TY - JOUR A1 - Klotz, Stefan A1 - Kopper, Andreas A1 - Westner, Markus A1 - Strahringer, Susanne T1 - Von Schatten-IT zu Business-managed IT: Fachbereichs-IT gezielt gestalten JF - Wirtschaftsinformatik & Management N2 - Fachbereichs-IT, Schatten-IT, Business-managed IT. All diese Begriffe beschreiben IT, die neben den eigentlichen, regulären IT-Systemen oder -Prozessen in Unternehmen existieren und von Mitarbeiterinnen und Mitarbeitern der Fachbereiche genutzt werden. Im Fall von„Schatten-IT“ handelt es sich um IT-Systeme und -Prozesse (IT-Instanzen), die sich ohne Kenntnis der IT-Verantwortlichen etabliert haben; im Fall von„Business-managed IT“ entstehen die IT-Systeme und -Prozesse in Kenntnis der bzw. in Abstimmung mit den IT-Verantwortlichen im Unternehmen.„Fachbereichs-IT“ subsumiert Schatten-IT und Business-managed IT. Welche Ursachen führen zu solchen IT-Instanzen, welche Potenziale und Risiken haben diese IT-Instanzen und wie lassen sie sich steuern? KW - Business-managed IT KW - Fachbereichs IT KW - IT Governance KW - Schatten IT KW - Shadow IT Y1 - 2022 U6 - https://doi.org/10.1365/s35764-022-00421-7 SN - 1867-5913 SN - 1867-5905 VL - 14 IS - 4 SP - 282 EP - 287 PB - Springer Nature ER - TY - CHAP A1 - Joblin, Mitchell A1 - Apel, Sven A1 - Hunsen, Claus A1 - Mauerer, Wolfgang T1 - Classifying Developers into Core and Peripheral: An Empirical Study on Count and Network Metrics T2 - 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE), Buenos Aires, Argentina, 20-28 May 2017 N2 - Knowledge about the roles developers play in a software project is crucial to understanding the project's collaborative dynamics. In practice, developers are often classified according to the dichotomy of core and peripheral roles. Typically, count-based operationalizations, which rely on simple counts of individual developer activities (e.g., number of commits), are used for this purpose, but there is concern regarding their validity and ability to elicit meaningful insights. To shed light on this issue, we investigate whether count-based operationalizations of developer roles produce consistent results, and we validate them with respect to developers' perceptions by surveying 166 developers. Improving over the state of the art, we propose a relational perspective on developer roles, using fine-grained developer networks modeling the organizational structure, and by examining developer roles in terms of developers' positions and stability within the developer network. In a study of 10 substantial open-source projects, we found that the primary difference between the count-based and our proposed network-based core-peripheral operationalizations is that the network-based ones agree more with developer perception than count-based ones. Furthermore, we demonstrate that a relational perspective can reveal further meaningful insights, such as that core developers exhibit high positional stability, upper positions in the hierarchy, and high levels of coordination with other core developers, which confirms assumptions of previous work. Y1 - 2017 U6 - https://doi.org/10.1109/icse.2017.23 SP - 164 EP - 174 PB - IEEE ER - TY - CHAP A1 - Jaritz, Sabine A1 - Marx, Susanne ED - Bernert, Christian ED - Scheuerer, Steffen ED - Wehnes, Harald T1 - Externe Begleitung für KI-Projekte in KMUs T2 - KI in der Projektwirtschaft 2: Eine neue Ära der Effizienz und Innovation N2 - Dieser Beitrag befasst sich mit der Rolle externer Unterstützungsangebote in der Umsetzung von Projekten zur Nutzung von Künstlicher Intelligenz (KI) im Mittelstand. Während Großunternehmen Mittel und Ressourcen haben, externe Beratungsleistungen einzukaufen, um sich bei KI-Themen unterstützen zu lassen, so haben kleine und mittlere Unternehmen (KMUs) diese Möglichkeit in der Regel nur eingeschränkt. Die Nachfrage nach Support, um für das KI-Zeitalter gerüstet zu sein, ist auch bei KMUs groß. Der Artikel bietet einen Überblick über die verschiedenen Anbietergruppen und ihre unterschiedlichen Angebotsformen für KMUs. Dazu werden im ersten Schritt diverse Angebotsformen, wie Wissensvermittlung mit Hilfe von Informationsmaterialien und Veranstaltungen, Erstgespräche, Potenzialanalysen, individuelle Beratung bei KI-Projekten und Vernetzung, auf Basis einer Desk-Research erfasst. Im zweiten Schritt wird sich dann auf individuelle Beratung von KMUs als spezifische Angebotsform fokussiert. Durch Tiefeninterviews mit KI-Beratern wird beleuchtet, welche Art von KI-Projekten von KMUs derzeit priorisiert werden und welche zentralen Aufgaben die externen Begleitungen dabei übernehmen. KW - Künstliche Intelligenz KW - Transformation KW - Projekte KW - Mittelstand Y1 - 2024 SN - 978-3-381-11141-1 U6 - https://doi.org/10.24053/9783381111428 SP - 15 EP - 25 PB - UKV CY - Tübingen ER - TY - JOUR A1 - Klotz, Stefan A1 - Kopper, Andreas A1 - Westner, Markus A1 - Strahringer, Susanne T1 - Causing factors, outcomes, and governance of Shadow IT and business-managed IT BT - A systematic literature review JF - International Journal of Information Systems and Project Management N2 - Shadow IT and Business-managed IT describe the autonomous deployment/procurement or management of Information Technology (IT) instances, i.e., software, hardware, or IT services, by business entities. For Shadow IT, this happens covertly, i.e., without alignment with the IT organization; for Business-managed IT this happens overtly, i.e., in alignment with the IT organization or in a split responsibility model. We conduct a systematic literature review and structure the identified research themes in a framework of causing factors, outcomes, and governance. As causing factors, we identify enablers, motivators, and missing barriers. Outcomes can be benefits as well as risks/shortcomings of Shadow IT and Business-managed IT. Concerning governance, we distinguish two subcategories: general governance for Shadow IT and Business-managed IT and instance governance for overt Business-managed IT. Thus, a specific set of governance approaches exists for Business-managed IT that cannot be applied to Shadow IT due to its covert nature. Hence, we extend the existing conceptual understanding and allocate research themes to Shadow IT, Business-managed IT, or both concepts and particularly distinguish the governance of the two concepts. Besides, we find that governance themes have been the primary research focus since 2016, whereas older publications (until 2015) focused on causing factors. KW - Shadow IT KW - Business-managed IT KW - IT governance KW - literature review KW - outcomes KW - Betriebliches Informationssystem KW - Datensicherung KW - Literaturbericht Y1 - 2019 UR - http://www.sciencesphere.org/ijispm/archive/ijispm-070102.pdf U6 - https://doi.org/10.12821/ijispm070102 SN - 2182-7796 SN - 2182-7788 SN - 2182-780X VL - 7 IS - 1 SP - 15 EP - 43 ER - TY - CHAP A1 - Joblin, Mitchell A1 - Mauerer, Wolfgang A1 - Apel, Sven A1 - Siegmund, Janet A1 - Riehle, Dirk T1 - From Developer Networks to Verified Communities: A Fine-Grained Approach T2 - 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, 16-24 May 2015, Florence, Italy N2 - Effective software engineering demands a coordinated effort. Unfortunately, a comprehensive view on developer coordination is rarely available to support software-engineering decisions, despite the significant implications on software quality, software architecture, and developer productivity. We present a fine-grained, verifiable, and fully automated approach to capture a view on developer coordination, based on commit information and source-code structure, mined from version-control systems. We apply methodology from network analysis and machine learning to identify developer communities automatically. Compared to previous work, our approach is fine-grained, and identifies statistically significant communities using order-statistics and a community-verification technique based on graph conductance. To demonstrate the scalability and generality of our approach, we analyze ten open-source projects with complex and active histories, written in various programming languages. By surveying 53 open-source developers from the ten projects, we validate the authenticity of inferred community structure with respect to reality. Our results indicate that developers of open-source projects form statistically significant community structures and this particular view on collaboration largely coincides with developers' perceptions of real-world collaboration. KW - collaboration KW - Computer languages KW - Measurement KW - Open Source Software KW - Software systems KW - Standards Y1 - 2015 SN - 978-1-4799-1934-5 U6 - https://doi.org/10.1109/icse.2015.73 SP - 563 EP - 573 PB - IEEE ER - TY - CHAP A1 - Klotz, Stefan A1 - Westner, Markus A1 - Strahringer, Susanne A1 - Schieder, Christian T1 - Transformed Knowledge Sharing Through Business-managed IT and Shadow IT T2 - Proceedings of the 25th Americas Conference on Information Systems (AMCIS 2019), Cancún, Mexiko, August 15-17 N2 - Business-managed IT and Shadow IT describe the autonomous deployment/management of IT instances by business units. For the former, this happens in alignment with the IT organization of the enterprise, for the latter, without alignment. We analyze why and how Business-managed IT and Shadow IT transform knowledge sharing with two case studies drawing on the theoretical lens of the knowledge-based view. Several motivators lead to the autonomous implementation of knowledge management systems (KMSs), for example, shortcomings of existing systems. The implemented KMSs have multiple benefits for knowledge sharing, such as a reduction of knowledge sharing barriers. However, we notice that the Shadow IT KMS leads to challenges for cross-unit knowledge sharing due to the covert nature of Shadow IT. Based on the findings of our case studies, we develop a mid-range theory to explain the transformation of knowledge sharing in enterprises supported by Business-managed IT and Shadow IT. KW - Business-managed IT KW - Shadow IT KW - knowledge sharing KW - knowledge management system Y1 - 2019 UR - https://aisel.aisnet.org/amcis2019/org_transformation_is/org_transformation_is/5/ SP - 1 EP - 10 PB - AIS ER - TY - JOUR A1 - Joblin, Mitchell A1 - Apel, Sven A1 - Mauerer, Wolfgang T1 - Evolutionary trends of developer coordination: a network approach JF - Empirical Software Engineering N2 - Software evolution is a fundamental process that transcends the realm of technical artifacts and permeates the entire organizational structure of a software project. By means of a longitudinal empirical study of 18 large open-source projects, we examine and discuss the evolutionary principles that govern the coordination of developers. By applying a network-analytic approach, we found that the implicit and self-organizing structure of developer coordination is ubiquitously described by non-random organizational principles that defy conventional software-engineering wisdom. In particular, we found that: (a) developers form scale-free networks, in which the majority of coordination requirements arise among an extremely small number of developers, (b) developers tend to accumulate coordination requirements with more and more developers over time, presumably limited by an upper bound, and (c) initially developers are hierarchically arranged, but over time, form a hybrid structure, in which core developers are hierarchically arranged and peripheral developers are not. Our results suggest that the organizational structure of large projects is constrained to evolve towards a state that balances the costs and benefits of developer coordination, and the mechanisms used to achieve this state depend on the project’s scale. KW - Developer coordination KW - Developer networks KW - Software evolution Y1 - 2016 U6 - https://doi.org/10.1007/s10664-016-9478-9 VL - 22 IS - 4 SP - 2050 EP - 2094 PB - Springer ER - TY - CHAP A1 - Jaritz, Sabine ED - Bernert, Christian ED - Scheurer, Steffen ED - Wehnes, Harald T1 - KI in der Projektmanagement-Lehre T2 - KI in der Projektwirtschaft: Was verändert sich durch KI im Projektmanagement? N2 - Der Artikel beschäftigt sich mit dem Einbezug von Künstlicher Intelligenz (KI) in die Projektmanagement-Lehre an Hochschulen. Um zeitgemäße Projektmanagement-Lehre anbieten zu können, ist es förderlich, KI in die Lehre einzubeziehen, und so Studierende bei der Entwicklung von Future Skills zu unterstützen. Die Integration von KI in die Lehre wird anhand von vier Handlungsfeldern aufgezeigt. Im Sinne eines Call-to-Action wird ermutigt, KI-bezogene Lernziele explizit zu definieren und diese mit den Prüfungsleistungen und den Lehr-/Lernaktivitäten entsprechend des vorgestellten didaktischen Ansatzes des Constructive Alignment aufeinander abzustimmen. Es werden drei Good-Practice-Beispiele vorgestellt, die als Anregung dienen sollen. Der Beitrag plädiert für Experimente im Zusammenhang mit dem Einsatz von KI in der Lehre. Durch experimentelles Lernen können Studierende Kompetenzen im Umgang mit KI aufbauen und sich so auf eine künftige Arbeitswelt vorbereiten, die von Projektarbeit und KI-Unterstützung geprägt sein wird. KW - Künstliche Intelligenz KW - Lehre KW - Projektmanagement Y1 - 2024 SN - 978-3-381-11131-2 U6 - https://doi.org/10.24053/9783381111329 SP - 201 EP - 210 PB - UKV CY - Tübingen ER - TY - JOUR A1 - Joblin, Mitchell A1 - Mauerer, Wolfgang T1 - An Interactive Survey Framework for Validation of Social Network Analysis JF - The R Journal N2 - Abstract Social network analysis is extremely well supported by the R community and is routinely used for studying the relationships between people engaged in collaborative activities. While there has been rapid development of new approaches and metrics in this field, the challenging question of validity (how well insights derived from social networks agree with reality) is often difficult to address. We propose the use of several R packages to generate interactive surveys that are specifically well suited for validating social network analyses. Using our web-based survey application, we were able to validate the results of applying community-detection algorithms to infer the organizational structure of software developers contributing to open-source projects. Y1 - 2016 UR - https://journal.r-project.org/archive/2016/RJ-2016-010/index.html VL - 8 IS - 1 SP - 149 EP - 158 ER - TY - CHAP A1 - Ettl, Katrin A1 - Greiner, Nina A1 - Kudienko, Natalie A1 - Lauer, Norina A1 - Lichtenauer, Norbert A1 - Meussling-Sentpali, Annette A1 - Mohr, Christa A1 - Pfingsten, Andrea ED - Weber, Karsten ED - Haug, Sonja ED - Lauer, Norina ED - Meussling-Sentpali, Annette ED - Mohr, Christa ED - Pfingsten, Andrea ED - Raptis, Georgios ED - Bahr, Gudrun T1 - Forschungsdesign Pflege und Therapie im Projekt TePUS T2 - Digitale Technik für ambulante Pflege und Therapie: Herausforderungen, Lösungen, Anwendungen und Forschungsperspektiven N2 - Beim Projekt DeinHaus 4.0 Oberpfalz – TePUS (Telepräsenzroboter für die Pflege und Unterstützung von Schlaganfallpatientinnen und -patienten) handelt es sich um eine Längsschnittstudie im Mixed-Methods-Design zur Untersuchung telepräsenz und appgestützter Angebote aus den Bereichen Pflege, Logopädie und Physiotherapie. T3 - Schriftenreihe der OTH Regensburg - 1 KW - Pflege KW - Logopädie KW - Physiotherapie KW - Schlaganfall KW - Digitalisierung KW - Ambulante Pflege KW - Ambulante Therapie KW - Roboter Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-55448 SN - 978-3-83766235-1 SP - 59 EP - 78 PB - transcript CY - Bielefeld ER - TY - CHAP A1 - Ettl, Katrin A1 - Lichtenauer, Norbert A1 - Mohr, Christa ED - Weber, Karsten ED - Haug, Sonja ED - Lauer, Norina ED - Meussling-Sentpali, Annette ED - Mohr, Christa ED - Pfingsten, Andrea ED - Raptis, Georgios ED - Bahr, Gudrun T1 - Telenursing bei Schlaganfall BT - Auswahl existierender Software und Apps aus pflegewissenschaftlicher Sicht für das Projekt DeinHaus 4.0 Oberpfalz T2 - Digitale Technik für ambulante Pflege und Therapie: Herausforderungen, Lösungen, Anwendungen und Forschungsperspektiven N2 - Schlaganfallbetroffene haben oft einen komplexen Unterstützungsbedarf. Der Artikel beschäftigt sich damit, welche Telenursing-Anwendungen für das Projekt DeinHaus 4.0 ausgewählt wurden, um Schlaganfallbetroffene dabei zu unterstützen selbstbestimmt zu Hause zu leben. T3 - Schriftenreihe der OTH Regensburg - 1 KW - Pflege KW - Digitalisierung KW - Telenursing KW - Schlaganfall KW - Apps KW - Roboter KW - ambulante Pflege Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-55458 SN - 978-3-8394-6235-5 SN - 978-3-83766235-1 SP - 79 EP - 95 PB - transcript CY - Bielefeld ER - TY - CHAP A1 - Bock, T. A1 - Mottok, Jürgen A1 - Köhler, Thorsten ED - Mottok, Jürgen ED - Ziemann, Olaf T1 - A gesture-based human-machine interface using stereoscopic depth images T2 - 2nd Applied Research Conference 2012 (ARC 2012), 25./26. June 2012, Nuremberg N2 - Reasonable integration of gesture-based automotive HMI-functionality offers potential safety benefits by reducing driver distractions and glance times to operate tertiary in-car devices. Stereo camera systems are a well investigated choice to perform the task of generating depth data for spatial gesture recognition. This paper describes the functionality of our stereo vision software, which is intended for application in a target system based on CMOS wafer-level cameras. The retrieved point cloud data was passed to a gesture-based sample application. Y1 - 2012 SP - 166 EP - 169 PB - Shaker CY - Aachen ER - TY - CHAP A1 - Lichtenauer, Norbert A1 - Meussling-Sentpali, Annette ED - Weber, Karsten ED - Haug, Sonja ED - Lauer, Norina ED - Meussling-Sentpali, Annette ED - Mohr, Christa ED - Pfingsten, Andrea ED - Raptis, Georgios ED - Bahr, Gudrun T1 - Telenursing-Interventionen bei Schlaganfall BT - Überblick über den Forschungsstand T2 - Digitale Technik für ambulante Pflege und Therapie: Herausforderungen, Lösungen, Anwendungen und Forschungsperspektiven N2 - Systematische Literatursuche zum Einsatz von Telenursing-Interventionen bei Schlaganfallpatientinnen und Schlaganfallpatienten. T3 - Schriftenreihe der OTH Regensburg - 1 KW - Digitalisierung KW - Telemedizin KW - Schlaganfall KW - Pflege KW - Telenursing KW - Interventionen KW - Schlaganfall KW - Review Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-55175 SN - 978-3-8376-6235-1 SP - 97 EP - 118 PB - transcript CY - Bielefeld ER - TY - JOUR A1 - Leusch, Vera A1 - Corsten, Sabine A1 - Giordano, Katharina A1 - Kreiter, Daniel A1 - Lauer, Norina T1 - App erleichtert Gespräche über das Leben JF - Aktivieren : das Magazin für die soziale Betreuung N2 - Das Forschungsteam BaSeTaLK hat gemeinsam mit Menschen im Alter eine App zur Biografiearbeit fr Bewohner:innen in Senioreneinrichtungen entwickelt. Sie befähigt insbesondere Ehrenamtliche, biografische Gespräche zu führen. KW - Biografieforschung KW - Digitalisierung Y1 - 2022 UR - https://www.basetalk.de/wp-content/uploads/2022/10/Aktivieren_05_2022_App_erleichtert_Gespraeche_ueber_das_Leben.pdf SN - 2364-303X VL - 8 IS - 5 SP - 32 EP - 35 PB - Vincentz CY - Hannover ER - TY - JOUR A1 - Ebner, Andrea A1 - Frikel, Jürgen A1 - Lorenz, Dirk A1 - Schwab, J. A1 - Haltmeier, Markus T1 - Regularization of inverse problems by filtered diagonal frame decomposition JF - Applied and Computational Harmonic Analysis N2 - Inverse problems are at the heart of many practical problems such as image reconstruction or nondestructive testing. A characteristic feature is their instability with respect to data perturbations. To stabilize the inversion process, regularization methods must be developed and applied. In this paper, we introduce the concept of filtered diagonal frame decomposition, which extends the classical filtered SVD to the case of frames. The use of frames as generalized singular systems allows a better match to a given class of potential solutions and is also beneficial for problems where the SVD is not analytically available. We show that filtered diagonal frame decompositions yield convergent regularization methods, derive convergence rates under source conditions and prove order optimality. Our analysis applies to bounded and unbounded forward operators. As a practical application of our tools, we study filtered diagonal frame decompositions for inverting the Radon transform as an unbounded operator on L2(R2). Y1 - 2023 U6 - https://doi.org/10.1016/j.acha.2022.08.005 N1 - Preprint unter: https://arxiv.org/pdf/2008.06219.pdf OPUS-Einrag unter: https://opus4.kobv.de/opus4-oth-regensburg/admin/document/edit/id/2290 VL - 62 IS - January SP - 66 EP - 83 PB - Elsevier ER - TY - JOUR A1 - Maier, Robert A1 - Grabinger, Lisa A1 - Urlhart, David A1 - Mottok, Jürgen T1 - Causal Models to Support Scenario-Based Testing of ADAS JF - IEEE Transactions on Intelligent Transportation Systems N2 - In modern vehicles, system complexity and technical capabilities are constantly growing. As a result, manufacturers and regulators are both increasingly challenged to ensure the reliability, safety, and intended behavior of these systems. With current methodologies, it is difficult to address the various interactions between vehicle components and environmental factors. However, model-based engineering offers a solution by allowing to abstract reality and enhancing communication among engineers and stakeholders. Applying this method requires a model format that is machine-processable, human-understandable, and mathematically sound. In addition, the model format needs to support probabilistic reasoning to account for incomplete data and knowledge about a problem domain. We propose structural causal models as a suitable framework for addressing these demands. In this article, we show how to combine data from different sources into an inferable causal model for an advanced driver-assistance system. We then consider the developed causal model for scenario-based testing to illustrate how a model-based approach can improve industrial system development processes. We conclude this paper by discussing the ongoing challenges to our approach and provide pointers for future work. KW - automated driving systems KW - Automation KW - Bayesian networks KW - Causal inference KW - Data models KW - ISO Standards KW - model-based testing KW - Safety KW - Task analysis KW - Testing KW - Vehicles Y1 - 2023 U6 - https://doi.org/10.1109/TITS.2023.3317475 SN - 1524-9050 SP - 1 EP - 17 PB - IEEE ER - TY - CHAP A1 - Kristen, Meret A1 - Engl, Fabian A1 - Mottok, Jürgen T1 - Enhancing Phishing Detection: An Eye-Tracking Study on User Interaction and Oversights in Phishing Emails T2 - SECURWARE 2024 : The Eighteenth International Conference on Emerging Security Information, Systems and Technologies, November 03-07, 2024, Nice, France N2 - Phishing remains a significant threat to organizational security, necessitating effective countermeasures. This paper presents findings from an in-depth eye-tracking study with 103 participants, evaluating the effectiveness of phishing awareness tools and trainings. The study examines how a phishing awareness system influences user behavior, efficiency, and the ability to identify phishing attempts. By analyzing eye movements, the study reveals real-time interactions and oversights, providing insights into the decision-making process. Results indicate that while the system improves the efficiency of users already proficient in phishing detection, it does not universally enhance recognition rates. Notably, participants using the tool spent significantly less time looking at attachment-related phishing markers, indicating partial efficiency improvements. Since phishing attempts containing suspicious attachments were successful in 19% of cases, as compared to an overall phishing success rate of 15%, the phishing awareness tool is particularly useful here. A usability evaluation revealed that users reporting a higher perceived usability score profited more from the help of the tool. Additionally, no improvement in phishing detection rates was observed in users who had completed prior IT-security training, highlighting the necessity for a paradigm shift in phishing training to adequately prepare users for phishing attempts. Y1 - 2024 UR - https://www.thinkmind.org/library/SECURWARE/SECURWARE_2024/securware_2024_2_80_30041.html SN - 978-1-68558-206-7 SP - 71 EP - 80 PB - IARIA ER - TY - CHAP A1 - Staufer, Susanne A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Nadimpalli, Vamsi Krishna A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Learning elements in online learning management systems T2 - Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-67725 SP - 3121 EP - 3130 PB - IATED ER - TY - CHAP A1 - Göppel, Simon A1 - Frikel, Jürgen A1 - Haltmeier, Markus ED - Palm, Christoph ED - Breininger, Katharina ED - Deserno, Thomas M. ED - Handels, Heinz ED - Maier, Andreas ED - Maier-Hein, Klaus H. ED - Tolxdorff, Thomas M. T1 - Data-proximal Neural Networks for Limited-view CT T2 - Bildverarbeitung für die Medizin 2025 : Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025 N2 - Limited-angle computed tomography (CT) requires solving an inverse problem that is both ill-conditioned and underdetermined. In recent years, learned reconstruction methods have proven highly effective in addressing this challenge. Most of these methods follow a two-step process: first, an initial reconstruction method is applied to the data to generate an auxiliary reconstruction; second, a neural network is used to map the auxiliary reconstruction closer to the ground truth images. However, when applied to unseen data, there are no guarantees that the network’s output will remain consistent with the available measurement data. To address this, we recently introduced a data-proximal network architecture. In this paper, we implement this approach for limited-angle CT and compare its performance with a standard residual network and a null space network. Y1 - 2025 SN - 978-3-658-47421-8 U6 - https://doi.org/10.1007/978-3-658-47422-5_41 SP - 185 EP - 190 PB - Springer Fachmedien Wiesbaden CY - Wiesbaden ER - TY - CHAP A1 - Selig, Tim A1 - Bauer, Patrick A1 - Frikel, Jürgen A1 - März, Thomas A1 - Storath, Martin A1 - Weinmann, Andreas ED - Palm, Christoph ED - Breininger, Katharina ED - Deserno, Thomas M. ED - Handels, Heinz ED - Maier, Andreas ED - Maier-Hein, Klaus H. ED - Tolxdorff, Thomas M. T1 - Two-stage Approach for Low-dose and Sparse-angle CT Reconstruction using Backprojection T2 - Bildverarbeitung für die Medizin 2025 (BVM 2025): Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025 N2 - This paper presents a novel two-stage approach for computed tomography (CT) reconstruction, focusing on sparse-angle and low-dose setups to minimize radiation exposure while maintaining high image quality. Two-stage approaches consist of an initial reconstruction followed by a neural network for image refinement. In the initial reconstruction, we apply the backprojection (BP) instead of the traditional filtered backprojection (FBP). This enhances computational speed and offers potential advantages for more complex geometries, such as fan-beam and cone-beam CT. Additionally, BP addresses noise and artifacts in sparse-angle CT by leveraging its inherent noise-smoothing effect, which reduces streaking artifacts common in FBP reconstructions. For the second stage, we fine-tune the DRUNet proposed by Zhang et al. to further improve reconstruction quality. We call our method BP-DRUNet and evaluate its performance on a synthetically generated ellipsoid dataset alongside thewell-established LoDoPaBCT dataset. Our results show that BP-DRUNet produces competetive results in terms of PSNR and SSIM metrics compared to the FBP-based counterpart, FBPDRUNet, and delivers visually competitive results across all tested angular setups. Y1 - 2025 SN - 978-3-658-47421-8 U6 - https://doi.org/10.1007/978-3-658-47422-5_67 SP - 286 EP - 291 PB - Springer VS CY - Wiesbaden ER - TY - JOUR A1 - Marterer, Verena A1 - Radouchová, Michaela A1 - Soukup, Radek A1 - Hipp, Susanne A1 - Blecha, Tomáš T1 - Wearable textile antennas: investigation on material variants, fabrication methods, design and application JF - Fashion and Textiles N2 - With the ongoing miniaturization of wireless devices, the importance of wearable textiles in the antenna segment has increased significantly in recent years. Due to the widespread utilization of wireless body sensor networks for healthcare and ubiquitous applications, the design of wearable antennas offers the possibility of comprehensive monitoring, communication, and energy harvesting and storage. This article reviews a number of properties and benefits to realize comprehensive background information and application ideas for the development of lightweight, compact and low-cost wearable patch antennas. Furthermore, problems and challenges that arise are addressed. Since both electromagnetic and mechanical specifications must be fulfilled, textile and flexible antennas require an appropriate trade-off between materials, antenna topologies, and fabrication methods—depending on the intended application and environmental factors. This overview covers each of the above issues, highlighting research to date while correlating antenna topology, feeding techniques, textile materials, and contacting options for the defined application of wearable planar patch antennas. KW - Wearable communication KW - Textile antenna KW - Patch antenna KW - Design requirements KW - Smart textiles KW - E-textiles Y1 - 2024 U6 - https://doi.org/10.1186/s40691-023-00369-1 VL - 11 PB - Springer Open ER - TY - GEN A1 - Horn, L. C A1 - Pippig, S. A1 - Raptis, Georgios A1 - Fischer, Uta A1 - Kohler, U. A1 - Hentschel, Bettina A1 - Martin, Rosemarie T1 - 00083 PAI-1 AND UFA AS PARAMETERS OF TUMORASSOCIATED PROTEOLYSIS IN CERVICAL CARCINOMA T2 - International Journal of Gynecologic Cancer Y1 - 2005 U6 - https://doi.org/10.1136/ijgc-00009577-200509001-00083 SN - 1048-891X VL - 15 IS - Suppl 2 EP - 74 PB - BMJ ER - TY - CHAP A1 - Franz, Maja A1 - Zurita, Pía A1 - Diefenthaler, Markus A1 - Mauerer, Wolfgang T1 - Co-Design of Quantum Hardware and Algorithms in Nuclear and High Energy Physics T2 - EPJ Web of Conferences N2 - Quantum computing (QC) has emerged as a promising technology, and is believed to have the potential to advance nuclear and high energy physics (NHEP) by harnessing quantum mechanical phenomena to accelerate computations. In this paper, we give a brief overview of the current state of quantum computing by highlighting challenges it poses and opportunities it offers to the NHEP community. Noisy intermediate-scale quantum (NISQ) computers, while limited by imperfections and small scale, may hold promise for near-term quantum advantages when coupled with co-designed quantum algorithms and special-purpose quantum processing units (QPUs). We explore various applications in NHEP, including quantum simulation, event classification, and realtime experiment control, emphasising the potential of variational quantum circuits and related techniques. To identify current interests of the community, we perform an analysis of recent literature in NHEP related to QC. Y1 - 2024 U6 - https://doi.org/10.1051/epjconf/202429512002 VL - 295 PB - EDP Sciences ER - TY - JOUR A1 - Polz, Julius A1 - Glawion, Luca A1 - Gebisso, Hiob A1 - Altenstrasser, Lukas A1 - Graf, Maximilian A1 - Kunstmann, Harald A1 - Vogl, Stefanie A1 - Chwala, Christian T1 - Temporal Super-Resolution, Ground Adjustment, and Advection Correction of Radar Rainfall Using 3-D-Convolutional Neural Networks JF - IEEE Transactions on Geoscience and Remote Sensing N2 - Weather radars are highly sophisticated tools for quantitative precipitation estimation (QPE) and provide observations with unmatched spatial representativeness. However, their indirect measurement of precipitation high above ground leads to strong systematic errors compared to direct rain gauge measurements. Additionally, the temporal undersampling from 5-min instantaneous radar measurements requires advection correction. We present ResRadNet, a 3-D-convolutional residual neural network approach, to reduce these errors and, at the same time, increase the temporal resolution of the radar rainfall fields by a 5-min short-range prediction of 1-min time-steps. The network is trained to process spatiotemporal sequences of radar rainfall estimates from a composite product derived from 17 C-band weather radars in Germany. In contrast to previous approaches, we present a method that emphasizes the generation of spatiotemporally consistent and advection-corrected country-wide rainfall maps. Our approach significantly increased the Pearson correlation coefficient (PCC) of the radar product (from 0.63 to 0.74) and decreased the root mean squared error (mse) by 22% when compared to 247 rain gauges at a 5-min resolution. An additional large-scale comparison to eight years of data from 1138 independent manual daily gauges confirmed that the improvement is robust and transferable to new locations. Overall, our study shows the benefits of using 3-D convolutional neural networks (CNNs) for weather radar rainfall estimation to provide 1-min, ground-adjusted, that is, bias-corrected with respect to on-ground sensors, and advection-corrected radar rainfall estimates. KW - Rain KW - Radar measurements KW - Meteorological radar KW - Three-dimensional displays KW - Spaceborne radar KW - Spatial resolution KW - Reflectivity KW - Convolutional neural network (CNN) KW - deep learning KW - precipitation KW - residual neural network KW - weather radar Y1 - 2024 U6 - https://doi.org/10.1109/TGRS.2024.3371577 VL - 62 SP - 1 EP - 10 ER - TY - CHAP A1 - Staufer, Susanne A1 - Nadimpalli, Vamsi Krishna A1 - Hauser, Florian A1 - Bittner, Dominik A1 - Grabinger, Lisa A1 - Bugert, Flemming A1 - Ezer, Timur A1 - Röhrl, Simon A1 - Mottok, Jürgen T1 - Persistence of Questionnaire Data on Learning Styles, Learning Strategies AND Personality Traits T2 - ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain N2 - In the context of learning, questionnaires are carried out to gain information about learners. This learner profile has various benefits, like adapting the learning content, promoting of self-reflection, or increasing motivation in learning and therefore better learning results. Some researchers take the results of such questionnaires as ground truth or trust them blindly. Examining how persistent questionnaires are, asking the same questions twice, and comparing the results is a way to prove or falsify this statement. Our research procedure compares the results of three different questionnaires. The first questionnaire is the ILS (index of learning styles) according to the Felder-Silverman Learning Style Model (FSLSM) with about 44 questions. Learning strategies are examined with the LIST-K questionnaire consisting of 39 questions after Klingsieck. The third and last questionnaire is about personality traits. With only ten questions, Rammstedt et al. describe the BFI-10 questionnaire for personality traits. To compare results, the same study with the three named questionnaires is carried out twice with three to four months in between. The sample includes 35 students in their bachelor studies taking the course Software Engineering in a blended learning format. After collecting the questionnaire data from the students, a comparison is made in two different ways. First, we compare the data points based on the given answers. Second, a comparison is made based on the calculated questionnaire results because each of the three questionnaires has its own analysis method. For example, the analysis method of the ILS delivers as a result four integers representing the four characteristics of a learning style, while LIST-K makes a factor analysis. The results of the paper show that both the given answers and the calculated questionnaire results differ. Not one student has given the same answer inside each questionnaire with causes, like a change of learning style, learning strategy, and personality traits, or not filling in conscientiously. KW - learning style KW - learning strategy KW - personality traits KW - questionnaire study Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-78246 SN - 978-84-09-63010-3 SN - 2340-1095 SP - 6310 EP - 6319 PB - IATED ER - TY - RPRT A1 - Taiber, Joachim A1 - Chowdury, M. A1 - Hammond, G. A1 - Hipp, V. A1 - Huttner, B. A1 - Lonien, J. A1 - Mottok, Jürgen A1 - Neukart, Florian A1 - Stengel, T. T1 - Unsettled Topics Concerning the Impact of Quantum Technologies on Automotive Cybersecurity N2 - Quantum computing is considered the “next big thing” when it comes to solving computational problems impossible to tackle using conventional computers. However, a major concern is that quantum computers could be used to crack current cryptographic schemes designed to withstand traditional cyberattacks. This threat also impacts future automated vehicles as they become embedded in a vehicle-to-everything (V2X) ecosystem. In this scenario, encrypted data is transmitted between a complex network of cloud-based data servers, vehicle-based data servers, and vehicle sensors and controllers. While the vehicle hardware ages, the software enabling V2X interactions will be updated multiple times. It is essential to make the V2X ecosystem quantum-safe through use of “post-quantum cryptography” as well other applicable quantum technologies. This SAE EDGE™ Research Report considers the following three areas to be unsettled questions in the V2X ecosystem: How soon will quantum computing pose a threat to connected and automated vehicle technologies? What steps and measures are needed to make a V2X ecosystem “quantum-safe?” What standardization is needed to ensure that quantum technologies do not pose an unacceptable risk from an automotive cybersecurity perspective? Y1 - 2020 U6 - https://doi.org/10.4271/EPR2020026 SN - 2640-3536 CY - Warrendale, Pennsylvania, USA ER - TY - JOUR A1 - Reicheneder, Matthias A1 - Westner, Markus A1 - Matschi, Markus T1 - IT-Near- und Offshoring in deutschen Großunternehmen: Aktueller Stand, Motive und Auswahlkriterien JF - HMD Praxis der Wirtschaftsinformatik N2 - Die vorliegende Studie untersucht die aktuelle IT-Near- und Offshoring-Praxis in deutschen Großunternehmen. Dafür wurden 33 CIOs und IT-Führungskräfte mittels Interviews befragt. Haupttreiber der geografischen Verlagerung von IT-Services ins Ausland ist die Ressourcenverfügbarkeit in anderen Ländern, bedingt durch den Fachkräftemangel in Deutschland. Dies trifft auch auf die Auswahl geeigneter IT-Services für das Near- und Offshoring zu. Während IT-Near- und Offshoring historisch primär aufgrund von Kosteneinsparungen initiiert wurde, spielt dieser Aspekt heute eine untergeordnete Rolle. Die Interviewteilnehmer und -teilnehmerinnen sehen in Kosteneinsparungen zwar immer noch einen positiven Effekt, erwarten aber, dass dieser in Zukunft aufgrund der Angleichung des Kostenniveaus schwinden wird. Die Unternehmen verlagern hauptsächlich Applikationsbetrieb und -entwicklung, erkennen jedoch zunehmend das Potenzial, auch höherwertige Aufgaben, z. B. Projektmanagement und Unternehmensarchitekturmanagement, aus geografisch entfernteren Ländern erbringen zu lassen. Unternehmen, die ausschließlich IT-Nearshoring betreiben, erbringen weniger als ein Drittel ihrer IT-Services aus nahegelegenen Ländern. Firmen mit IT-Offshoring-Präsenzen weisen einen höheren IT-Near‑/Offshoringgrad auf und verlagern knapp die Hälfte der eigenen IT-Serviceerbringung ins Ausland. Die beliebtesten Länder sind Portugal für das Nearshoring und Indien für das Offshoring. KW - Nearshoring KW - Offshoring KW - IT Services KW - Drivers KW - Selection Criteria KW - Large Companies KW - Study KW - Motive KW - Auswahlkriterien KW - Großunternehmen KW - Studie Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-79582 SN - 1436-3011 N1 - Corresponding author der OTH Regensbrg: Markus Westner PB - Springer Nature CY - Wiesbaden ER - TY - JOUR A1 - Mauerer, Wolfgang A1 - Joblin, Mitchell A1 - Tamburri, Damian A1 - Paradis, Carlos A1 - Kazman, Rick A1 - Apel, Sven T1 - In Search of Socio-Technical Congruence: A Large-Scale Longitudinal Study JF - IEEE Transactions on Software Engineering (TSE) N2 - This paper describes a large-scale empirical study investigating the relevance of socio-technical congruence over key basic software quality metrics, namely, bugs and churn. That is, we explore whether alignment or misalignment of social communication structures and technical dependencies in large software projects influences software quality. To this end, we have defined a quantitative and operational notion of socio-technical congruence, which we call /socio-technical motif congruence/ (STMC). STMC is a measure of the degree to which developers working on the same file or on two related files, need to communicate. As socio-technical congruence is a complex and multi-faceted phenomenon, the interpretability of the results is one of our main concerns, so we have employed a careful mixed-methods statistical analysis. In particular, we provide analyses with similar techniques as employed by seminal work in the field to ensure comparability of our results with the existing body of work. The major result of our study, based on an analysis of 25 large open-source projects, is that STMC is /not/ related to project quality measures---software bugs and churn---in any temporal scenario. That is, we find no statistical relationship between the alignment of developer tasks and developer communications on one hand, and project outcomes on the other hand. We conclude that, wherefore congruence does matter as literature shows, then its measurable effect lies elsewhere. KW - Socio-Technical Congruence KW - Human Factors in Software Engineering; KW - Graph Analysis KW - Empirical Software Engineering KW - Quantitative Software Engineering KW - Mixed-Methods Research KW - Socio-Technical Analysis Y1 - 2022 U6 - https://doi.org/10.1109/TSE.2021.3082074 N1 - Corresponding author: Wolfgang Mauerer VL - 48 IS - 8 SP - 3159 EP - 3184 PB - IEEE ER - TY - CHAP A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Ezer, Timur A1 - Mottok, Jürgen A1 - Gruber, Hans ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Integrating deliberate practice in software engineering education T2 - ICERI 2024 Proceedings, 17th annual International Conference of Education, Research and Innovation,11-13 November, 2024, Seville, Spain Y1 - 2024 U6 - https://doi.org/10.21125/iceri.2024.1331 SP - 5457 EP - 5466 PB - IATED ER - TY - GEN A1 - Stark, T. A1 - Schreistetter, Stefan A1 - Reuter, Rebecca A1 - Hauser, Florian A1 - Holmqvist, Kenneth A1 - Mottok, Jürgen A1 - Gruber, Hans T1 - Learning from Gaze: Eye Movement Modeling Examples in Software Engineering Education T2 - Earli Book of Abstracts Y1 - 2021 UR - https://earli.org/assets/files/BOA-2021.pdf SP - 291 PB - Earli ER - TY - CHAP A1 - Gabriel, Christian A1 - Wittmann, Christoffer A1 - Hacker, B. A1 - Mauerer, Wolfgang A1 - Huntington, E. A1 - Sabuncu, M. A1 - Marquardt, Christoph A1 - Leuchs, Gerd T1 - A high-speed secure quantum random number generator based on vacuum states T2 - IEEE/OSA Conference on Lasers and Electro-Optics (CLEO), 06-11 May 2012, San Jose CA USA N2 - A high-speed continuous-variable quantum random bit generator with an expected effective bit generation rate of up to 10 GBit/s is presented. The obtained bit sequences are truly random and unique, i.e. they cannot be known by an adversary. Y1 - 2012 PB - Optical Society of America ER - TY - JOUR A1 - Moser, Elisabeth A1 - Jobst, Simon A1 - Bierl, Rudolf A1 - Jenko, Frank T1 - A Deep Learning System to Transform Cross-Section Spectra to Varying Environmental Conditions JF - Vibrational Spectroscopy N2 - Absorption cross-sections provide a basis for many gas sensing applications. Therefore, any error in molecular cross-sections caused by varying environmental conditions propagates to spectroscopic applications. Original molecular cross-sections in varying environmental conditions can only be simulated for some molecules, whereas for most multi-atom molecules, one must rely on high-precision measurements at certain environmental configurations. In this study, a deep learning system trained with simulated absorption cross-sections for predicting cross-sections at a different pressure configuration is presented. The system’s capability to transfer to measured, multi-atom cross-sections is demonstrated. Thus, it provides an alternative to (pseudo-) line lists whenever the required information for simulation is unavailable. The predictive performance of the system was evaluated on validation data via simulation, and its transfer learning capabilities were demonstrated on actual measurement chlorine nitrate data. From the comparison between the system and line lists, the system shows slightly worse performance than pseudo-line lists but its predictive quality is still deemed acceptable with less than 5% relative integral change with a highly localized error around the peak center. This opens a promising way for further research to use deep learning to simulate the effect of varying environmental conditions on absorption cross-sections. KW - Spectroscopy KW - Deep learning KW - Simulation KW - Pressure broadening KW - Pseudo-line lists KW - Transfer learning Y1 - 2022 U6 - https://doi.org/10.1016/j.vibspec.2022.103410 SN - 0924-2031 VL - 122 IS - September PB - Elsevier ER - TY - THES A1 - Ramsauer, Ralf T1 - OSS Architecture for Mixed-Criticality Systems BT - A Dual View from a Software and System Engineering Perspective N2 - Computer-based automation in industrial appliances led to a growing number of logically dependent, but physically separated embedded control units per appliance. Many of those components are safety-critical systems, and require adherence to safety standards, which is inconsonant with the relentless demand for features in those appliances. Features lead to a growing amount of control units per appliance, and to a increasing complexity of the overall software stack, being unfavourable for safety certifications. Modern CPUs provide means to revise traditional separation of concerns design primitives: the consolidation of systems, which yields new engineering challenges that concern the entire software and system stack. Multi-core CPUs favour economic consolidation of formerly separated systems with one efficient single hardware unit. Nonetheless, the system architecture must provide means to guarantee the freedom from interference between domains of different criticality. System consolidation demands for architectural and engineering strategies to fulfil requirements (e.g., real-time or certifiability criteria) in safety-critical environments. In parallel, there is an ongoing trend to substitute ordinary proprietary base platform software components by mature OSS variants for economic and engineering reasons. There are fundamental differences of processual properties in development processes of OSS and proprietary software. OSS in safety-critical systems requires development process assessment techniques to build an evidence-based fundament for certification efforts that is based upon empirical software engineering methods. In this thesis, I will approach from both sides: the software and system engineering perspective. In the first part of this thesis, I focus on the assessment of OSS components: I develop software engineering techniques that allow to quantify characteristics of distributed OSS development processes. I show that ex-post analyses of software development processes can be used to serve as a foundation for certification efforts, as it is required for safety-critical systems. In the second part of this thesis, I present a system architecture based on OSS components that allows for consolidation of mixed-criticality systems on a single platform. Therefore, I exploit virtualisation extensions of modern CPUs to strictly isolate domains of different criticality. The proposed architecture shall eradicate any remaining hypervisor activity in order to preserve realtime capabilities of the hardware by design, while guaranteeing strict isolation across domains. KW - real-time operating system KW - mixed-criticality KW - static hardware partitioning KW - development processes KW - development process reconstruction KW - quantitative software engineering Y1 - 2021 UR - https://www.repo.uni-hannover.de/bitstream/handle/123456789/11815/Dissertation_Ramsauer-Ralf.pdf?sequence=3&isAllowed=y PB - Leibniz Universität Hannover ER - TY - CHAP A1 - Marinkovic, Minja A1 - Galka, Stefan A1 - Meißner, Sebastian T1 - Digital Twins for Internal Transport Systems: Use Cases, Functions, and System Architecture T2 - Proceedings of the 56th Hawaii International Conference on System Sciences: January 3-6, 2023, Maui, Hawaii, USA N2 - Internal transport systems are an essential part of intralogistics in production and distribution facilities. These are characterized by a variety of technologies as well as a multitude of interactions with other processes, such as warehouse, picking, and production processes. Therefore, resource planning and control of these systems is complex, especially for discontinuous conveyors. In this task, users can be supported by Digital Twins for decision-making, as they are suitable for investigating both future system states and possible actions. However, relevant use cases that are generally applicable across sectors as well as a generic system architecture for Digital Twins for resource planning and process control of in-plant transport systems have not yet been sufficiently investigated. In this paper, use cases are presented, relevant functions defined, and, finally, a generic functional and a logical reference architecture described. This is conducted with the design science in information systems research method together with a Systems Engineering approach. The use cases are determined at industrial partners of the research project TwInTraSys, which explores Digital Twins for the planning and control of internal transport systems. They are generalized and, thus, also applicable to other production and distribution facilities in different sectors. Further, the reference architecture can provide a basis for the successful implementation of the Digital Twin. KW - Intelligent Decision Support for Logistics and Supply Chain Management KW - intralogistics KW - internal transport systems KW - digital twin Y1 - 2023 SN - 978-0-9981331-6-4 SP - 1195 EP - 1204 PB - University of Hawaiʻi at Mānoa CY - Honolulu, HI ER - TY - CHAP A1 - Schmidbauer, Lukas A1 - Wintersperger, Karen A1 - Lobe, Elisabeth A1 - Mauerer, Wolfgang T1 - Polynomial Reduction Methods and their Impact on QAOA Circuits T2 - IEEE International Conference on Quantum Software (QSW), 7-13 July 2024, Shenzhen, China N2 - Abstraction layers are of paramount importance in software architecture, as they shield the higher-level formulation of payload computations from lower-level details. Since quantum computing (QC) introduces many such details that are often unaccustomed to computer scientists, an obvious desideratum is to devise appropriate abstraction layers for QC. For discrete optimisation, one such abstraction is to cast problems in quadratic unconstrained binary optimisation (QUBO) form, which is amenable to a variety of quantum approaches. However, different mathematically equivalent forms can lead to different behaviour on quantum hardware, ranging from ease of mapping onto qubits to performance scalability. In this work, we show how using higher-order problem formulations (that provide better expressivity in modelling optimisation tasks than plain QUBO formulations) and their automatic transformation into QUBO form can be used to leverage such differences to prioritise between different desired non-functional properties for quantum optimisation. Based on a practically relevant use-case and a graph-theoretic analysis, we evaluate how different transformation approaches influence widely used quantum performance metrics (circuit depth, gates count, gate distribution, qubit scaling), and also consider the classical computational efforts required to perform the transformations, as they influence possibilities for achieving future quantum advantage. Furthermore, we establish more general properties and invariants of the transformation methods. Our quantitative study shows that the approach allows us to satisfy different trade-offs, and suggests various possibilities for the future construction of general-purpose abstractions and automatic generation of useful quantum circuits from high-level problem descriptions. KW - HW-SW co design KW - NISQ systems KW - noisy quantum computing KW - quantum software engineering Y1 - 2024 U6 - https://doi.org/10.1109/QSW62656.2024.00018 SP - 35 EP - 45 ER - TY - CHAP A1 - Reindl, Andrea A1 - Lang, Andreas A1 - Niemetz, Michael A1 - Meier, Hans T1 - Switching and Averaging Models of a Bidirectional, Half-Bridge Based DC-DC converter with Load Distribution T2 - Proceedings of the 15th International Modelica Conference 2023, Aachen, October 9-11 N2 - Batteries are used in numerous applications such as mobile devices, electric vehicles, home storage systems and islanded microgrids. Bidirectional DC-DC converters are vital for the integration of batteries, for the power conversion during (dis)charge and the battery management. Modeling of these is helpful, especially for the design of larger, more complex systems consisting of multiple DC-DC converters in parallel. Due to the high switching frequencies, the simulation of DC-DC converters is associated with increased computational time and effort. In this paper, three models of different complexity and accuracy are proposed for a bidirectional DC-DC converter consisting of two phase-shifted half-bridges. Two switching models, which differ mainly in the way the mosfets are driven, account for the individual switching operations and exhibit high accuracy. An averaging model replaces the switching elements with current and voltage sources providing the mean values. It is particularly suitable for multiple components and longer simulation durations. The dynamic behavior of the models is analyzed using the step responses of the load current. For validation, these are compared with the theoretical transfer function. The three models are analyzed comparatively in terms of computational time and effort. The calculation time of the averaging model has been reduced by two thirds compared to the strictly complementary switching model and by 96% relative to the model with diode emulation mode. The averaging model requires only one third of the computation time of the complementary switching model and only 3.5% of that of the model with diode emulation. Recommendations for the use of the models are given and a possible use case is shown. Two parallel connected DC-DC converters with load current sharing between them are simulated using the averaging model. KW - Bidirectional DC/DC Converter KW - Averaging Model KW - Switching Model KW - Computational Effort KW - Modelica KW - Half Bridge KW - Circuit Averaging Y1 - 2023 U6 - https://doi.org/10.3384/ecp204683 PB - OJS ER - TY - CHAP A1 - Bugert, Flemming A1 - Staufer, Susanne A1 - Bittner, Dominik A1 - Nadimpalli, Vamsi Krishna A1 - Ezer, Timur A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Mottok, Jürgen T1 - Ariadne's Thread for Unravelling Learning Paths: Identifying Learning Styles via Hidden Markov Models T2 - 2024 IEEE Global Engineering Education Conference (EDUCON), 08-11 May 2024, Kos Island, Greece N2 - Modern education through Learning Management Systems (LMSs) provides learners with personalized learning paths. This is achieved by first querying the learning style according to the theory of Felder and Silverman to recommend suitable learning content. However, a rigid learning style representation is lacking of adaptability to the learners' choices. Therefore, the present study evaluates the idea of providing adaption to the representation of learning styles by using Hidden Markov Models (HMMs). Thus, data is collected from participants out of the Higher Education Area. The Index of Learning Styles questionnaire is used to obtain the learning style based on the theory of Felder and Silverman. Also, a questionnaire that asks the respondents to create a preferred learning path with the sequence length of nine learning elements is provided. From the given data, we initially evaluate the probability relationships between learning styles and learning elements. Then, we use the Viterbi algorithm in HMMs to identify alterations in learning styles from the provided learning paths. The alignment is then quantified by introducing a metric called support value. The findings imply that our concept can be used to adapt the learning style based on the user's real choice of learning elements. Thus, the proposed model also offers a way to integrate a feedback loop within LMSs leading to an improvement of learning path recommendation algorithms. KW - Surveys KW - Knowledge engineering KW - Feedback loop KW - Learning management systems KW - Uncertainty KW - Viterbi algorithm Y1 - 2024 U6 - https://doi.org/10.1109/EDUCON60312.2024.10578825 SN - 2165-9567 SP - 1 EP - 7 PB - IEEE ER - TY - CHAP A1 - Völkl, Jakob A1 - Melzer, Matthias A1 - Dünnweber, Jan A1 - Sarkar, Amitrajit T1 - Dynamic Route Planning for a Data Collecting Luggage Transport Service T2 - 18th IEEE International Conference on Control & Automation, June 18-21, 2024, Reykjavík, Iceland N2 - Control and Automation of services of the urban infrastructure offered to citizens and tourists are elementary parts of a smart city. But both rely on a stable supply of data from sensors spread across the whole city, e. g., the fill level sensors of waste bins needed for a waste management tool which we developed in a collaboration with the Regensburg city council for the on-demand collection of waste bins. Europe has a lot of historic cities like Regensburg with narrow streets and huge building walls, some made from granite and fieldstones, which often represents an insurmountable obstacle to wireless data transmission. The reduction of the road traffic volume poses an additional challenge for city planners. By means of networked planning and simulation software, the situation, state and efficiency of citywide logistic services can be monitored and optimized. In the course of such optimizations, we propose the combination of digital and logistic services. As an example, we show that monitoring state information, such as the waste bin fill levels, can be accomplished using the same vehicles and the same planning software, that is used for luggage transportation. Moreover, we describe how we adapted a solver for a variant of the TSP, namely the prize-collecting traveling salesman, to optimize the route planning dynamically. Y1 - 2024 PB - IEEE ER - TY - INPR A1 - Borg, Leise A1 - Frikel, Jürgen A1 - Jørgensen, Jakob Sauer A1 - Quinto, Eric Todd T1 - Theorems that Characterize Artifacts for Arbitrary Limited X-ray CT Data N2 - This article provides a mathematical classification of artifacts from arbitrary incom-plete X-ray tomography data when using the classical filtered backprojection algorithm. Usingmicrolocal analysis, we prove that all artifacts arise from points at the boundary of the data set.Our results show that, depending on the geometry of the data set boundary, two types of artifactscan arise: object-dependent and object-independent artifacts. The object-dependent artifacts aregenerated by singularities of the object being scanned and these artifacts can extend all along lines.This is a generalization of the streak artifacts observed in limited angle CT. The article also char-acterizes two new phenomena: the object-independent artifacts are caused only by the geometryof the data set boundary; they occur along lines if the boundary of the data set is not smooth andalong curves if the boundary of the data set is smooth. In addition to the geometric descriptionof artifacts, the article also provides characterizations of their strength in Sobolev scale in certaincases. Moreover, numerical reconstructions from simulated and real data are presented illustratingour theorems.This work is motivated by a reconstruction we present from a synchrotron data set in whichartifacts along lines appeared that were independent of the object.The results of this article apply to a wide range of well-known incomplete data problems, in-cluding limited angle CT and region of interest tomography, as well as to unconventional x-ray CTimaging setups. Some of those problems are explicitly addressed in this article, theoretically and numerically. Y1 - 2017 UR - https://www.researchgate.net/publication/318360078_Theorems_that_Characterize_Artifacts_for_Arbitrary_Limited_X-ray_CT_Data ET - version 6 ER - TY - CHAP A1 - Borg, Leise A1 - Jørgensen, Jakob Sauer A1 - Frikel, Jürgen A1 - Quinto, Eric Todd A1 - Sporring, Jon T1 - Reducing artifacts from varying projection truncations T2 - 3rd International Conference on Tomography of Materials and Structures, Lund, Sweden, 26-30 June 2017, ICTMS2017-65-1 N2 - We study samples with full and partial occlusion causing streak artifacts, and propose two mod-ifications of filtered backprojection for artifact removal. Data is obtained by the SPring-8 synchrotron using a monochromatic parallel-beam scan [1]. Thresholding in the sinogram segments the metal, resulting in edges on which we apply 1) a smooth transition, or 2) a Dirichlet boundary condition. KW - X-ray tomography KW - projection truncation KW - streak artifacts KW - boundary conditions Y1 - 2017 UR - https://meetingorganizer.copernicus.org/ICTMS2017/ICTMS2017-65-1.pdf ER - TY - CHAP A1 - Bugert, Flemming A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Hauser, Florian A1 - Nadimpalli, Vamsi Krishna A1 - Staufer, Susanne A1 - Mottok, Jürgen T1 - Towards Learning Style Prediction based on Personality T2 - Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023 N2 - This paper assesses the relation between personality, demographics, and learning style. Hence, data is collected from 200 participants using 1) the BFI-10 to obtain the participant’s expression of personality traits according to the five-factor model, 2) the ILS to determine the participant’s learning style according to Felder and Silverman, and 3) a demographic questionnaire. From the obtained data, we train and evaluate a Bayesian network. Using Bayesian statistics, we show that age and gender slightly influence personality and that demographics as well as personality have at least a minor effect on learning styles. We also discuss the limitations and future work of the presented approach. Y1 - 2023 SN - 978-1-4503-9956-2 U6 - https://doi.org/10.1145/3593663.3593682 SP - 48 EP - 55 PB - ACM ER - TY - CHAP A1 - Bittner, Dominik A1 - Hauser, Florian A1 - Nadimpalli, Vamsi Krishna A1 - Grabinger, Lisa A1 - Staufer, Susanne A1 - Mottok, Jürgen T1 - Towards Eye Tracking based Learning Style Identification T2 - Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023 N2 - The dropout rate at universities has been very high for years. Thereby, the inexperience and lack of knowledge of students in dealing with individual learning paths in various courses of study plays a decisive role. Adaptive learning management systems are suitable countermeasures, in which learners’ learning styles are classified using questionnaires or computationally intensive algorithms before a learning path is suggested accordingly. In this paper, a study design for student learning style classification using eye tracking is presented. Furthermore, qualitative and quantitative analyses clarify certain relationships between students’ eye movements and learning styles. With the help of classification based on eye tracking, the filling out of questionnaires or the integration of computationally or cost-intensive algorithms can be made redundant in the future. Y1 - 2023 SN - 978-1-4503-9956-2 U6 - https://doi.org/10.1145/3593663.3593680 SP - 138 EP - 147 PB - ACM ER - TY - CHAP A1 - Frikel, Jürgen A1 - Quinto, Eric Todd ED - Burger, Martin ED - Quinto, Eric Todd ED - Louis, Alfred K. T1 - Artifacts in limited view tomography T2 - Oberwolfach Reports Y1 - 2014 U6 - https://doi.org/10.4171/OWR/2014/37 VL - 11 IS - 3 SP - 2047 EP - 2114 ER - TY - CHAP A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Bittner, Dominik A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Staufer, Susanne A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Towards personalized learning paths in adaptive learning management systems: bayesian modelling of psychological theories T2 - Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023 N2 - In educational research, non-personalized learning content increases learners' cognitive load, causing them to lower their performance and sometimes drop out of the course. Personalizing learning content with learners’ unique characteristics, like learning styles, personality traits, and learning strategies, is being suggested to improve learners’ success. Several theories exist for assessing learners’ unique characteristics. By the end of 2020, 71 learning style theories have been formulated, and research has shown that combining multiple learning style theories to recommend learning paths yields better results. As of the end of 2022, there is no single research that demonstrates a relationship between the Index of Learning Styles (ILS) based Felder-Silverman learning style model (FSLSM) dimensions, Big Five (BFI-10) based personality traits, and the Learning strategies in studying (LIST-K) based learning strategies factors for personalizing learning content. In this paper, an innovative approach is proposed to estimate the relationship between these theories and map the corresponding learning elements to create personalized learning paths. Respective questionnaires were distributed to 297 higher education students for data collection. A three-step approach was formulated to estimate the relationship between the models. First, a literature search was conducted to find existing studies. Then, an expert interview was carried out with a group of one software engineering education research professor, three doctoral students, and two master’s students. Finally, the correlations between the students' questionnaire responses were calculated. To achieve this, a Bayesian Network was built with expert knowledge from the three-step approach, and the weights were learned from collected data. The probability of individual FSLSM learning style dimensions was estimated for a new test sample. Based on the literature, the learning elements were mapped to the respective FSLSM learning style dimensions and were initiated as learning paths to the learners. The next steps are proposed to extend this framework and dynamically recommend learning paths in real time. In addition, the individual levels of learning style dimensions, personality traits, and learning strategies can be considered to improve the recommendations. Further, using probabilities for mapping learning elements to learning styles can increase the chance of initiating multiple learning paths for an individual learner. Y1 - 2023 U6 - https://doi.org/10.21125/iceri.2023.1144 SP - 4593 EP - 4603 PB - IATED ER - TY - CHAP A1 - Ezer, Timur A1 - Plößl, Moritz A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Staufer, Susanne A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Hauser, Florian A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Deep learning for eye movement classification T2 - ICERI 2024 Proceedings, 17th annual International Conference of Education, Research and Innovation,11-13 November, 2024, Seville, Spain Y1 - 2024 U6 - https://doi.org/10.21125/iceri.2024.1028 SP - 4056 EP - 4065 PB - IATED ER - TY - INPR A1 - Gaube, Susanne A1 - Jussupow, Ekaterina A1 - Kokje, Eesha A1 - Khan, Jowaria A1 - Bondi-Kelly, Elizabeth A1 - Schicho, Andreas A1 - Kitamura, Felipe Campos A1 - Koch, Timo Kevin A1 - Ezer, Timur A1 - Mottok, Jürgen A1 - Lermer, Eva A1 - Ghassemi, Marzyeh A1 - Colak, Errol T1 - Underreliance Harms Human-AI Collaboration More Than Overreliance in Medical Imaging N2 - Importance: The use of artificial intelligence (AI) to support clinicians in diagnostic decision-making holds significant potential; however, evidence regarding its clinical utility remains mixed. In many cases, the interaction between healthcare professionals and AI systems does not improve collaborative performance compared to the standalone performance of humans or AI. Currently, the underlying mechanisms that limit human-AI collaboration are poorly understood. Objective: To examine the impact of AI advice on diagnostic decision-making among experts and novices, focusing on understanding the role of explainability (XAI) on users’ reliance on advice. Design, Setting, and Participants: A mixed-methods design combining a crossover experimental design with a think-aloud and an eye-tracking study arm was conducted in 2023. Participants were task experts (radiologists) and novices (non-radiologist physicians and medical trainees) from 10 countries, with the think-aloud and eye-tracking conducted in Germany. Intervention: Participants reviewed 50 patient cases containing head CT scans and patient information. Every case was reviewed in three time-separate sessions in randomized order. In each session, participants were exposed to a different experimental condition: (a) control, i.e., no AI prediction presented; (b) basic advice, i.e., AI prediction without annotations; and (c) XAI advice, i.e., AI prediction with annotations. For each case, participants had to determine if the patients had an intracranial hemorrhage (ICH), rate their confidence, and, if applicable, the usefulness of the AI advice. Main Outcome(s) and Measure(s): Diagnostic performance, confidence in the diagnosis, case reading time, and AI advice usefulness ratings. Results: The data analysis included 125 participants. The mean age was 28.5 years (SD = 6.72), and 55.2% identified as female. Underreliance on correct AI advice was associated with high uncertainty and had a more detrimental impact on diagnostic performance than overreliance on incorrect advice. XAI advice reduced underreliance and improved performance and confidence, particularly when reviewing more difficult cases with ICH. AI advice, particularly XAI, did not reduce reading time. XAI was perceived as more useful than basic AI advice, especially among novices. Conclusions and Relevance: Our findings indicate that underreliance on AI might be more harmful than overreliance, highlighting the need to develop efficient counterstrategies beyond current XAI methods. Y1 - 2024 U6 - https://doi.org/10.31219/osf.io/4wv8j PB - OSFPreprints ER - TY - CHAP A1 - Huang, Wenfei A1 - Melzer, Matthias A1 - Dünnweber, Jan T1 - Optimizing Smart Retail by Experiment Using an Online AI Model Exploration Interface T2 - 2024 Winter Simulation Conference (WSC), 15-18 December 2024, Orlando, FL, USA N2 - Smart retail technologies save grocery store operators a lot of work. At the same time, these technologies produce valuable data for building sustainable and economical inventory management strategies. AI models can be trained for sales forecasting using the data. The forecasts support the provisioning of fresh food over the whole week and help reducing food waste. In this paper, we present a Web portal which we developed to allow grocery store operators experiments with AI models revealing interrelations between observed and anticipated customer behavior. Clickable diagrams facilitate the exploration of data sets combining historical data and synthetically generated data. Pricing and ordering can be adapted accordingly to the simulated forecasts. By means of a case study, we show that our simulations are not only useful for predicting future sales but for other smart retail tasks as well. Y1 - 2024 U6 - https://doi.org/10.1109/WSC63780.2024.10838897 SP - 2631 EP - 2642 PB - IEEE ER - TY - CHAP A1 - Hoess, Nicole A1 - Paradis, Carlos A1 - Kazman, Rick A1 - Mauerer, Wolfgang T1 - Does the Tool Matter? Exploring Some Causes of Threats to Validity in Mining Software Repositories T2 - 2025 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), Montreal, QC, Canada, March, 4-7, 2025 N2 - Software repositories are an essential source of information for software engineering research on topics such as project evolution and developer collaboration. Appropriate mining tools and analysis pipelines are therefore an indispensable precondition for many research activities. Ideally, valid results should not depend on technical details of data collection and processing. It is, however, widely acknowledged that mining pipelines are complex, with a multitude of implementation decisions made by tool authors based on their interests and assumptions. This raises the questions if (and to what extent) tools agree on their results and are interchangeable. In this study, we use two tools to extract and analyse ten large software projects, quantitatively and qualitatively comparing results and derived data to better understand this concern. We analyse discrepancies from a technical point of view, and adjust code and parametrisation to minimise replication differences. Our results indicate that despite similar trends, even simple metrics such as the numbers of commits and developers may differ by up to 500%. We find that such substantial differences are often caused by minor technical details. We show how tool-level and data post-processing changes can overcome these issues, but find they may require considerable efforts. We summarise identified causes in our lessons learned to help researchers and practitioners avoid common pitfalls, and reflect on implementation decisions and their influence in ensuring obtained data meets explicit and implicit expectations. Our findings lead us to hypothesise that similar uncertainties exist in other analysis tools, which may limit the validity of conclusions drawn in tool-centric research. KW - Codes KW - Collaboration KW - Data collection KW - Data mining KW - Developer Networks KW - Empirical Software Engineering KW - Market research KW - Measurement KW - Mining Software Repositories KW - Pipelines KW - Research Software KW - Software engineering KW - Uncertainty Y1 - 2025 SN - 979-8-3315-3510-0 U6 - https://doi.org/10.1109/SANER64311.2025.00067 SP - 645 EP - 656 PB - IEEE ER - TY - CHAP A1 - Bittner, Dominik A1 - Hauser, Florian A1 - Engl, Fabian A1 - Mottok, Jürgen ED - Mottok, Jürgen ED - Hagel, Georg T1 - Eye Movement Modelling Examples on Usability Heuristics T2 - Proceedings of the 6th European Conference on Software Engineering Education : ECSEE 2025, Seeon Germany, June 02-04, 2025 N2 - The user interface (UI) and user experience (UX) design is of crucial importance for human-computer interaction (HCI), particularly in the context of web applications. In light of the high expectations of users and the competitive nature of the market, it is imperative to employ usability measurement techniques to avoid losing users. Heuristic evaluation (HE) is a cost- and resource-efficient method for evaluating the usability of websites in which evaluators are guided by heuristics. However, the level of expertise of the evaluators has a significant impact on the results, with experts identifying up to 50% more usability issues than novices. To address this gap, this paper proposes Eye Movement Modeling Examples (EMMEs) to demonstrate Jakob Nielsen’s ten usability heuristics in an easy-to-understand format for all levels of experience while also incorporating expert knowledge. In particular, the eye movements and verbal feedback of a usability expert are recorded as the expert analyses the usability of a simple website application in terms of Jakob Nielsen’s ten usability heuristics. This reveals the strategies and cognitive processes of the expert when assessing the usability of a website and makes them more tangible for non-experts or novices. The findings of a questionnaire-based assessment indicate that EMMEs are perceived as beneficial and supportive during the learning process. Ultimately, this comprehensive analysis not only enables a deeper understanding of heuristics for usability novices, but could also lead to EMMEs being applied more efficiently in diverse domains. Y1 - 2025 SN - 9798400712821 U6 - https://doi.org/10.1145/3723010.3723035 SP - 106 EP - 114 PB - ACM ER - TY - RPRT A1 - Marschall, Felix T1 - HEKATE - Implementierung eines Dashboards zur Visualisierung von Auswertungen des HASKI Konzepts für einen umfassenden Einblick in den Lernprozess BT - Projektarbeit N2 - In der gegenwärtigen Bildungslandschaft erfährt die adaptive Hochschullehre eine zunehmende Relevanz, da traditionelle Lehrmethoden vielfach nicht mehr hinreichend sind, um den individuellen Bedürfnissen der Studierenden zu entsprechen. Das Projekt HEKATE zielt darauf ab, die Erkenntnisse aus dem HASKI-System, einem innovativen Ansatz für personalisierte Lernunterstützung basierend auf KI und maschinellem Lernen, effektiv zu visualisieren. HEKATE ergänzt das HASKI-System durch die Entwicklung eines Dashboards, welches eine transparente und nachvollziehbare Darstellung der Lernstildaten ermöglicht. Das Ziel des Projekts besteht in der Umsetzung einer Visualisierungslösung, die sich durch eine hohe Benutzerfreundlichkeit sowie Leistungsfähigkeit auszeichnet und alle relevanten Lern- und Nutzungsdaten Studierender adäquat abbildet. Die funktionalen Anforderungen umfassten die präzise Darstellung von Lernstil-Ergebnissen, Quiz- und Übungsergebnissen sowie die Integration des ARIADNE-Konzepts. Des Weiteren werden nichtfunktionale Ziele definiert, welche eine hohe Benutzerfreundlichkeit, Systemsicherheit, kurze Ladezeiten sowie eine verlässliche Datenverarbeitung umfassten. Hekate bietet sowohl für Studierende als auch für Lehrende einen erheblichen Mehrwert, indem es Lern- und Nutzungsmuster auf einfache und intuitive Weise visualisiert. Die Integration in die HASKI-Umgebung und Moodle gewährleistet eine nahtlose Einbindung der Anwendung in bestehende Lernumgebungen, wodurch sich der Nutzen weiter steigert. In künftigen Entwicklungsstufen könnten zusätzliche Visualisierungsoptionen und Funktionen integriert werden, um das System weiter zu optimieren und an die Bedürfnisse der Nutzer anzupassen. N2 - In the current educational landscape, adaptive university teaching is becoming increasingly relevant, as traditional teaching methods are often no longer sufficient to meet the individual needs of students. The HEKATE project aims to effectively visualise the findings from the HASKI system, an innovative approach to personalised learning support based on AI and machine learning. HEKATE complements the HASKI system by developing a dashboard that enables a transparent and comprehensible visualisation of learning style data. The aim of the project is to implement a visualisation solution that is characterised by a high level of user-friendliness and performance and adequately depicts all relevant learning and usage data of students. The functional requirements included the precise visualisation of learning style results, quiz and exercise results as well as the integration of the ARIADNE concept. Non-functional goals were also defined, which included a high level of user-friendliness, system security, short loading times and reliable data processing. Hekate offers significant added value for both students and teachers by visualising learning and usage patterns in a simple and intuitive way. The integration into the HASKI environment and Moodle ensures a seamless integration of the application into existing learning environments, which further increases the benefits. In future development stages, additional visualisation options and functions could be integrated in order to further optimise the system and adapt it to the needs of users. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-79221 PB - Regensburg ER - TY - CHAP A1 - Hauser, Florian A1 - Staufer, Susanne A1 - Grabinger, Lisa A1 - Röhrl, Simon A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - On the analysis of student learning strategies: using the LIST-K questionnaire ro generate ai-based individualized learning paths T2 - Proceedings of the 16th annual International Conference of Education, Research and Innovation (ICERI 2023), Seville, Spain, 11/13/2023 - 11/14/2023 N2 - This paper presents the results of a data collection with the LIST-K questionnaire. This questionnaire measures students’ learning strategies and shows which strategies are particularly dominant or rather weak. Learning strategies have long been a major area of research in educational science and psychology. In these disciplines, learning strategies are understood as intentional behaviors and cognitive skills that learners employ to effectively complete learning tasks, by selecting, acquiring, organizing, and integrating information into their existing knowledge for long-term retention. The LIST-K, developed by Klingsieck in 2018, was chosen for accessing learning strategies due to its thematic suitability, widespread use, and test economy. It covers a total of four main categories (i.e., cognitive strategies, metacognitive strategies, management of internal resources, and management of external resources), each of which are subdivided into further subscales. With a total of 39 items answered via a 5-step Likert scale, the LIST-K can cover the topic relatively comprehensively and at the same time be completed in a reasonable amount of time of approximately 10 minutes. The LIST-K was used as part of a combined data collection along with other questionnaires on their personal data, their preferences regarding certain learning elements, their learning style (i.e. the ILS), and personality (i.e. the BFI-10). A total of 207 students from different study programs participated via an online survey created using the survey tool "LimeSurvey". Participation in the study was voluntary, anonymously, and in compliance with the GDPR. Overall, the results of the LIST-K show that students are willing to work intensively on relevant topics intensively and to perform beyond the requirements of the course seeking additional learning material. At the same time, however, it is apparent that the organization of their own learning process could still be improved. For example, students start repeating content too late (mean=2.70; SD=0.92) and do not set goals for themselves and do not create a learning plan (mean=3.19; SD=0.90). They also learn without a schedule (mean=2.23; SD=0.97) and miss opportunities to learn together with other students (mean=3.17; SD=0.94). The findings of the data collection will be used to create an AI-based adaptive learning management system that will create individualized learning paths for students in their respective courses. From the results of the LIST-K, it appears that the adaptive learning management system should primarily support organizational aspects of student learning. Even small impulses (an individual schedule of when to learn what or a hierarchical structuring of the learning material) could help students to complete their courses more successfully and improve their learning. Y1 - 2023 U6 - https://doi.org/10.21125/iceri.2023.1147 SP - 4611 EP - 4620 PB - IATED ER - TY - CHAP A1 - Dünnweber, Jan A1 - Sarkar, Amitrajit A1 - Puthiyadath, Vimal Kumar A1 - Barde, Omkar ED - Saeed, Khalid ED - Dvorský, Jiří T1 - A Tale of Four Cities - Improving Bus and Waste Collection Schedules in Practical Smart City Applications T2 - Computer Information Systems and Industrial Management N2 - Computer-based Improvements of waste collection and public transport procedures are often a part of smart city initiatives. When we envision an ideal bus network, it will primarily connect the most crowded bus stops. Similarly, an ideal waste collection vehicle will arrive at every container exactly at the time when it is fully loaded. Beyond doubt, this will reduce traffic and support environmentally friendly intentions like waste separation, as it will make more containers manageable. A difficulty of putting that vision into practice is that vehicles cannot always be where they are needed. Knowing the best time for arriving at a position is not insufficient for finding the optimal route. Therefore, we compare four different approaches to optimized routing: Regensburg, Christchurch, Malaysia, and Bangalore. Our analysis shows that the best schedules result from adapting field-tested routes frequently based on sensor measurements and route optimizing computations. KW - Smart city KW - Bus schedules KW - Waste management Y1 - 2021 SN - 978-3-030-84340-3 U6 - https://doi.org/10.1007/978-3-030-84340-3_30 SP - 369 EP - 380 PB - Springer CY - Cham ER - TY - CHAP A1 - Stadler, Timo A1 - Sarkar, Amitrajit A1 - Dünnweber, Jan ED - Saeed, Khalid ED - Dvorský, Jiří T1 - Bus Demand Forecasting for Rural Areas Using XGBoost and Random Forest Algorithm T2 - CISIM2021: 20th International Conference on Computer Information Systems and Industrial Management Applications, September 24-26 2021, Ełk, Poland N2 - In recent years, mobility solutions have experienced a significant upswing. Consequently, it has increased the importance of forecasting the number of passengers and determining the associated demand for vehicles. We analyze all bus routes in a rural area in contrast to other work that predicts just a single bus route. Some differences in bus routes in rural areas compared to cities are highlighted and substantiated by a case study data using Roding, a town in the rural district of Cham in northern Bavaria, as an example. Data collected and we selected a random forest model that lets us determine the passenger demand, bus line effectiveness, or general user behavior. The prediction accuracy of the selected model is currently 87%. The collected data helps to build new mobility-as-a-service solutions, such as on-call buses or dynamic route optimizations, as we show with our simulation. KW - Transportation KW - Rural mobility KW - Prediction KW - Öffentlicher Personennahverkehr KW - Ländlicher Raum KW - Verkehrsnachfrage KW - Prognosemodell KW - Random Forest Y1 - 2021 SN - 978-3-030-84340-3 U6 - https://doi.org/10.1007/978-3-030-84340-3_36 SP - 442 EP - 453 PB - Springer CY - Cham ER - TY - CHAP A1 - Carbonelli, Cecilia A1 - Felderer, Michael A1 - Jung, Matthias A1 - Lobe, Elisabeth A1 - Lochau, Malte A1 - Luber, Sebastian A1 - Mauerer, Wolfgang A1 - Ramler, Rudolf A1 - Schäfer, Ina A1 - Schroth, Christoph ED - Exman, Iaakov ED - Perez-Castillo, Ricardo ED - Piattini, Mario ED - Felderer, Michael T1 - Challenges for Quantum Software Engineering: An Industrial Application Scenario Perspective T2 - Quantum Software: Aspects of Theory and System Design N2 - Quantum software is becoming a key enabler for applying quantum computing to industrial use cases. This poses challenges to quantum software engineering in providing efficient and effective means to develop such software. Eventually, this must be reliably achieved in time, on budget, and in quality, using sound and well-principled engineering approaches. Given that quantum computers are based on fundamentally different principles than classical machines, this raises the question if, how, and to what extent established techniques for systematically engineering software need to be adapted. In this chapter, we analyze three paradigmatic application scenarios for quantum software engineering from an industrial perspective. The respective use cases center around (1) optimization and quantum cloud services, (2) quantum simulation, and (3) embedded quantum computing. Our aim is to provide a concise overview of the current and future applications of quantum computing in diverse industrial settings. We derive presumed challenges for quantum software engineering and thus provide research directions for this emerging field. KW - industrial use cases KW - quantum computing KW - quantum software engineering KW - software development KW - software engineering Y1 - 2024 SN - 978-3-031-64135-0 SN - 978-3-031-64136-7 U6 - https://doi.org/10.1007/978-3-031-64136-7_12 PB - Springer-Nature ER - TY - INPR A1 - Ammermann, Joshua A1 - Mauerer, Wolfgang A1 - Schäfer, Ina T1 - Towards View-based Development of Quantum Software N2 - Quantum computing is an interdisciplinary field that relies on the expertise of many different stakeholders. The views of various stakeholders on the subject of quantum computing may differ, thereby complicating communication. To address this, we propose a view-based quantum development approach based on a Single Underlying Model (SUM) and a supporting quantumIntegrated Development Environment (IDE). We highlight emerging challenges for future research. KW - Quantum Computing KW - View-based Development KW - Integrated Development Environment Y1 - 2024 ER - TY - CHAP A1 - Biersack, Stefan A1 - Schmailzl, Marc A1 - Linner, Thomas A1 - Eder, Friedrich A1 - Obergrießer, Mathias ED - Schermer, Detleff ED - Brehm, Eric T1 - Von der Handarbeit zur Hochtechnologie im Reallabor: Die Möglichkeit der BIM-basierten Planung und effizienten Produktion von Ziegelwänden durch Roboter T2 - Mauerwerk-Kalender 2025 KW - Mauerwerk KW - Mauerwerksbau Y1 - 2025 SN - 978-3-433-03445-3 U6 - https://doi.org/10.1002/9783433612019.ch7 VL - 2025 PB - Ernst & Sohn ET - 1. Aufl ER - TY - CHAP A1 - Bugert, Flemming A1 - Nadimpalli, Vamsi Krishna A1 - Bittner, Dominik A1 - Ezer, Timur A1 - Grabinger, Lisa A1 - Maier, Robert A1 - Röhrl, Simon A1 - Staufer, Susanne A1 - Hauser, Florian A1 - Mottok, Jürgen ED - Mottok, Jürgen ED - Hagel, Georg T1 - ML based Evaluation Methodology for Learning Path Recommender Systems T2 - Proceedings of the 6th European Conference on Software Engineering Education : ECSEE 2025, Seeon Germany, June 02-04, 2025 N2 - In education, recommender systems can provide students with personalized learning materials based on their preferences. When comparing various recommendation algorithms, the main question is, which algorithm provides the most suitable recommendations for each student. Answering this question requires a quantitative evaluation methodology (i.e. a concrete metric) for ranking the results of (even non-deterministic) recommender systems. While there is already literature on this topic, the uniqueness of our approach lies in the application of machine learning: we deploy a likelihood based analysis via Hidden Markov Models named Aiakos. With this strategy, we aim to provide data-driven insights about accuracy and stability of recommendations towards a more reasonable selection of the appropriate recommender system. The training data for the Hidden Markov Models is collected from 80 students. Data from another 26 students is then used to discuss the behavior of our evaluation procedure considering a single recommendation as well as the results from 100 recommendations. Furthermore, the proposed concept allows to be applied to other domains as well. Y1 - 2025 SN - 9798400712821 U6 - https://doi.org/10.1145/3723010.3723022 SP - 40 EP - 48 PB - ACM ER - TY - RPRT A1 - Schultz, Maximilian A1 - Scharf, Anna A1 - Hauer, Franziska A1 - Haug, Sonja A1 - Weber, Karsten T1 - KINiro, Künstliche Intelligenz für Nichtregierungsorganisationen - Bedarf, Akzeptanz und Umsetzungsmöglichkeiten. 2. Arbeitspapier: Künstliche Intelligenz in Nichtregierungsorganisationen: Explorative Studie in einem neuen Forschungsfeld N2 - Hintergrund und Fragestellung Nichtregierungsorganisationen (NRO) sind ein wichtiger Bestandteil der Zivilgesellschaft und interagieren auch mit Regierungen, Unternehmen und anderen gesellschaftlichen Akteuren. Aufgrund der komplexer werdenden Arbeit von NROs scheint Künstliche Intelligenz (KI) Möglichkeiten zur Bewältigung aktueller und zukünftiger Herausforderungen zu bieten. Jedoch ist wenig über die Arbeit von NROs mit KI bekannt. Methodik Es wurden fünf explorative Interviews mit Vertreter*innen von Nichtregierungsorganisationen (NROs) zum Thema Wissen, Akzeptanz, Bedarfe und Risikoeinschätzungen geführt und ausgewertet. Dabei sind NROs aus verschiedenen Handlungsfeldern und Größe interviewt. Es wurden informelle Vorgespräche geführt, um eine erste Orientierung im Forschungsfeld zu generieren. Aus den Erkenntnissen der Vorgespräche und den Ergebnissen des Scoping Reviews ist ein Leitfaden erstellt worden, der zur Orientierung für die Expert*inneninterviews dient. Im Anschluss wurden dann fünf explorative leitfadengestützte Expert*inneninterviews durchgeführt und qualitativ ausgewertet. Ergebnisse Ein zentraler Befund ist, dass das Thema KI gerade in den NROs ankommt und es noch keine gefestigten Strukturen und Vorstellungen zum Einsatz von KI gibt. KI wird in einzelnen spezifischen Projekten eingesetzt, ohne dass diese umfassend in Arbeitsabläufe integriert ist. Die Akzeptanz von KI ist generell positiv; die Technologie wird als potenzielle Lösung für strukturelle Herausforderungen und Unterstützung im Alltag gesehen. Die Nutzung von KI-Anwendungen beschränkt sich jedoch mit Ausnahme von Large Language Models auf Pilotprojekte. Mit jüngerem Alter und Techni� kaffinität ist eine höhere Akzeptanz verbunden. Besonders kritisch werden Anwendungen von KI im Sozial- oder Gesundheitsbereich als Ersatz für menschliche Interaktionen gesehen. Betont werden auch ethische Bedenken und eine hohe Bedeutsamkeit von Datenschutz. Schlussfolgerung Künstliche Intelligenz in Nichtregierungsorganisationen ist ein aufkommendes und sich entwickelndes Forschungsthema. Die Interviews unterstreichen den Bedarf an mehr Wissen, ethischen Richtlinien und finanziellen Ressourcen für eine effektive Nutzung von KI in NROs. Ein umfassendes Verständnis von KI und eine tiefergehende, systematische Integration in Arbeitsabläufe in diesen Organisationen müssen noch entwickelt werden. KW - Künstliche Intelligenz KW - Nichtregierungsorganisationen KW - explorative Interviews KW - KI KW - NRO Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-73118 PB - OTH Regensburg CY - Regensburg ER - TY - RPRT A1 - Scharf, Anna A1 - Hauer, Franziska A1 - Schultz, Maximilian A1 - Haug, Sonja A1 - Weber, Karsten T1 - KINiro, Künstliche Intelligenz für Nichtregierungsorganisationen - Bedarf, Akzeptanz und Umsetzungsmöglichkeiten. 1. Arbeitspapier: Künstliche Intelligenz in Nichtregierungsorganisationen: Ein Scoping Review über ein junges Forschungsfeld N2 - Hintergrund und Fragestellung Nichtregierungsorganisationen (NRO) sind ein wichtiger Bestandteil der Zivilgesellschaft und interagieren auch mit Regierungen, Unternehmen und anderen gesellschaftlichen Akteuren. Aufgrund der komplexer werdenden Arbeit von NROs scheint Künstliche Intelligenz (KI) Möglichkeiten zur Bewältigung aktueller und zukünftiger Herausforderungen zu bieten. Jedoch ist wenig über die Arbeit von NROs mit KI bekannt. Daher beschäftigt sich das Projekt KINiro in diesem ersten Working Paper mit der Frage, welche (nicht-)wissenschaftlichen Erkenntnisse zum Themenkomplex NROs und KI bereits vorliegen. Methodik Es wurde ein Scoping Review zur Erfassung (nicht-)wissenschaftlicher Texte zu NROs und KI durchgeführt. Die systematische Literaturrecherche wurde in den Datenbanken Web of Science, Science Gate und WISO durchgeführt. In den Review wurden schließlich 14 Titel eingeschlossen und qualitativ analysiert. Ergebnisse Die Mehrheit der gefundenen Treffer sind Pressemitteilungen. Unter den Treffern befinden sich lediglich zwei (wissenschaftliche) Studien. Die NROs setzen sich auf verschiedenen Ebenen mit der Thematik von KI auseinander, wobei sich zwei Herangehensweisen unterscheiden lassen. Einige NROs nehmen am gesellschaftlichen Diskurs über den Einsatz von KI teil und treiben diesen in theoretischer Hinsicht voran, ohne die Technik dabei selbst zu nutzen. Andere NROs integrieren die KI-Systeme praktisch in ihre Arbeitsabläufe oder führen Projekte zum Zweck der NRO mit KI-Unterstützung durch. Für die Entwicklung von KI-Anwendungen wird mit For-Profit-Unternehmen kooperiert und die Expertise der Unternehmen mit Daten der NROs kombiniert. Durch den Einsatz von KI erhoffen sich NROs einen gezielteren Einsatz von Ressourcen. Hierbei zeigt sich, dass für die Nutzung in KI-Systemen ein interdisziplinärer Konsens über Standards in Datenerhebung und Speicherung als notwendig angesehen wird. Schlussfolgerung Aus der geringen Anzahl an gefundenen Texten, insbesondere (wissenschaftlichen) Studien, und dem Veröffentlichungszeitraum, der in den vergangenen sieben Jahren liegt, lässt sich schließen, dass es sich um einen jungen Forschungsbereich handelt. Die ausgeschlossenen Titel zeigen auf, dass NROs aktuell noch häufiger mit der Digitalisierunge allgemein beschäftigt sind und die Auseinandersetzung mit KI erst noch am Anfang steht. KW - Künstliche Intelligenz KW - Nichtregierungsorganisationen KW - Scoping Review KW - KI KW - NRO Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-73090 PB - OTH Regensburg CY - Regensburg ER - TY - CHAP A1 - Hauer, Franziska A1 - Schultz, Maximilian A1 - Haug, Sonja A1 - Weber, Karsten ED - Baumgartner, Martin ED - Hayn, Dieter ED - Pfeifer, Bernhard ED - Schreier, Günter T1 - Acceptance and Usage of AI Applications in Health-Focused NGOs T2 - dHealth 2025, Proceedings of the 19th Health Informatics Meets Digital Health Conference N2 - Background: AI applications promise to be a valuable tool for healthfocused NGOs. While often operating with limited resources, these organizations recognize the potential of AI to streamline processes and support workflows through automation. However, challenges such as data privacy concerns—especially regarding personal medical data—and the low prioritization of implementation hinder progress. Objectives: This study examines the extent to which German health-focused NGOs can currently benefit from the application of AI. It evaluates demands, available resources, and use cases. Methods: A health-focused subset of data from project KINiro was analyzed. This research utilized a mixed-methods approach, combining two rounds of qualitative interviews with a quantitative survey. Results: The study revealed that while health-focused NGOs are in the early stages of AI implementation, there are hurdles such as ethical concerns and a lack of resources. Conclusion: AI has the potential to support health-focused NGOs in their work, if the challenges like resources, ethics, and data privacy are effectively addressed. KW - Künstliche Intelligenz KW - Nichtregierungsorganisationen KW - Gesundheit KW - Large Language Models KW - qualitative Research KW - Artificial Intelligence KW - Non-Governmental Organizations Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-80613 SN - 978-1-64368-592-2 SP - 123 EP - 128 PB - IOS Press CY - Wien ER - TY - JOUR A1 - Schönberger, Manuel T1 - Applicability of Quantum Computing on Database Query Optimization JF - SIGMOD '22: proceedings of the 2022 International Conference on Management of Data : June 12-17, 2022, Philadelphia, PA, USA N2 - We evaluate the applicability of quantum computing on two fundamental query optimization problems, join order optimization and multi query optimization (MQO). We analyze the problem dimensions that can be solved on current gate-based quantum systems and quantum annealers, the two currently commercially available architectures. First, we evaluate the use of gate-based systems on MQO, previously solved with quantum annealing. We show that, contrary to classical computing, a different architecture requires involved adaptations. We moreover propose a multi-step reformulation for join ordering problems to make them solvable on current quantum systems. Finally, we systematically evaluate our contributions for gate-based quantum systems and quantum annealers. Doing so, we identify the scope of current limitations, as well as the future potential of quantum computing technologies for database systems. Y1 - 2022 U6 - https://doi.org/10.1145/3514221.3520257 SP - 2512 EP - 2514 PB - ACM CY - New York, NY ER - TY - GEN A1 - Schönberger, Manuel A1 - Scherzinger, Stefanie A1 - Mauerer, Wolfgang T1 - Quantum Computing for DB - Applicability on Multi Query Optimization and Join Order Optimization T2 - Frühjahrstreffen Fachgruppe Datenbanken in Potsdam, 2022 Y1 - UR - https://www.lfdr.de/Publications/2022/FGDB_Poster_Schoenberger.pdf ER - TY - CHAP A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Bittner, Dominik A1 - Staufer, Susanne A1 - Röhrl, Simon A1 - Hauser, Florian A1 - Ezer, Timur A1 - Grabinger, Lisa A1 - Maier, Robert A1 - Mottok, Jürgen T1 - Probabilistic Machine Learning for Simulating Complex Learner Profiles T2 - 2024 21st International Conference on Information Technology Based Higher Education and Training (ITHET), 06-08 November 2024, Paris, France N2 - Data is the foundation of all machine learning applications. In education science, especially for the learner characteristics that drive personalized learning, it is difficult to collect and often uncertain. It is challenging to model, train, evaluate, and analyze the underlying algorithms when developing AI-based systems and having small sample sizes. To address these problems, we present a synthetic data generator utilising probabilistic models. This generator can effectively model and simulate complex learner profiles. To achieve this, we collected extensive data on learning styles, learning strategies, personalities, and preferred learning paths from 593 students over several semesters at a higher education level. Then, Bayesian networks, Hidden Markov Models, and Markov Chains are used to model the relationships between learner profiles. Using the Bayesian information criterion, and cross-validation with log-likelihood scores, we compare various models to select the best fitting one for synthesizing the data. The synthetic data is then evaluated using statistical validation techniques. In addition, we developed a simulation module with the option to simulate learner profiles based on manual user-defined inputs. The data and code used in this work are available as open source1110.5281/zenodo.13768136 [Titel anhand dieser DOI in Citavi-Projekt übernehmen] contributing to open science and developers for customized simulated data. In the future, this data will refine the training, evaluation, analysis, and benchmarking of algorithms for personalized learning. KW - probabilistic models KW - synthetic data KW - learner characteristics KW - generative AI KW - higher education area Y1 - 2024 SN - 979-8-3315-1663-5 U6 - https://doi.org/10.1109/ITHET61869.2024.10837641 SN - 2473-2060 SP - 1 EP - 10 PB - IEEE ER - TY - CHAP A1 - Nadimpalli, Vamsi Krishna A1 - Staufer, Susanne A1 - Ezer, Timur A1 - Bugert, Flemming A1 - Bittner, Dominik A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Röhrl, Simon A1 - Maier, Robert A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Predicting learner characteristics using machine learning T2 - ICERI 2024 Proceedings, 17th annual International Conference of Education, Research and Innovation,11-13 November, 2024, Seville, Spain N2 - In education science research, data collection is challenging due to difficulty identifying students at the higher education level, privacy concerns, and varying levels of student engagement. Importantly, psychological questionnaires can be lengthy, leading to incomplete responses. We conducted repeated studies, and over time, the focus of the research adapted, introducing new materials and consequently leading to missing learner characteristics in some datasets. In this research, the issue of incomplete learner characteristics is addressed using data from three different studies: winter term 2022/2023 (n=297), summer term 2023 (n=274), and winter term 2023/2024 (n=25). These studies collected various learner characteristics, such as learning styles, personalities, learning strategies, and learning element preferences. However, learning element preferences and learning strategies were missing in the winter term of 2022, and the summer term of 2023 respectively. To analyze the data and predict these missing features, statistical analysis, and machine learning techniques were employed. Then, these models are rigorously evaluated using cross-validation and performance metrics like accuracy, precision, recall, and F1-score. Our findings provide insights into the relationships between learners' learning styles, personalities, learning strategies, and learning element preferences. This offers valuable implications for the design and implementation of educational interventions, like learning path recommendations. The results imply that machine learning models can predict missing learner characteristics, thus addressing the problem of incomplete data in educational research Y1 - 2024 U6 - https://doi.org/10.21125/iceri.2024.1454 SP - 6005 EP - 6014 PB - IATED ER - TY - CHAP A1 - Schönberger, Manuel A1 - Franz, Maja A1 - Scherzinger, Stefanie A1 - Mauerer, Wolfgang T1 - Peel | Pile? Cross-Framework Portability of Quantum Software T2 - 2022 IEEE 19th International Conference on Software Architecture Companion (ICSA-C), 12-15 March 2022, Honolulu, HI, USA N2 - In recent years, various vendors have made quantum software frameworks available. Yet with vendor-specific frameworks, code portability seems at risk, especially in a field where hardware and software libraries have not yet reached a consolidated state, and even foundational aspects of the technologies are still in flux. Accordingly, the development of vendor-independent quantum programming languages and frameworks is often suggested. This follows the established architectural pattern of introducing additional levels of abstraction into software stacks, thereby piling on layers of abstraction. Yet software architecture also provides seemingly less abstract alternatives, namely to focus on hardware-specific formulations of problems that peel off unnecessary layers. In this article, we quantitatively and experimentally explore these strategic alternatives, and compare popular quantum frameworks from the software implementation perspective. We find that for several specific, yet generalisable problems, the mathematical formulation of the problem to be solved is not just sufficiently abstract and serves as precise description, but is likewise concrete enough to allow for deriving framework-specific implementations with little effort. Additionally, we argue, based on analysing dozens of existing quantum codes, that porting between frameworks is actually low-effort, since the quantum- and framework-specific portions are very manageable in terms of size, commonly in the order of mere hundreds of lines of code. Given the current state-of-the-art in quantum programming practice, this leads us to argue in favour of peeling off unnecessary abstraction levels. KW - Computer Science KW - Quantum Physics KW - Software Engineering Y1 - 2022 U6 - https://doi.org/10.1109/ICSA-C54293.2022.00039 N1 - Preprint unter: https://arxiv.org/abs/2203.06289 PB - IEEE ER - TY - INPR A1 - Schramm, Simon A1 - Pieper, Matthias A1 - Vogl, Stefanie T1 - Orthogonal Procrustes Based Anomaly Detection and Error Prediction for Vehicle Bills of Materials T2 - SSRN N2 - Industrial Bill of Materials (BOM) suffer from an surging complexity and cause errors in production which have detrimental effects on a product’s profitability. Currently, BOM anomalies have to be identified manually and errors have to be detected in the same way. This preprint describes a combination of data analysis and Machine Learning methods, such as hierarchical and agglomerative clustering, an isolation forest algorithm, association mining and a multi-output Artificial Neural Network, all based on a deterministic distance measure for an industrial BOMs. Solving the orthogonal Procrustes problem for complex, multi-level matrices, a distance measure for real world industrial BOMs was derived. A multi-output MLP was used in order to predict error probabilities with a time- reference. Our results show how to detect anomalies and predict errors in a complex, multi-level BOM based on historical, labelled data. While other authors focus on the mere comparison of BOMs, we aimed at a holistic approach, combining descriptive and predictive methods in order to forecast where in a BOM and at what time of BOM creation process errors occur. The resulting, prescriptive system was tested using real world data and has shown to effectively predict where and when BOM errors are probable to occur. Consequently, the prescriptive system is superior to prior, purely predictive systems, can help to decrease errors and thereby decreases product development time and cost in real world companies. KW - Orthogonal Procrustes KW - Bill of Materials KW - Isolation forest KW - Multi-output Multi Layer Perceptron KW - Association mining KW - Prescriptive modeling Y1 - 2022 U6 - https://doi.org/10.2139/ssrn.4120321 PB - Elsevier ER - TY - INPR A1 - Schönberger, Manuel A1 - Trummer, Immanuel A1 - Mauerer, Wolfgang T1 - Quantum-Inspired Digital Annealing for Join Ordering T2 - Proceedings of the VLDB Endowment N2 - Finding the optimal join order (JO) is one of the most important problems in query optimisation, and has been extensively considered in research and practise. As it involves huge search spaces, approximation approaches and heuristics are commonly used, which explore a reduced solution space at the cost of solution quality. To explore even large JO search spaces, we may consider special-purpose software, such as mixed-integer linear programming (MILP) solvers, which have successfully solved JO problems. However, even mature solvers cannot overcome the limitations of conventional hardware prompted by the end of Moore’s law. We consider quantum-inspired digital annealing hardware, which takes inspiration from quantum processing units (QPUs). Unlike QPUs, which likely remain limited in size and reliability in the near and mid-term future, the digital annealer (DA) can solve large instances of mathematically encoded optimisation problems today. We derive a novel, native encoding for the JO problem tailored to this class of machines that substantially improves over known MILP and quantum-based encodings, and reduces encoding size over the state-of-the-art. By augmenting the computation with a novel readout method, we derive valid join orders for each solution obtained by the (probabilistically operating) DA. Most importantly and despite an extremely large solution space, our approach scales to practically relevant dimensions of around 50 relations and improves result quality over conventionally employed approaches, adding a novel alternative to solving the long-standing JO problem. Y1 - 2023 ER - TY - INPR A1 - Schmidl, Sebastian A1 - Deng, Yangshen A1 - Ma, Pingchuan A1 - Schönberger, Manuel A1 - Mauerer, Wolfgang T1 - Reproducibility Report for ACM SIGMOD 2023 Paper: Ready to Leap (by Co-Design)? Join Order Optimisation N2 - The paper “Ready to Leap (by Co-Design)? Join Order Optimisation on Quantum Hardware” proposes the first approach to solve the problem of join order optimization on quantum hardware. The authors characterize the applicability and limitations of current state-of-the-art quantum hardware, i. e. gate-based quantum computing and quantum annealing, for join ordering and recommend key improvements to the physical hardware to reach practical utility. Based on the provided database queries and QPU system processing data, we have been able to reproduce the original paper’s key insights and quantum problem characteristics reported in its experimental section. The authors provided a self-contained and fully automated reproduction package, including data (database queries, statistics, and collected QPU processing data), experiment scripts, and plotting routines that allowed the identical reconstruction of the three main figures in the paper. Y1 - 2024 UR - https://www.lfdr.de/Publications/2024/SIGMOD_ARI_2023___Paper_37.pdf ER - TY - GEN A1 - Schönberger, Manuel A1 - Scherzinger, Stefanie A1 - Mauerer, Wolfgang T1 - Applicability of Quantum Computing on Database Query Optimization T2 - Frühjahrstreffen Fachgruppe Datenbanken in Potsdam (Poster Presentation) Y1 - 2022 ER - TY - CHAP A1 - Buchmann, Thomas A1 - Schwägerl, Felix T1 - Ensuring well-formedness of configured domain models in model-driven product lines based on negative variability T2 - FOSD '12: Proceedings of the 4th International Workshop on Feature-Oriented Software Development, 24. + 25. September 2012, Dresden N2 - Model-driven development is a well-known practice in modern software engineering. Many tools exist which allow developers to build software in a model-based or even model-driven way, but they do not provide dedicated support for software product line development. Only recently some approaches combined model-driven engineering and software product line engineering. In this paper we present an approach that allows for combining feature models and Ecore-based domain models and provides extensive support to keep the mapping between the involved models consistent. Our key contribution is a declarative textual language which allows to phrase domain-specific consistency constraints which are preserved during the configuration process in order to ensure context-sensitive syntactical correctness of derived domain models. Y1 - 2012 U6 - https://doi.org/10.1145/2377816.2377822 SP - 37 EP - 44 PB - ACM Press CY - New York, USA ER - TY - THES A1 - ZInner, Helge T1 - Vernetzung heterogener Feldbusse auf Basis des Standards Ethernet Audio Video Bridging Y1 - 2015 UR - https://d-nb.info/1079219927 CY - Ilmenau ER - TY - CHAP A1 - Palm, Christoph T1 - Fusion of Serial 2D Section Images and MRI Reference BT - an Overview T2 - Workshop Innovative Verarbeitung bioelektrischer und biomagnetischer Signale (bbs2014), Berlin, 10.04.2014 N2 - Serial 2D section images with high resolution, resulting from innovative imaging methods become even more valuable, if they are fused with in vivo volumes. Achieving this goal, the 3D context of the sections would be restored, the deformations would be corrected and the artefacts would be eliminated. However, the registration in this field faces big challenges and is not solved in general. On the other hand, several approaches have been introduced dealing at least with some of these difficulties. Here, a brief overview of the topic is given and some of the solutions are presented. It does not constitute the claim to be a complete review, but could be a starting point for those who are interested in this field. KW - Kernspintomografie KW - Optimierung KW - Magnetic Resonance Imaging KW - MRI KW - Literaturbericht Y1 - 2014 U6 - https://doi.org/10.13140/RG.2.1.1358.3449 ER - TY - JOUR A1 - Lehmann, Thomas M. A1 - Palm, Christoph T1 - Color Line Search for Illuminant Estimation in Real World Scenes JF - Journal of the Optical Society of America (JOSA) A N2 - The estimation of illuminant color is mandatory for many applications in the field of color image quantification. However, it is an unresolved problem if no additional heuristics or restrictive assumptions apply. Assuming uniformly colored and roundly shaped objects, Lee has presented a theory and a method for computing the scene-illuminant chromaticity from specular highlights [H. C. Lee, J. Opt. Soc. Am. A 3, 1694 (1986)]. However, Lee’s method, called image path search, is less robust to noise and is limited in the handling of microtextured surfaces. We introduce a novel approach to estimate the color of a single illuminant for noisy and microtextured images, which frequently occur in real-world scenes. Using dichromatic regions of different colored surfaces, our approach, named color line search, reverses Lee’s strategy of image path search. Reliable color lines are determined directly in the domain of the color diagrams by three steps. First, regions of interest are automatically detected around specular highlights, and local color diagrams are computed. Second, color lines are determined according to the dichromatic reflection model by Hough transform of the color diagrams. Third, a consistency check is applied by a corresponding path search in the image domain. Our method is evaluated on 40 natural images of fruit and vegetables. In comparison with those of Lee’s method, accuracy and stability are substantially improved. In addition, the color line search approach can easily be extended to scenes of objects with macrotextured surfaces. Y1 - 2001 U6 - https://doi.org/10.1364/JOSAA.18.002679 VL - 18 IS - 11 SP - 2679 EP - 2691 ER - TY - JOUR A1 - Palm, Christoph T1 - Color Texture Classification by Integrative Co-Occurrence Matrices JF - Pattern Recognition N2 - Integrative Co-occurrence matrices are introduced as novel features for color texture classification. The extended Co-occurrence notation allows the comparison between integrative and parallel color texture concepts. The information profit of the new matrices is shown quantitatively using the Kolmogorov distance and by extensive classification experiments on two datasets. Applying them to the RGB and the LUV color space the combined color and intensity textures are studied and the existence of intensity independent pure color patterns is demonstrated. The results are compared with two baselines: gray-scale texture analysis and color histogram analysis. The novel features improve the classification results up to 20% and 32% for the first and second baseline, respectively. KW - Color texture KW - Co-occurrence matrix KW - Integrative features KW - KolmogKorov distance KW - Image classification Y1 - 2004 U6 - https://doi.org/10.1016/j.patcog.2003.09.010 VL - 37 IS - 5 SP - 965 EP - 976 ER - TY - CHAP A1 - Palm, Christoph A1 - Lehmann, Thomas M. A1 - Bredno, J. A1 - Neuschaefer-Rube, C. A1 - Klajman, S. A1 - Spitzer, Klaus T1 - Automated Analysis of Stroboscopic Image Sequences by Vibration Profiles T2 - Advances in Quantitative Laryngoscopy, Voice and Speech Research, Procs. 5th International Workshop N2 - A method for automated segmentation of vocal cords in stroboscopic video sequences is presented. In contrast to earlier approaches, the inner and outer contours of the vocal cords are independently delineated. Automatic segmentation of the low contrasted images is carried out by connecting the shape constraint of a point distribution model to a multi-channel regionbased balloon model. This enables us to robustly compute a vibration profile that is used as a new diagnostic tool to visualize several vibration parameters in only one graphic. The vibration profiles are studied in two cases: one physiological vibration and one functional pathology. KW - Vibration Profile KW - Stroboscopic Images KW - Contour Detection KW - Balloon Model KW - Point Distribution Model Y1 - 2001 UR - https://www.researchgate.net/publication/242439073_Automated_Analysis_of_Stroboscopic_Image_Sequences_by_Vibration_Profiles ER - TY - CHAP A1 - Palm, Christoph A1 - Lehmann, Thomas M. A1 - Spitzer, Klaus T1 - Color Texture Analysis of Moving Vocal Cords Using Approaches from Statistics and Signal Theory T2 - Advances in Quantitative Laryngoscopy, Voice and Speech Research, Procs. 4th International Workshop, Friedrich Schiller University, Jena N2 - Textural features are applied for detection of morphological pathologies of vocal cords. Cooccurrence matrices as statistical features are presented as well as filter bank analysis by Gabor filters. Both methods are extended to handle color images. Their robustness against camera movement and vibration of vocal cords is evaluated. Classification results due to three in vivo sequences are in between 94.4 % and 98.9%. The classification errors decrease if color features are used instead of grayscale features for both statistical and Fourier features KW - Color Texture KW - Gabor Filter KW - Cooccurrence Matrix KW - Image Processing Y1 - 2000 SP - 49 EP - 56 ER - TY - BOOK A1 - Palm, Christoph T1 - Integrative Auswertung von Farbe und Textur Y1 - 2003 UR - http://publications.rwth-aachen.de/record/58707/files/Palm_Christoph.pdf PB - Der Andere Verlag ER - TY - CHAP A1 - Palm, Christoph A1 - Lehmann, Thomas M. A1 - Spitzer, Klaus T1 - Bestimmung der Lichtquellenfarbe bei der Endoskopie mikrotexturierter Oberflächen des Kehlkopfes T2 - 5. Workshop Farbbildverarbeitung, Ilmenau, 1999 N2 - Zur Unterstützung der Diagnose von Stimmlippenerkrankungen werden innerhalb des Forschungsprojektes Quantitative Digitale Laryngoskopie objektive Parameter zur Beschreibung der Bewegung, der Farbe sowie der Form der Stimmlippen entwickelt und klinisch evaluiert. Während die Bewegungsanalyse Aufschluß über funktionelle Stimmstörungen gibt, beschreiben Parameter der Farb- und Formanalyse morphologische Veränderungen des Stimmlippengewebes. In diesem Beitrag werden die Methoden und bisherigen Ergebnisse zur Bewegungs- und Farbanalyse vorgestellt. Die Bewegungsanalyse wurde mit einem erweiterten Konturmodell (Snakes) durchgeführt. Aufgrund des modifizierten Konturmodells konnten die Konturen der Stimmlippen automatisch über die gesmate Bildsequenz zuverlässig detektiert werden. Die Vermssung der Konturen liefert neue quantitative Parameter zur Befundung von laryngoskopischen Stimmlippenaufnahmen. Um die Farbeigenschaften der Stimmlippen zu bestimmen, wurde ausgehend vom RGB-Bild die Objektfarbe unabhängig von der Farbe der Lichtquelle durch Verwendung von Clusterverfahren und der Viertelkreisanalyse berechnet. Mit dieser Farbanalyse konnte die Farbe der Lichtquelle ermittelt und das beleuchtungsunabhängige Farbbild berechnet werden. Die Quanitifizierung der Rötung der Stimmlippen ist z.B. ein entscheidendes Kriterium zur Diagnostik der akuten Laryngitis. KW - Konturverfolgung KW - Snakes KW - Dichromatisches Reflexionsmodell KW - Farbkonstanz KW - Laryngoskopie Y1 - 1999 UR - http://www.germancolorgroup.de/html/Vortr_99_pdf/01_Palm.pdf SP - 3 EP - 10 ER - TY - JOUR A1 - Palm, Christoph A1 - Lehmann, Thomas M. T1 - Classification of Color Textures by Gabor Filtering JF - Machine GRAPHICS & VISION Y1 - 2002 VL - 11 IS - 2/3 SP - 195 EP - 219 ER - TY - JOUR A1 - Souza Jr., Luis Antonio de A1 - Passos, Leandro A. A1 - Mendel, Robert A1 - Ebigbo, Alanna A1 - Probst, Andreas A1 - Messmann, Helmut A1 - Palm, Christoph A1 - Papa, João Paulo T1 - Assisting Barrett's esophagus identification using endoscopic data augmentation based on Generative Adversarial Networks JF - Computers in Biology and Medicine N2 - Barrett's esophagus figured a swift rise in the number of cases in the past years. Although traditional diagnosis methods offered a vital role in early-stage treatment, they are generally time- and resource-consuming. In this context, computer-aided approaches for automatic diagnosis emerged in the literature since early detection is intrinsically related to remission probabilities. However, they still suffer from drawbacks because of the lack of available data for machine learning purposes, thus implying reduced recognition rates. This work introduces Generative Adversarial Networks to generate high-quality endoscopic images, thereby identifying Barrett's esophagus and adenocarcinoma more precisely. Further, Convolution Neural Networks are used for feature extraction and classification purposes. The proposed approach is validated over two datasets of endoscopic images, with the experiments conducted over the full and patch-split images. The application of Deep Convolutional Generative Adversarial Networks for the data augmentation step and LeNet-5 and AlexNet for the classification step allowed us to validate the proposed methodology over an extensive set of datasets (based on original and augmented sets), reaching results of 90% of accuracy for the patch-based approach and 85% for the image-based approach. Both results are based on augmented datasets and are statistically different from the ones obtained in the original datasets of the same kind. Moreover, the impact of data augmentation was evaluated in the context of image description and classification, and the results obtained using synthetic images outperformed the ones over the original datasets, as well as other recent approaches from the literature. Such results suggest promising insights related to the importance of proper data for the accurate classification concerning computer-assisted Barrett's esophagus and adenocarcinoma detection. KW - Maschinelles Lernen KW - Barrett's esophagus KW - Machine learning KW - Adenocarcinoma KW - Generative adversarial networks KW - Neuronales Netz KW - Adenocarcinom KW - Speiseröhrenkrebs KW - Diagnose Y1 - 2020 U6 - https://doi.org/10.1016/j.compbiomed.2020.104029 VL - 126 IS - November PB - Elsevier ER - TY - CHAP A1 - Palm, Christoph A1 - Metzler, V. A1 - Moham, B. A1 - Dieker, O. A1 - Lehmann, Thomas M. A1 - Spitzer, Klaus ED - Evers, H. ED - Glombitza, G. ED - Lehmann, Thomas M. ED - Meinzer, H.-P. T1 - Co-Occurrence Matrizen zur Texturklassifikation in Vektorbildern T2 - Bildverarbeitung für die Medizin N2 - Statistische Eigenschaften natürlicher Grauwerttexturen werden mit Co-Occurrence Matrizen, basierend auf der Grauwertstatistik zweiter Ordnung, modelliert. Die Matrix gibt dann die apriori Wahrscheinlichkeiten aller Grauwertpaare an. Da in der medizinischen Bildverarbeitung verstärkt Multispektralbilder ausgewertet werden, wird das bekannte Konzept hier auf beliebige Vektorbilder erweitert. Dadurch kann bei der Texturklassifikation die zur Verfügung stehende Information vollständig genutzt werden. Insbesondere zur Detektion von Farbtexturen ist dieser Ansatz geeignet, da Wertepaare unterschiedlicher Spektralebenen ausgewertet werden können. Ebenso kann die Methode auch bei der Multiskalendekomposition von Intensitätsbildern zur Verbesserung der Texturerkennung beitragen. Die in den Matrizen entstehenden Muster lassen dann über die Extraktion geeigneter Texturdeskriptoren Rückschlüsse auf die Texturen des Bildes zu. KW - Texturerkennung KW - Vektorbilder KW - Multispektralbilder KW - Multiskalenbilder KW - Klassifikation Y1 - 1999 U6 - https://doi.org/10.1007/978-3-642-60125-5_69 SP - 367 EP - 371 PB - Springer CY - Berlin ER - TY - CHAP A1 - Palm, Christoph A1 - Neuschaefer-Rube, C. A1 - Lehmann, Thomas M. A1 - Spitzer, Klaus ED - Evers, H. ED - Glombitza, G. ED - Lehmann, Thomas M. ED - Meinzer, H.-P. T1 - Wissensbasierte Bewegungskompensation in aktiven Konturmodellen T2 - Bildverarbeitung für die Medizin N2 - Zur Analyse von Lippenbewegungsabläufen wird ein aktives Konturmodell eingesetzt. Probleme bereitet die hohe Sprechgeschwindigkeit, die in star ken Objektverschiebungen result iert und bislang nicht durch eine alleinige Konturanpassung kompensiert werden kann. In diesem Beitrag werden die klassischen aktiven Konturmodelle um eine Vorjustierung der Grobkonturen erweitert, die eine energiebasierte Konturanpassung erst möglich macht. Die Schätzung der Verschiebung zur Vorjustierung basiert auf dem Gradientenbild und einem prädikatenlogisch formulierten Regelwerk, das Annahmen und Nebenbedingungen als Wissensbasis enthält. Mit Hilfe dieser Erweiterungen ist eine automatisierte Konturverfolgung der Lippen möglich. KW - Aktives Konturmodell KW - Pradikatenlogik KW - Bewegungsschatzung Y1 - 1999 U6 - https://doi.org/10.1007/978-3-642-60125-5_2 SP - 8 EP - 12 PB - Springer CY - Berlin ER - TY - CHAP A1 - Mendel, Robert A1 - Souza Jr., Luis Antonio de A1 - Rauber, David A1 - Papa, João Paulo A1 - Palm, Christoph T1 - Semi-supervised Segmentation Based on Error-Correcting Supervision T2 - Computer vision - ECCV 2020: 16th European conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXIX N2 - Pixel-level classification is an essential part of computer vision. For learning from labeled data, many powerful deep learning models have been developed recently. In this work, we augment such supervised segmentation models by allowing them to learn from unlabeled data. Our semi-supervised approach, termed Error-Correcting Supervision, leverages a collaborative strategy. Apart from the supervised training on the labeled data, the segmentation network is judged by an additional network. The secondary correction network learns on the labeled data to optimally spot correct predictions, as well as to amend incorrect ones. As auxiliary regularization term, the corrector directly influences the supervised training of the segmentation network. On unlabeled data, the output of the correction network is essential to create a proxy for the unknown truth. The corrector’s output is combined with the segmentation network’s prediction to form the new target. We propose a loss function that incorporates both the pseudo-labels as well as the predictive certainty of the correction network. Our approach can easily be added to supervised segmentation models. We show consistent improvements over a supervised baseline on experiments on both the Pascal VOC 2012 and the Cityscapes datasets with varying amounts of labeled data. KW - Semi-Supervised Learning KW - Machine Learning Y1 - 2020 SN - 978-3-030-58525-9 U6 - https://doi.org/10.1007/978-3-030-58526-6_9 SP - 141 EP - 157 PB - Springer CY - Cham ER - TY - JOUR A1 - Graßmann, Felix A1 - Mengelkamp, Judith A1 - Brandl, Caroline A1 - Harsch, Sebastian A1 - Zimmermann, Martina E. A1 - Linkohr, Birgit A1 - Peters, Annette A1 - Heid, Iris M. A1 - Palm, Christoph A1 - Weber, Bernhard H. F. T1 - A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography JF - Ophtalmology N2 - Purpose Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding disease risk and progression, several systems based on color fundus photographs are known. Most of these require in-depth and time-consuming analysis of fundus images. Herein, we present an automated computer-based classification algorithm. Design Algorithm development for AMD classification based on a large collection of color fundus images. Validation is performed on a cross-sectional, population-based study. Participants. We included 120 656 manually graded color fundus images from 3654 Age-Related Eye Disease Study (AREDS) participants. AREDS participants were >55 years of age, and non-AMD sight-threatening diseases were excluded at recruitment. In addition, performance of our algorithm was evaluated in 5555 fundus images from the population-based Kooperative Gesundheitsforschung in der Region Augsburg (KORA; Cooperative Health Research in the Region of Augsburg) study. Methods. We defined 13 classes (9 AREDS steps, 3 late AMD stages, and 1 for ungradable images) and trained several convolution deep learning architectures. An ensemble of network architectures improved prediction accuracy. An independent dataset was used to evaluate the performance of our algorithm in a population-based study. Main Outcome Measures. κ Statistics and accuracy to evaluate the concordance between predicted and expert human grader classification. Results. A network ensemble of 6 different neural net architectures predicted the 13 classes in the AREDS test set with a quadratic weighted κ of 92% (95% confidence interval, 89%–92%) and an overall accuracy of 63.3%. In the independent KORA dataset, images wrongly classified as AMD were mainly the result of a macular reflex observed in young individuals. By restricting the KORA analysis to individuals >55 years of age and prior exclusion of other retinopathies, the weighted and unweighted κ increased to 50% and 63%, respectively. Importantly, the algorithm detected 84.2% of all fundus images with definite signs of early or late AMD. Overall, 94.3% of healthy fundus images were classified correctly. Conclusions Our deep learning algoritm revealed a weighted κ outperforming human graders in the AREDS study and is suitable to classify AMD fundus images in other datasets using individuals >55 years of age. KW - Senile Makuladegeneration KW - Krankheitsverlauf KW - Mustererkennung KW - Maschinelles Lernen Y1 - 2018 U6 - https://doi.org/10.1016/j.ophtha.2018.02.037 N1 - Corresponding authors: Bernhard H. F. Weber, University of Regensburg, and Christoph Palm VL - 125 IS - 9 SP - 1410 EP - 1420 PB - Elsevier ER - TY - CHAP A1 - Höng, Simon K. A1 - Wiederer, Jonas A1 - Eder, Friedrich A1 - Obergriesser, Mathias A1 - Linner, Thomas T1 - Towards AI-enhanced facade planning : integrating human expertise with machine learning-driven parametric modeling T2 - EC³ & CIB W78 : 2025 European Conference on Computing in Construction & 42nd CIB W78 IT in Construction Conference N2 - Planning modern facade systems is complex, requiring optimization across multiple domains.This paper proposes an AI-enhanced workflow for facade planning, harnessing computer vision and human input via a Large Language Model.A generative AI system then guides a parametric model to produce 3D facade designs. Automated checks provide feedback to a Reinforcement Learning system, to iteratively determine optimal solutions.These solutions are verified and finalized by human expertise, ensuring improved outcomes with reduce planning time and effort.The approach illustrates how combining advanced AI methods with human expertise can address the multifactorial challenges of facade design within current industry practices. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-84862 SN - 978-9-083451-31-2 SN - 2684-1150 VL - 6 SP - 192 EP - 199 PB - European Council for Computing in Construction ER - TY - JOUR A1 - Hantsch, Carolin A1 - Westner, Markus A1 - Matschi, Markus T1 - IT/OT Convergence: Status Quo and Implementation Recommendations N2 - This study examines IT/OT Convergence in 31 predominantly large German companies. It presents an "IT/OT Governance Framework" as a specific model for successful convergence implementation. The in-terviews revealed that companies are at very different stages of maturity in implementing IT/OT conver-gence. The analysis reveals a heterogeneous level of convergence maturity across the interviewed compa-nies, the majority of which are at the beginning or in the implementation phase. Close cooperation between IT and OT is favoured, but without IT completely taking over OT. An IT/OT tandem consisting of a CIO and a central OT responsible person is seen as the ideal way to take responsibility. Six specific recommen-dations were derived from the interviews and included in the IT/OT Governance Framework developed. These include ensuring top management support, using security as a driver, introducing a central OT re-sponsible person, bringing IT and OT teams closer together, continuously demonstrating the added value of convergence, and taking a step-by-step approach to implementation KW - IT/OT Konvergenz KW - IT KW - OT KW - Governance KW - Framework Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-77586 N1 - This document is an English translation of the article Hantsch, C., Westner, M. & Matschi, M. IT/OT-Konvergenz: Status-Quo und Umsetzungsempfehlungen. HMD (2024). https://doi.org/10.1365/s40702-024-01111-1 N1 - Die deutsche Originalveröffentlichung ist abgelegt unter: https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/7793 ER - TY - CHAP A1 - Ho, Joe Ee A1 - Ooi, Boon Yaik A1 - Westner, Markus T1 - Application Integration Framework for Large Language Models T2 - 2024 5th International Conference on Artificial Intelligence and Data Sciences (AiDAS), Bangkok, Thailand, 03-04 September 2024 N2 - Large Language Models (LLMs) have unlocked new opportunities in processing non-structured information. However, integrating LLM into conventional applications poses challenges due to their non-deterministic nature. This paper introduces a framework designed to effectively integrate LLM into intermediate modules by ensuring more consistent and reliable outputs. The framework includes three key components: the Sieve, which captures and retries processing of incorrect outputs; the Circuit Breaker, which stops processing persistently incorrect outputs; and the Optimizer, which enhances processing efficiency by combining inputs into single prompts. Experimental results employing structured methodology demonstrate the framework's effectiveness, achieving significant improvements a 71.05% reduction in processing time and an 82.97% reduction in token usage while maintaining high accuracy. The proposed framework, agnostic to specific LLM implementations, aids the integration of LLMs into diverse applications, enhancing automation and efficiency in fields such as finance, healthcare, and education. KW - error handling KW - token efficiency KW - AI integration KW - data pipeline optimization KW - automation KW - data processing framework Y1 - 2024 SN - 979-8-3315-2855-3 U6 - https://doi.org/10.1109/AiDAS63860.2024.10730541 SP - 1 EP - 6 PB - IEEE ER - TY - CHAP A1 - Preiß, Niklas A1 - Westner, Markus T1 - Towards a Taxonomy for Digital Assistant Technologies: Addressing the Jingle-Jangle Fallacies T2 - 38th Bled eConference: empowering transformation: shaping digital futures for all: conference proceedings, 8.-11.6.2025, Bled N2 - This study proposes a unified taxonomy for Digital Assistant Technologies (DATs) to resolve terminological inconsistencies and eliminate »Jingle-Jangle fallacies.« By employing a systematic taxonomy development method on 137 papers, the framework categorizes DATs across four meta-characteristics: AI technology, context, intelligence, and interaction. This taxonomy facilitates the clear differentiation of three primary DAT concepts: assistant, chatbot, and agent. By providing a structured framework, the study enhances conceptual clarity, fosters more focused research, and ensures better alignment of DATs. Y1 - 2025 SN - 9789612869984 U6 - https://doi.org/10.18690/um.fov.4.2025.1 SP - 1 EP - 20 PB - University of Maribor Press ER - TY - GEN A1 - Capellmann, Dominik A1 - Westner, Markus T1 - ChatGPT in Software Engineering: Potentials, Challenges and Possible Applications for Unit Testing and Code Debugging T2 - 21st International Conference on Applied Computing 2024 Y1 - 2024 ER - TY - CHAP A1 - Stadlbauer, Jana A1 - Frommeld, Debora A1 - Chow, Rosan A1 - Weber, Karsten ED - Grabbe, Lars C. T1 - Partizipative Designpraktiken für verkörperte Künstliche Intelligenz T2 - Designforschung und KI N2 - Der Beitrag thematisiert partizipative Designpraktiken für verkörperte Künstliche Intelligenz und untersucht, wie Nutzende stärker in den Gestaltungsprozess eingebunden werden können. Ausgehend von Design-Thinking-Modellen, die Nutzendengruppen aktiv an der Technikgestaltung beteiligen, geht der Gedanke des Beitrags noch weiter und stellt das Konzept des participatory theatre vor – eine explorative Methode, die im Rahmen der Ausstellung ‚Leben mit Robotern‘ an der OTH Regensburg eingesetzt wurde. Besuchende konnten sich als Roboter verkleiden und in Rollenspielen Interaktionen mit Technik simulieren. Diese performative Herangehensweise eröffnete neue Perspektiven auf das Design von Robotern und auf die Wahrnehmung verkörperter KI. Mit einer qualitativen, inhaltsanalytischen Auswertung von knapp 90 Aussagen von Besuchenden wird untersucht, wie Menschen auf das Design von Robotik und KI reagiert haben und inwieweit alltagsrelevante Designprinzipien zur Sprache kommen. Die Ergebnisse zeigen eine mehrheitlich offene bis begeisterte Haltung gegenüber Robotern. Kritik und Zurückhaltung wurde seltener geäußert. Es wird diskutiert, inwieweit zentrale Aspekte wie Design einen Einfluss auf die Wahrnehmung von Robotern haben können. Der Beitrag betont die gesellschaftliche Relevanz ästhetischer Gestaltung und plädiert für interdisziplinäre, explorative Forschungsansätze, um KI-Systeme nutzungsnah und kulturell sensibel zu entwickeln. Y1 - 2025 SN - 9783658497972 U6 - https://doi.org/10.1007/978-3-658-49798-9_8 SN - 2731-9458 SP - 123 EP - 137 PB - Springer CY - Wiesbaden ER - TY - CHAP A1 - Maier, Johannes A1 - Haug, Sonja A1 - Huber, Michaela A1 - Katzky, Uwe A1 - Neumann, Sabine A1 - Perret, Jérôme A1 - Prinzen, Martin A1 - Weber, Karsten A1 - Wittenberg, Thomas A1 - Wöhl, Rebecca A1 - Scorna, Ulrike A1 - Palm, Christoph T1 - Development of a haptic and visual assisted training simulation concept for complex bone drilling in minimally invasive hand surgery T2 - CARS Conference, 5.10.-7.10.2017 Y1 - 2017 ER - TY - GEN ED - Tolxdorff, Thomas ED - Deserno, Thomas M. ED - Handels, Heinz ED - Maier, Andreas ED - Maier-Hein, Klaus H. ED - Palm, Christoph T1 - Bildverarbeitung für die Medizin 2020 BT - Algorithmen – Systeme – Anwendungen. Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin N2 - In den letzten Jahren hat sich der Workshop "Bildverarbeitung für die Medizin" durch erfolgreiche Veranstaltungen etabliert. Ziel ist auch 2020 wieder die Darstellung aktueller Forschungsergebnisse und die Vertiefung der Gespräche zwischen Wissenschaftlern, Industrie und Anwendern. Die Beiträge dieses Bandes - einige davon in englischer Sprache - umfassen alle Bereiche der medizinischen Bildverarbeitung, insbesondere Bildgebung und -akquisition, Maschinelles Lernen, Bildsegmentierung und Bildanalyse, Visualisierung und Animation, Zeitreihenanalyse, Computerunterstützte Diagnose, Biomechanische Modellierung, Validierung und Qualitätssicherung, Bildverarbeitung in der Telemedizin u.v.m. KW - Bildanalyse KW - Bildverarbeitung KW - Computerunterstützte Medizin KW - Deep Learning KW - Visualisierung Y1 - 2020 SN - 978-3-658-29266-9 U6 - https://doi.org/10.1007/978-3-658-29267-6 PB - Springer Vieweg CY - Wiesbaden ER - TY - CHAP A1 - Schwägerl, Felix A1 - Buchmann, Thomas A1 - Westfechtel, Bernhard T1 - Multi-variant model transformations - a problem statement T2 - Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering N2 - Model Transformations are a key element of Model-Driven Software Engineering. As soon as variability is involved, transformations become increasingly complicated. The lack of support for variability in model transformations impairs the acceptance of approaches to organized reuse such as software product lines. In this position paper, the general problem of multi-variant model transformations is formulated for MOF-based, XMI-serialized models. A simplistic case study is presented to specify the input and the expected output of such a transformation. Furthermore, requirements for tool support are defined, including a standardized representation of both multi-variant model instances and variability information, as well as an execution specification for multi-variant transformations. A literature review reveals that the problem is weakly identified and often solved using ad-hoc solutions; there exists no tool providing a general solution to the proposed problem statement. The observation s presented here may serve for the future development of standards and tools. KW - Model-Driven Software Engineering KW - Software Product Lines KW - Model Transformations KW - Code Generation Y1 - 2016 SN - 978-989-758-189-2 U6 - https://doi.org/10.5220/0005878702030209 SN - 2184-4895 SP - 203 EP - 209 PB - SCITEPRESS ER - TY - JOUR A1 - Hantsch, Carolin A1 - Westner, Markus A1 - Matschi, Markus T1 - IT/OT-Konvergenz: Status-Quo und Umsetzungsempfehlungen JF - HMD Praxis der Wirtschaftsinformatik N2 - Organisationen machen große Anstrengungen zur Verbesserung ihrer Ambidextrie, d. h. ihrer Fähigkeit sowohl Exploitationsziele (z. B. Effizienz, Vorhersagbarkeit) als auch Explorationsziele (z. B. Anpassbarkeit, Innovation) zu erreichen. Obwohl gemäß der Praxisliteratur Technologie in Software-Projekten dabei eine zentrale Rolle spielen kann, gibt es kaum Forschung dazu, wie technologische Faktoren Ambidexterie in Software-Projekten beeinflussen. In dieser Studie untersuchen wir die Rolle dreier technologischer Faktoren: kontinuierliche Integration, Standardisierung und Microservice-Architektur. Die Ergebnisse einer Mehrinformanten-Umfrage in 95 Projekten in der Schweiz und Dänemark zeigen, dass kontinuierliche Integration und Standardisierung mit höherer Ambidexterie einhergehen, während der Zusammenhang zwischen Microservice-Architektur und Ambidextrie nicht signifikant ist. Unser Artikel geht über die existierende Forschung hinaus, indem er zeigt, dass kontinuierliche Integration und Standardisierung nicht nur Exploitation, sondern auch Exploration fördern können. Wir diskutieren auch Gründe für den insignifikanten Zusammenhang zwischen Microservice-Architektur und Ambidextrie. N2 - This study examines IT/OT Convergence in 31 predominantly large German companies. It presents an “IT/OT Governance Framework” as a specific model for successful convergence implementation. The analysis reveals a heterogeneous level of convergence maturity across the examined companies, the majority of which are at the beginning or in the implementation phase. Close cooperation between IT and OT is favored, but without IT completely taking over OT. An IT/OT tandem consisting of a CIO and a central OT responsible person is seen as the ideal way to take responsibility. Six specific recommendations were derived from the interviews and included in the IT/OT Governance Framework developed. These include ensuring top management support, using security as a driver, introducing a central OT responsible person, bringing IT and OT teams physically closer together, continuously demonstrating the added value of convergence, and taking a step-by-step approach to implementation. KW - IT/OT Convergence KW - Operational Technology KW - OT KW - Governance Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-77937 N1 - Corresponding author der OTH Regensburg: Markus Westner PB - Springer Nature ER - TY - CHAP A1 - Saffert, Anne-Sophie A1 - Wiederer, Jonas A1 - Höng, Simon A1 - Linner, Thomas A1 - Obergrießer, Mathias A1 - Neumann, Patrick T1 - Towards AI-based optimization of human-centered and robot-assisted construction processes T2 - Proceedings of the 42nd International Symposium on Automation and Robotics in Construction (ISARC), Montreal, Canada July 28-31, 2025 N2 - This research explores an innovative AI-driven approach to optimizing construction processes with a focus on humancentered design, addressing key challenges in the construction industry, such as skilled labor shortages and ergonomic risks associated withwork-related musculoskeletal disorders. By integrating process design with AI-based algorithms into simulation tools, various construction process layout variants including robot-assisted scenarios can be simulated and evaluated based on user-specific key performance indicators (e.g., ergonomic score, layouting parameters) to identify optimized solutions. A data processing algorithm automates the process, eliminating the need for manual simulation variations and resulting in increased operational productivity. The AI-based system evaluates and optimizes process layouts by adjusting control parameters. A case study on a brick laying process serves as an exemplary use case, highlighting the necessity and impact of adopting process optimization. The findings emphasize the transformative potential of automated process optimization within simulation environments to rethink existing construction practices, enhance worker well-being, and boost operational productivity. KW - AI-based Learning KW - Simulation KW - Process optimization KW - Human Factors KW - Parametric Design Automation Y1 - 2025 SN - 978-0-6458322-2-8 U6 - https://doi.org/10.22260/ISARC2025/0112 SN - 2413-5844 N1 - Präsentationsvideo: https://www.youtube.com/watch?v=QL-1mIuy-_M SP - 861 EP - 868 PB - IAARC ER - TY - CHAP A1 - Schwägerl, Felix A1 - Uhrig, Sabrina T1 - Tool Support for the Evaluation of Matching Algorithms in the Eclipse Modeling Framework T2 - Proceedings of the 1st International Conference on Model-Driven Engineering and Software Development, February 19-21, 2013, in Barcelona, Spain, Vol. 1 N2 - In the field of model-driven development, sophisticated support for comparing model versions is urgently needed. Unfortunately, algorithms for model matching have been rarely evaluated so far. This paper deals with two extensions to the Eclipse Modeling Framework (EMF) that facilitate the evaluation of matching algorithms for EMF models, with the goal to combine user involvement and automated testing in the evaluation process. First a tree editor is presented that allows for the manual and semi-automated creation of match models which formalize the intended matching result. Second a benchmarking procedure is implemented which – given the intended match and the actual results of matching algorithms – automatically derives the number of a and b errors in a target-performance comparison. These results are valuable for drawing conclusions about the specific qualities of matching algorithms or for finding an adequate set of parameters for a configurable algorithm. KW - EMF Models KW - Model Comparison KW - Matching Algorithms KW - Evaluation Y1 - 2013 SN - 978-989-8565-42-6 U6 - https://doi.org/10.5220/0004310801010110 SN - 2184-4348 SP - 101 EP - 110 PB - SciTePress - Science and and Technology Publications ER - TY - CHAP A1 - Buchmann, Thomas A1 - Schwägerl, Felix T1 - Using Meta-code Generation to Realize Higher-order Model Transformations T2 - Proceedings of the 8th International Joint Conference on Software Technologies, July 29-31, 2013, in Reykjavík, Iceland, Vol. 1 N2 - Model-driven engineering is a wide-spread paradigm in modern software engineering. During the last couple of years, many tools and languages have been developed, which are especially designed for model transformations — a discipline which is needed in many model-driven engineering approaches. While most of the existing model-to-model tools and languages are tailored towards batch transformations for specific model instances, they lack support for generic transformation problems, where the metamodel is unknown beforehand. In this paper we present a two-step meta-code generation approach that derives a metamodel-specific modelto- model transformation from a model-to-text transformation. The approach has been successfully applied to the problem of product derivation in model-driven software product lines. KW - Model-driven Development KW - M2M Transformations KW - Model Transformations KW - Higher-order Transformations KW - Software Product Lines Y1 - 2013 SN - 978-989-8565-68-6 U6 - https://doi.org/https://doi.org/10.5220/0004522305360541 SP - 536 EP - 541 PB - SciTePress - Science and and Technology Publications ER - TY - CHAP A1 - Greiner, Nina A1 - Currle, Edda A1 - Bahr, Gudrun A1 - Weber, Karsten ED - Weber, Karsten ED - Haug, Sonja ED - Lauer, Norina ED - Mohr, Christa ED - Pfingsten, Andrea ED - Raptis, Georgios ED - Bahr, Gudrun T1 - Die Rekrutierung von Proband*innen im Projekt DeinHaus 4.0 Oberpfalz BT - Prozess, Herausforderungen und Bewertung T2 - Digitale Technik für ambulante Pflege und Therapie III - Nutzung, Akzeptanz, Wirkung und Lebensqualität N2 - Beschrieben wird der Rekrutierungsprozess im Projekt DeinHaus 4.0. Hierbei werden die spezifischen Herausforderungen bei der Akquise von Schlaganfallbetroffenen aufgezeigt und diskutiert. T3 - Regensburger Beiträge zur Digitalisierung des Gesundheitswesens - 4 KW - Rekrutierung KW - Schlaganfallpatient KW - Forschungsprojekt KW - Telerehabilitation KW - Herausforderungen Y1 - 2024 SN - 978-3-8394-6728-2 U6 - https://doi.org/10.14361/9783839467282-004 SP - 29 EP - 61 PB - transcript CY - Bielefeld ER - TY - CHAP A1 - Staufer, Susanne A1 - Bugert, Flemming A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Ezer, Timur A1 - Nadimpalli, Vamsi Krishna A1 - Bittner, Dominik A1 - Röhrl, Simon A1 - Mottok, Jürgen ED - Gómez Chova, Luis ED - González Martínez, Chelo ED - Lees, Joanna T1 - Tyche algorithm: Markov models for generating learning paths in learning management systems T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - In the intricate tapestry of the cosmos, where celestial threads weave stories of destiny, an enigmatic deity stands at the intersection of chance and fate — Tyche, the goddess of fortune. In science and probability, coincidence plays a distinctive role in Bayesian Networks (BNs) and Markov Models (MMs). This paper introduces the Tyche algorithm named after the goddess of fortune. The Tyche algorithm is a Markov model designed to generate learning paths in Learning Management Systems (LMSs). A learning path is a type of individualization that personalises the order of learning elements within an LMS course. Learning elements are fundamental components within an LMS course, depicting the learning content in diverse ways. In our case, the learning path tailoring is based on the learner’s learning style according to Felder-Silverman Learning Style Model (FSLSM) – an indicator for the ideal pathway and learning element for the learner’s optimum learning. The Tyche algorithm offers the advantage to provide students the most suitable learning path. Tyche is a MM structure with various matrices containing transition probabilities depending on the learning style. Nine categories of learning elements defined in a previous survey form the basis of the node structure of the MM. For a generic approach, a survey was designed to obtain the transition probabilities depending on the individual learning style. The survey with more than 100 German students participated is processed with the tool LimeSurvey. Students are asked about their learning style using the Index of Learning Styles (ILS) questionnaire according to Felder-Silverman and about the percentage probabilities of learning elements to get their individual sequence as learning path. The percentages are queried in two different ways. Firstly, the students were asked to provide a sequence of learning elements within each position of the sequence filled with probabilities for all learning elements. Secondly, a learning element is given and the students are asked to indicate which learning element they would work on next. The first way of asking for the probabilities is used to find the start node in the MM, whereas the second approach forms the probability matrices between the nodes within the MM. As result of the survey, the Tyche algorithm presents generic transition probabilities. It improves the learning process of individuals only by asking for their learning style: it generates individual learning paths through the learning elements within an LMS based on the MM explained above by solely getting the answers of the ILS questionnaire as input. In the future, other questionnaires such as BFI-10 for personality traits or LIST-K for learning strategies may offer a more comprehensive input. However, the next step is to evaluate Tyche with about 25 students in a software engineering lecture. This is planned for the year 2024. KW - Markov model KW - learning style KW - learning elements KW - learning management system KW - higher education area Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-71148 SN - 978-84-09-59215-9 SN - 2340-1079 SP - 4195 EP - 4205 PB - IATED Academy ER - TY - CHAP A1 - Franz, Maja A1 - Winker, Tobias A1 - Groppe, Sven A1 - Mauerer, Wolfgang T1 - Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation T2 - 2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 15-20 September 2024, Montreal, QC, Canada N2 - Identifying optimal join orders (JOs) stands out as a key challenge in database research and engineering. Owing to the large search space, established classical methods rely on approximations and heuristics. Recent efforts have successfully explored reinforcement learning (RL) for JO. Likewise, quantum versions of RL have received considerable scientific attention. Yet, it is an open question if they can achieve sustainable, overall practical advantages with improved quantum processors. In this paper, we present a novel approach that uses quantum reinforcement learning (QRL) for JO based on a hybrid variational quantum ansatz. It is able to handle general bushy join trees instead of resorting to simpler left-deep variants as compared to approaches based on quantum(-inspired) optimisation, yet requires multiple orders of magnitudes fewer qubits, which is a scarce resource even for post-NISQ systems. Despite moderate circuit depth, the ansatz exceeds current NISQ capabilities, which requires an evaluation by numerical simulations. While QRL may not significantly outperform classical approaches in solving the JO problem with respect to result quality (albeit we see parity), we find a drastic reduction in required trainable parameters. This benefits practically relevant aspects ranging from shorter training times compared to classical RL, less involved classical optimisation passes, or better use of available training data, and fits data-stream and low-latency processing scenarios. Our comprehensive evaluation and careful discussion delivers a balanced perspective on possible practical quantum advantage, provides insights for future systemic approaches, and allows for quantitatively assessing trade-offs of quantum approaches for one of the most crucial problems of database management systems. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-76877 N1 - Corresponding author der OTH Regensburg: Maja Franz SP - 409 EP - 420 PB - IEEE ER -