Stockmann, Lars, et al. “Using Architectural Runtime Verification for Offline Data Analysis.” <i>Journal of Automotive Software Engineering</i>, 2021, doi:<a href=\"https://doi.org/10.2991/jase.d.210205.001\">10.2991/jase.d.210205.001</a>.","chicago":"Stockmann, Lars, Sven Laux, and Eric Bodden. “Using Architectural Runtime Verification for Offline Data Analysis.” <i>Journal of Automotive Software Engineering</i>, 2021. <a href=\"https://doi.org/10.2991/jase.d.210205.001\">https://doi.org/10.2991/jase.d.210205.001</a>.","short":"L. Stockmann, S. Laux, E. Bodden, Journal of Automotive Software Engineering (2021).","ieee":"L. Stockmann, S. Laux, and E. Bodden, “Using Architectural Runtime Verification for Offline Data Analysis,” <i>Journal of Automotive Software Engineering</i>, 2021, doi: <a href=\"https://doi.org/10.2991/jase.d.210205.001\">10.2991/jase.d.210205.001</a>.","apa":"Stockmann, L., Laux, S., &#38; Bodden, E. (2021). Using Architectural Runtime Verification for Offline Data Analysis. <i>Journal of Automotive Software Engineering</i>. <a href=\"https://doi.org/10.2991/jase.d.210205.001\">https://doi.org/10.2991/jase.d.210205.001</a>"},"publication":"Journal of Automotive Software Engineering","user_id":"5786","doi":"10.2991/jase.d.210205.001","language":[{"iso":"eng"}],"_id":"21595","main_file_link":[{"url":"https://www.bodden.de/pubs/sb21architectural.pdf"}],"publication_status":"published","date_updated":"2022-01-06T06:55:06Z","publication_identifier":{"issn":["2589-2258"]},"author":[{"id":"48144","full_name":"Stockmann, Lars","first_name":"Lars","last_name":"Stockmann"},{"full_name":"Laux, Sven","first_name":"Sven","last_name":"Laux"},{"id":"59256","full_name":"Bodden, Eric","first_name":"Eric","orcid":"0000-0003-3470-3647","last_name":"Bodden"}],"year":"2021","status":"public","title":"Using Architectural Runtime Verification for Offline Data Analysis"},{"user_id":"5786","main_file_link":[{"url":"https://www.bodden.de/pubs/phdFischer.pdf"}],"language":[{"iso":"eng"}],"_id":"21596","publisher":"Universität Paderborn","date_updated":"2022-01-06T06:55:06Z","status":"public","title":"Computing on Encrypted Data using Trusted Execution Environments","year":"2021","author":[{"full_name":"Fischer, Andreas","last_name":"Fischer","first_name":"Andreas"}],"type":"dissertation","department":[{"_id":"76"}],"date_created":"2021-04-08T11:23:13Z","citation":{"bibtex":"@book{Fischer_2021, title={Computing on Encrypted Data using Trusted Execution Environments}, publisher={Universität Paderborn}, author={Fischer, Andreas}, year={2021} }","ama":"Fischer A. <i>Computing on Encrypted Data Using Trusted Execution Environments</i>. Universität Paderborn; 2021.","short":"A. Fischer, Computing on Encrypted Data Using Trusted Execution Environments, Universität Paderborn, 2021.","chicago":"Fischer, Andreas. <i>Computing on Encrypted Data Using Trusted Execution Environments</i>. Universität Paderborn, 2021.","ieee":"A. Fischer, <i>Computing on Encrypted Data using Trusted Execution Environments</i>. Universität Paderborn, 2021.","mla":"Fischer, Andreas. <i>Computing on Encrypted Data Using Trusted Execution Environments</i>. Universität Paderborn, 2021.","apa":"Fischer, A. (2021). <i>Computing on Encrypted Data using Trusted Execution Environments</i>. Universität Paderborn."}}]