@inproceedings{LinssMuellerKaluzaetal.2023, author = {Linß, Marco and M{\"u}ller, Anke and Kaluza, Anke and Miller, Stefan}, title = {Mit Sicherheit mehr Wissen - wie Daten uns helfen k{\"o}nnen, das Studium zu verbessern}, booktitle = {Tagungsband zum 5. Symposium zur Hochschullehre in den MINT-F{\"a}chern}, subtitle = {ein Beispiel aus der Hochschule Hof}, editor = {D{\"o}lling, Hanna and Sch{\"a}fle, Claudia and K{\"u}rsten, Susanne and Hunger, Marianne and Hirtt, Jim and Riegler, Peter}, publisher = {BayZiel}, address = {M{\"u}nchen}, issn = {1612-4537}, doi = {10.57825/repo_in-4410}, pages = {150 -- 158}, year = {2023}, abstract = {Der Beitrag beruht auf den fast 10-j{\"a}hrigen Erfahrungen im Rahmen von drei F{\"o}rderprojekten des Freistaats Bayern. An der Hochschule Hof wurden, u. a. auf Basis einer entwickelten MINT-Datenbank und deren Analysen, zahlreiche Maßnahmen abgeleitet, durchgef{\"u}hrt und evaluiert. Basierend darauf wurde im letzten WiSe ein neues, modulares Studiengangkonzept im Bereich der Ingenieurwissenschaften eingef{\"u}hrt. Als wesentliche Erkenntnisse lassen sich folgende Aussagen festhalten: • Eingangspr{\"u}fungen verbessern die Studienerfolgsquote • ca. 10 \% einer Kohorte wollen gar nicht studieren • NotenMonitoringProgramme sind ein wichtiger Baustein f{\"u}r die Studienberatung bzw. den Studienerfolg • Notenanrechnung braucht definierte Rahmenbedingungen • Tutorien sind erst bei einer Teilnahme > 60 \% richtig wirksam • Prognosen zum Studienerfolg sind anhand der Hochschulzugangs-berechtigungsnote bzw. anhand dem Studierverhalten im ersten Semester m{\"o}glich • der wichtigste Faktor f{\"u}r den Studienerfolg ist die/der Studierende selbst}, language = {de} } @inproceedings{KobrasSollHerrmannetal.2023, author = {Kobras, Louis and Soll, Marcus and Herrmann, Franziska and Meussen, Bernhard and Haase, Jan and Versick, Daniel}, title = {Erstellung neuer Remote-Labore zur F{\"o}rderung des MINT-Studiums}, booktitle = {Tagungsband zum 5. Symposium zur Hochschullehre in den MINT-F{\"a}chern}, editor = {D{\"o}lling, Hanna and Sch{\"a}fle, Claudia and K{\"u}rsten, Susanne and Hunger, Marianne and Hirtt, Jim and Riegler, Peter}, publisher = {BayZiel}, address = {M{\"u}nchen}, issn = {1612-4537}, doi = {10.57825/repo_in-4391}, pages = {206 -- 213}, year = {2023}, abstract = {Praktische Erfahrungen in Laboren unterst{\"u}tzen das Vermitteln von fachspezifischen Kompetenzen in der Lehre. In den letzten Jahren ist dabei zunehmend der Wechsel zu Remote-Laboren erfolgt. Remote-Labore erm{\"o}glichen das Umgehen von logistischen Beschr{\"a}nkungen. Unterschiedliche Institute k{\"o}nnen beispielsweise zus{\"a}tzliche physische Instanzen eines Versuchsaufbaus hinter demselben digitalen Experiment hinzuf{\"u}gen oder virtuelle Kopien/digital twins eines Versuchsaufbaus verwenden. Zus{\"a}tzlich erfordern virtuelle Experimente keine Aufsicht durch Laborpersonal oder Anwesenheit in sicherheitskritischen Bereichen, sodass Lernende ihre Versuche unabh{\"a}ngig von Verf{\"u}gbarkeit von Laborplatz und -personal durchf{\"u}hren k{\"o}nnen. Aktuell befinden sich drei Remote-Labore im Aufbau: Ein IT-Security-Labor, ein Geb{\"a}udeautomationslabor und ein CoBotik-Labor. Diese werden kurz pr{\"a}sentiert; erg{\"a}nzend wird der Aufbau eines Labors beispielhaft am IT-Security-Labor demonstriert.}, language = {de} } @inproceedings{SchmiedtNeumaier2023, author = {Schmiedt, Anja Bettina and Neumaier, Stefanie}, title = {„Gamification trifft Hybride Lehre" {\"U}ber ein Lehrprojekt in der mathematischen Statistik}, booktitle = {Tagungsband zum 5. Symposium zur Hochschullehre in den MINT-F{\"a}chern}, editor = {D{\"o}lling, Hanna and Sch{\"a}fle, Claudia and K{\"u}rsten, Susanne and Hunger, Marianne and Hirtt, Jim and Riegler, Peter}, publisher = {BayZiel}, address = {M{\"u}nchen}, issn = {1612-4537}, doi = {10.57825/repo_in-4435}, pages = {159 -- 166}, year = {2023}, abstract = {Unter dem Titel „Gamification trifft Hybride Lehre" wurde im Sommersemester 2023 ein Lehrprojekt im Fach Statistik des Studiengangs Wirtschaftsmathematik-Aktuarwissenschaften der Technischen Hochschule Rosenheim durchgef{\"u}hrt. Unterschiedliche hybrid-synchrone Lernsettings wurden in einem technisch entsprechend ausgestatteten Lehr-Experimentierraum mit den Studierenden erprobt. Als Ansatz zur Vor- und Nachbereitung der hybriden Lehre kam Gamification bzw. Gameful Motivation zum Einsatz. Im Lehrprojektteam mit Stefanie Neumaier wurde die hybride Lehre mittels der sog. EMPAMOS-Methode vorbereitet und reflektiert. Dabei ging es nicht darum, den spielfremden Kontext (die hybride Lehre) in ein Spiel zu verwandeln, sondern Spielelemente zur Zielerreichung einzusetzen. Die Auseinandersetzung mit hybriden Formaten wird dabei f{\"u}r Studierende und Lehrende als ein Zukunftsthema gesehen, nicht zuletzt f{\"u}r den Erwerb von Future Skills in einer Arbeitswelt, in der sich hybride Kollaboration etabliert.}, language = {de} } @inproceedings{MorisseHeidemannMoeller2023, author = {Morisse, Karsten and Heidemann, Christian and M{\"o}ller, Sebastian}, title = {Informatik-Grundlagenmodul mit den Methoden Inverted Classroom und Scrum}, booktitle = {Tagungsband zum 5. Symposium zur Hochschullehre in den MINT-F{\"a}chern}, editor = {D{\"o}lling, Hanna and Sch{\"a}fle, Claudia and K{\"u}rsten, Susanne and Hunger, Marianne and Hirtt, Jim and Riegler, Peter}, publisher = {BayZiel}, address = {M{\"u}nchen}, issn = {1612-4537}, doi = {10.57825/repo_in-4393}, pages = {124 -- 131}, year = {2023}, abstract = {Im Modul Algorithmen und Datenstrukturen ist das Inverted Classroom Modell mit der Scrum-Methodik kombiniert. Die Studierenden erarbeiten die Inhalte des Moduls im Lernmanagementsystem mithilfe von Videoaufzeichnungen, digitalem Skript und interaktiven {\"U}bungseinheiten. Der Wegfall der klassischen Vorlesung erm{\"o}glicht mehr Zeit zur Beantwortung von Fragen, Diskussionen sowie der Reflexion des Erlernten durch H{\"o}rsaal-Quizze. Die Themen der Veranstaltung werden vorgegeben, aber die Bearbeitung erfolgt individuell und die Studierenden gestalten ihre eigenen Lernprozesse. Theorie und Praxis der Veranstaltung werden analog zur Scrum-Methodik in mehrw{\"o}chigen Sprints im Team bearbeitet. Die Aufgaben sind in den Kontext einer virtuellen Betriebssystemumgebung eingebettet und bauen aufeinander auf. Das Softwareprojekt wird hierzu als GitLab-Repository zur Verf{\"u}gung gestellt. Die Verwendung von Git und integrierten Test-Routinen entsprechen einer realit{\"a}tsnahen Vorgehensweise, wie sie in der Softwareentwicklung allgemein g{\"a}ngige Praxis ist.}, language = {de} } @inproceedings{AmicoPulham2023, author = {Amico, Gianluca and Pulham, Susan}, title = {Mathe meets Medi(t)ation - ein integratives Lehrkonzept zur F{\"o}rderung von Future Skills}, booktitle = {Tagungsband zum 5. Symposium zur Hochschullehre in den MINT-F{\"a}chern}, editor = {D{\"o}lling, Hanna and Sch{\"a}fle, Claudia and K{\"u}rsten, Susanne and Hunger, Marianne and Hirtt, Jim and Riegler, Peter}, publisher = {BayZiel}, address = {M{\"u}nchen}, issn = {1612-4537}, doi = {10.57825/repo_in-4408}, pages = {268 -- 276}, year = {2023}, abstract = {Mathe meets Medi(t)ation beschreibt ein innovatives Lehrkonzept, das auf der Verbindung des integrativen Ansatzes zur F{\"o}rderung von fachlichen und {\"u}berfachlichen Lerninhalten (Future Skills) und dem Lehrkonzept des Lernteamcoachings basiert (LTC). Das Konzept kann als Beispiel dienen, wie Future Skills in fachliche Lehre integriert und gef{\"o}rdert werden k{\"o}nnen und wie fachliche Lehre davon profitieren kann. Ziel des innovativen Konzepts ist es Studierende mithilfe von Future Skills f{\"u}r das Studium und die sich schnell ver{\"a}ndernde Arbeitswelt vorzubereiten und zugleich den Lernstoff auf tiefer kognitiver Ebene zu erschließen. Hierzu wird das Future Skills Modell der htw saar vorgestellt, die einzelnen Elemente des integrativen Lehrkonzepts, die in den synchronen und asynchronen Phasen des LTC eingebettet wurden, werden beschrieben und exemplarische Szenarien werden dargestellt. Abschließend werden erste Erfahrungen und Zukunftsvisionen des erstmalig pilotierten Lehrkonzepts diskutiert.}, language = {de} } @inproceedings{GaisserKnoblauchMartin2023, author = {Gaisser, Sibylle and Knoblauch, Anke and Martin, Annette}, title = {F{\"u}r MINT begeistern - Interesse wecken und Ber{\"u}hrungs{\"a}ngste abbauen durch das Ansbacher Modell}, booktitle = {Tagungsband zum 5. Symposium zur Hochschullehre in den MINT-F{\"a}chern}, editor = {D{\"o}lling, Hanna and Sch{\"a}fle, Claudia and K{\"u}rsten, Susanne and Hunger, Marianne and Hirtt, Jim and Riegler, Peter}, publisher = {BayZiel}, address = {M{\"u}nchen}, issn = {1612-4537}, doi = {10.57825/repo_in-4392}, pages = {18 -- 24}, year = {2023}, abstract = {Sinkende Studierendenzahlen im MINT-Bereich stellen ein Problem f{\"u}r die Hochschulen und die Gesellschaft dar. Die Ursachen liegen u.a. darin, dass sich die Sch{\"u}lerinnen und Sch{\"u}ler den MINT-Anforderungen zunehmend nicht gewachsen f{\"u}hlen oder diese wenig attraktiv finden. Beidem kann durch zielgruppenspezifische Angebote an den HAWs begegnet werden. In der Fakult{\"a}t Technik der Hochschule Ansbach wurde im Verlauf der letzten acht Jahre ein Konzept entwickelt, in dem Teilnehmende vom Vorschulalter bis zum Abitur altersgem{\"a}ß in Laborversuchen mit allen Sinnen angesprochen werden. Das Maßnahmenpaket besteht aus verschiedenen Pr{\"a}senzangeboten vom einfachen spielerischen Experimentieren f{\"u}r Vorschulkinder bis hin zu Vertiefungsworkshops und Schnupperangeboten f{\"u}r Teilnehmende aus den Oberstufen. Um die hohe zeitliche Belastung der einzelnen Hochschulangeh{\"o}rigen zu reduzieren, werden die Maßnahmen fakult{\"a}tsintern koordiniert und unter Einbeziehung m{\"o}glichst vieler Fakult{\"a}tsmitglieder realisiert.}, language = {de} } @inproceedings{EbbertLoeselStroessneretal.2023, author = {Ebbert, Ronald and L{\"o}sel, Ralf and Str{\"o}ßner, Regina and Heuser, Stefan}, title = {Digitales Praktikum zur Wirkstoffentwicklung}, booktitle = {Tagungsband zum 5. Symposium zur Hochschullehre in den MINT-F{\"a}chern}, editor = {D{\"o}lling, Hanna and Sch{\"a}fle, Claudia and K{\"u}rsten, Susanne and Hunger, Marianne and Hirtt, Jim and Riegler, Peter}, publisher = {BayZiel}, address = {M{\"u}nchen}, issn = {1612-4537}, doi = {10.57825/repo_in-4389}, pages = {184 -- 191}, year = {2023}, abstract = {Ein Chemiestudium beinhaltet traditionell hohe Praktikumsanteile. Auch das hier vorgestellte Master-Modul „Wirkstoffchemie" sah bisher ein Laborpraktikum vor, in dem drei Gruppen mit verschiedenen thematischen Schwerpunkten die fr{\"u}hen Phasen der modernen Wirkstoffentwicklung bearbeiteten. Die Corona-Pandemie hat die Chance er{\"o}ffnet, das Praktikum in ein digitales, Moodle-basiertes Planspiel zu transformieren, das mit Pr{\"a}sentationen, Videos und PDFs arbeitet. Zu Beginn bearbeiten Studierende Aufgabenstellungen individuell. Im weiteren Verlauf folgen Gruppenarbeiten, bei denen die Studierenden das im Rahmen der Vorlesung Gelernte diskutieren und anwenden k{\"o}nnen. In dieser Phase stehen die Studierenden auch mit den Dozenten in enger Interaktion. Durch das digitale Konzept erh{\"a}lt das Praktikum einen starken Projekt-Charakter. Erlerntes Wissen kann auf einen konkreten Fall angewendet und in die Praxis {\"u}berf{\"u}hrt werden. Die Studierenden gewinnen so einen tiefen Einblick in die moderne Wirkstoffforschung.}, language = {de} } @inproceedings{HardyRoth2023, author = {Hardy, Edme H. and Roth, Stefan}, title = {cosh-Version des Online-Br{\"u}ckenkurses Physik}, booktitle = {Tagungsband zum 5. Symposium zur Hochschullehre in den MINT-F{\"a}chern}, editor = {D{\"o}lling, Hanna and Sch{\"a}fle, Claudia and K{\"u}rsten, Susanne and Hunger, Marianne and Hirtt, Jim and Riegler, Peter}, publisher = {BayZiel}, address = {M{\"u}nchen}, issn = {1612-4537}, doi = {10.57825/repo_in-4387}, pages = {53 -- 56}, year = {2023}, abstract = {Um den {\"U}bergang zwischen Schule und Hochschule in den MINT -F{\"a}chern zu unterst{\"u}tzen, entwickeln bundesweit 14 Hochschulen gemeinsam einen Online-Br{\"u}ckenkurs Physik (OBKP). Der Kurs kann ohne Anmeldung genutzt werden. Er enth{\"a}lt Eingangs- und Abschlusstests, Lektionstexte und -videos, Experimentvideos sowie GeoGebra-Elemente und interaktive {\"U}bungsaufgaben. Zu vielen Konzepten gibt es „Basiswissen". Die im Rahmen der Kooperation erarbeiteten Inhalte stehen unter der freien Lizenz CC BY-SA. Es besteht jedoch Weiterentwicklungsbedarf. Seit 2021 bietet der cosh-Mindestanforderungskatalog Physik einen Rahmen f{\"u}r eine Reduktion der sehr umfangreichen Kurs-Inhalte. Weiterhin bedarf der Kurs einer technischen Revision insbesondere im Hinblick auf Editierbarkeit, mobile Endger{\"a}te und Einbindung in Lernplattformen. Im Rahmen eines Transferprojektes mit der Hochschule Biberach wird daher eine „cosh-Version" des OBKP erarbeitet. Die dabei genutzte Technik wird speziell f{\"u}r Online-Kurse entwickelt.}, language = {de} } @article{PeintnerMangerBergeretal.2025, author = {Peintner, Jakob and Manger, Carina and Berger, Melanie and Riener, Andreas}, title = {Balancing transparency and control: The impact of AI explanation detail on user perception in automated vehicles}, volume = {2025}, pages = {101742}, journal = {Transportation Research Interdisciplinary Perspectives}, number = {34}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2590-1982}, doi = {https://doi.org/10.1016/j.trip.2025.101742}, year = {2025}, abstract = {As automated vehicle technology advances, explainable AI has emerged as a critical tool to enable users to understand and predict the behavior of AI systems, particularly in safety-critical applications such as automated driving. However, increased transparency in AI explanations may inadvertently contribute to an "illusion of control", a cognitive bias in which drivers overestimate their influence or understanding of the AI's actions. We aim to better understand how the level of detail in AI explanations affects users of automated vehicles. In a virtual reality study, N = 44 participants experienced different explanation levels (low, medium, high) in an automated ride (SAE L4) compared to a baseline condition with no explanations. The results show a significant improvement in participants' user experience, acceptance, and explanation satisfaction, with more detailed explanations. Our findings also indicate that as AI explanations become more detailed, users' perceived level of control increases significantly, although this perception does not correlate with actual control capabilities. At the same time, it decreased their desire to take control, indicating users' susceptibility to the 'illusion of control' bias in the context of automated driving. Overall, this suggests that the design of explanation interfaces should strive for a balanced level of detail that promotes AI transparency without causing cognitive overload. At the same time, explainable AI can be utilized to decrease users' desire to intervene in the AI's actions.}, language = {en} } @article{Bodenschatz2024, author = {Bodenschatz, Anja}, title = {When own interest stands against the "greater good" - Decision randomization in ethical dilemmas of autonomous systems that involve their user's self-interest}, volume = {2}, pages = {100097}, journal = {Computers in Human Behavior: Artificial Humans}, number = {2}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2949-8821}, doi = {https://doi.org/10.1016/j.chbah.2024.100097}, year = {2024}, abstract = {Autonomous systems (ASs) decide upon ethical dilemmas and their artificial intelligence as well as situational settings become more and more complex. However, to study common-sense morality concerning ASs abstracted dilemmas on autonomous vehicle (AV) accidents are a common tool. A special case of ethical dilemmas is when the AS's users are affected. Many people want AVs to adhere to utilitarian programming (e.g., to save the larger group), or egalitarian programming (i.e., to treat every person equally). However, they want their own AV to protect them instead of the "greater good". That people reject utilitarian programming as an AS's user while supporting the idea from an impartial perspective has been termed the "social dilemma of AVs". Meanwhile, preferences for another technical capability, which would implement egalitarian programming, have not been elicited for dilemmas involving self-interest: decision randomization. This paper investigates normative and descriptive preferences for a self-protective, self-sacrificial, or randomized choice by an AS in a dilemma where people are the sole passenger of an AV, and their survival stands against the survival of several others. Results suggest that randomization may mitigate the "social dilemma of AVs" by bridging between a societally accepted programming and the urge of ASs' users for self-protection.}, language = {en} } @article{RufinoJuniorRivaSanseverinoGalloetal.2024, author = {Rufino J{\´u}nior, Carlos Ant{\^o}nio and Riva Sanseverino, Eleonora and Gallo, Pierluigi and Koch, Daniel and Diel, Sergej and Walter, Gero and Trilla, Llu{\´i}s and Ferreira, Victor Jos{\´e} and Benveniste, Gabriela and Kotak, Yash and Eichman, Joshua and Schweiger, Hans-Georg and Zanin, Hudson}, title = {Towards to Battery Digital Passport: Reviewing Regulations and Standards for Second-Life Batteries}, volume = {10}, pages = {115}, journal = {Batteries}, number = {4}, publisher = {MDPI}, address = {Basel}, issn = {2313-0105}, doi = {https://doi.org/10.3390/batteries10040115}, year = {2024}, abstract = {Greenhouse gas emissions from transportation harm the environment. In response to these environmental concerns, numerous countries encourage the adoption of electric vehicles (EVs) as a more environmentally friendly option than traditional gasoline-powered vehicles. Advances in battery technology have made batteries an alternative solution for energy storage in stationary applications and for electric mobility. Reduced lithium-ion batteries (LIBs) production costs due to economies of scale, electrode material and cell design developments, and manufacturing process improvements have driven this success. This trend is expected to increase the number of LIBs on the market that may be discarded in the environment at the end of their useful life if more sustainable alternatives are not technologically mature. This coming environmental concern can be mitigated by collecting wasted EV batteries, reconfiguring them, and reusing them for applications with less stringent weight, performance, and size requirements. This method would extend battery life and reduce environmental effects. The present work investigates the main regulatory structures of the second-life battery industry that require rules, technical standards, and laws. To achieve this objective, a systematic review was carried out following a strict protocol that includes identifying relevant studies, extracting data and information, evaluating, and summarizing information. This paper explains the primary rules and technical standards governing the second-life battery business. The findings highlight the need for universities, research institutions, and government agencies to evaluate the second-life battery industry objectively. This would enable the creation of new technological regulations and laws for this burgeoning industry.}, language = {en} } @article{KugeleObergfellSax2021, author = {Kugele, Stefan and Obergfell, Philipp and Sax, Eric}, title = {Model-based resource analysis and synthesis of service-oriented automotive software architectures}, volume = {20}, journal = {Software and Systems Modeling}, number = {6}, publisher = {Springer}, address = {Berlin}, issn = {1619-1374}, doi = {https://doi.org/10.1007/s10270-021-00896-9}, pages = {1945 -- 1975}, year = {2021}, abstract = {Context Automotive software architectures describe distributed functionality by an interaction of software components. One drawback of today's architectures is their strong integration into the onboard communication network based on predefined dependencies at design time. The idea is to reduce this rigid integration and technological dependencies. To this end, service-oriented architecture offers a suitable methodology since network communication is dynamically established at run-time. Aim We target to provide a methodology for analysing hardware resources and synthesising automotive service-oriented architectures based on platform-independent service models. Subsequently, we focus on transforming these models into a platform-specific architecture realisation process following AUTOSAR Adaptive. Approach For the platform-independent part, we apply the concepts of design space exploration and simulation to analyse and synthesise deployment configurations, i. e., mapping services to hardware resources at an early development stage. We refine these configurations to AUTOSAR Adaptive software architecture models representing the necessary input for a subsequent implementation process for the platform-specific part. Result We present deployment configurations that are optimal for the usage of a given set of computing resources currently under consideration for our next generation of E/E architecture. We also provide simulation results that demonstrate the ability of these configurations to meet the run time requirements. Both results helped us to decide whether a particular configuration can be implemented. As a possible software toolchain for this purpose, we finally provide a prototype. Conclusion The use of models and their analysis are proper means to get there, but the quality and speed of development must also be considered.}, language = {en} } @inproceedings{CostadeAraujoBaluReichmannetal.2025, author = {Costa de Araujo, Jo{\~a}o Paulo and Balu, Balahari Vignesh and Reichmann, Eik and Kelly, Jessica and Kugele, Stefan and Mata, N{\´u}ria and Grunske, Lars}, title = {Applying Concept-Based Models for Enhanced Safety Argumentation - Summary}, booktitle = {Software Engineering 2025: Proceedings}, editor = {Koziolek, Anne and Lamprecht, Anna-Lena and Th{\"u}m, Thomas and Burger, Erik}, publisher = {Gesellschaft f{\"u}r Informatik}, address = {Bonn}, issn = {2944-7682}, doi = {https://doi.org/10.18420/se2025-18}, pages = {65 -- 66}, year = {2025}, abstract = {In this extended abstract we summarize our work on using Concept Bottleneck Models (CBMs) for an enhanced safety argumentation of vision-based Machine Learning (ML) perception components in safety critical systems. This paper has been published at the International Symposium on Software Reliability Engineering (ISRRE'24)}, language = {en} } @inproceedings{KugeleSchreyerLamprecht2025, author = {Kugele, Stefan and Schreyer, Lorenz and Lamprecht, Martin}, title = {Cause-Effect Chain-Based Diagnosis of Automotive On-Board Energy Systems}, booktitle = {Software Engineering 2025: Proceedings}, editor = {Koziolek, Anne and Lamprecht, Anna-Lena and Th{\"u}m, Thomas and Burger, Erik}, publisher = {Gesellschaft f{\"u}r Informatik}, address = {Bonn}, issn = {2944-7682}, doi = {https://doi.org/10.18420/se2025-36}, pages = {111 -- 112}, year = {2025}, abstract = {This summary refers to the paper Cause-Effect Chain-Based Diagnosis of Automotive On-Board Energy Systems [KSL24]. This paper has been published in the Proceedings of the 18th European Conference on Software Architecture, ECSA 2024 in September 2024.}, language = {en} } @inproceedings{KugeleObergfellSax2022, author = {Kugele, Stefan and Obergfell, Philipp and Sax, Eric}, title = {Model-based resource analysis and synthesis of service-oriented automotive software architectures}, booktitle = {Software Engineering 2022}, editor = {Grunske, Lars and Siegmund, J. and Vogelsang, A.}, publisher = {Gesellschaft f{\"u}r Informatik}, address = {Bonn}, isbn = {978-3-88579-714-2}, doi = {https://doi.org/10.18420/se2022-ws-017}, pages = {55 -- 56}, year = {2022}, abstract = {This summary refers to the paper Model-based resource analysis and synthesis of serviceoriented automotive software architectures [KOS21]. This paper has been published in the Journal on Software and Systems Modeling (SoSyM) in September 2021.}, language = {en} } @unpublished{RufinoJuniorRivaSanseverinoGalloetal.2023, author = {Rufino J{\´u}nior, Carlos Ant{\^o}nio and Riva Sanseverino, Eleonora and Gallo, Pierluigi and Amaral, Murilo Machado and Koch, Daniel and Kotak, Yash and Diel, Sergej and Walter, Gero and Schweiger, Hans-Georg and Zanin, Hudson}, title = {A Comprehensive Review of EV Lithium-Ion Battery Degradation}, publisher = {Preprints}, address = {Basel}, doi = {https://doi.org/10.20944/preprints202306.0228.v2}, year = {2023}, abstract = {Lithium-ion batteries with improved energy densities have made understanding the Solid Electrolyte Interphase (SEI) generation mechanisms that cause mechanical, thermal, and chemical failures more complicated. SEI processes reduce battery capacity and power. Thus, a review of this area's understanding is important. It is essential to know how batteries degrade in EVs to estimate battery lifespan as it goes, predict, and minimize losses, and determine the ideal time for a replacement. Lithium-ion batteries used in EVs mainly suffer two types of degradation: calendar degradation and cycling degradation. Despite the existence of several existing works in the literature, several aspects of battery degradation remain unclear or have not been analyzed in detail. This work presents a systematic review of existing works in the literature. The results of the present investigation provide insight into the complex relationships among various factors affecting battery degradation mechanisms. Specifically, this systematic review examined the effects of time, side reactions, temperature fluctuations, high charge/discharge rates, depth of discharge, mechanical stress, thermal stress, and the voltage relationship on battery performance and longevity. The results revealed that these factors interact in complex ways to influence the degradation mechanisms of batteries. For example, high charge currents and deep discharges were found to accelerate degradation, while low temperatures and moderate discharge depths were shown to be beneficial for battery longevity. Additionally, the results showed that the relationship between cell voltage and State-of-Charge (SOC) plays a critical role in determining the rate of degradation. Overall, these findings have important implications for the design and operation of battery systems, as they highlight the need to carefully manage a range of factors to maximize battery performance and longevity. The result is an analysis of the main articles published in this field in recent years. This work aims to present new knowledge about fault detection, diagnosis, and management of lithium-ion batteries based on battery degradation concepts. The new knowledge is presented and discussed in a structured and comprehensive way.}, language = {en} } @article{HussenetherRufinoJuniorSelaibePiresetal.2026, author = {Hußenether, Thomas and Rufino J{\´u}nior, Carlos Ant{\^o}nio and Selaibe Pires, Tom{\´a}s and Mishra, Tarani and Nahar, Jinesh and Vaghani, Akash and Polzer, Richard and Diel, Sergej and Schweiger, Hans-Georg}, title = {Analysis of the Measurement Uncertainties in the Characterization Tests of Lithium-Ion Cells}, volume = {19}, pages = {825}, journal = {Energies}, number = {3}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {https://doi.org/10.3390/en19030825}, year = {2026}, abstract = {The transition to renewable energy systems and electric mobility depends on the effectiveness, reliability, and durability of lithium-ion battery technology. Accurate modeling and control of battery systems are essential to ensure safety, efficiency, and cost-effectiveness in electric vehicles and grid storage. In engineering and materials science, battery models depend on physical parameters such as capacity, energy, state of charge (SOC), internal resistance, power, and self-discharge rate. These parameters are affected by measurement uncertainty. Despite the widespread use of lithium-ion cells, few studies quantify how measurement uncertainty propagates to derived battery parameters and affects predictive modeling. This study quantifies how uncertainty in voltage, current, and temperature measurements reduces the accuracy of derived parameters used for simulation and control. This work presents a comprehensive uncertainty analysis of 18650 format lithium-ion cells with nickel cobalt aluminum oxide (NCA), nickel manganese cobalt oxide (NMC), and lithium iron phosphate (LFP) cathodes. It applies the law of error propagation to quantify uncertainty in key battery parameters. The main result shows that small variations in voltage, current, and temperature measurements can produce measurable deviations in internal resistance and SOC. These findings challenge the common assumption that such uncertainties are negligible in practice. The results also highlight a risk for battery management systems that rely on these parameters for control and diagnostics. The results show that propagated uncertainty depends on chemistry because of differences in voltage profiles, kinetic limitations, and temperature sensitivity. This observation informs cell selection and testing for specific applications. Improved quantification and control of measurement uncertainty can improve model calibration and reduce lifetime and cost risks in battery systems. These results support more robust diagnostic strategies and more defensible warranty thresholds. This study shows that battery testing and modeling should report and propagate measurement uncertainty explicitly. This is important for data-driven and physics-informed models used in industry and research.}, language = {en} } @article{RufinoJuniorRivaSanseverinoGalloetal.2024, author = {Rufino J{\´u}nior, Carlos Ant{\^o}nio and Riva Sanseverino, Eleonora and Gallo, Pierluigi and Amaral, Murilo Machado and Koch, Daniel and Kotak, Yash and Diel, Sergej and Walter, Gero and Schweiger, Hans-Georg and Zanin, Hudson}, title = {Unraveling the Degradation Mechanisms of Lithium-Ion Batteries}, volume = {17}, pages = {3372}, journal = {Energies}, number = {14}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {https://doi.org/10.3390/en17143372}, year = {2024}, abstract = {Lithium-Ion Batteries (LIBs) usually present several degradation processes, which include their complex Solid-Electrolyte Interphase (SEI) formation process, which can result in mechanical, thermal, and chemical failures. The SEI layer is a protective layer that forms on the anode surface. The SEI layer allows the movement of lithium ions while blocking electrons, which is necessary to prevent short circuits in the battery and ensure safe operation. However, the SEI formation mechanisms reduce battery capacity and power as they consume electrolyte species, resulting in irreversible material loss. Furthermore, it is important to understand the degradation reactions of the LIBs used in Electric Vehicles (EVs), aiming to establish the battery lifespan, predict and minimise material losses, and establish an adequate time for replacement. Moreover, LIBs applied in EVs suffer from two main categories of degradation, which are, specifically, calendar degradation and cycling degradation. There are several studies about battery degradation available in the literature, including different degradation phenomena, but the degradation mechanisms of large-format LIBs have rarely been investigated. Therefore, this review aims to present a systematic review of the existing literature about LIB degradation, providing insight into the complex parameters that affect battery degradation mechanisms. Furthermore, this review has investigated the influence of time, C-rate, depth of discharge, working voltage window, thermal and mechanical stresses, and side reactions in the degradation of LIBs.}, language = {en} } @article{SantosNetoKanieskietal.2025, author = {Santos, Cassiano and Neto, Milad Kalume and Kanieski, Jo{\~a}o Marcos and Rufino J{\´u}nior, Carlos Ant{\^o}nio and Schweiger, Hans-Georg and Zanin, Hudson}, title = {A multidimensional assessment of electrification in automotive powertrains: Technical, operational, and strategic perspectives}, volume = {2025}, pages = {107377}, journal = {Results in Engineering}, number = {28}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2590-1230}, doi = {https://doi.org/10.1016/j.rineng.2025.107377}, year = {2025}, abstract = {Global transportation is undergoing a profound transformation, driven by the convergence of decarbonization targets and advances in electrification technologies. Electrification, ranging from mild Hybrid Electric Vehicles (mHEVs) to Battery Electric Vehicles (BEVs), represents the main technological path in the transition from internal combustion engines. This transition is inherently multidimensional, simultaneously reshaping vehicle design, manufacturing systems, supply chains, customer value, and environmental outcomes in interconnected ways. Each architecture, including mHEV, Hybrid Electric Vehicle (HEV), Plug-in Hybrid Electric Vehicle (PHEV), and BEV, presents different tradeoffs in these dimensions, requiring a structured framework for systematic comparison. To address this gap, this work details an integrated framework that systematically compares electrification pathways across five interrelated dimensions: vehicle concepts, research and development, manufacturing and logistics, customer experience, and environmental footprint. This framework culminates in a decision matrix that consolidates trade-offs into a practical SWOT based tool for strategic planning.}, language = {en} } @article{SalamatMatternOlzemetal.2026, author = {Salamat, Babak and Mattern, Dominik and Olzem, Sebastian-Sven and Elsbacher, Gerhard and Seidel, Christian and Tonello, Andrea M.}, title = {GMP3: Learning-Driven, Bellman-Guided Trajectory Planning for AAVs in Real-Time on SE(3)}, volume = {14}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2026.3661193}, pages = {22720 -- 22733}, year = {2026}, abstract = {We propose GMP3, a multiphase global path planning framework that generates dynamically feasible three-dimensional trajectories for unmanned aerial vehicles (UAVs) operating in cluttered environments. The framework extends traditional path planning from Euclidean position spaces to the Lie group SE(3), allowing joint learning of translational motion and rotational dynamics. A modified Bellman-based operator is introduced to support reinforcement learning (RL) policy updates while leveraging prior trajectory information for improved convergence. GMP3 is designed as a distributed framework in which agents influence each other and share policy information along the trajectory: each agent refines its assigned segment and shares with its neighbors via a consensus-based scheme, enabling cooperative policy updates and convergence toward a path shaped globally even under kinematic constraints.We also propose DroneManager, a modular ground control software that interfaces the planner with real UAVs platforms via the Micro Air Vehicle Link (MAVLink) protocol, supporting real-time deployment and feedback. Simulation studies and indoor flight experiments validate the effectiveness of the proposed method in constrained 3D environments, demonstrating reliable obstacle avoidance and smooth, feasible trajectories across both position and orientation.}, language = {en} } @article{PugetGanzBertrametal.2025, author = {Puget, Chlo{\´e} and Ganz, Jonathan and Bertram, Christof and Conrad, Thomas and Baeblich, Malte and Voss, Anne and Landmann, Katharina and Haake, Alexander F. H. and Spree, Andreas and Hartung, Svenja and Aeschlimann, Leonore and Soto, Sara and de Brot, Simone and Dettwiler, Martina and Aupperle-Lellbach, Heike and Bolfa, Pompei and Bartel, Alexander and Kiupel, Matti and Breininger, Katharina and Aubreville, Marc and Klopfleisch, Robert}, title = {Artificial intelligence predicts c-KIT exon 11 genotype by phenotype in canine cutaneous mast cell tumors: Can human observers learn it?}, volume = {63}, journal = {Veterinary Pathology}, number = {2}, publisher = {Sage}, address = {London}, issn = {1544-2217}, doi = {https://doi.org/10.1177/03009858251380284}, pages = {369 -- 379}, year = {2025}, abstract = {Canine cutaneous mast cell tumors (ccMCTs) are frequent neoplasms with variable biological behaviors. Internal tandem duplication mutations in c-KIT exon 11 (c-KIT-11-ITD) are associated with poor prognosis but predict therapeutic response to tyrosine kinase inhibitors. In a previous work, deep learning algorithms managed to predict the presence of c-KIT-11-ITD on digitalized hematoxylin and eosin-stained histological slides (whole-slide images, WSIs) in up to 87\% of cases, suggesting the existence of morphological features characterizing ccMCTs carrying c-KIT-11-ITD. This 3-stage blinded study aimed to identify morphological features indicative of c-KIT-11-ITD and to evaluate the ability of human observers to learn this task. 17 untrained pathologists first classified 8 WSIs and 200 image patches (highly relevant for algorithmic classification) of ccMCTs as either positive or negative for c-KIT-11-ITD. Second, they self-trained to recognize c-KIT-11-ITD by looking at the same WSIs and patches correctly sorted. Third, pathologists classified 15 new WSIs and 200 new patches according to c-KIT-11-ITD status. In addition, participants reported microscopic features they considered relevant for their decision. Without training, participants correctly classified the c-KIT-11-ITD status of 63\%-88\% of WSIs and 43\%-55\% of patches. With self-training, 25\%-38\% of WSIs and 55\%-56\% of patches were correctly classified. High cellular pleomorphism, anisokaryosis, and sparse cytoplasmic granulation were commonly suggested as features associated with c-KIT-11-ITD-positive ccMCTs, none of which showed reliable predictivity in a follow-up study. The results indicate that transfer of algorithmic skills to the human observer is difficult. A c-KIT-11-ITD-specific morphological feature remains to be extracted from the artificial intelligence model.}, language = {en} } @article{RappsilberKruegerRaspeetal.2026, author = {Rappsilber, Tim and Kr{\"u}ger, Simone and Raspe, Tina and Reclo, Rudolf and Schweiger, Hans-Georg}, title = {Toxic gas emission in electric vehicles: What a battery fire means for occupant safety}, volume = {2026}, pages = {104717}, journal = {Fire Safety Journal}, number = {162}, publisher = {Elsevier}, address = {New York}, issn = {1873-7226}, doi = {https://doi.org/10.1016/j.firesaf.2026.104717}, year = {2026}, abstract = {This work investigates the ability of occupants to escape from a battery electric vehicle during a thermal runaway of the traction battery initiated by nail penetration. Such events generate intense fires and large amounts of toxic gases, rapidly reducing the time available for safe evacuation. In controlled full-scale outdoor experiments on two identical mid-range battery electric vehicles, the smoke gas composition inside the cabin is examined. Using FTIR spectrometers and an oxygen analyzer, temporal and spatial concentrations of organic carbonates, hydrocarbons, hydrogen fluoride, hydrogen cyanide, acetylene, and oxygen are measured. Sampling locations include the driver's breathing zone, the right rear passenger's breathing zone, and the exterior right rear wheel housing. The study further evaluates occupant's escape capability using the fractional effective dose (FED) model in accordance with ISO 13571. Results show that toxic gases can reach harmful concentrations within minutes after smoke enters the cabin, though smoke entry times vary widely with fire progression. Differences in fire development and smoke dispersion strongly affect FED values and thus the time available for self-rescue. Overall, the findings provide an important basis for assessing occupant safety during battery electric vehicle fires and highlight the need for improved mitigation strategies.}, language = {en} } @article{RosbachAmmelingGanzetal.2026, author = {Rosbach, Emely and Ammeling, Jonas and Ganz, Jonathan and Bertram, Christof and Conrad, Thomas and Riener, Andreas and Aubreville, Marc}, title = {Stuck on Suggestions: Automation Bias, the Anchoring Effect, and the Factors That Shape Them in Computational Pathology}, volume = {3}, pages = {2026:007}, journal = {Machine Learning for Biomedical Imaging}, number = {MELBA-BVM 2025 Special Issue}, publisher = {Melba editors}, address = {[s. l.]}, issn = {2766-905X}, doi = {https://doi.org/10.59275/j.melba.2026-87b1}, pages = {126 -- 147}, year = {2026}, abstract = {Artificial intelligence (AI)-driven clinical decision support systems (CDSS) hold promise to improve diagnostic accuracy and efficiency in computational pathology. However, collaboration between human experts and AI may give rise to cognitive biases, such as automation and anchoring bias, wherein users may be inclined to blindly adopt system recommendations or be disproportionately influenced by the presence of AI predictions, even when they are inaccurate. These biases may be exacerbated under time pressure, pervasive in routine pathology diagnostics, or shaped by individual user characteristics. To investigate these effects, we conducted a web-based experiment in which trained pathology experts (n = 28) estimated tumor cell percentages twice: once independently and once with the aid of an AI. A subset of the estimates in each condition was performed under time constraints. Our findings indicate that AI integration generally enhances diagnostic performance. However, it also introduced a 7\% automation bias rate, quantified as the number of accepted negative consultations, where a previously correct independent assessment gets overturned by inaccurate AI guidance. While time pressure did not increase the frequency of automation bias occurrence, it appeared to intensify its severity, as evidenced by a performance decline linked to increased automation reliance under cognitive load. A linear mixed-effects model (LMM) analysis, simulating weighted averaging, revealed a statistically significant positive coefficient for AI advice, indicating a moderate degree of anchoring on system output. This effect was further intensified under time pressure, suggesting that anchoring bias may become more pronounced when cognitive resources are limited. A secondary LMM evaluation assessing automation reliance, used as a proxy for both automation and anchoring bias, demonstrated that professional experience and self-efficacy were associated with reduced dependence on system support, whereas higher confidence during AI-assisted decision-making was linked to increased automation reliance. Together, these findings underscore the dual nature of AI integration in clinical workflows, offering performance benefits while also introducing risks of cognitive bias-driven diagnostic errors. As an initial investigation focused on a single medical specialty and diagnostic task, this study aims to lay the groundwork for future research to explore these phenomena across diverse clinical contexts, ultimately supporting the establishment of appropriate reliance on automated systems and the safe, effective integration of human-AI collaboration in medical decision-making.}, language = {en} } @article{PugetGanzOstermaieretal.2024, author = {Puget, Chlo{\´e} and Ganz, Jonathan and Ostermaier, Julian and Conrad, Thomas and Parlak, Eda and Bertram, Christof and Kiupel, Matti and Breininger, Katharina and Aubreville, Marc and Klopfleisch, Robert}, title = {Artificial intelligence can be trained to predict c-KIT-11 mutational status of canine mast cell tumors from hematoxylin and eosin-stained histological slides}, volume = {62}, journal = {Veterinary Pathology}, number = {2}, publisher = {Sage}, address = {London}, issn = {1544-2217}, doi = {https://doi.org/10.1177/03009858241286806}, pages = {152 -- 160}, year = {2024}, abstract = {Numerous prognostic factors are currently assessed histologically and immunohistochemically in canine mast cell tumors (MCTs) to evaluate clinical behavior. In addition, polymerase chain reaction (PCR) is often performed to detect internal tandem duplication (ITD) mutations in exon 11 of the c-KIT gene ( c-KIT-11-ITD) to predict the therapeutic response to tyrosine kinase inhibitors. This project aimed at training deep learning models (DLMs) to identify MCTs with c-KIT-11-ITD solely based on morphology. Hematoxylin and eosin (HE) stained slides of 368 cutaneous, subcutaneous, and mucocutaneous MCTs (195 with ITD and 173 without) were stained consecutively in 2 different laboratories and scanned with 3 different slide scanners. This resulted in 6 data sets (stain-scanner variations representing diagnostic institutions) of whole-slide images. DLMs were trained with single and mixed data sets and their performances were assessed under stain-scanner variations (domain shifts). The DLM correctly classified HE slides according to their c-KIT-11-ITD status in up to 87\% of cases with a 0.90 sensitivity and a 0.83 specificity. A relevant performance drop could be observed when the stain-scanner combination of training and test data set differed. Multi-institutional data sets improved the average accuracy but did not reach the maximum accuracy of algorithms trained and tested on the same stain-scanner variant (ie, intra-institutional). In summary, DLM-based morphological examination can predict c-KIT-11-ITD with high accuracy in canine MCTs in HE slides. However, staining protocol and scanner type influence accuracy. Larger data sets of scans from different laboratories and scanners may lead to more robust DLMs to identify c- KIT mutations in HE slides.}, language = {en} }