--- _id: '7734' abstract: - lang: eng text: ' Der Konferenzbeitrag zeigt den Forschungs- und Technikstand bezüglich des Griff-in-die-Kiste auf. Basierend auf einer Literaturrecherche werden Beispiele für regelbasierte und lernende Verfahren vorgestellt. Anschließend erfolgt eine systematische Gegenüberstellung der Verfahren. Hierfür werden die Anforderungen, die ein Griff-in-die-Kiste-System zu erfüllen hat, dargelegt. Die Kriterien resultieren aus einer Expertenbefragung des produktionstechnischen Umfelds der Weidmüller Gruppe. Neben den Anforderungen werden die Gewichtungen zur Bildung einer Rangfolge ermittelt. Die erarbeiteten Anforderungen dienen anschließend zur Bewertung der regelbasierten und lernenden Verfahren. Die Analyse mündet in einer methodischen Lücke zwischen beiden Paradigmen und stellt die Ausgangsbasis für die weitere Arbeit zur Entwicklung des industriellen Griff-in-die-Kiste dar. Abschließend werden erste Arbeitsergebnisse zur Objekterkennung von Reihenklemmen veröffentlicht. In einer Untersuchung werden die Zuverlässigkeit, die Robustheit sowie die Einrichtdauer einer Objekterkennung mithilfe von Deep Learning ermittelt. Das angestrebte Forschungsergebnis stellt einen Entwicklungsschritt von automatisierten Systemen, die in einem definierten Wirkbereich eigenständig arbeiten, zu autonomen Systemen, die selbstständig auf zeitvariante Größen reagieren, dar.' author: - first_name: Tobias full_name: Stuke, Tobias id: '79141' last_name: Stuke - first_name: Thomas full_name: Bartsch, Thomas id: '43513' last_name: Bartsch - first_name: Thomas full_name: Rauschenbach, Thomas last_name: Rauschenbach citation: ama: Stuke T, Bartsch T, Rauschenbach T. Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie. 1st ed. (Härle C, Jäkel J, Sand G, Hochschule für Technik, Wirtschaft und Kultur Leipzig, eds.). Open Access; 2022:145-154. doi:https://doi.org/10.33968/2022.14 apa: 'Stuke, T., Bartsch, T., & Rauschenbach, T. (2022). Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie. In C. Härle, J. Jäkel, G. Sand, & Hochschule für Technik, Wirtschaft und Kultur Leipzig (Eds.), Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkräftemangel (1st ed., pp. 145–154). Open Access. https://doi.org/10.33968/2022.14' bjps: 'Stuke T, Bartsch T and Rauschenbach T (2022) Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie, 1st ed., Härle C et al. (eds). Pforzheim: Open Access.' chicago: 'Stuke, Tobias, Thomas Bartsch, and Thomas Rauschenbach. Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie. Edited by Christian Härle, Jens Jäkel, Guido Sand, and Hochschule für Technik, Wirtschaft und Kultur Leipzig. Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkräftemangel. 1st ed. Pforzheim: Open Access, 2022. https://doi.org/10.33968/2022.14.' chicago-de: 'Stuke, Tobias, Thomas Bartsch und Thomas Rauschenbach. 2022. Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie. Hg. von Christian Härle, Jens Jäkel, Guido Sand, und Hochschule für Technik, Wirtschaft und Kultur Leipzig. Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkräftemangel. 1. Aufl. Pforzheim: Open Access. doi:https://doi.org/10.33968/2022.14, .' din1505-2-1: 'Stuke, Tobias ; Bartsch, Thomas ; Rauschenbach, Thomas ; Härle, C. ; Jäkel, J. ; Sand, G. ; Hochschule für Technik, Wirtschaft und Kultur Leipzig (Hrsg.): Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie. 1. Aufl. Pforzheim : Open Access, 2022' havard: T. Stuke, T. Bartsch, T. Rauschenbach, Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie, 1st ed., Open Access, Pforzheim, 2022. ieee: 'T. Stuke, T. Bartsch, and T. Rauschenbach, Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie, 1st ed. Pforzheim: Open Access, 2022, pp. 145–154. doi: https://doi.org/10.33968/2022.14.' mla: 'Stuke, Tobias, et al. “Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie.” Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkräftemangel, edited by Christian Härle et al., 1st ed., Open Access, 2022, pp. 145–54, https://doi.org/10.33968/2022.14.' short: T. Stuke, T. Bartsch, T. Rauschenbach, Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie, 1st ed., Open Access, Pforzheim, 2022. ufg: 'Stuke, Tobias/Bartsch, Thomas/Rauschenbach, Thomas: Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie, hg. von Härle, Christian u. a., Pforzheim 12022.' van: 'Stuke T, Bartsch T, Rauschenbach T. Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie. 1st ed. Härle C, Jäkel J, Sand G, Hochschule für Technik, Wirtschaft und Kultur Leipzig, editors. Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkräftemangel. Pforzheim: Open Access; 2022.' conference: end_date: 2022-03-11 location: Pforzheim name: 18. Konferenz für Angewandte Auto­mati­sierungs­technik in Lehre und Entwicklung an Hochschulen (AALE) start_date: 2022-03-09 corporate_editor: - Hochschule für Technik, Wirtschaft und Kultur Leipzig date_created: 2022-04-22T11:44:38Z date_updated: 2024-08-08T13:55:46Z department: - _id: DEP7015 doi: https://doi.org/10.33968/2022.14 edition: '1' editor: - first_name: Christian full_name: Härle, Christian last_name: Härle - first_name: Jens full_name: Jäkel, Jens last_name: Jäkel - first_name: Guido full_name: Sand, Guido last_name: Sand keyword: - Griff-in-die-Kiste - Bildverarbeitung - Robotik - Deep Learning - lernende Verfahren - regelbasierte Verfahren language: - iso: ger page: 145 – 154 place: Pforzheim publication: 'Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkräftemangel' publication_identifier: unknown: - 978-3-910103-00-9 publication_status: published publisher: Open Access status: public title: Adaptiver Griff-in-die-Kiste – Die methodische Lücke zwischen Forschung und Industrie type: conference_editor_article user_id: '83781' year: '2022' ... --- _id: '8888' abstract: - lang: ger text: "Diese Arbeit handelt von der Frage, wie Tonaufnahmen-basierte Lernprozesse im Learning Management System der Hochschule für Musik Detmold, Moodle, erweitert werden können. Dazu werden LMS zunächst definiert und anschließend in die Bildungslandschaft eingeordnet. Daraufhin wird der Status Quo betrachtet mit der Feststellung, dass ein Bedarf an Werkzeugen besteht. Dieser Bedarf wurde durch die Programmierung zweier Anwendungen adressiert, die eine Integration im LMS ermöglichen und damit zu einer erhöhten Nutzbarkeit von Tonaufnahmen und musikalischen Inhalten führen sollen. Zum einen ist das eine Implementation des DTW Algorithmus, mittels welchem sich Synchronisationsdaten zwischen zwei verschiedenen Musikdarstellungen desselben Stückes berechnen lassen. Damit ließe sich bspw. ein Interface erstellen, auf dem die Anzeige der Musikwiedergabe mit der Anzeige einer Notenpartitur synchronisiert wird. Die zweite Anwendung fällt in den Bereich des maschinellen Lernens – es wurde ein automatischer Instrumentenklassifizierer geschrieben. Dieser eignet sich zur Erstellung von automatischen Taggings, zwecks Organisation von Daten und Gehörübungen. Die Nutzung einer CNN-Architektur hat sich dabei als effektiv erwiesen: Nach insgesamt 39 Lernepochen und knapp 7 Millionen gelernten Parametern konnte eine Genauigkeit von 95% erzielt werden. Als Datensatz diente die frei verfügbare Aufnahmensammlung des britischen Philharmonia Orchesters (vgl. Thorben Dittes). \r\nIm zweiten Kapitel soll ein Abstecken der Zwecke der einzelnen Programme die Designentscheidungen informieren, welche daraufhin erläutert werden. Im dritten Teil wird anschließend mit ScoreTube eine DTW Implementation von Berndt et al. zum Vergleich herangezogen, um die vorliegende Arbeit in den aktuellen Diskurs einzuordnen. Der Beitrag endet mit einer Evaluation der Ergebnisse und einem Ausblick auf potenzielle zukünftige Arbeiten." author: - first_name: Dennis full_name: Treiber, Dennis id: '72911' last_name: Treiber citation: ama: 'Treiber D. Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen. Technische Hochschule Ostwestfalen-Lippe; 2022.' apa: 'Treiber, D. (2022). Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen. Technische Hochschule Ostwestfalen-Lippe.' bjps: 'Treiber D (2022) Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen. Detmold: Technische Hochschule Ostwestfalen-Lippe.' chicago: 'Treiber, Dennis. Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen. Detmold: Technische Hochschule Ostwestfalen-Lippe, 2022.' chicago-de: 'Treiber, Dennis. 2022. Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen. Detmold: Technische Hochschule Ostwestfalen-Lippe.' din1505-2-1: 'Treiber, Dennis: Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen. Detmold : Technische Hochschule Ostwestfalen-Lippe, 2022' havard: 'D. Treiber, Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen., Technische Hochschule Ostwestfalen-Lippe, Detmold, 2022.' ieee: 'D. Treiber, Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen. Detmold: Technische Hochschule Ostwestfalen-Lippe, 2022.' mla: 'Treiber, Dennis. Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen. Technische Hochschule Ostwestfalen-Lippe, 2022.' short: 'D. Treiber, Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen., Technische Hochschule Ostwestfalen-Lippe, Detmold, 2022.' ufg: 'Treiber, Dennis: Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen., Detmold 2022.' van: 'Treiber D. Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen. Detmold: Technische Hochschule Ostwestfalen-Lippe; 2022. 53 p.' date_created: 2022-09-07T09:31:21Z date_updated: 2023-03-15T13:50:16Z ddc: - '004' defense_date: 2022-08-31 department: - _id: DEP2001 file: - access_level: open_access content_type: application/pdf creator: 5r2-ybz date_created: 2022-09-07T09:25:33Z date_updated: 2022-09-07T09:25:33Z file_id: '8889' file_name: BA - Verwendung von Tonaufnahmen im LMS - Dennis Treiber.pdf file_size: 1302756 relation: main_file title: Die Verwendung von Tonaufnahmen im LMS file_date_updated: 2022-09-07T09:25:33Z has_accepted_license: '1' jel: - C61 keyword: - learning management system - dynamic time warping - deep learning - convolutional neural network language: - iso: ger oa: '1' page: '53' place: Detmold publication_status: published publisher: Technische Hochschule Ostwestfalen-Lippe status: public supervisor: - first_name: Aristotelis full_name: Hadjakos, Aristotelis id: '58704' last_name: Hadjakos - first_name: Guido full_name: Falkemeier, Guido id: '29084' last_name: Falkemeier title: 'Die Verwendung von Tonaufnahmen im LMS : Entwicklung spezifischer digitaler Werkzeuge an Hochschulen.' type: bachelor_thesis user_id: '15514' year: 2022 ... --- _id: '9161' abstract: - lang: eng text: Employees in household-related services have so far been neglected in research and practice. The overall goal of our project is to identify work-related stress of this special target group, develop recommendations, and disseminate them using low-threshold, attractive edutainment offers. In this context, this contribution presents a learning platform design for the special target group of domestic workers, such as gardeners or cleaners. The design is based on a requirements analysis with respect to this special target group, which we as well outline in this contribution. author: - first_name: Valentin full_name: Grimm, Valentin id: '74000' last_name: Grimm - first_name: Laura full_name: Geiger, Laura last_name: Geiger - first_name: Jessica full_name: Rubart, Jessica id: '45672' last_name: Rubart - first_name: Gudrun full_name: Faller, Gudrun last_name: Faller citation: ama: Grimm V, Geiger L, Rubart J, Faller G. Requirements and Design of a Training System for Domestic Workers. Vol P-322. (Henning PA, Striewe M, Wölfel M, Gesellschaft für Informatik , eds.). Gesellschaft für Informatik e.V.; 2022:213-214. doi:10.18420/delfi2022-037 apa: 'Grimm, V., Geiger, L., Rubart, J., & Faller, G. (2022). Requirements and Design of a Training System for Domestic Workers. In P. A. Henning, M. Striewe, M. Wölfel, & Gesellschaft für Informatik (Eds.), DELFI 2022 : die 20. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V., 12.-14. September 2022, Karlsruhe: Vol. P-322 (pp. 213–214). Gesellschaft für Informatik e.V. https://doi.org/10.18420/delfi2022-037' bjps: 'Grimm V et al. (2022) Requirements and Design of a Training System for Domestic Workers, Henning PA et al. (eds). Bonn: Gesellschaft für Informatik e.V.' chicago: 'Grimm, Valentin, Laura Geiger, Jessica Rubart, and Gudrun Faller. Requirements and Design of a Training System for Domestic Workers. Edited by Peter A. Henning, Michael Striewe, Matthias Wölfel, and Gesellschaft für Informatik . DELFI 2022 : Die 20. Fachtagung Bildungstechnologien Der Gesellschaft Für Informatik e.V., 12.-14. September 2022, Karlsruhe. Vol. P-322. GI-Edition : Lecture Notes in Informatics. Proceedings . Bonn: Gesellschaft für Informatik e.V., 2022. https://doi.org/10.18420/delfi2022-037.' chicago-de: 'Grimm, Valentin, Laura Geiger, Jessica Rubart und Gudrun Faller. 2022. Requirements and Design of a Training System for Domestic Workers. Hg. von Peter A. Henning, Michael Striewe, Matthias Wölfel, und Gesellschaft für Informatik . DELFI 2022 : die 20. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V., 12.-14. September 2022, Karlsruhe. Bd. P-322. GI-Edition : lecture notes in informatics. Proceedings . Bonn: Gesellschaft für Informatik e.V. doi:10.18420/delfi2022-037, .' din1505-2-1: 'Grimm, Valentin ; Geiger, Laura ; Rubart, Jessica ; Faller, Gudrun ; Henning, P. A. ; Striewe, M. ; Wölfel, M. ; Gesellschaft für Informatik (Hrsg.): Requirements and Design of a Training System for Domestic Workers, GI-Edition : lecture notes in informatics. Proceedings . Bd. P-322. Bonn : Gesellschaft für Informatik e.V., 2022' havard: V. Grimm, L. Geiger, J. Rubart, G. Faller, Requirements and Design of a Training System for Domestic Workers, Gesellschaft für Informatik e.V., Bonn, 2022. ieee: 'V. Grimm, L. Geiger, J. Rubart, and G. Faller, Requirements and Design of a Training System for Domestic Workers, vol. P-322. Bonn: Gesellschaft für Informatik e.V., 2022, pp. 213–214. doi: 10.18420/delfi2022-037.' mla: 'Grimm, Valentin, et al. “Requirements and Design of a Training System for Domestic Workers.” DELFI 2022 : Die 20. Fachtagung Bildungstechnologien Der Gesellschaft Für Informatik e.V., 12.-14. September 2022, Karlsruhe, edited by Peter A. Henning et al., vol. P-322, Gesellschaft für Informatik e.V., 2022, pp. 213–14, https://doi.org/10.18420/delfi2022-037.' short: V. Grimm, L. Geiger, J. Rubart, G. Faller, Requirements and Design of a Training System for Domestic Workers, Gesellschaft für Informatik e.V., Bonn, 2022. ufg: 'Grimm, Valentin u. a.: Requirements and Design of a Training System for Domestic Workers, Bd. P-322, hg. von Henning, Peter A. u. a., Bonn 2022 (GI-Edition : lecture notes in informatics. Proceedings ).' van: 'Grimm V, Geiger L, Rubart J, Faller G. Requirements and Design of a Training System for Domestic Workers. Henning PA, Striewe M, Wölfel M, Gesellschaft für Informatik , editors. DELFI 2022 : die 20. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V., 12.-14. September 2022, Karlsruhe. Bonn: Gesellschaft für Informatik e.V.; 2022. (GI-Edition : lecture notes in informatics. Proceedings ; vol. P-322).' conference: end_date: 2022-09-14 location: Karlsruhe, DE name: 20. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V. (DELFI) start_date: 2022-09-12 corporate_editor: - 'Gesellschaft für Informatik ' date_created: 2022-11-08T14:38:12Z date_updated: 2024-08-02T09:19:02Z department: - _id: DEP8008 - _id: DEP8000 doi: 10.18420/delfi2022-037 editor: - first_name: Peter A. full_name: Henning, Peter A. last_name: Henning - first_name: Michael full_name: Striewe, Michael last_name: Striewe - first_name: Matthias full_name: Wölfel, Matthias last_name: Wölfel keyword: - E-Learning - Minority Group - Gameful Design - Gamification language: - iso: eng main_file_link: - url: https://dl.gi.de/handle/20.500.12116/38838 page: 213-214 place: Bonn publication: 'DELFI 2022 : die 20. Fachtagung Bildungstechnologien der Gesellschaft für Informatik e.V., 12.-14. September 2022, Karlsruhe' publication_identifier: isbn: - 978-3-88579-716-6 issn: - 1617-5468 publication_status: published publisher: Gesellschaft für Informatik e.V. quality_controlled: '1' series_title: 'GI-Edition : lecture notes in informatics. Proceedings ' status: public title: Requirements and Design of a Training System for Domestic Workers type: conference_editor_article user_id: '83781' volume: P-322 year: '2022' ... --- _id: '12817' abstract: - lang: eng text: Sub-optimal control policies in intersection traffic signal controllers (TSC) contribute to congestion and lead to negative effects on human health and the environment. Reinforcement learning (RL) for traffic signal control is a promising approach to design better control policies and has attracted considerable research interest in recent years. However, most work done in this area used simplified simulation environments of traffic scenarios to train RL-based TSC. To deploy RL in real-world traffic systems, the gap between simplified simulation environments and real-world applications has to be closed. Therefore, we propose LemgoRL, a benchmark tool to train RL agents as TSC in a realistic simulation environment of Lemgo, a medium-sized town in Germany. In addition to the realistic simulation model, LemgoRL encompasses a traffic signal logic unit that ensures compliance with all regulatory and safety requirements. LemgoRL offers the same interface as the well-known OpenAI gym toolkit to enable easy deployment in existing research work. To demonstrate the functionality and applicability of LemgoRL, we train a state-of-the-art Deep RL algorithm on a CPU cluster utilizing a framework for distributed and parallel RL and compare its performance with other methods. Our benchmark tool drives the development of RL algorithms towards real-world applications. author: - first_name: Arthur full_name: Müller, Arthur last_name: Müller - first_name: Vishal full_name: Rangras, Vishal id: '76044' last_name: Rangras - first_name: Tobias full_name: Ferfers, Tobias last_name: Ferfers - first_name: Florian full_name: Hufen, Florian last_name: Hufen - first_name: Lukas full_name: Schreckenberg, Lukas last_name: Schreckenberg - first_name: Jürgen full_name: Jasperneite, Jürgen id: '1899' last_name: Jasperneite - first_name: Georg full_name: Schnittker, Georg last_name: Schnittker - first_name: Michael full_name: Waldmann, Michael last_name: Waldmann - first_name: Maxim full_name: Friesen, Maxim id: '61517' last_name: Friesen - first_name: Marco full_name: Wiering, Marco last_name: Wiering citation: ama: Müller A, Rangras V, Ferfers T, et al. Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control. (Wani MA, Sethi I, Shi W, et al., eds.). IEEE; 2022:507-514. doi:10.1109/icmla52953.2021.00085 apa: Müller, A., Rangras, V., Ferfers, T., Hufen, F., Schreckenberg, L., Jasperneite, J., Schnittker, G., Waldmann, M., Friesen, M., & Wiering, M. (2022). Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control. In M. A. Wani, I. Sethi, W. Shi, G. Qu, D. Stan Raicu, R. Jin, IEEE ICMLA , & Institute of Electrical and Electronics Engineers (Eds.), 20th IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 507–514). IEEE. https://doi.org/10.1109/icmla52953.2021.00085 bjps: 'Müller A et al. (2022) Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control, Wani MA et al. (eds). [Piscataway, NJ]: IEEE.' chicago: 'Müller, Arthur, Vishal Rangras, Tobias Ferfers, Florian Hufen, Lukas Schreckenberg, Jürgen Jasperneite, Georg Schnittker, Michael Waldmann, Maxim Friesen, and Marco Wiering. Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control. Edited by M. Arif Wani, Ishwar Sethi, Weisong Shi, Guangzhi Qu, Daniela Stan Raicu, Ruoming Jin, IEEE ICMLA , and Institute of Electrical and Electronics Engineers. 20th IEEE International Conference on Machine Learning and Applications (ICMLA). [Piscataway, NJ]: IEEE, 2022. https://doi.org/10.1109/icmla52953.2021.00085.' chicago-de: 'Müller, Arthur, Vishal Rangras, Tobias Ferfers, Florian Hufen, Lukas Schreckenberg, Jürgen Jasperneite, Georg Schnittker, Michael Waldmann, Maxim Friesen und Marco Wiering. 2022. Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control. Hg. von M. Arif Wani, Ishwar Sethi, Weisong Shi, Guangzhi Qu, Daniela Stan Raicu, Ruoming Jin, IEEE ICMLA , und Institute of Electrical and Electronics Engineers. 20th IEEE International Conference on Machine Learning and Applications (ICMLA). [Piscataway, NJ]: IEEE. doi:10.1109/icmla52953.2021.00085, .' din1505-2-1: 'Müller, Arthur ; Rangras, Vishal ; Ferfers, Tobias ; Hufen, Florian ; Schreckenberg, Lukas ; Jasperneite, Jürgen ; Schnittker, Georg ; Waldmann, Michael ; u. a. ; Wani, M. A. ; Sethi, I. ; Shi, W. ; Qu, G. ; Stan Raicu, D. ; Jin, R. ; IEEE ICMLA ; Institute of Electrical and Electronics Engineers (Hrsg.): Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control. [Piscataway, NJ] : IEEE, 2022' havard: A. Müller, V. Rangras, T. Ferfers, F. Hufen, L. Schreckenberg, J. Jasperneite, G. Schnittker, M. Waldmann, M. Friesen, M. Wiering, Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control, IEEE, [Piscataway, NJ], 2022. ieee: 'A. Müller et al., Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control. [Piscataway, NJ]: IEEE, 2022, pp. 507–514. doi: 10.1109/icmla52953.2021.00085.' mla: Müller, Arthur, et al. “Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control.” 20th IEEE International Conference on Machine Learning and Applications (ICMLA), edited by M. Arif Wani et al., IEEE, 2022, pp. 507–14, https://doi.org/10.1109/icmla52953.2021.00085. short: A. Müller, V. Rangras, T. Ferfers, F. Hufen, L. Schreckenberg, J. Jasperneite, G. Schnittker, M. Waldmann, M. Friesen, M. Wiering, Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control, IEEE, [Piscataway, NJ], 2022. ufg: 'Müller, Arthur u. a.: Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control, hg. von Wani, M. Arif u. a., [Piscataway, NJ] 2022.' van: 'Müller A, Rangras V, Ferfers T, Hufen F, Schreckenberg L, Jasperneite J, et al. Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control. Wani MA, Sethi I, Shi W, Qu G, Stan Raicu D, Jin R, et al., editors. 20th IEEE International Conference on Machine Learning and Applications (ICMLA). [Piscataway, NJ]: IEEE; 2022.' conference: end_date: 2021-12-16 location: Online name: 20th IEEE International Conference on Machine Learning and Applications (ICMLA) start_date: 2021-12-13 corporate_editor: - ' IEEE ICMLA ' - Institute of Electrical and Electronics Engineers date_created: 2025-04-17T08:45:40Z date_updated: 2025-06-26T13:28:21Z department: - _id: DEP5023 doi: 10.1109/icmla52953.2021.00085 editor: - first_name: 'M. Arif ' full_name: 'Wani, M. Arif ' last_name: Wani - first_name: 'Ishwar ' full_name: 'Sethi, Ishwar ' last_name: Sethi - first_name: Weisong full_name: ' Shi, Weisong' last_name: ' Shi' - first_name: 'Guangzhi ' full_name: 'Qu, Guangzhi ' last_name: Qu - first_name: 'Daniela ' full_name: 'Stan Raicu, Daniela ' last_name: Stan Raicu - first_name: 'Ruoming ' full_name: 'Jin, Ruoming ' last_name: Jin keyword: - deep reinforcement learning - traffic signal control - intelligent transportation system - traffic simulation language: - iso: eng page: 507-514 place: '[Piscataway, NJ]' publication: 20th IEEE International Conference on Machine Learning and Applications (ICMLA) publication_identifier: isbn: - 978-1-6654-4337-1 publication_status: published publisher: IEEE status: public title: Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control type: conference_editor_article user_id: '83781' year: '2022' ... --- _id: '6689' abstract: - lang: eng text: "Free amino nitrogen (FAN) concentrations in beer mash can be determined with machine learning algorithms\r\nfrom near-infrared (NIR) spectra. NIR spectroscopy is an alternative to a classical chemical analysis and\r\nallows for the application of inline process quality control. This study investigates the capabilities of\r\ndifferent machine learning techniques such as Ordinary Least Squares (OLS) regression, Decision Tree\r\nRegressor (DTR), Bayesian Ridge Regression (BRR), Ridge Regression (RR), K-nearest neighbours (KNN)\r\nregression as well as Support Vector Regression (SVR) to predict the FAN content in beer mash from NIR\r\nspectra. Various pre-processing strategies such as principal component analysis (PCA) and data\r\nstandardization were used to process NIR data that were used to train the machine learning algorithms.\r\nAlgorithm training was conducted with NIR data obtained from 16 beer mashes with varying FAN\r\nconcentrations. The trained models were then validated with 4 beer mashes that were not used for model\r\ntraining. Machine learning algorithms based on linear regression showed the highest prediction accuracy on\r\nunpre-processed data. BRR reached a root mean square error of calibration (RMSEC) of 2.58 mg/L (R2 = 0.96)\r\nand a prediction accuracy (RMSEP) of 2.81 mg/L (R2 = 0.96). The FAN concentration range of the investigated\r\nsamples was between approx. 180 and 220 mg/L. Machine learning based NIR spectra analysis is an alternative\r\nto classical chemical FAN level determination methods and can also be used as inline sensor system." article_type: original author: - first_name: Patrick full_name: Wefing, Patrick id: '68976' last_name: Wefing - first_name: Florian full_name: Conradi, Florian id: '68967' last_name: Conradi - first_name: Johannes full_name: Rämisch, Johannes last_name: Rämisch - first_name: Peter full_name: Neubauer, Peter last_name: Neubauer - first_name: Jan full_name: Schneider, Jan id: '13209' last_name: Schneider orcid: 0000-0001-6401-8873 citation: ama: Wefing P, Conradi F, Rämisch J, Neubauer P, Schneider J. Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms. Brewing science . 2021;74(9/10):107-121. doi:https://doi.org/10.23763/BrSc21-10wefing apa: Wefing, P., Conradi, F., Rämisch, J., Neubauer, P., & Schneider, J. (2021). Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms. Brewing Science , 74(9/10), 107–121. https://doi.org/10.23763/BrSc21-10wefing bjps: Wefing P et al. (2021) Determination of Free Amino Nitrogen in Beer Mash with an Inline NIR Transflectance Probe and Data Evaluation by Machine Learning Algorithms. Brewing science 74, 107–121. chicago: 'Wefing, Patrick, Florian Conradi, Johannes Rämisch, Peter Neubauer, and Jan Schneider. “Determination of Free Amino Nitrogen in Beer Mash with an Inline NIR Transflectance Probe and Data Evaluation by Machine Learning Algorithms.” Brewing Science 74, no. 9/10 (2021): 107–21. https://doi.org/10.23763/BrSc21-10wefing.' chicago-de: 'Wefing, Patrick, Florian Conradi, Johannes Rämisch, Peter Neubauer und Jan Schneider. 2021. Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms. Brewing science 74, Nr. 9/10: 107–121. doi:https://doi.org/10.23763/BrSc21-10wefing, .' din1505-2-1: 'Wefing, Patrick ; Conradi, Florian ; Rämisch, Johannes ; Neubauer, Peter ; Schneider, Jan: Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms. In: Brewing science Bd. 74, Carl (2021), Nr. 9/10, S. 107–121' havard: P. Wefing, F. Conradi, J. Rämisch, P. Neubauer, J. Schneider, Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms, Brewing Science . 74 (2021) 107–121. ieee: 'P. Wefing, F. Conradi, J. Rämisch, P. Neubauer, and J. Schneider, “Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms,” Brewing science , vol. 74, no. 9/10, pp. 107–121, 2021, doi: https://doi.org/10.23763/BrSc21-10wefing.' mla: Wefing, Patrick, et al. “Determination of Free Amino Nitrogen in Beer Mash with an Inline NIR Transflectance Probe and Data Evaluation by Machine Learning Algorithms.” Brewing Science , vol. 74, no. 9/10, 2021, pp. 107–21, https://doi.org/10.23763/BrSc21-10wefing. short: P. Wefing, F. Conradi, J. Rämisch, P. Neubauer, J. Schneider, Brewing Science 74 (2021) 107–121. ufg: 'Wefing, Patrick u. a.: Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms, in: Brewing science 74 (2021), H. 9/10,  S. 107–121.' van: Wefing P, Conradi F, Rämisch J, Neubauer P, Schneider J. Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms. Brewing science . 2021;74(9/10):107–21. date_created: 2021-11-02T10:06:04Z date_updated: 2025-01-30T15:43:53Z department: - _id: DEP1308 - _id: DEP4028 doi: https://doi.org/10.23763/BrSc21-10wefing intvolume: ' 74' issue: 9/10 keyword: - mashing - NIR - machine learning - FAN language: - iso: eng main_file_link: - open_access: '1' url: https://www.researchgate.net/publication/355735532_Determination_of_free_amino_nitrogen_in_beer_mash_with_an_inline_NIR_transflectance_probe_and_data_evaluation_by_machine_learning_algorithms oa: '1' page: 107 - 121 publication: 'Brewing science ' publication_identifier: eissn: - 0723-1520 issn: - 1866-5195 publication_status: published publisher: Carl quality_controlled: '1' status: public title: Determination of free amino nitrogen in beer mash with an inline NIR transflectance probe and data evaluation by machine learning algorithms type: journal_article user_id: '83781' volume: 74 year: '2021' ... --- _id: '7519' abstract: - lang: eng text: Increasing consumer engagement is a cornerstone of companies' social media efforts. However, how social media brand engagement behavior affects brand performance remains largely unexplored. We capture engagement along two dimensions - volume and variety - and measure brand performance using consumers' brand attachment, attitudes, and purchase intentions. Based on the power law of practice and combining survey measures with social media data, our analyses reveal a diminishing marginal utility of engagement volume, as the positive impact of engagement behavior on brand outcomes declines at higher engagement levels. However, the variation across performed activities attenuates these diminishing returns on engagement volume. We find consistent evidence for these effects across two studies with 1347 consumers who interacted with different brands. The results question companies' often unidimensional focus on increasing engagement volume. Instead, our findings suggest that to maximize brand performance on social media platforms, companies should also encourage engagement variety. article_type: original author: - first_name: Tobias full_name: Schäfers, Tobias id: '77945' last_name: Schäfers orcid: 0000-0002-2533-335X - first_name: Tomas full_name: Falk, Tomas last_name: Falk - first_name: Ashish full_name: Kumar, Ashish last_name: Kumar - first_name: Julia full_name: Schamari, Julia last_name: Schamari citation: ama: Schäfers T, Falk T, Kumar A, Schamari J. More of the same? Effects of volume and variety of social media brand engagement behavior. Journal of Business Research. 2021;135:282-294. doi:10.1016/j.jbusres.2021.06.033 apa: Schäfers, T., Falk, T., Kumar, A., & Schamari, J. (2021). More of the same? Effects of volume and variety of social media brand engagement behavior. Journal of Business Research, 135, 282–294. https://doi.org/10.1016/j.jbusres.2021.06.033 bjps: Schäfers T et al. (2021) More of the Same? Effects of Volume and Variety of Social Media Brand Engagement Behavior. Journal of Business Research 135, 282–294. chicago: 'Schäfers, Tobias, Tomas Falk, Ashish Kumar, and Julia Schamari. “More of the Same? Effects of Volume and Variety of Social Media Brand Engagement Behavior.” Journal of Business Research 135 (2021): 282–94. https://doi.org/10.1016/j.jbusres.2021.06.033.' chicago-de: 'Schäfers, Tobias, Tomas Falk, Ashish Kumar und Julia Schamari. 2021. More of the same? Effects of volume and variety of social media brand engagement behavior. Journal of Business Research 135: 282–294. doi:10.1016/j.jbusres.2021.06.033, .' din1505-2-1: 'Schäfers, Tobias ; Falk, Tomas ; Kumar, Ashish ; Schamari, Julia: More of the same? Effects of volume and variety of social media brand engagement behavior. In: Journal of Business Research Bd. 135. Amsterdam [u.a.], Elsevier (2021), S. 282–294' havard: T. Schäfers, T. Falk, A. Kumar, J. Schamari, More of the same? Effects of volume and variety of social media brand engagement behavior, Journal of Business Research. 135 (2021) 282–294. ieee: 'T. Schäfers, T. Falk, A. Kumar, and J. Schamari, “More of the same? Effects of volume and variety of social media brand engagement behavior,” Journal of Business Research, vol. 135, pp. 282–294, 2021, doi: 10.1016/j.jbusres.2021.06.033.' mla: Schäfers, Tobias, et al. “More of the Same? Effects of Volume and Variety of Social Media Brand Engagement Behavior.” Journal of Business Research, vol. 135, 2021, pp. 282–94, https://doi.org/10.1016/j.jbusres.2021.06.033. short: T. Schäfers, T. Falk, A. Kumar, J. Schamari, Journal of Business Research 135 (2021) 282–294. ufg: 'Schäfers, Tobias u. a.: More of the same? Effects of volume and variety of social media brand engagement behavior, in: Journal of Business Research 135 (2021),  S. 282–294.' van: Schäfers T, Falk T, Kumar A, Schamari J. More of the same? Effects of volume and variety of social media brand engagement behavior. Journal of Business Research. 2021;135:282–94. date_created: 2022-04-13T10:52:38Z date_updated: 2025-06-26T13:24:36Z department: - _id: DEP1521 doi: 10.1016/j.jbusres.2021.06.033 external_id: isi: - '000683569100021' intvolume: ' 135' isi: '1' keyword: - Social media - Brand engagement - Diminishing marginal utility - Learning curve language: - iso: eng page: 282-294 place: Amsterdam [u.a.] publication: Journal of Business Research publication_identifier: eissn: - 1873-7978 issn: - 0148-2963 publication_status: published publisher: Elsevier quality_controlled: '1' status: public title: More of the same? Effects of volume and variety of social media brand engagement behavior type: scientific_journal_article user_id: '83781' volume: 135 year: '2021' ... --- _id: '11803' abstract: - lang: eng text: Sub-optimal control policies in intersection traffic signal controllers (TSC) contribute to congestion and lead to negative effects on human health and the environment. Reinforcement learning (RL) for traffic signal control is a promising approach to design better control policies and has attracted considerable research interest in recent years. However, most work done in this area used simplified simulation environments of traffic scenarios to train RL-based TSC. To deploy RL in real-world traffic systems, the gap between simplified simulation environments and real-world applications has to be closed. Therefore, we propose LemgoRL, a benchmark tool to train RL agents as TSC in a realistic simulation environment of Lemgo, a medium-sized town in Germany. In addition to the realistic simulation model, LemgoRL encompasses a traffic signal logic unit that ensures compliance with all regulatory and safety requirements. LemgoRL offers the same interface as the well-known OpenAI gym toolkit to enable easy deployment in existing research work. To demonstrate the functionality and applicability of LemgoRL, we train a state-of-the-art Deep RL algorithm on a CPU cluster utilizing a framework for distributed and parallel RL and compare its performance with other methods. Our benchmark tool drives the development of RL algorithms towards real-world applications. author: - first_name: Arthur full_name: Müller, Arthur last_name: Müller - first_name: Vishal full_name: Rangras, Vishal id: '76044' last_name: Rangras - first_name: Georg full_name: Schnittker, Georg last_name: Schnittker - first_name: Michael full_name: Waldmann, Michael last_name: Waldmann - first_name: Maxim full_name: Friesen, Maxim id: '61517' last_name: Friesen - first_name: Tobias full_name: Ferfers, Tobias last_name: Ferfers - first_name: Lukas full_name: Schreckenberg, Lukas last_name: Schreckenberg - first_name: Florian full_name: Hufen, Florian last_name: Hufen - first_name: Jürgen full_name: Jasperneite, Jürgen id: '1899' last_name: Jasperneite - first_name: Marco full_name: Wiering, Marco last_name: Wiering citation: ama: Müller A, Rangras V, Schnittker G, et al. Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control. (Wani MA, IEEE ICMLA, Institute of Electrical and Electronics Engineers, eds.). IEEE; 2021. doi:10.1109/ICMLA52953.2021.00085 apa: Müller, A., Rangras, V., Schnittker, G., Waldmann, M., Friesen, M., Ferfers, T., Schreckenberg, L., Hufen, F., Jasperneite, J., & Wiering, M. (2021). Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control. In M. A. Wani, IEEE ICMLA, & Institute of Electrical and Electronics Engineers (Eds.), 20th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE. https://doi.org/10.1109/ICMLA52953.2021.00085 bjps: 'Müller A et al. (2021) Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control, Wani MA, IEEE ICMLA, and Institute of Electrical and Electronics Engineers (eds). Piscataway, NJ: IEEE.' chicago: 'Müller, Arthur, Vishal Rangras, Georg Schnittker, Michael Waldmann, Maxim Friesen, Tobias Ferfers, Lukas Schreckenberg, Florian Hufen, Jürgen Jasperneite, and Marco Wiering. Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control. Edited by M. Arif Wani, IEEE ICMLA, and Institute of Electrical and Electronics Engineers. 20th IEEE International Conference on Machine Learning and Applications (ICMLA). Piscataway, NJ: IEEE, 2021. https://doi.org/10.1109/ICMLA52953.2021.00085.' chicago-de: 'Müller, Arthur, Vishal Rangras, Georg Schnittker, Michael Waldmann, Maxim Friesen, Tobias Ferfers, Lukas Schreckenberg, Florian Hufen, Jürgen Jasperneite und Marco Wiering. 2021. Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control. Hg. von M. Arif Wani, IEEE ICMLA, und Institute of Electrical and Electronics Engineers. 20th IEEE International Conference on Machine Learning and Applications (ICMLA). Piscataway, NJ: IEEE. doi:10.1109/ICMLA52953.2021.00085, .' din1505-2-1: 'Müller, Arthur ; Rangras, Vishal ; Schnittker, Georg ; Waldmann, Michael ; Friesen, Maxim ; Ferfers, Tobias ; Schreckenberg, Lukas ; Hufen, Florian ; u. a. ; Wani, M. A. ; IEEE ICMLA ; Institute of Electrical and Electronics Engineers (Hrsg.): Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control. Piscataway, NJ : IEEE, 2021' havard: A. Müller, V. Rangras, G. Schnittker, M. Waldmann, M. Friesen, T. Ferfers, L. Schreckenberg, F. Hufen, J. Jasperneite, M. Wiering, Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control, IEEE, Piscataway, NJ, 2021. ieee: 'A. Müller et al., Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control. Piscataway, NJ: IEEE, 2021. doi: 10.1109/ICMLA52953.2021.00085.' mla: Müller, Arthur, et al. “Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control.” 20th IEEE International Conference on Machine Learning and Applications (ICMLA), edited by M. Arif Wani et al., IEEE, 2021, https://doi.org/10.1109/ICMLA52953.2021.00085. short: A. Müller, V. Rangras, G. Schnittker, M. Waldmann, M. Friesen, T. Ferfers, L. Schreckenberg, F. Hufen, J. Jasperneite, M. Wiering, Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control, IEEE, Piscataway, NJ, 2021. ufg: 'Müller, Arthur u. a.: Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control, hg. von Wani, M. Arif/ IEEE ICMLA, Institute of Electrical and Electronics Engineers, Piscataway, NJ 2021.' van: 'Müller A, Rangras V, Schnittker G, Waldmann M, Friesen M, Ferfers T, et al. Towards Real-World Deployment of Reinforcement Learning for Traffic  Signal Control. Wani MA, IEEE ICMLA, Institute of Electrical and Electronics Engineers, editors. 20th IEEE International Conference on Machine Learning and Applications (ICMLA). Piscataway, NJ: IEEE; 2021.' conference: end_date: 2021-12-16 location: 'Pasadena, CA, USA ' name: 20th IEEE International Conference on Machine Learning and Applications (ICMLA) start_date: 2021-12-13 corporate_editor: - ' IEEE ICMLA' - ' Institute of Electrical and Electronics Engineers' date_created: 2024-07-30T05:54:40Z date_updated: 2024-07-30T07:45:47Z department: - _id: DEP5000 - _id: DEP5019 - _id: DEP5020 - _id: DEP6020 doi: 10.1109/ICMLA52953.2021.00085 editor: - first_name: M. Arif full_name: Wani, M. Arif last_name: Wani external_id: arxiv: - arXiv:2103.16223 keyword: - deep reinforcement learning - traffic signal control - intelligent transportation system - traffic simulation language: - iso: eng place: Piscataway, NJ publication: 20th IEEE International Conference on Machine Learning and Applications (ICMLA) publication_identifier: eisbn: - '9781665443371' publication_status: published publisher: IEEE status: public title: Towards Real-World Deployment of Reinforcement Learning for Traffic Signal Control type: conference_editor_article user_id: '83781' year: '2021' ... --- _id: '12800' abstract: - lang: eng text: his paper presents the cognitive module of the Cognitive Architecture for Artificial Intelligence (CAAI) in cyber-physical production systems (CPPS). The goal of this architecture is to reduce the implementation effort of artificial intelligence (AI) algorithms in CPPS. Declarative user goals and the provided algorithm-knowledge base allow the dynamic pipeline orchestration and configuration. A big data platform (BDP) instantiates the pipelines and monitors the CPPS performance for further evaluation through the cognitive module. Thus, the cognitive module is able to select feasible and robust configurations for process pipelines in varying use cases. Furthermore, it automatically adapts the models and algorithms based on model quality and resource consumption. The cognitive module also instantiates additional pipelines to evaluate algorithms from different classes on test functions. CAAI relies on well-defined interfaces to enable the integration of additional modules and reduce implementation effort. Finally, an implementation based on Docker, Kubernetes, and Kafka for the virtualization and orchestration of the individual modules and as messaging technology for module communication is used to evaluate a real-world use case. author: - first_name: Jan full_name: Strohschein, Jan last_name: Strohschein - first_name: Andreas full_name: Fischbach, Andreas last_name: Fischbach - first_name: Andreas full_name: Bunte, Andreas id: '58885' last_name: Bunte - first_name: Heide full_name: Faeskorn-Woyke, Heide last_name: Faeskorn-Woyke - first_name: Natalia full_name: Moriz, Natalia id: '44238' last_name: Moriz - first_name: Thomas full_name: Bartz-Beielstein, Thomas last_name: Bartz-Beielstein citation: ama: Strohschein J, Fischbach A, Bunte A, Faeskorn-Woyke H, Moriz N, Bartz-Beielstein T. Cognitive capabilities for the CAAI in cyber-physical production systems. The International Journal of Advanced Manufacturing Technology. 2021;115(11-12):3513-3532. doi:10.1007/s00170-021-07248-3 apa: Strohschein, J., Fischbach, A., Bunte, A., Faeskorn-Woyke, H., Moriz, N., & Bartz-Beielstein, T. (2021). Cognitive capabilities for the CAAI in cyber-physical production systems. The International Journal of Advanced Manufacturing Technology, 115(11–12), 3513–3532. https://doi.org/10.1007/s00170-021-07248-3 bjps: Strohschein J et al. (2021) Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems. The International Journal of Advanced Manufacturing Technology 115, 3513–3532. chicago: 'Strohschein, Jan, Andreas Fischbach, Andreas Bunte, Heide Faeskorn-Woyke, Natalia Moriz, and Thomas Bartz-Beielstein. “Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems.” The International Journal of Advanced Manufacturing Technology 115, no. 11–12 (2021): 3513–32. https://doi.org/10.1007/s00170-021-07248-3.' chicago-de: 'Strohschein, Jan, Andreas Fischbach, Andreas Bunte, Heide Faeskorn-Woyke, Natalia Moriz und Thomas Bartz-Beielstein. 2021. Cognitive capabilities for the CAAI in cyber-physical production systems. The International Journal of Advanced Manufacturing Technology 115, Nr. 11–12: 3513–3532. doi:10.1007/s00170-021-07248-3, .' din1505-2-1: 'Strohschein, Jan ; Fischbach, Andreas ; Bunte, Andreas ; Faeskorn-Woyke, Heide ; Moriz, Natalia ; Bartz-Beielstein, Thomas: Cognitive capabilities for the CAAI in cyber-physical production systems. In: The International Journal of Advanced Manufacturing Technology Bd. 115. London [u.a.], Springer (2021), Nr. 11–12, S. 3513–3532' havard: J. Strohschein, A. Fischbach, A. Bunte, H. Faeskorn-Woyke, N. Moriz, T. Bartz-Beielstein, Cognitive capabilities for the CAAI in cyber-physical production systems, The International Journal of Advanced Manufacturing Technology. 115 (2021) 3513–3532. ieee: 'J. Strohschein, A. Fischbach, A. Bunte, H. Faeskorn-Woyke, N. Moriz, and T. Bartz-Beielstein, “Cognitive capabilities for the CAAI in cyber-physical production systems,” The International Journal of Advanced Manufacturing Technology, vol. 115, no. 11–12, pp. 3513–3532, 2021, doi: 10.1007/s00170-021-07248-3.' mla: Strohschein, Jan, et al. “Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems.” The International Journal of Advanced Manufacturing Technology, vol. 115, no. 11–12, 2021, pp. 3513–32, https://doi.org/10.1007/s00170-021-07248-3. short: J. Strohschein, A. Fischbach, A. Bunte, H. Faeskorn-Woyke, N. Moriz, T. Bartz-Beielstein, The International Journal of Advanced Manufacturing Technology 115 (2021) 3513–3532. ufg: 'Strohschein, Jan u. a.: Cognitive capabilities for the CAAI in cyber-physical production systems, in: The International Journal of Advanced Manufacturing Technology 115 (2021), H. 11–12,  S. 3513–3532.' van: Strohschein J, Fischbach A, Bunte A, Faeskorn-Woyke H, Moriz N, Bartz-Beielstein T. Cognitive capabilities for the CAAI in cyber-physical production systems. The International Journal of Advanced Manufacturing Technology. 2021;115(11–12):3513–32. date_created: 2025-04-15T13:05:17Z date_updated: 2025-06-26T13:39:22Z department: - _id: DEP5023 doi: 10.1007/s00170-021-07248-3 external_id: isi: - '000659025000010' intvolume: ' 115' isi: '1' issue: 11-12 keyword: - Cognition - Industry 40 - Big data platform - Machine learning - CPPS - Optimization - Algorithm selection - Simulation language: - iso: eng page: 3513-3532 place: London [u.a.] publication: The International Journal of Advanced Manufacturing Technology publication_identifier: eissn: - 1433-3015 issn: - 0268-3768 publication_status: published publisher: 'Springer ' status: public title: Cognitive capabilities for the CAAI in cyber-physical production systems type: scientific_journal_article user_id: '83781' volume: 115 year: '2021' ... --- _id: '4097' abstract: - lang: eng text: The capabilities of object detection are well known, but many projects don’t use them, despite potential benefit. Even though the use of object detection algorithms is facilitated through frameworks and publications, a big issue is the creation of the necessary training data. To tackle this issue, this work shows the design and evaluation of a prototype, which allows users to create synthetic datasets for object detection in images. The prototype is evaluated using YOLOv3 as the underlying detector and shows that the generated datasets are equally good in quality as manually created data. This encourages a wide adoption of object detection algorithms in different areas, since image creation and labeling is often the most time consuming step. author: - first_name: Andreas full_name: Besginow, Andreas id: '61743' last_name: Besginow - first_name: Sebastian full_name: Büttner, Sebastian id: '61868' last_name: Büttner - first_name: Carsten full_name: Röcker, Carsten id: '61525' last_name: Röcker citation: ama: 'Besginow A, Büttner S, Röcker C. Making Object Detection Available to Everyone - A Hardware Prototype for Semi-automatic Synthetic Data Generation. In: 22nd International Conference on Human-Computer Interaction. Vol 12203. Lecture Notes in Computer Science . Springer; 2020:178-192. doi:https://doi.org/10.1007/978-3-030-50344-4_14' apa: Besginow, A., Büttner, S., & Röcker, C. (2020). Making Object Detection Available to Everyone - A Hardware Prototype for Semi-automatic Synthetic Data Generation. 22nd International Conference on Human-Computer Interaction, 12203, 178–192. https://doi.org/10.1007/978-3-030-50344-4_14 bjps: 'Besginow A, Büttner S and Röcker C (2020) Making Object Detection Available to Everyone - A Hardware Prototype for Semi-Automatic Synthetic Data Generation. 22nd International Conference on Human-Computer Interaction, vol. 12203. Berlin: Springer, pp. 178–192.' chicago: 'Besginow, Andreas, Sebastian Büttner, and Carsten Röcker. “Making Object Detection Available to Everyone - A Hardware Prototype for Semi-Automatic Synthetic Data Generation.” In 22nd International Conference on Human-Computer Interaction, 12203:178–92. Lecture Notes in Computer Science . Berlin: Springer, 2020. https://doi.org/10.1007/978-3-030-50344-4_14.' chicago-de: 'Besginow, Andreas, Sebastian Büttner und Carsten Röcker. 2020. Making Object Detection Available to Everyone - A Hardware Prototype for Semi-automatic Synthetic Data Generation. In: 22nd International Conference on Human-Computer Interaction, 12203:178–192. Lecture Notes in Computer Science . Berlin: Springer. doi:https://doi.org/10.1007/978-3-030-50344-4_14, .' din1505-2-1: 'Besginow, Andreas ; Büttner, Sebastian ; Röcker, Carsten: Making Object Detection Available to Everyone - A Hardware Prototype for Semi-automatic Synthetic Data Generation. In: 22nd International Conference on Human-Computer Interaction, Lecture Notes in Computer Science . Bd. 12203. Berlin : Springer, 2020, S. 178–192' havard: 'A. Besginow, S. Büttner, C. Röcker, Making Object Detection Available to Everyone - A Hardware Prototype for Semi-automatic Synthetic Data Generation, in: 22nd International Conference on Human-Computer Interaction, Springer, Berlin, 2020: pp. 178–192.' ieee: 'A. Besginow, S. Büttner, and C. Röcker, “Making Object Detection Available to Everyone - A Hardware Prototype for Semi-automatic Synthetic Data Generation,” in 22nd International Conference on Human-Computer Interaction, Copenhagen, Denmark, 2020, vol. 12203, pp. 178–192. doi: https://doi.org/10.1007/978-3-030-50344-4_14.' mla: Besginow, Andreas, et al. “Making Object Detection Available to Everyone - A Hardware Prototype for Semi-Automatic Synthetic Data Generation.” 22nd International Conference on Human-Computer Interaction, vol. 12203, Springer, 2020, pp. 178–92, https://doi.org/10.1007/978-3-030-50344-4_14. short: 'A. Besginow, S. Büttner, C. Röcker, in: 22nd International Conference on Human-Computer Interaction, Springer, Berlin, 2020, pp. 178–192.' ufg: 'Besginow, Andreas/Büttner, Sebastian/Röcker, Carsten: Making Object Detection Available to Everyone - A Hardware Prototype for Semi-automatic Synthetic Data Generation, in: o. Hg.: 22nd International Conference on Human-Computer Interaction, Bd. 12203, Berlin 2020 (Lecture Notes in Computer Science ),  S. 178–192.' van: 'Besginow A, Büttner S, Röcker C. Making Object Detection Available to Everyone - A Hardware Prototype for Semi-automatic Synthetic Data Generation. In: 22nd International Conference on Human-Computer Interaction. Berlin: Springer; 2020. p. 178–92. (Lecture Notes in Computer Science ; vol. 12203).' conference: end_date: 2020-07-24 location: Copenhagen, Denmark name: 22nd International Conference on Human-Computer Interaction start_date: 2020-07-19 date_created: 2020-11-26T14:10:04Z date_updated: 2025-06-26T13:28:35Z department: - _id: DEP5023 doi: https://doi.org/10.1007/978-3-030-50344-4_14 intvolume: ' 12203' keyword: - Object detection - Synthetic datasets - Machine learning - Deep learning language: - iso: eng main_file_link: - open_access: '1' url: https://link.springer.com/chapter/10.1007/978-3-030-50344-4_14 oa: '1' page: 178-192 place: Berlin publication: 22nd International Conference on Human-Computer Interaction publication_identifier: eisbn: - 978-3-030-50344-4 isbn: - 978-3-030-50343-7 publication_status: published publisher: Springer series_title: 'Lecture Notes in Computer Science ' status: public title: Making Object Detection Available to Everyone - A Hardware Prototype for Semi-automatic Synthetic Data Generation type: conference user_id: '83781' volume: 12203 year: '2020' ... --- _id: '4100' author: - first_name: Tobias full_name: Schmohl, Tobias id: '71782' last_name: Schmohl orcid: https://orcid.org/0000-0002-7043-5582 - first_name: Susanne full_name: Schwickert, Susanne id: '27269' last_name: Schwickert - first_name: Oliver full_name: Glahn, Oliver id: '76018' last_name: Glahn citation: ama: 'Schmohl T, Schwickert S, Glahn O. Conceptual Design of an AI-Based Learning Assistant . Bologna: Libreriauniversitaria.it; 2020:309-313. doi:10.26352/E618_2384-9509' apa: 'Schmohl, T., Schwickert, S., & Glahn, O. (2020). Conceptual Design of an AI-Based Learning Assistant . The Future of Education (pp. 309–313). Bologna: Libreriauniversitaria.it. https://doi.org/10.26352/E618_2384-9509' bjps: 'Schmohl T, Schwickert S and Glahn O (2020) Conceptual Design of an AI-Based Learning Assistant . Bologna: Libreriauniversitaria.it.' chicago: 'Schmohl, Tobias, Susanne Schwickert, and Oliver Glahn. Conceptual Design of an AI-Based Learning Assistant . The Future of Education. Bologna: Libreriauniversitaria.it, 2020. https://doi.org/10.26352/E618_2384-9509.' chicago-de: 'Schmohl, Tobias, Susanne Schwickert und Oliver Glahn. 2020. Conceptual Design of an AI-Based Learning Assistant . The Future of Education. Bologna: Libreriauniversitaria.it. doi:10.26352/E618_2384-9509, .' din1505-2-1: 'Schmohl, Tobias ; Schwickert, Susanne ; Glahn, Oliver: Conceptual Design of an AI-Based Learning Assistant . Bologna : Libreriauniversitaria.it, 2020' havard: T. Schmohl, S. Schwickert, O. Glahn, Conceptual Design of an AI-Based Learning Assistant , Libreriauniversitaria.it, Bologna, 2020. ieee: 'T. Schmohl, S. Schwickert, and O. Glahn, Conceptual Design of an AI-Based Learning Assistant . Bologna: Libreriauniversitaria.it, 2020, pp. 309–313.' mla: Schmohl, Tobias, et al. “Conceptual Design of an AI-Based Learning Assistant .” The Future of Education, Libreriauniversitaria.it, 2020, pp. 309–13, doi:10.26352/E618_2384-9509. short: T. Schmohl, S. Schwickert, O. Glahn, Conceptual Design of an AI-Based Learning Assistant , Libreriauniversitaria.it, Bologna, 2020. ufg: 'Schmohl, Tobias et. al. (2020): Conceptual Design of an AI-Based Learning Assistant , Bologna.' van: 'Schmohl T, Schwickert S, Glahn O. Conceptual Design of an AI-Based Learning Assistant . The Future of Education. Bologna: Libreriauniversitaria.it; 2020.' conference: end_date: 2020-07-19 location: Florenz name: ' 10 th International Conference The Future of Education ' start_date: 2020-07-18 date_created: 2020-11-27T08:28:18Z date_updated: 2023-03-15T13:49:50Z department: - _id: DEP1022 - _id: DEP2000 doi: 10.26352/E618_2384-9509 keyword: - Artificial Intelligence - intelligent tutoring system - reflection - project-based learning - online-learning - interactive video language: - iso: eng main_file_link: - open_access: '1' url: https://www.academia.edu/43653971/The_Future_of_Education_Conference_Proceedings_2020 oa: '1' page: 309-313 place: Bologna publication: The Future of Education publication_identifier: eisbn: - 978-88-85813-87-8 publication_status: published publisher: Libreriauniversitaria.it quality_controlled: '1' status: public title: 'Conceptual Design of an AI-Based Learning Assistant ' type: conference_editor_article user_id: '79260' year: 2020 ... --- _id: '12807' abstract: - lang: eng text: Writing chorales in the style of Bach has been a music theory exercise for generations of music students. As such it is not surprising that automatic Bach chorale harmonization has been a topic in music technology for decades. We suggest several improvements to current neural network solutions based on musicological insights into human choral composition practices. Evaluations with expert listeners show that the generated chorales closely resemble Bach's harmonization style. author: - first_name: Alexander full_name: Leemhuis, Alexander last_name: Leemhuis - first_name: Simon full_name: Waloschek, Simon last_name: Waloschek - first_name: Aristotelis full_name: Hadjakos, Aristotelis id: '58704' last_name: Hadjakos citation: ama: Leemhuis A, Waloschek S, Hadjakos A. Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization. Vol 1168. (Cellier P, Driessens K, eds.). Springer International Publishing; 2020:462-469. doi:10.1007/978-3-030-43887-6_39 apa: 'Leemhuis, A., Waloschek, S., & Hadjakos, A. (2020). Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization. In P. Cellier & K. Driessens (Eds.), Machine Learning and Knowledge Discovery in Databases : International Workshops of ECML PKDD 2019 (Vol. 1168, pp. 462–469). Springer International Publishing. https://doi.org/10.1007/978-3-030-43887-6_39' bjps: 'Leemhuis A, Waloschek S and Hadjakos A (2020) Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization, Cellier P and Driessens K (eds). Cham: Springer International Publishing.' chicago: 'Leemhuis, Alexander, Simon Waloschek, and Aristotelis Hadjakos. Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization. Edited by Peggy Cellier and Kurt Driessens. Machine Learning and Knowledge Discovery in Databases : International Workshops of ECML PKDD 2019. Vol. 1168. Communications in Computer and Information Science . Cham: Springer International Publishing, 2020. https://doi.org/10.1007/978-3-030-43887-6_39.' chicago-de: 'Leemhuis, Alexander, Simon Waloschek und Aristotelis Hadjakos. 2020. Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization. Hg. von Peggy Cellier und Kurt Driessens. Machine Learning and Knowledge Discovery in Databases : International Workshops of ECML PKDD 2019. Bd. 1168. Communications in Computer and Information Science . Cham: Springer International Publishing. doi:10.1007/978-3-030-43887-6_39, .' din1505-2-1: 'Leemhuis, Alexander ; Waloschek, Simon ; Hadjakos, Aristotelis ; Cellier, P. ; Driessens, K. (Hrsg.): Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization, Communications in Computer and Information Science . Bd. 1168. Cham : Springer International Publishing, 2020' havard: A. Leemhuis, S. Waloschek, A. Hadjakos, Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization, Springer International Publishing, Cham, 2020. ieee: 'A. Leemhuis, S. Waloschek, and A. Hadjakos, Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization, vol. 1168. Cham: Springer International Publishing, 2020, pp. 462–469. doi: 10.1007/978-3-030-43887-6_39.' mla: 'Leemhuis, Alexander, et al. “Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization.” Machine Learning and Knowledge Discovery in Databases : International Workshops of ECML PKDD 2019, edited by Peggy Cellier and Kurt Driessens, vol. 1168, Springer International Publishing, 2020, pp. 462–69, https://doi.org/10.1007/978-3-030-43887-6_39.' short: A. Leemhuis, S. Waloschek, A. Hadjakos, Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization, Springer International Publishing, Cham, 2020. ufg: 'Leemhuis, Alexander/Waloschek, Simon/Hadjakos, Aristotelis: Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization, Bd. 1168, hg. von Cellier, Peggy/Driessens, Kurt, Cham 2020 (Communications in Computer and Information Science ).' van: 'Leemhuis A, Waloschek S, Hadjakos A. Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization. Cellier P, Driessens K, editors. Machine Learning and Knowledge Discovery in Databases : International Workshops of ECML PKDD 2019. Cham: Springer International Publishing; 2020. (Communications in Computer and Information Science ; vol. 1168).' conference: end_date: 2019-09-20 location: Würzburg name: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) start_date: 2019-09-16 date_created: 2025-04-16T07:52:39Z date_updated: 2025-06-26T13:36:14Z department: - _id: DEP2000 doi: 10.1007/978-3-030-43887-6_39 editor: - first_name: Peggy full_name: Cellier, Peggy last_name: Cellier - first_name: Kurt full_name: Driessens, Kurt last_name: Driessens intvolume: ' 1168' keyword: - Bach chorale harmonization - Deep learning - Beam search language: - iso: eng page: 462–469 place: Cham publication: 'Machine Learning and Knowledge Discovery in Databases : International Workshops of ECML PKDD 2019' publication_identifier: eisbn: - 978-3-030-43887-6 eissn: - 1865-0937 isbn: - 978-3-030-43886-9 issn: - 1865-0929 publication_status: published publisher: Springer International Publishing series_title: 'Communications in Computer and Information Science ' status: public title: Bacher than Bach? On Musicologically Informed AI-Based Bach Chorale Harmonization type: conference_editor_article user_id: '83781' volume: 1168 year: '2020' ... --- _id: '12812' abstract: - lang: eng text: Discerning unexpected from expected data patterns is the key challenge of anomaly detection. Although a multitude of solutions has been applied to this modern Industry 4.0 problem, it remains an open research issue to identify the key characteristics subjacent to an anomaly, sc. generate hypothesis as to why they appear. In recent years, machine learning models have been regarded as universal solution for a wide range of problems. While most of them suffer from non-self-explanatory representations, Gaussian Processes (GPs) deliver interpretable and robust statistical data models, which are able to cope with unreliable, noisy, or partially missing data. Thus, we regard them as a suitable solution for detecting and appropriately representing anomalies and their respective characteristics. In this position paper, we discuss the problem of automatic and interpretable anomaly detection by means of GPs. That is, we elaborate on why GPs are well suited for anomaly detection and what the current challenges are when applying these probabilistic models to large-scale production data. author: - first_name: Fabian full_name: Berns, Fabian last_name: Berns - first_name: Markus full_name: Lange-Hegermann, Markus id: '71761' last_name: Lange-Hegermann - first_name: Christian full_name: Beecks, Christian last_name: Beecks citation: ama: Berns F, Lange-Hegermann M, Beecks C. Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. (Panetto H, Madani K, Smirnov A, eds.). SCITEPRESS - Science and Technology Publications; 2020:87-92. doi:10.5220/0010130300870092 apa: Berns, F., Lange-Hegermann, M., & Beecks, C. (2020). Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. In H. Panetto, K. Madani, & A. Smirnov (Eds.), Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics IN4PL - Volume 1 (pp. 87–92). SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0010130300870092 bjps: Berns F, Lange-Hegermann M and Beecks C (2020) Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0, Panetto H, Madani K and Smirnov A (eds). SCITEPRESS - Science and Technology Publications. chicago: Berns, Fabian, Markus Lange-Hegermann, and Christian Beecks. Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. Edited by H. Panetto, K. Madani, and A. Smirnov. Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics IN4PL - Volume 1. SCITEPRESS - Science and Technology Publications, 2020. https://doi.org/10.5220/0010130300870092. chicago-de: Berns, Fabian, Markus Lange-Hegermann und Christian Beecks. 2020. Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. Hg. von H. Panetto, K. Madani, und A. Smirnov. Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics IN4PL - Volume 1. SCITEPRESS - Science and Technology Publications. doi:10.5220/0010130300870092, . din1505-2-1: 'Berns, Fabian ; Lange-Hegermann, Markus ; Beecks, Christian ; Panetto, H. ; Madani, K. ; Smirnov, A. (Hrsg.): Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0 : SCITEPRESS - Science and Technology Publications, 2020' havard: F. Berns, M. Lange-Hegermann, C. Beecks, Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0, SCITEPRESS - Science and Technology Publications, 2020. ieee: 'F. Berns, M. Lange-Hegermann, and C. Beecks, Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. SCITEPRESS - Science and Technology Publications, 2020, pp. 87–92. doi: 10.5220/0010130300870092.' mla: Berns, Fabian, et al. “Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0.” Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics IN4PL - Volume 1, edited by H. Panetto et al., SCITEPRESS - Science and Technology Publications, 2020, pp. 87–92, https://doi.org/10.5220/0010130300870092. short: F. Berns, M. Lange-Hegermann, C. Beecks, Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0, SCITEPRESS - Science and Technology Publications, 2020. ufg: 'Berns, Fabian/Lange-Hegermann, Markus/Beecks, Christian: Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0, hg. von Panetto, H./Madani, K./Smirnov, A., o. O. 2020.' van: Berns F, Lange-Hegermann M, Beecks C. Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0. Panetto H, Madani K, Smirnov A, editors. Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics IN4PL - Volume 1. SCITEPRESS - Science and Technology Publications; 2020. conference: end_date: 2020-11-04 location: Budapest, HUNGARY name: International Conference on Innovative Intelligent Industrial Production and Logistics (IN4PL) start_date: 2020-11-02 date_created: 2025-04-17T06:20:07Z date_updated: 2025-06-26T13:31:38Z department: - _id: DEP5000 doi: 10.5220/0010130300870092 editor: - first_name: H. full_name: Panetto, H. last_name: Panetto - first_name: K. full_name: Madani, K. last_name: Madani - first_name: A. full_name: Smirnov, A. last_name: Smirnov keyword: - Anomaly Detection - Gaussian Processes - Explainable Machine Learning - Industry 4.0 language: - iso: eng page: 87-92 publication: ' Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics IN4PL - Volume 1' publication_identifier: isbn: - 978-989-758-476-3 publication_status: published publisher: SCITEPRESS - Science and Technology Publications status: public title: Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0 type: conference_editor_article user_id: '83781' year: '2020' ... --- _id: '13641' abstract: - lang: eng text: The neuro-physiological response to stress has far-reaching implications for learning and memory processes. Here, we examined whether and how the stress-induced release of cortisol, following the socially-evaluated cold pressor test, influenced the acquisition of preferences in an evaluative conditioning (EC) procedure. We found that when the stressor preceded the evaluation phase, cortisol responders showed decreased evaluative conditioning effects. By contrast, impairing effects of a stressor-induced cortisol release before encoding were not found. Moreover, explicit memory was not found to be affected by the stressor or its timing. Implications of the timing-dependent effects of stress-induced cortisol release on EC and the relation between stress and associative memory are discussed. author: - first_name: Georg full_name: Halbeisen, Georg id: '85780' last_name: Halbeisen orcid: 0000-0002-9529-2215 - first_name: Benjamin full_name: Buttlar, Benjamin last_name: Buttlar - first_name: Siri-Maria full_name: Kamp, Siri-Maria last_name: Kamp - first_name: Eva full_name: Walther, Eva last_name: Walther citation: ama: Halbeisen G, Buttlar B, Kamp SM, Walther E. The timing-dependent effects of stress-induced cortisol release on evaluative conditioning. International Journal of Psychophysiology. 2020;152:44-52. doi:10.1016/j.ijpsycho.2020.04.007 apa: Halbeisen, G., Buttlar, B., Kamp, S.-M., & Walther, E. (2020). The timing-dependent effects of stress-induced cortisol release on evaluative conditioning. International Journal of Psychophysiology, 152, 44–52. https://doi.org/10.1016/j.ijpsycho.2020.04.007 bjps: Halbeisen G et al. (2020) The Timing-Dependent Effects of Stress-Induced Cortisol Release on Evaluative Conditioning. International Journal of Psychophysiology 152, 44–52. chicago: 'Halbeisen, Georg, Benjamin Buttlar, Siri-Maria Kamp, and Eva Walther. “The Timing-Dependent Effects of Stress-Induced Cortisol Release on Evaluative Conditioning.” International Journal of Psychophysiology 152 (2020): 44–52. https://doi.org/10.1016/j.ijpsycho.2020.04.007.' chicago-de: 'Halbeisen, Georg, Benjamin Buttlar, Siri-Maria Kamp und Eva Walther. 2020. The timing-dependent effects of stress-induced cortisol release on evaluative conditioning. International Journal of Psychophysiology 152: 44–52. doi:10.1016/j.ijpsycho.2020.04.007, .' din1505-2-1: 'Halbeisen, Georg ; Buttlar, Benjamin ; Kamp, Siri-Maria ; Walther, Eva: The timing-dependent effects of stress-induced cortisol release on evaluative conditioning. In: International Journal of Psychophysiology Bd. 152, Elsevier BV (2020), S. 44–52' havard: G. Halbeisen, B. Buttlar, S.-M. Kamp, E. Walther, The timing-dependent effects of stress-induced cortisol release on evaluative conditioning, International Journal of Psychophysiology. 152 (2020) 44–52. ieee: 'G. Halbeisen, B. Buttlar, S.-M. Kamp, and E. Walther, “The timing-dependent effects of stress-induced cortisol release on evaluative conditioning,” International Journal of Psychophysiology, vol. 152, pp. 44–52, 2020, doi: 10.1016/j.ijpsycho.2020.04.007.' mla: Halbeisen, Georg, et al. “The Timing-Dependent Effects of Stress-Induced Cortisol Release on Evaluative Conditioning.” International Journal of Psychophysiology, vol. 152, 2020, pp. 44–52, https://doi.org/10.1016/j.ijpsycho.2020.04.007. short: G. Halbeisen, B. Buttlar, S.-M. Kamp, E. Walther, International Journal of Psychophysiology 152 (2020) 44–52. ufg: 'Halbeisen, Georg u. a.: The timing-dependent effects of stress-induced cortisol release on evaluative conditioning, in: International Journal of Psychophysiology 152 (2020),  S. 44–52.' van: Halbeisen G, Buttlar B, Kamp SM, Walther E. The timing-dependent effects of stress-induced cortisol release on evaluative conditioning. International Journal of Psychophysiology. 2020;152:44–52. date_created: 2026-03-27T10:16:23Z date_updated: 2026-04-08T13:56:40Z department: - _id: DEP1500 doi: 10.1016/j.ijpsycho.2020.04.007 extern: '1' external_id: isi: - '000534573000005' pmid: - '32302644' intvolume: ' 152' isi: '1' keyword: - Affective learning - Socially-evaluated cold pressor test - Free salivary cortisol - Hypothalamus-pituitary-adrenal axis - Evaluative conditioning language: - iso: eng page: 44-52 pmid: '1' publication: International Journal of Psychophysiology publication_identifier: eissn: - 1872-7697 issn: - 0167-8760 publication_status: published publisher: Elsevier BV quality_controlled: '1' status: public title: The timing-dependent effects of stress-induced cortisol release on evaluative conditioning type: scientific_journal_article user_id: '83781' volume: 152 year: '2020' ... --- _id: '6850' abstract: - lang: ger text: 'Dieser Beitrag betrachtet die Konzeption und den Einsatz von eTutorien im Rahmen der Hochschullehre. Dabei wird deutlich, dass eTutorien eine E-Learning-Maßnahme darstellen, die in einem bestimmten Kontext eingesetzt werden kann. Dozenten von digitalen Tutorien müssen sich dabei aber neuen Herausforderungen stellen. Das Fehlen von visueller oder akustischer Rückmeldung der Zuhörerschaft ist gewöhnungsbedürftig und muss über ein gut ausgewogenes akustisches Format mit visuellen Elementen kompensiert werden. eTutorien stellen damit eine sinnvolle Ergänzung des klassischen Tutoriums dar. Der Bedarf von nicht-digitalen Ergänzungsveranstaltungen wie z. B. Übungsgruppen und Präsenztutorien ist aber weiterhin gegeben. ' author: - first_name: Korbinian full_name: von Blanckenburg, Korbinian id: '58841' last_name: von Blanckenburg - first_name: Eike full_name: Knost, Eike last_name: Knost citation: ama: 'von Blanckenburg K, Knost E. Einsatz von eTutorien als komplementäre Lehr- und Lernform. In: Schmohl T, Schäffer D, eds. Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen. Vol 2. 2. Auflage. TeachingXchange. Bielefeld: wbv ; 2019:41-46. doi: 10.25656/01:18561' apa: 'von Blanckenburg, K., & Knost, E. (2019). Einsatz von eTutorien als komplementäre Lehr- und Lernform. In T. Schmohl & D. Schäffer (Eds.), Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen (2. Auflage, Vol. 2, pp. 41–46). Bielefeld: wbv . https://doi.org/ 10.25656/01:18561' bjps: 'von Blanckenburg K and Knost E (2019) Einsatz von eTutorien als komplementäre Lehr- und Lernform. In Schmohl T and Schäffer D (eds), Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen, 2. Auflage., vol. 2. Bielefeld: wbv , pp. 41–46.' chicago: 'Blanckenburg, Korbinian von, and Eike Knost. “Einsatz von eTutorien als komplementäre Lehr- und Lernform.” In Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen, edited by Tobias Schmohl and Dennis Schäffer, 2. Auflage., 2:41–46. TeachingXchange. Bielefeld: wbv , 2019. https://doi.org/ 10.25656/01:18561.' chicago-de: 'von Blanckenburg, Korbinian und Eike Knost. 2019. Einsatz von eTutorien als komplementäre Lehr- und Lernform. In: Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen, hg. von Tobias Schmohl und Dennis Schäffer, 2:41–46. 2. Auflage. TeachingXchange. Bielefeld: wbv . doi: 10.25656/01:18561, .' din1505-2-1: 'von Blanckenburg, Korbinian ; Knost, Eike: Einsatz von eTutorien als komplementäre Lehr- und Lernform. In: Schmohl, T. ; Schäffer, D. (Hrsg.): Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen, TeachingXchange. Bd. 2. 2. Auflage. Bielefeld : wbv , 2019, S. 41–46' havard: 'K. von Blanckenburg, E. Knost, Einsatz von eTutorien als komplementäre Lehr- und Lernform, in: T. Schmohl, D. Schäffer (Eds.), Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen, 2. Auflage, wbv , Bielefeld, 2019: pp. 41–46.' ieee: 'K. von Blanckenburg and E. Knost, “Einsatz von eTutorien als komplementäre Lehr- und Lernform,” in Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen, 2. Auflage., vol. 2, T. Schmohl and D. Schäffer, Eds. Bielefeld: wbv , 2019, pp. 41–46.' mla: von Blanckenburg, Korbinian, and Eike Knost. “Einsatz von eTutorien als komplementäre Lehr- und Lernform.” Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen, edited by Tobias Schmohl and Dennis Schäffer, 2. Auflage, vol. 2, wbv , 2019, pp. 41–46, doi: 10.25656/01:18561. short: 'K. von Blanckenburg, E. Knost, in: T. Schmohl, D. Schäffer (Eds.), Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen, 2. Auflage, wbv , Bielefeld, 2019, pp. 41–46.' ufg: 'von Blanckenburg, Korbinian/Knost, Eike (2019): Einsatz von eTutorien als komplementäre Lehr- und Lernform, in: Tobias Schmohl/Dennis Schäffer (Hgg.): Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen (=TeachingXchange 2), Bielefeld, 2. Auflage, S. 41–46.' van: 'von Blanckenburg K, Knost E. Einsatz von eTutorien als komplementäre Lehr- und Lernform. In: Schmohl T, Schäffer D, editors. Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen. 2. Auflage. Bielefeld: wbv ; 2019. p. 41–6. (TeachingXchange; vol. 2).' date_created: 2021-12-07T13:32:41Z date_updated: 2023-03-15T13:50:08Z department: - _id: DEP1514 doi: ' 10.25656/01:18561' edition: 2. Auflage editor: - first_name: Tobias full_name: Schmohl, Tobias id: '71782' last_name: Schmohl - first_name: Dennis full_name: Schäffer, Dennis id: '58926' last_name: Schäffer intvolume: ' 2' keyword: - E-Learning - Hochschule - Hochschullehre - Virtuelle Hochschule - Visuelles Medium - Lehrveranstaltung - Tutorium - Online-Angebot - Online-Kurs - Virtuelle Lehre - Digitale Medien - Interaktive Medien - Elektronische Medien - Ostwestfalen-Lippe - Deutschland language: - iso: ger page: 41-46 place: Bielefeld publication: Lehrexperimente der Hochschulbildung- Didaktische Innovationen aus den Fachdisziplinen publication_identifier: isbn: - 978-3-7639-6114-6 publication_status: published publisher: 'wbv ' series_title: TeachingXchange status: public title: Einsatz von eTutorien als komplementäre Lehr- und Lernform type: book_chapter user_id: '15514' volume: 2 year: 2019 ... --- _id: '4102' abstract: - lang: eng text: Complexity is a fundamental part of product design and manufacturing today, owing to increased demands for customization and advances in digital design techniques. Assembling and repairing such an enormous variety of components means that workers are cognitively challenged, take longer to search for the relevant information and are prone to making mistakes. Although in recent years deep learning approaches to object recognition have seen rapid advances, the combined potential of deep learning and augmented reality in the industrial domain remains relatively under explored. In this paper we introduce AR-ProMO, a combined hardware/software solution that provides a generalizable assistance system for identifying mistakes during product assembly and repair. author: - first_name: Hitesh full_name: Dhiman, Hitesh id: '71767' last_name: Dhiman - first_name: Sebastian full_name: Büttner, Sebastian id: '61868' last_name: Büttner - first_name: Carsten full_name: Röcker, Carsten id: '61525' last_name: Röcker - first_name: Raphael full_name: Reisch, Raphael last_name: Reisch citation: ama: 'Dhiman H, Büttner S, Röcker C, Reisch R. Handling Work Complexity with AR/Deep Learning. In: Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia. ACM; 2019:518–522. doi:10.1145/3369457.3370919' apa: 'Dhiman, H., Büttner, S., Röcker, C., & Reisch, R. (2019). Handling Work Complexity with AR/Deep Learning. In Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia (pp. 518–522). Perth/Fremantle, WA, Australia: ACM. https://doi.org/10.1145/3369457.3370919' bjps: 'Dhiman H et al. (2019) Handling Work Complexity with AR/Deep Learning. Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia. ACM, pp. 518–522.' chicago: 'Dhiman, Hitesh, Sebastian Büttner, Carsten Röcker, and Raphael Reisch. “Handling Work Complexity with AR/Deep Learning.” In Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia, 518–522. ACM, 2019. https://doi.org/10.1145/3369457.3370919.' chicago-de: 'Dhiman, Hitesh, Sebastian Büttner, Carsten Röcker und Raphael Reisch. 2019. Handling Work Complexity with AR/Deep Learning. In: Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia, 518–522. ACM. doi:10.1145/3369457.3370919, .' din1505-2-1: 'Dhiman, Hitesh ; Büttner, Sebastian ; Röcker, Carsten ; Reisch, Raphael: Handling Work Complexity with AR/Deep Learning. In: Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia : ACM, 2019, S. 518–522' havard: 'H. Dhiman, S. Büttner, C. Röcker, R. Reisch, Handling Work Complexity with AR/Deep Learning, in: Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia, ACM, 2019: pp. 518–522.' ieee: 'H. Dhiman, S. Büttner, C. Röcker, and R. Reisch, “Handling Work Complexity with AR/Deep Learning,” in Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia, Perth/Fremantle, WA, Australia, 2019, pp. 518–522.' mla: 'Dhiman, Hitesh, et al. “Handling Work Complexity with AR/Deep Learning.” Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia, ACM, 2019, pp. 518–522, doi:10.1145/3369457.3370919.' short: 'H. Dhiman, S. Büttner, C. Röcker, R. Reisch, in: Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia, ACM, 2019, pp. 518–522.' ufg: 'Dhiman, Hitesh et. al. (2019): Handling Work Complexity with AR/Deep Learning, in: Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia, S. 518–522.' van: 'Dhiman H, Büttner S, Röcker C, Reisch R. Handling Work Complexity with AR/Deep Learning. In: Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI’19) : 2nd Dec-5th Dec 2019, Perth/Fremantle, WA, Australia. ACM; 2019. p. 518–522.' conference: end_date: 2019-12-05 location: Perth/Fremantle, WA, Australia name: '31st Australian Conference on Human-Computer-Interaction (OzCHI''19) ' start_date: 201912-02 date_created: 2020-11-27T10:22:40Z date_updated: 2023-03-15T13:49:50Z department: - _id: DEP5023 doi: 10.1145/3369457.3370919 keyword: - Augmented Reality - Deep Learning language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1145/3369457.3370919 oa: '1' page: ' 518–522' publication: 'Proceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI''19) : 2nd Dec.-5th Dec. 2019, Perth/Fremantle, WA, Australia' publication_identifier: isbn: - 978-1-4503-7696-9 publication_status: published publisher: ACM status: public title: Handling Work Complexity with AR/Deep Learning type: conference user_id: '15514' year: 2019 ... --- _id: '4312' abstract: - lang: eng text: Computer-aided assistance systems are entering the world of work and production. Such systems utilize augmented- and virtual-reality for operator training and live guidance as well as mobile maintenance and support. This is particularly important in the modern production reality of ever-changing products and `lot size one' customization of production.This paper focuses on the application of machine learning approach to extend the functionality of assistance systems. Machine learning provides tools to analyse large amounts of data and extract meaningful information. The goal here is to recognize the movement of an operator which would enable automatic display of instructions relevant to them.We present the challenges facing machine learning applications in human-centered assistance systems and a framework to assess machine learning approaches feasible for this scenario. The approach is assessed on a historical data set and then deployed in a work station for live testing. The post-hoc, or historical, analysis yields promising results. The ad-hoc, or live, analysis is a complex task and the results are affected by multiple factors, most of which are introduced by the human influence.The contribution of this paper is an approach to adapt state- of-the-art machine learning to operator movement recognition with a special focus on approaches to spatial time series data pre-processing. Presented experiment results validate the approach and show that it performs well in a real-world scenario. author: - first_name: Marta full_name: Fullen, Marta last_name: Fullen - first_name: Alexander full_name: Maier, Alexander id: '11158' last_name: Maier - first_name: Arthur full_name: Nazarenko, Arthur last_name: Nazarenko - first_name: Sascha full_name: Jenderny, Sascha last_name: Jenderny - first_name: Carsten full_name: Röcker, Carsten id: '61525' last_name: Röcker citation: ama: 'Fullen M, Maier A, Nazarenko A, Jenderny S, Röcker C. Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition. In: IEEE, ed. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). Piscataway, NJ : IEEE; 2019:296-302. doi:10.1109/INDIN41052.2019.8972122' apa: 'Fullen, M., Maier, A., Nazarenko, A., Jenderny, S., & Röcker, C. (2019). Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition. In IEEE (Ed.), 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) (pp. 296–302). Piscataway, NJ : IEEE. https://doi.org/10.1109/INDIN41052.2019.8972122' bjps: 'Fullen M et al. (2019) Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition. In IEEE (ed.), 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). Piscataway, NJ : IEEE, pp. 296–302.' chicago: 'Fullen, Marta, Alexander Maier, Arthur Nazarenko, Sascha Jenderny, and Carsten Röcker. “Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition.” In 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), edited by IEEE, 296–302. Piscataway, NJ : IEEE, 2019. https://doi.org/10.1109/INDIN41052.2019.8972122.' chicago-de: 'Fullen, Marta, Alexander Maier, Arthur Nazarenko, Sascha Jenderny und Carsten Röcker. 2019. Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition. In: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), hg. von IEEE, 296–302. Piscataway, NJ : IEEE. doi:10.1109/INDIN41052.2019.8972122, .' din1505-2-1: 'Fullen, Marta ; Maier, Alexander ; Nazarenko, Arthur ; Jenderny, Sascha ; Röcker, Carsten: Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition. In: IEEE (Hrsg.): 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). Piscataway, NJ  : IEEE, 2019, S. 296–302' havard: 'M. Fullen, A. Maier, A. Nazarenko, S. Jenderny, C. Röcker, Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition, in: IEEE (Ed.), 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), IEEE, Piscataway, NJ , 2019: pp. 296–302.' ieee: 'M. Fullen, A. Maier, A. Nazarenko, S. Jenderny, and C. Röcker, “Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition,” in 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), IEEE, Ed. Piscataway, NJ : IEEE, 2019, pp. 296–302.' mla: 'Fullen, Marta, et al. “Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition.” 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), edited by IEEE, IEEE, 2019, pp. 296–302, doi:10.1109/INDIN41052.2019.8972122.' short: 'M. Fullen, A. Maier, A. Nazarenko, S. Jenderny, C. Röcker, in: IEEE (Ed.), 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), IEEE, Piscataway, NJ , 2019, pp. 296–302.' ufg: 'Fullen, Marta et. al. (2019): Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition, in: IEEE (Hg.): 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), Piscataway, NJ , S. 296–302.' van: 'Fullen M, Maier A, Nazarenko A, Jenderny S, Röcker C. Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition. In: IEEE, editor. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). Piscataway, NJ : IEEE; 2019. p. 296–302.' conference: end_date: 2019-07-25 location: Helsinki, Finland, name: 17th International Conference on Industrial Informatics (INDIN) start_date: 2019-07-22 corporate_editor: - IEEE date_created: 2021-01-06T13:59:10Z date_updated: 2023-03-15T13:49:51Z department: - _id: DEP5023 doi: 10.1109/INDIN41052.2019.8972122 keyword: - augmented reality - computer based training - data handling - industrial training - learning (artificial intelligence) - time series language: - iso: eng page: 296 - 302 place: 'Piscataway, NJ ' publication: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) publication_identifier: isbn: - 978-1-7281-2927-3 issn: - 2378-363X publication_status: published publisher: IEEE status: public title: 'Machine Learning for Assistance Systems: Pattern-Based Approach to Online Step Recognition' type: book_chapter user_id: '15514' year: 2019 ... --- _id: '4327' abstract: - lang: eng text: In ever changing world, the industrial systems become more and more complex. Machine feedback in the form of alarms and notifications, due to its growing volume, becomes overwhelming for the operator. In addition, expectations in relation to system availability are growing as well. Therefore, there exists strong need for new solutions guaranteeing fast troubleshooting of problems that arise during system operation. The approach proposed in this study uses advantages of the Asset Administration Shell, machine learning, and human-machine interaction in order to create the assistance system which holistically addresses the issue of troubleshooting complex industrial systems. author: - first_name: Dorota full_name: Lang, Dorota id: '68941' last_name: Lang - first_name: Paul full_name: Wunderlich, Paul id: '52317' last_name: Wunderlich - first_name: Mario full_name: Heinz, Mario id: '68913' last_name: Heinz - first_name: Lukasz full_name: Wisniewski, Lukasz id: '1710' last_name: Wisniewski - first_name: Jürgen full_name: Jasperneite, Jürgen id: '1899' last_name: Jasperneite - first_name: Oliver full_name: Niggemann, Oliver id: '10876' last_name: Niggemann - first_name: Carsten full_name: Röcker, Carsten id: '61525' last_name: Röcker citation: ama: 'Lang D, Wunderlich P, Heinz M, et al. Assistance System to Support Troubleshooting of Complex Industrial Systems. In: 14th IEEE International Workshop on Factory Communication Systems (WFCS). Piscataway, NJ: IEEE; 2018. doi:10.1109/WFCS.2018.8402380' apa: 'Lang, D., Wunderlich, P., Heinz, M., Wisniewski, L., Jasperneite, J., Niggemann, O., & Röcker, C. (2018). Assistance System to Support Troubleshooting of Complex Industrial Systems. In 14th IEEE International Workshop on Factory Communication Systems (WFCS). Piscataway, NJ: IEEE. https://doi.org/10.1109/WFCS.2018.8402380' bjps: 'Lang D et al. (2018) Assistance System to Support Troubleshooting of Complex Industrial Systems. 14th IEEE International Workshop on Factory Communication Systems (WFCS). Piscataway, NJ: IEEE.' chicago: 'Lang, Dorota, Paul Wunderlich, Mario Heinz, Lukasz Wisniewski, Jürgen Jasperneite, Oliver Niggemann, and Carsten Röcker. “Assistance System to Support Troubleshooting of Complex Industrial Systems.” In 14th IEEE International Workshop on Factory Communication Systems (WFCS). Piscataway, NJ: IEEE, 2018. https://doi.org/10.1109/WFCS.2018.8402380.' chicago-de: 'Lang, Dorota, Paul Wunderlich, Mario Heinz, Lukasz Wisniewski, Jürgen Jasperneite, Oliver Niggemann und Carsten Röcker. 2018. Assistance System to Support Troubleshooting of Complex Industrial Systems. In: 14th IEEE International Workshop on Factory Communication Systems (WFCS). Piscataway, NJ: IEEE. doi:10.1109/WFCS.2018.8402380, .' din1505-2-1: 'Lang, Dorota ; Wunderlich, Paul ; Heinz, Mario ; Wisniewski, Lukasz ; Jasperneite, Jürgen ; Niggemann, Oliver ; Röcker, Carsten: Assistance System to Support Troubleshooting of Complex Industrial Systems. In: 14th IEEE International Workshop on Factory Communication Systems (WFCS). Piscataway, NJ : IEEE, 2018' havard: 'D. Lang, P. Wunderlich, M. Heinz, L. Wisniewski, J. Jasperneite, O. Niggemann, C. Röcker, Assistance System to Support Troubleshooting of Complex Industrial Systems, in: 14th IEEE International Workshop on Factory Communication Systems (WFCS), IEEE, Piscataway, NJ, 2018.' ieee: D. Lang et al., “Assistance System to Support Troubleshooting of Complex Industrial Systems,” in 14th IEEE International Workshop on Factory Communication Systems (WFCS), Imperia, Italy , 2018. mla: Lang, Dorota, et al. “Assistance System to Support Troubleshooting of Complex Industrial Systems.” 14th IEEE International Workshop on Factory Communication Systems (WFCS), IEEE, 2018, doi:10.1109/WFCS.2018.8402380. short: 'D. Lang, P. Wunderlich, M. Heinz, L. Wisniewski, J. Jasperneite, O. Niggemann, C. Röcker, in: 14th IEEE International Workshop on Factory Communication Systems (WFCS), IEEE, Piscataway, NJ, 2018.' ufg: 'Lang, Dorota et. al. (2018): Assistance System to Support Troubleshooting of Complex Industrial Systems, in: 14th IEEE International Workshop on Factory Communication Systems (WFCS), Piscataway, NJ.' van: 'Lang D, Wunderlich P, Heinz M, Wisniewski L, Jasperneite J, Niggemann O, et al. Assistance System to Support Troubleshooting of Complex Industrial Systems. In: 14th IEEE International Workshop on Factory Communication Systems (WFCS). Piscataway, NJ: IEEE; 2018.' conference: end_date: 2018-06-15 location: 'Imperia, Italy ' name: 14th IEEE International Workshop on Factory Communication Systems (WFCS) start_date: 2018-06-13 date_created: 2021-01-08T08:26:30Z date_updated: 2023-03-15T13:49:52Z department: - _id: DEP5023 - _id: DEP5019 doi: 10.1109/WFCS.2018.8402380 keyword: - Maintenance engineering - Adaptation models - Machine learning - Data models - Standards - Software - Bayes methods language: - iso: eng main_file_link: - open_access: '1' oa: '1' place: Piscataway, NJ publication: 14th IEEE International Workshop on Factory Communication Systems (WFCS) publication_identifier: eisbn: - 978-1-5386-1066-4 publication_status: published publisher: IEEE status: public title: Assistance System to Support Troubleshooting of Complex Industrial Systems type: conference user_id: '45673' year: 2018 ... --- _id: '9650' abstract: - lang: eng text: "In Germany, there is much academic discourse on and scientific inquiry into pedagogical issues of science teaching and learning at the school level. Concepts like ‘Bildung’ (inquiry-based self-formation) or ‘Didaktik’ (instruction-based reflections on teaching) are almost directly associated with institutions or actors rooted in pedagogical departments. Unfortunately, those departments rarely focus on issues of science teaching and learning at the University level – and if they do so, they most often try to apply conceptions and models borrowed from upper or post-secondary education. The few research-based institutions that address specific issues of higher education are commonly fitted out so that they are nowhere near the impacts of research institutions covering teaching methodology in primary or secondary education, for example. Yet from an international perspective, the university as an institution does hold a great potential to improve educational practice in a systematic, cross-disciplinary and research-based way. Around the globe, more and more institutions rely on the notion of scholarship in this context: ‘The improvement of learning and teaching is dependent upon the development of scholarship and research in teaching’ (Prosser & Trigwell, 1999, p. 8). If incorporated at the heart of tertiary education, scholarship could contribute to develop new faculty in the German higher-educational sector.\r\n" author: - first_name: Tobias full_name: Schmohl, Tobias id: '71782' last_name: Schmohl orcid: https://orcid.org/0000-0002-7043-5582 citation: ama: Schmohl T. Towards a New Scholarship of German Science Education. 7th ed. (PIXEL, ed.). libreriauniversitaria.it edizioni; 2018. apa: Schmohl, T. (2018). Towards a New Scholarship of German Science Education. In PIXEL (Ed.), International Conference New Perspectives in Science Education (7th ed.). libreriauniversitaria.it edizioni. bjps: 'Schmohl T (2018) Towards a New Scholarship of German Science Education, 7th ed., PIXEL (ed.). Padova: libreriauniversitaria.it edizioni.' chicago: 'Schmohl, Tobias. Towards a New Scholarship of German Science Education. Edited by PIXEL. International Conference New Perspectives in Science Education . 7th ed. Padova: libreriauniversitaria.it edizioni, 2018.' chicago-de: 'Schmohl, Tobias. 2018. Towards a New Scholarship of German Science Education. Hg. von PIXEL. International Conference New Perspectives in Science Education . 7. Aufl. Padova: libreriauniversitaria.it edizioni.' din1505-2-1: 'Schmohl, Tobias ; PIXEL (Hrsg.): Towards a New Scholarship of German Science Education. 7. Aufl. Padova : libreriauniversitaria.it edizioni, 2018' havard: T. Schmohl, Towards a New Scholarship of German Science Education, 7th ed., libreriauniversitaria.it edizioni, Padova, 2018. ieee: 'T. Schmohl, Towards a New Scholarship of German Science Education, 7th ed. Padova: libreriauniversitaria.it edizioni, 2018.' mla: Schmohl, Tobias. “Towards a New Scholarship of German Science Education.” International Conference New Perspectives in Science Education , edited by PIXEL, 7th ed., libreriauniversitaria.it edizioni, 2018. short: T. Schmohl, Towards a New Scholarship of German Science Education, 7th ed., libreriauniversitaria.it edizioni, Padova, 2018. ufg: 'Schmohl, Tobias: Towards a New Scholarship of German Science Education, hg. von PIXEL, Padova 72018.' van: 'Schmohl T. Towards a New Scholarship of German Science Education. 7th ed. PIXEL, editor. International Conference New Perspectives in Science Education . Padova: libreriauniversitaria.it edizioni; 2018.' conference: end_date: 2018-03-23 location: Florence, Italy name: 'New Perspectives in Science Education - 7th Edition ' start_date: 2018-03-22 corporate_editor: - PIXEL date_created: 2023-03-23T09:16:24Z date_updated: 2023-04-05T09:17:06Z department: - _id: DEP2000 edition: '7' keyword: - Scholarship of Teaching and Learning - Scholarship of Academic Development - Higher Education - community building language: - iso: eng main_file_link: - open_access: '1' oa: '1' place: Padova publication: ' International Conference New Perspectives in Science Education ' publication_identifier: eisbn: - 978-88-6292-976-9 publication_status: published publisher: libreriauniversitaria.it edizioni related_material: link: - relation: other url: https://conference.pixel-online.net/library_scheda.php?id_abs=2911 - relation: other url: https://conference.pixel-online.net/files/npse/ed0007/FP/3516-SSE2911-FP-NPSE7.pdf status: public title: Towards a New Scholarship of German Science Education type: conference_editor_article user_id: '45673' year: '2018' ... --- _id: '7592' author: - first_name: Tobias full_name: Schmohl, Tobias id: '71782' last_name: Schmohl orcid: https://orcid.org/0000-0002-7043-5582 citation: ama: 'Schmohl T. The Research—Education Nexus: Basic Premises and Practical Application of the “Scholarship” Movement. Vol 7. Bologna: Libreriauniversitaria.it; 2017:317-321.' apa: 'Schmohl, T. (2017). The research—education nexus: Basic premises and practical application of the “Scholarship” movement. The Future of Education (Vol. 7, pp. 317–321). Bologna: Libreriauniversitaria.it.' bjps: 'Schmohl T (2017) The Research—Education Nexus: Basic Premises and Practical Application of the ‘Scholarship’ Movement. Bologna: Libreriauniversitaria.it.' chicago: 'Schmohl, Tobias. The Research—Education Nexus: Basic Premises and Practical Application of the “Scholarship” Movement. The Future of Education. Vol. 7. Bologna: Libreriauniversitaria.it, 2017.' chicago-de: 'Schmohl, Tobias. 2017. The research—education nexus: Basic premises and practical application of the „Scholarship“ movement. The Future of Education. Bd. 7. Bologna: Libreriauniversitaria.it.' din1505-2-1: 'Schmohl, Tobias: The research—education nexus: Basic premises and practical application of the „Scholarship“ movement. Bd. 7. Bologna : Libreriauniversitaria.it, 2017' havard: 'T. Schmohl, The research—education nexus: Basic premises and practical application of the “Scholarship” movement, Libreriauniversitaria.it, Bologna, 2017.' ieee: 'T. Schmohl, The research—education nexus: Basic premises and practical application of the “Scholarship” movement, vol. 7. Bologna: Libreriauniversitaria.it, 2017, pp. 317–321.' mla: 'Schmohl, Tobias. “The Research—Education Nexus: Basic Premises and Practical Application of the ‘Scholarship’ Movement.” The Future of Education, vol. 7, Libreriauniversitaria.it, 2017, pp. 317–21.' short: 'T. Schmohl, The Research—Education Nexus: Basic Premises and Practical Application of the “Scholarship” Movement, Libreriauniversitaria.it, Bologna, 2017.' ufg: 'Schmohl, Tobias (2017): The research—education nexus: Basic premises and practical application of the „Scholarship“ movement (= 7), Bologna.' van: 'Schmohl T. The research—education nexus: Basic premises and practical application of the “Scholarship” movement. Vol. 7, The Future of Education. Bologna: Libreriauniversitaria.it; 2017.' conference: end_date: 2017-06-09 location: Florenz name: The Future of Education start_date: 2017-06-08 date_created: 2022-04-14T11:05:45Z date_updated: 2023-03-15T13:50:10Z department: - _id: DEP2000 - _id: DEP1200 intvolume: ' 7' keyword: - Scholarship of Academic Development - Scholarship of Teaching and Learning language: - iso: eng main_file_link: - open_access: '1' url: https://conference.pixel-online.net/FOE/files/foe/ed0007/FP/3516-ICL2488-FP-FOE7.pdf oa: '1' page: 317-321 place: Bologna publication: The Future of Education publication_identifier: isbn: - ' ‎ 978-8862928687' publication_status: published publisher: Libreriauniversitaria.it quality_controlled: '1' status: public title: 'The research—education nexus: Basic premises and practical application of the "Scholarship" movement' type: conference_editor_article user_id: '79260' volume: 7 year: 2017 ... --- _id: '4254' abstract: - lang: eng text: The current trend of integrating machines and factories into cyber-physical systems (CPS) creates an enormous complexity for operators of such systems. Especially the search for the root cause of cascading failures becomes highly time-consuming. Within this paper, we address the question on how to help human users to better and faster understand root causes of such situations. We propose a concept of interactive alarm flood reduction and present the implementation of a first vertical prototype for such a system. We consider this prototype as a first artifact to be discussed by the research community and aim towards an incremental further development of the system in order to support humans in complex error situations. author: - first_name: Sebastian full_name: Büttner, Sebastian id: '61868' last_name: Büttner - first_name: Paul full_name: Wunderlich, Paul id: '52317' last_name: Wunderlich - first_name: Mario full_name: Heinz, Mario id: '68913' last_name: Heinz - first_name: Oliver full_name: Niggemann, Oliver id: '10876' last_name: Niggemann - first_name: Carsten full_name: Röcker, Carsten id: '61525' last_name: Röcker citation: ama: 'Büttner S, Wunderlich P, Heinz M, Niggemann O, Röcker C. Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction. In: Holzinger A, ed. Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings. Vol 10410. Lecture Notes in Computer Science . Cham: Springer; 2017:69-82.' apa: 'Büttner, S., Wunderlich, P., Heinz, M., Niggemann, O., & Röcker, C. (2017). Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction. In A. Holzinger (Ed.), Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings (Vol. 10410, pp. 69–82). Cham: Springer.' bjps: 'Büttner S et al. (2017) Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction. In Holzinger A (ed.), Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings, vol. 10410. Cham: Springer, pp. 69–82.' chicago: 'Büttner, Sebastian, Paul Wunderlich, Mario Heinz, Oliver Niggemann, and Carsten Röcker. “Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction.” In Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings, edited by Andreas Holzinger, 10410:69–82. Lecture Notes in Computer Science . Cham: Springer, 2017.' chicago-de: 'Büttner, Sebastian, Paul Wunderlich, Mario Heinz, Oliver Niggemann und Carsten Röcker. 2017. Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction. In: Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings, hg. von Andreas Holzinger, 10410:69–82. Lecture Notes in Computer Science . Cham: Springer.' din1505-2-1: 'Büttner, Sebastian ; Wunderlich, Paul ; Heinz, Mario ; Niggemann, Oliver ; Röcker, Carsten: Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction. In: Holzinger, A. (Hrsg.): Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings, Lecture Notes in Computer Science . Bd. 10410. Cham : Springer, 2017, S. 69–82' havard: 'S. Büttner, P. Wunderlich, M. Heinz, O. Niggemann, C. Röcker, Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction, in: A. Holzinger (Ed.), Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings, Springer, Cham, 2017: pp. 69–82.' ieee: 'S. Büttner, P. Wunderlich, M. Heinz, O. Niggemann, and C. Röcker, “Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction,” in Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings, Reggio, Italy, 2017, vol. 10410, pp. 69–82.' mla: 'Büttner, Sebastian, et al. “Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction.” Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings, edited by Andreas Holzinger, vol. 10410, Springer, 2017, pp. 69–82.' short: 'S. Büttner, P. Wunderlich, M. Heinz, O. Niggemann, C. Röcker, in: A. Holzinger (Ed.), Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings, Springer, Cham, 2017, pp. 69–82.' ufg: 'Büttner, Sebastian et. al. (2017): Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction, in: Andreas Holzinger (Hg.): Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings (=Lecture Notes in Computer Science 10410), Cham, S. 69–82.' van: 'Büttner S, Wunderlich P, Heinz M, Niggemann O, Röcker C. Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction. In: Holzinger A, editor. Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 84, 89, 129 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings. Cham: Springer; 2017. p. 69–82. (Lecture Notes in Computer Science ; vol. 10410).' conference: end_date: 2017-09-01 location: Reggio, Italy name: International Cross-Domain Conference, CD-MAKE 2017 start_date: 2017-08-29 date_created: 2020-12-10T13:40:04Z date_updated: 2023-03-15T13:49:51Z department: - _id: DEP5023 editor: - first_name: Andreas full_name: Holzinger, Andreas last_name: Holzinger intvolume: ' 10410' keyword: - Alarm flood reduction - Machine learning - Assistive system language: - iso: eng main_file_link: - open_access: '1' oa: '1' page: 69-82 place: Cham publication: ' Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings' publication_identifier: eisbn: - '9783319668086 ' isbn: - 978-3-319-66807-9 publication_status: published publisher: Springer series_title: 'Lecture Notes in Computer Science ' status: public title: 'Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction' type: conference user_id: '15514' volume: 10410 year: 2017 ... --- _id: '811' author: - first_name: Freda full_name: Böhl, Freda id: '60139' last_name: Böhl citation: ama: 'Böhl F. eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion. Lemgo: Hochschule Ostwestfalen-Lippe; 2017.' apa: 'Böhl, F. (2017). eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion. Lemgo: Hochschule Ostwestfalen-Lippe.' bjps: 'Böhl F (2017) eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion. Lemgo: Hochschule Ostwestfalen-Lippe.' chicago: 'Böhl, Freda. eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion. Lemgo: Hochschule Ostwestfalen-Lippe, 2017.' chicago-de: 'Böhl, Freda. 2017. eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion. Lemgo: Hochschule Ostwestfalen-Lippe.' din1505-2-1: 'Böhl, Freda: eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion. Lemgo : Hochschule Ostwestfalen-Lippe, 2017' havard: 'F. Böhl, eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion, Hochschule Ostwestfalen-Lippe, Lemgo, 2017.' ieee: 'F. Böhl, eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion. Lemgo: Hochschule Ostwestfalen-Lippe, 2017.' mla: 'Böhl, Freda. eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion. Hochschule Ostwestfalen-Lippe, 2017.' short: 'F. Böhl, eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion, Hochschule Ostwestfalen-Lippe, Lemgo, 2017.' ufg: 'Böhl, Freda (2017): eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion, Lemgo.' van: 'Böhl F. eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion. Lemgo: Hochschule Ostwestfalen-Lippe; 2017. 60 p.' date_created: 2019-04-05T13:36:50Z date_updated: 2023-03-15T13:50:13Z ddc: - '370' department: - _id: DEP2001 file: - access_level: closed content_type: application/pdf creator: 6bl-f5s date_created: 2019-04-05T13:36:10Z date_updated: 2019-04-05T13:36:10Z file_id: '812' file_name: BA_eLearning in der Hochschullehre.pdf file_size: 1626480 relation: main_file file_date_updated: 2019-04-05T13:36:10Z has_accepted_license: '1' keyword: - E-Learning - eLearning language: - iso: ger page: '60' place: Lemgo publication_status: published publisher: Hochschule Ostwestfalen-Lippe status: public supervisor: - first_name: Heizo full_name: Schulze, Heizo id: '29126' last_name: Schulze - first_name: Aristotelis full_name: Had-jakos, Aristotelis last_name: Had-jakos title: 'eLearning in der Hochschullehre: Entwicklung eines Leitfadens für den Studiengang Medienproduktion' type: bachelor_thesis user_id: '45673' year: 2017 ... --- _id: '4298' abstract: - lang: eng text: In this paper, we present the current state-of-the-art of decision making (DM) and machine learning (ML) and bridge the two research domains to create an integrated approach of complex problem solving based on human and computational agents. We present a novel classification of ML, emphasizing the human-in-the-loop in interactive ML (iML) and more specific on collaborative interactive ML (ciML), which we understand as a deep integrated version of iML, where humans and algorithms work hand in hand to solve complex problems. Both humans and computers have specific strengths and weaknesses and integrating humans into machine learning processes might be a very efficient way for tackling problems. This approach bears immense research potential for various domains, e.g., in health informatics or in industrial applications. We outline open questions and name future challenges that have to be addressed by the research community to enable the use of collaborative interactive machine learning for problem solving in a large scale. author: - first_name: Sebastian full_name: Robert, Sebastian last_name: Robert - first_name: Sebastian full_name: Büttner, Sebastian id: '61868' last_name: Büttner - first_name: Carsten full_name: Röcker, Carsten id: '61525' last_name: Röcker - first_name: Andreas full_name: Holzinger, Andreas last_name: Holzinger citation: ama: 'Robert S, Büttner S, Röcker C, Holzinger A. Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In: Holzinger A, ed. Machine Learning for Health Informatics : State-of-the-Art and Future Challenges . Vol 9605. Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence . Cham, CH: Springer; 2016:357-376. doi:10.1007/978-3-319-50478-0_18' apa: 'Robert, S., Büttner, S., Röcker, C., & Holzinger, A. (2016). Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In A. Holzinger (Ed.), Machine Learning for Health Informatics : State-of-the-Art and Future Challenges (Vol. 9605, pp. 357–376). Cham, CH: Springer. https://doi.org/10.1007/978-3-319-50478-0_18' bjps: 'Robert S et al. (2016) Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In Holzinger A (ed.), Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , vol. 9605. Cham, CH: Springer, pp. 357–376.' chicago: 'Robert, Sebastian, Sebastian Büttner, Carsten Röcker, and Andreas Holzinger. “Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning.” In Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , edited by Andreas Holzinger, 9605:357–76. Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence . Cham, CH: Springer, 2016. https://doi.org/10.1007/978-3-319-50478-0_18.' chicago-de: 'Robert, Sebastian, Sebastian Büttner, Carsten Röcker und Andreas Holzinger. 2016. Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In: Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , hg. von Andreas Holzinger, 9605:357–376. Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence . Cham, CH: Springer. doi:10.1007/978-3-319-50478-0_18, .' din1505-2-1: 'Robert, Sebastian ; Büttner, Sebastian ; Röcker, Carsten ; Holzinger, Andreas: Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In: Holzinger, A. (Hrsg.): Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence . Bd. 9605. Cham, CH : Springer, 2016, S. 357–376' havard: 'S. Robert, S. Büttner, C. Röcker, A. Holzinger, Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning, in: A. Holzinger (Ed.), Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , Springer, Cham, CH, 2016: pp. 357–376.' ieee: 'S. Robert, S. Büttner, C. Röcker, and A. Holzinger, “Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning,” in Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , vol. 9605, A. Holzinger, Ed. Cham, CH: Springer, 2016, pp. 357–376.' mla: 'Robert, Sebastian, et al. “Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning.” Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , edited by Andreas Holzinger, vol. 9605, Springer, 2016, pp. 357–76, doi:10.1007/978-3-319-50478-0_18.' short: 'S. Robert, S. Büttner, C. Röcker, A. Holzinger, in: A. Holzinger (Ed.), Machine Learning for Health Informatics : State-of-the-Art and Future Challenges , Springer, Cham, CH, 2016, pp. 357–376.' ufg: 'Robert, Sebastian et. al. (2016): Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning, in: Andreas Holzinger (Hg.): Machine Learning for Health Informatics : State-of-the-Art and Future Challenges (=Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence 9605), Cham, CH, S. 357–376.' van: 'Robert S, Büttner S, Röcker C, Holzinger A. Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning. In: Holzinger A, editor. Machine Learning for Health Informatics : State-of-the-Art and Future Challenges . Cham, CH: Springer; 2016. p. 357–76. (Lecture Notes in Computer Science /  Lecture Notes in Artificial Intelligence ; vol. 9605).' date_created: 2020-12-22T14:11:00Z date_updated: 2023-03-15T13:49:51Z department: - _id: DEP5023 doi: 10.1007/978-3-319-50478-0_18 editor: - first_name: Andreas full_name: Holzinger, Andreas last_name: Holzinger intvolume: ' 9605' keyword: - Decision making - Reasoning - Interactive machine learning - Collaborative interactive machine learning language: - iso: eng page: 357-376 place: Cham, CH publication: 'Machine Learning for Health Informatics : State-of-the-Art and Future Challenges ' publication_identifier: eisbn: - '978-3-319-50478-0 ' isbn: - '978-3-319-50477-3 ' publication_status: published publisher: Springer series_title: 'Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence ' status: public title: 'Reasoning Under Uncertainty: Towards Collaborative Interactive Machine Learning' type: book_chapter user_id: '15514' volume: 9605 year: 2016 ... --- _id: '2167' abstract: - lang: eng text: "Cyber-Physical Production Systems (CPPSs) are in the focus of research, industry and politics: By applying new IT and new computer science solutions, production systems will become more adaptable, more resource ef- ficient and more user friendly. The analysis and diagnosis of such systems is a major part of this trend: Plants should detect automatically wear, faults and suboptimal configurations. This paper reflects the current state-of- the-art in diagnosis against the requirements of CPPSs, identifies three main gaps and gives application scenarios to outline first ideas for potential solutions to close these gaps.\r\n" author: - first_name: Oliver full_name: Niggemann, Oliver id: '10876' last_name: Niggemann - first_name: Volker full_name: Lohweg, Volker id: '1804' last_name: Lohweg orcid: 0000-0002-3325-7887 citation: ama: 'Niggemann O, Lohweg V. On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda. In: Twenty-Ninth Conference on Artificial Intelligence (AAAI-15). Austin, Texas, USA; 2015.' apa: Niggemann, O., & Lohweg, V. (2015). On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda. In Twenty-Ninth Conference on Artificial Intelligence (AAAI-15). Austin, Texas, USA. bjps: Niggemann O and Lohweg V (2015) On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda. Twenty-Ninth Conference on Artificial Intelligence (AAAI-15). Austin, Texas, USA. chicago: Niggemann, Oliver, and Volker Lohweg. “On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda.” In Twenty-Ninth Conference on Artificial Intelligence (AAAI-15). Austin, Texas, USA, 2015. chicago-de: 'Niggemann, Oliver und Volker Lohweg. 2015. On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda. In: Twenty-Ninth Conference on Artificial Intelligence (AAAI-15). Austin, Texas, USA.' din1505-2-1: 'Niggemann, Oliver ; Lohweg, Volker: On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda. In: Twenty-Ninth Conference on Artificial Intelligence (AAAI-15). Austin, Texas, USA, 2015' havard: 'O. Niggemann, V. Lohweg, On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda, in: Twenty-Ninth Conference on Artificial Intelligence (AAAI-15), Austin, Texas, USA, 2015.' ieee: O. Niggemann and V. Lohweg, “On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda,” in Twenty-Ninth Conference on Artificial Intelligence (AAAI-15), 2015. mla: Niggemann, Oliver, and Volker Lohweg. “On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda.” Twenty-Ninth Conference on Artificial Intelligence (AAAI-15), 2015. short: 'O. Niggemann, V. Lohweg, in: Twenty-Ninth Conference on Artificial Intelligence (AAAI-15), Austin, Texas, USA, 2015.' ufg: 'Niggemann, Oliver/Lohweg, Volker (2015): On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda, in: Twenty-Ninth Conference on Artificial Intelligence (AAAI-15), Austin, Texas, USA.' van: 'Niggemann O, Lohweg V. On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda. In: Twenty-Ninth Conference on Artificial Intelligence (AAAI-15). Austin, Texas, USA; 2015.' date_created: 2019-12-04T12:43:12Z date_updated: 2023-03-15T13:49:39Z department: - _id: DEP5023 keyword: - Cyber-Physical Systems - Machine Learning - Diagnosis - Anomaly Detection language: - iso: eng main_file_link: - open_access: '1' url: https://www.aaai.org/ocs/index.php/AAAI/AAAI15/paper/view/9530/9691 oa: '1' place: Austin, Texas, USA publication: Twenty-Ninth Conference on Artificial Intelligence (AAAI-15) status: public title: On the Diagnosis of Cyber-Physical Production Systems - State-of-the-Art and Research Agenda type: conference user_id: '68554' year: 2015 ... --- _id: '4336' abstract: - lang: eng text: "Prolonged life expectancy along with the increasing complexity of medicine and health services raises health costs worldwide dramatically. Whilst the smart health concept has much potential to support the concept of the emerging P4-medicine (preventive, participatory, predictive, and personalized), such high-tech medicine produces large amounts of high-dimensional, weakly-structured data sets and massive amounts of unstructured information. All these technological approaches along with “big data” are turning the medical sciences into a data-intensive science. To keep pace with the growing amounts of complex data, smart hospital approaches are a commandment of the future, necessitating context aware computing along with advanced interaction paradigms in new physical-digital ecosystems.\r\n\r\nThe very successful synergistic combination of methodologies and approaches from Human-Computer Interaction (HCI) and Knowledge Discovery and Data Mining (KDD) offers ideal conditions for the vision to support human intelligence with machine learning.\r\n\r\nThe papers selected for this volume focus on hot topics in smart health; they discuss open problems and future challenges in order to provide a research agenda to stimulate further research and progress." citation: ama: 'Holzinger A, Röcker C, Ziefle M, eds. Smart Health: Open Problems and Future Challenges. Vol 8700. Heidelberg: Springer; 2015. doi:10.1007/978-3-319-16226-3' apa: 'Holzinger, A., Röcker, C., & Ziefle, M. (Eds.). (2015). Smart Health: Open Problems and Future Challenges (Vol. 8700). Heidelberg: Springer. https://doi.org/10.1007/978-3-319-16226-3' bjps: 'Holzinger A, Röcker C and Ziefle M (eds) (2015) Smart Health: Open Problems and Future Challenges. Heidelberg: Springer.' chicago: 'Holzinger, Andreas, Carsten Röcker, and Martina Ziefle, eds. Smart Health: Open Problems and Future Challenges. Vol. 8700. Lecture Notes in Computer Science /  Information Systems and Applications, Incl. Internet/Web, and HCI. Heidelberg: Springer, 2015. https://doi.org/10.1007/978-3-319-16226-3.' chicago-de: 'Holzinger, Andreas, Carsten Röcker und Martina Ziefle, Hrsg. 2015. Smart Health: Open Problems and Future Challenges. Bd. 8700. Lecture Notes in Computer Science /  Information Systems and Applications, incl. Internet/Web, and HCI. Heidelberg: Springer. doi:10.1007/978-3-319-16226-3, .' din1505-2-1: 'Holzinger, A. ; Röcker, C. ; Ziefle, M. (Hrsg.): Smart Health: Open Problems and Future Challenges, Lecture Notes in Computer Science /  Information Systems and Applications, incl. Internet/Web, and HCI. Bd. 8700. Heidelberg : Springer, 2015' havard: 'A. Holzinger, C. Röcker, M. Ziefle, eds., Smart Health: Open Problems and Future Challenges, Springer, Heidelberg, 2015.' ieee: 'A. Holzinger, C. Röcker, and M. Ziefle, Eds., Smart Health: Open Problems and Future Challenges, vol. 8700. Heidelberg: Springer, 2015.' mla: 'Holzinger, Andreas, et al., editors. Smart Health: Open Problems and Future Challenges. Vol. 8700, Springer, 2015, doi:10.1007/978-3-319-16226-3.' short: 'A. Holzinger, C. Röcker, M. Ziefle, eds., Smart Health: Open Problems and Future Challenges, Springer, Heidelberg, 2015.' ufg: 'Holzinger, Andreas et. al. (Hgg.) (2015): Smart Health: Open Problems and Future Challenges (=Lecture Notes in Computer Science /  Information Systems and Applications, incl. Internet/Web, and HCI 8700), Heidelberg.' van: 'Holzinger A, Röcker C, Ziefle M, editors. Smart Health: Open Problems and Future Challenges. Heidelberg: Springer; 2015. 275 p. (Lecture Notes in Computer Science /  Information Systems and Applications, incl. Internet/Web, and HCI; vol. 8700).' date_created: 2021-01-08T12:03:52Z date_updated: 2023-03-15T13:49:52Z department: - _id: DEP5023 doi: 10.1007/978-3-319-16226-3 editor: - first_name: Andreas full_name: Holzinger, Andreas last_name: Holzinger - first_name: Carsten full_name: Röcker, Carsten id: '61525' last_name: Röcker - first_name: Martina full_name: Ziefle, Martina last_name: Ziefle intvolume: ' 8700' keyword: - HCI - ambient assisted living - big data - computational intelligence - context awareness - data centric medicine - decision support - interactive data mining - keyword detection - knoweldge bases - knoweldge discovery - machine learning - medical decision support - medical informatics - natural language processing - pervasive health - smart home - ubiquitous computing - visualization - wearable sensors language: - iso: eng main_file_link: - open_access: '1' url: 'http://www.springerlink.com/content/978-3-319-16226-3 ' oa: '1' page: '275' place: Heidelberg publication_identifier: eisbn: - 978-3-319-16226-3 eissn: - 1611-3349 isbn: - 978-3-319-16225-6 issn: - 0302-9743 publication_status: published publisher: Springer series_title: Lecture Notes in Computer Science / Information Systems and Applications, incl. Internet/Web, and HCI status: public title: 'Smart Health: Open Problems and Future Challenges' type: book_editor user_id: '15514' volume: 8700 year: 2015 ... --- _id: '9856' abstract: - lang: eng text: According to the Bologna Accord in 2006 the study courses for architecture, urban planning and landscape planning at Kassel university were reformed to a bachelor and master education programme. New courses – so called “modules” were found. One of them “Wahrnehmung und Analyse von Räumen” – “landscape perception and analysis” – is an interdisciplinary course teaching and comparing three different perspectives – those of ecology, social science and landscape planning – on landscape. To manage a high number of students the e-learning platform “Moodle” is used. Also giving an introduction into GIS is a major part of the course. This article – after “landscape perception and analysis” started four years ago – gives an overview of the recent and future development of the course from a teachers perspective. - lang: eng text: Im Zuge des Bolognaprozesses wurde 2006 der Studiengang Landschaftsplanung an der Universität Kassel auf das Bachelor- und Mastersystem umgestellt. Eines der neuen „Lehrmodule“ ist „Wahrnehmung und Analyse von Räumen“, das interdis-ziplinär angelegt ist, und den Studierenden eine Einführung in die Erfassung von Landschaften gibt. Drei unterschiedliche Perspektiven auf Landschaft – ökologisch, sozialwissenschaftlich und landschaftsplanerisch – werden gelehrt und gegenübergestellt. Um die große Zahl der Studierenden zu betreuen, wird die E-Learning-Plattform „Moodle“ eingesetzt. Auch die Heranführung an Geographische Informationssysteme ist ein wesentlicher Teil der Ausbildung. Dieser Beitrag stellt nach nun vier Jahren „Wahrnehmung und Analyse von Räumen“ die Entwicklung des Moduls dar, und zeigt die wichtigsten Erkenntnisse aus der Sicht der Lehrenden. alternative_title: - WAHRNEHMUNG UND ANALYSE VON RÄUMEN – EIN INTERDISZIPLINÄRES LEHRMODUL IN DER UNIVERSITÄREN LANDSCHAFTSPLANUNGSAUSBILDUNG author: - first_name: Claas full_name: Leiner, Claas last_name: Leiner - first_name: Boris full_name: Stemmer, Boris id: '64889' last_name: Stemmer citation: ama: Leiner C, Stemmer B. Teaching Landscape Planning - Landscape Perception and Analysis. gisScience. 2011;(4):105-110. apa: Leiner, C., & Stemmer, B. (2011). Teaching Landscape Planning - Landscape Perception and Analysis. Gis.Science, 4, 105–110. bjps: Leiner C and Stemmer B (2011) Teaching Landscape Planning - Landscape Perception and Analysis. gis.Science 105–110. chicago: 'Leiner, Claas, and Boris Stemmer. “Teaching Landscape Planning - Landscape Perception and Analysis.” Gis.Science, no. 4 (2011): 105–10.' chicago-de: 'Leiner, Claas und Boris Stemmer. 2011. Teaching Landscape Planning - Landscape Perception and Analysis. gis.Science, Nr. 4: 105–110.' din1505-2-1: 'Leiner, Claas ; Stemmer, Boris: Teaching Landscape Planning - Landscape Perception and Analysis. In: gis.Science. Berlin, Wichmann (2011), Nr. 4, S. 105–110' havard: C. Leiner, B. Stemmer, Teaching Landscape Planning - Landscape Perception and Analysis, Gis.Science. (2011) 105–110. ieee: C. Leiner and B. Stemmer, “Teaching Landscape Planning - Landscape Perception and Analysis,” gis.Science, no. 4, pp. 105–110, 2011. mla: Leiner, Claas, and Boris Stemmer. “Teaching Landscape Planning - Landscape Perception and Analysis.” Gis.Science, no. 4, 2011, pp. 105–10. short: C. Leiner, B. Stemmer, Gis.Science (2011) 105–110. ufg: 'Leiner, Claas/Stemmer, Boris: Teaching Landscape Planning - Landscape Perception and Analysis, in: gis.Science (2011), H. 4,  S. 105–110.' van: Leiner C, Stemmer B. Teaching Landscape Planning - Landscape Perception and Analysis. gisScience. 2011;(4):105–10. date_created: 2023-04-24T09:11:32Z date_updated: 2023-05-11T14:46:20Z department: - _id: DEP9013 extern: '1' issue: '4' keyword: - Universitarian teaching - GIS - e-learning - bologna process language: - iso: eng main_file_link: - open_access: '1' url: https://gispoint.de/index.php?eID=dumpFile&t=f&f=13220&token=34e95e0810ebc46f00cd15f2b8ccdaa2d92d60f7&download= oa: '1' page: 105–110 place: Berlin publication: gis.Science publication_identifier: eissn: - 2698-4571 issn: - '1869-9391 ' publication_status: published publisher: Wichmann status: public title: Teaching Landscape Planning - Landscape Perception and Analysis type: scientific_journal_article user_id: '15514' year: '2011' ... --- _id: '2087' abstract: - lang: eng text: It is likely in real-world applications that only little data isavailable for training a knowledge-based system. We present a method forautomatically training the knowledge-representing membership functionsof a Fuzzy-Pattern-Classification system that works also when only littledata is available and the universal set is described insufficiently. Actually,this paper presents how the Modified-Fuzzy-Pattern-Classifier’s member-ship functions are trained using probability distribution functions. author: - first_name: Uwe full_name: Mönks, Uwe id: '1825' last_name: Mönks - first_name: Volker full_name: Lohweg, Volker id: '1804' last_name: Lohweg orcid: 0000-0002-3325-7887 - first_name: Denis full_name: Petker, Denis last_name: Petker citation: ama: 'Mönks U, Lohweg V, Petker D. Fuzzy-Pattern-Classifier Training with Small Data Sets. In: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02 July 2010, Dortmund, Germany; 2010.' apa: Mönks, U., Lohweg, V., & Petker, D. (2010). Fuzzy-Pattern-Classifier Training with Small Data Sets. In IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02 July 2010, Dortmund, Germany. bjps: Mönks U, Lohweg V and Petker D (2010) Fuzzy-Pattern-Classifier Training with Small Data Sets. IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02 July 2010, Dortmund, Germany. chicago: Mönks, Uwe, Volker Lohweg, and Denis Petker. “Fuzzy-Pattern-Classifier Training with Small Data Sets.” In IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010. chicago-de: 'Mönks, Uwe, Volker Lohweg und Denis Petker. 2010. Fuzzy-Pattern-Classifier Training with Small Data Sets. In: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02 July 2010, Dortmund, Germany.' din1505-2-1: 'Mönks, Uwe ; Lohweg, Volker ; Petker, Denis: Fuzzy-Pattern-Classifier Training with Small Data Sets. In: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems : 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010' havard: 'U. Mönks, V. Lohweg, D. Petker, Fuzzy-Pattern-Classifier Training with Small Data Sets, in: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems, 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010.' ieee: U. Mönks, V. Lohweg, and D. Petker, “Fuzzy-Pattern-Classifier Training with Small Data Sets,” in IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems, 2010. mla: Mönks, Uwe, et al. “Fuzzy-Pattern-Classifier Training with Small Data Sets.” IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems, 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010. short: 'U. Mönks, V. Lohweg, D. Petker, in: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems, 28 Jun 2010 - 02 July 2010, Dortmund, Germany, 2010.' ufg: 'Mönks, Uwe et. al. (2010): Fuzzy-Pattern-Classifier Training with Small Data Sets, in: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems.' van: 'Mönks U, Lohweg V, Petker D. Fuzzy-Pattern-Classifier Training with Small Data Sets. In: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems. 28 Jun 2010 - 02 July 2010, Dortmund, Germany; 2010.' date_created: 2019-12-02T08:15:18Z date_updated: 2023-03-15T13:49:38Z department: - _id: DEP5023 keyword: - Fuzzy Logic - Probability Theory - Fuzzy-Pattern-Classification - Machine Learning - Artificial Intelligence - Pattern Recognition language: - iso: eng main_file_link: - open_access: '1' url: https://www.th-owl.de/init/uploads/tx_initdb/00800426_01.pdf oa: '1' publication: IPMU 2010 - International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems publication_status: published publisher: 28 Jun 2010 - 02 July 2010, Dortmund, Germany status: public title: Fuzzy-Pattern-Classifier Training with Small Data Sets type: conference user_id: '45673' year: 2010 ...