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Using Bayesian Regularized Artificial Neural Networks to Predict the Tensile Strength of Additively Manufactured Polylactic Acid Parts

Vendittoli, Valentina; Polini, Wilma; Walter, Michael S. J.; Geißelsöder, Stefan (2024)

Applied Sciences 14, 3184 (8).
DOI: 10.3390/app14083184


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Additive manufacturing has transformed the production process by enabling the construction of components in a layer-by-layer approach. This study integrates Artificial Neural Networks to explore the nuanced relationship between process parameters and mechanical performance in Fused Filament Fabrication. Using a fractional Taguchi design, seven key process parameters are systematically varied to provide a robust dataset for model training. The resulting model confirms its accuracy in predicting tensile strength. In particular, the mean squared error is 0.002, and the mean absolute error is 0.024. These results significantly advance the understanding of 3D manufactured parts, shedding light on the intricate dynamics between process nuances and mechanical outcomes. Furthermore, they underscore the transformative role of machine learning in precision-driven quality prediction and optimization in additive manufacturing.

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Kopplung von KI, Strömungssimulation und Strömungsmessung

Zacharias, Konstantin; Welsch, Dennis; Geißelsöder, Stefan; Buchele, Alexander (2023)

mfund Konferenz 2023, Berlin.



Signal analysis and classification of interictal epileptiform discharges from EEG with machine learning

Stiehl, Annika; Geißelsöder, Stefan; Anselstetter, Fabienne; Bornfleth, Harald...

BMT 2023, 26.09. - 28.09.2023, Duisburg.
DOI: 10.1515/bmte-2023-2001


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Topological Analysis of Low Dimensional Phase Space Trajectories of High Dimensional EEG Signals For Classification of Interictal Epileptiform Discharges

Stiehl, Annika; Flammer, M; Anselstetter, Fabienne; Ille, Nicole; Bornfleth, Harald...

2023 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW), Rhodes Island, Greece, S. 1-5.
DOI: 10.1109/ICASSPW59220.2023.10193167


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Industrielle Anwendungen

Geißelsöder, Stefan (2023)

Knowledge Science – Fallstudien. Springer Vieweg, Wiesbaden, S. 193-205.
DOI: 10.1007/978-3-658-41155-8_9


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Different montages and dimension reduction methods for EEG signal analysis of Interictal Epileptic Discharges

Stiehl, Annika; Anselstetter, Fabienne; Ille, Nicole; Bornfleth, Harald...

Abstracts of the 2022 Joint Annual Conference of the Austrian (ÖGBMT), German (VDE DGBMT) and Swiss (SSBE)Societies for Biomedical Engineering 67 (S1), S. 88.
DOI: 10.1515/bmt-2022-2001


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Dimension reduction methods, persistent homology ans machine learning for EEG signal analysis of Interictal Epileptic Discharges

Stiehl, Annika; Geißelsöder, Stefan; Ille, Nicole; Anselstetter, Fabienne...

Proceedings of the Workshop Biosignale 2022 (24. - 26.08.2022).



On the intelligence of interacting autonomous robots and agents

Geißelsöder, Stefan (2022)

4th International Conference Business Meets Technology 2022.
DOI: 10.4995/BMT2022.2022.15555


Open Access
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ExDRa: Exploratory Data Science on Federated Raw Data

Baunsgaard, Sebastian ; Boehm, Matthias ; Chaudhary , Ankit; Derakhshan, Behrouz ...

SIGMOD '21: Proceedings of the 2021 International Conference on Management of Data, S. 2450–2463.


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Vorrichtung und Verfahren zur Erkennung von Anomalien in einer industriellen Anlage zur Ausführung eines Produktionsprozesses

Geißelsöder, Stefan; Hitzel, Klaus-Peter; Dilek, Hakan; Hertlein, Christian Klaus...

Europäisches Patent. Internationale Veröffentlichungsnummer: WO2022/069258/A1.



Model-independent search for neutrino sources with the ANTARES neutrino telescope

Albert, A.; André, M.; Anghinolfi, M; Anton, G; Ardid, Miguel; Aubert, J.-J.; et al., ....

Astroparticle Physics 114, S. 35-47.
DOI: 10.1016/j.astropartphys.2019.06.003


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Characterisation of the Hamamatsu photomultipliers for the KM3NeT Neutrino Telescope

Aiello, S.; Akrame, S.E.; Ameli, F.; Anassontzis, E. G.; André, M; Androulakis, G....

Journal of Instrumentation 13, P05035.


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Deep Learning mit unbalancierten Datensätzen

Geißelsöder, Stefan (2018)

Verhandlungen der Deutschen Physikalischen Gesellschaft e.V.. Würzburg 2018.



A polarized fast radio burst at low Galactic latitude

Petroff, E.; Burke-Spolaor, S.; Keane, E. F.; McLaughlin, M. A.; Miller , R....

Monthly Notices of the Royal Astronomical Society 469 (4), S. 4465-4482.
DOI: 10.1093/mnras/stx1098


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Results from the search for dark matter in the Milky Way with 9 years of data of the ANTARES neutrino telescope

Albert, A.; André, M.; Anghinolfi, M; Anton, G; Ardid, Miguel; Aubert, J.-J.; et al., ....

Physics Letters B 769, S. 249-254.


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Time-dependent search for neutrino emission from X-ray binaries with the ANTARES telescope

Albert, A.; André, M; Anton, G; Ardid, Miguel; Aubert, J.-J.; Avgitas, T.; et al., ....

Journal of Cosmology and Astroparticle Physics 04(2017), 019.
DOI: 10.1088/1475-7516/2017/04/019


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Search for high-energy neutrinos from bright GRBs with ANTARES

Albert, A.; André, M.; Anghinolfi, M; Anton, G; Ardid, Miguel; Aubert, J.-J.; et al., ....

Monthly Notices of the Royal Astronomical Society 469 (1), S. 906-915.
DOI: 10.1093/mnras/stx902


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Sperm whale long-range echolocation sounds revealed by ANTARES, a deep-sea neutrino telescope

André, M.; Caballé, A.; van der Schaar, M.; Solsona Berga, Alba; Houegnigan, Ludwig...

Scientific Reports 7, 45517.
DOI: 10.1038/srep45517


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Deep Learning für Neutrinoteleskope

Geißelsöder, Stefan (2017)

Verhandlungen der Deutschen Physikalischen Gesellschaft e.V.. Münster 2017.



First combined search for neutrino point-sources in the Southern Hemisphere with the ANTARES and IceCube neutrino telescopes

Adrián-Martínez, S.; Albert, A.; André, M; Anton, G; Ardid, Miguel; Aubert, J.-J....

The Astrophysical Journal 823, 65 (1).


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