TY - JOUR A1 - Geldof, Arne A1 - Kopačin, Jan A1 - Straus, Izidor A1 - Kriegl, Raphael A1 - Kravanja, Gaia A1 - Hribar, Luka A1 - Jezeršek, Matija A1 - Shamonin, Mikhail A1 - Kokot, Gašper A1 - Drevenšek‐Olenik, Irena T1 - Transfer of Energy and Momentum Between Magnetoactive Surface Microstructure and a Solid Object JF - Advanced Engineering Materials N2 - Transport systems utilizing magnetic materials are very promising for applications that require contactless operation and compatibility with biological processes. A critical parameter in these systems is the efficiency of energy and momentum transfer between the transporting platform and the objects being transported. We investigate the physical mechanisms driving directional transport of solid objects by microlamellar structures laser-inscribed on the surface of a magnetoactive elastomer (MAE). When subjected to a rotating magnetic field with a magnitude of 175 mT and a time period of 0.4 s, the lamellas reorient within a few milliseconds, reaching angular velocities up to 1100 rad s−1. This rapid motion is crucial for efficient momentum and energy transfer to objects in contact with the lamellas. The analysis of collisions of a single lamella with a lead ball with a 2.2 mm diameter shows that the lamella can transfer around 50 nJ of energy, propelling the ball to a speed of around 35 mm s−1. We show how this value sets the upper limit for the ball's transport speed on microlamellar structures. We also explain the background of three distinct transport regimes (kicking, pushing, and bouncing modes) observed on these magnetically driven “conveyor belts”. Y1 - 2026 U6 - https://doi.org/10.1002/adem.202502369 VL - 28 IS - 6 PB - Wiley ER - TY - CHAP A1 - Riemann, Janine A1 - Klug, Katharina A1 - Christ, Luisa A1 - Stadler, Sebastian T1 - Impact of Social Features on User Experience in Sport Tracking Applications T2 - 2025 11th International HCI and UX Conference in Indonesia (CHIuXiD), 05-06. December 2025, Bali, Indonesia N2 - Sport-tracking applications can enhance physical activity but may also induce stress through social comparison. This study examines how social comparison features influence user experience (UX), focusing on motivation, stress, and mental well-being. A survey of 101 German sport-tracking app users assessed intrinsic and extrinsic motivation, perceived stress, self-efficacy, enjoyment, social comparison orientation, and UX. Results reveal that higher social comparison consistently lowers intrinsic motivation, raises extrinsic motivation, and increases stress levels, while positive UX boosts intrinsic motivation and enjoyment and indirectly buffers stress. In particular, users who frequently evaluate their performance against others reported greater pressure to perform, heightened frustration, and a stronger focus on external validation. integrating adaptive feedback, and offering customizable social elements. Overall, the study contributes to understanding how UX and motivational dynamics interact in digital health tools and provides guidance for developing psychologically informed, health-oriented app environments. Conversely, app designs prioritizing mastery and personal progress over competitive ran kings foster autonomy, competence, and relatedness, supporting mental health and long-term adherence. These findings highlight the ambivalent effects of social features and underscore the need for sport-tracking apps to minimize harmful comparisons and promote self-determined motivation through supportive, user-friendly features. Practical implications include designing for sustainable engagement and well-being rather than exclusive competition. Y1 - 2025 SN - 979-8-3315-5572-6 U6 - https://doi.org/10.1109/CHIuXiD68326.2025.11323615 SP - 25 EP - 30 PB - IEEE ER - TY - JOUR A1 - Haug, Sonja A1 - Currle, Edda A1 - Weber, Karsten T1 - Acceptance of Medical History-Taking Supported by Artificial Intelligence and Chatbots: A Population-Based Survey in Germany JF - Healthcare N2 - Background/Objectives: Digital anamnesis tools, including chatbots, are increasingly being developed and evaluated, yet their implementation in German medical practices remains limited. This study examines the acceptance of medical history-taking assisted by artificial intelligence (AI) among the German population. The objective is to derive implications for integrating such systems into digitalization strategies of medical practices. Methods: This study is based on an online survey of the German population, aged between 18 and 74 years, conducted in two independent cross-sectional waves (trend design) in 2024 and 2025 with n = 1000 respondents in each year. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT), three hypotheses regarding the use of AI in medical history-taking were developed and tested using linear regression models. Results: Both waves reveal a high acceptance level of AI-supported anamnesis systems for people aged between 18 and 74, regardless of whether a chatbot is used in medical practice (Scenario 1) or at home (Scenario 2). The latter received slightly less approval for the intention to use (mean intention scores: 3.50 and 3.45, range from 1.0 to 5.0) than Scenario 1 (3.59, 3.56). The indices of Performance Expectancy (PE), Effort Expectancy (EE), and perceived Social Influence (SI) determine the intention to use a chatbot with the strongest correlation of the PE index (Scenario 1: ß =0.466, Scenario 2: ß = 0.475). Most respondents (73% and 75%) expressed a favorable opinion for digitally storing medical history data within their electronic health record (EHR). Conclusions: The findings suggest that gender- and age- specific differentiation—aside from considering the needs of older adults—may be less relevant for designing digitalization strategies than previously assumed. Instead, the focus of medical practices should lie on the practicability of the tool used. Despite currently low EHR utilization rates in Germany, medical practices may expect broad patient approval regarding the digital storage of medical history data. Y1 - 2026 U6 - https://doi.org/10.3390/healthcare14070905 N1 - Corresponding author der OTH Regensburg: Sonja Haug VL - 14 PB - MDPI CY - Basel ER - TY - BOOK A1 - Stadler, Anselm A1 - Mohr, Christa A1 - Teves, Stephanie T1 - Educational Concept - Using VR applications in nursing education T3 - VReduMED Handbook. for VR integration in care education, presenting the project toolkit, an educational concept and recommendations for its sustainable transfer N2 - The following chapter provides teachers with clear guidance on key aspects to consider when introducing XR. It is structured into three main sections. First, the technical prerequisites and conditions are outlined, focusing on aspects that should be taken into account prior to procurement as well as during integration into everyday teaching practice. Building on this, organizational factors that are essential for successful implementation are examined. Finally, the didactic integration of XR is addressed, highlighting the aspects that are critical for effective educational use. The findings from the VReduMED project are complemented by insights from international studies on this topic. Y1 - 2026 UR - https://www.vredumed.eu/wp-content/uploads/VReduMED_Handbook_version_18032026_FINAL.pdf SP - 68 EP - 77 PB - Interreg CENTRAL EUROPE ER - TY - JOUR A1 - Schmiedt, Anja B. A1 - Balakrishnan, Narayanaswamy A1 - Cramer, Erhard T1 - Generalized chi-squared based goodness-of-fit tests under progressive Type-II censoring for exponential and Weibull distributions JF - Communications in Statistics - Simulation and Computation N2 - We propose new goodness-of-fit tests for exponentiality based on progressively Type-II censored data. These tests utilize scale-invariant statistics obtained from the Mahalanobis norm of normalized order statistics, leading to three test statistics, corresponding to 𝐿2-, 𝐿1-, and 𝐿∞-norms of centered uniform spacings. Exact and asymptotic distributions of these statistics are presented. A power study evaluates the proposed tests against existing benchmarks across various alternative distributions and censoring plans, demonstrating superior performance in cases with small and moderate sample sizes. Furthermore, we extend the methodology to approximate goodness-of-fit tests for Weibull distributions via power transformation, ensuring robustness w.r.t. the approximated significance level under unknown shape parameters. An illustrative data example confirms the practical applicability of our tests. Our findings highlight the potential for further extending goodness-of-fit tests under progressive Type-II censoring to other null distributions. Y1 - 2026 U6 - https://doi.org/10.1080/03610918.2026.2625230 PB - Taylor & Francis ER - TY - JOUR A1 - Apel, Thomas A1 - Fellner, Klemens A1 - Kempf, Volker A1 - Salcedo-Lagunero, Reymart A1 - Zilk, Philipp T1 - Lipolysis on Lipid Droplets: Mathematical Modelling and Numerical Discretisations JF - Results in Mathematics N2 - Lipolysis is a life-essential metabolic process, which supplies fatty acids stored in lipid droplets to the body in order to match the demands of building new cells and providing cellular energy. In this paper, we present a first mathematical modelling approach for lipolysis, which takes into account that the involved enzymes act on the surface of lipid droplets. We postulate an active region near the surface where the substrates are within reach of the surface-bound enzymes and formulate a system of reaction-diffusion PDEs, which connect the active region to the inner core of lipid droplets via interface conditions. We establish two numerical discretisations based on finite element method and isogeometric analysis, and validate them to perform reliably. Since numerical tests are best performed on non-zero explicit stationary state solutions, we introduce and analyse a model, which describes besides lipolysis also a reverse process (yet in a physiologically much oversimplified way). The system is not coercive such that establishing well-posedness is a non-standard task. We prove the unique existence of global and equilibrium solutions. We establish exponential convergence to the equilibrium solutions using the entropy method. We then study the stationary state model and compute explicitly for radially symmetric solutions. Concerning the finite element methods, we show numerically the linear and quadratic convergence of the errors with respect to the - and -norms, respectively. Finally, we present numerical simulations of a prototypical PDE model of lipolysis and illustrate that enzyme clustering on lipid droplets can significantly slow down lipolysis. Y1 - 2026 U6 - https://doi.org/10.1007/s00025-026-02639-y VL - 81 IS - 3 PB - Springer Nature ER - TY - CHAP A1 - Hoffmann, Tim A1 - Dietrich, Florian A1 - Melzer, Matthias A1 - Dünnweber, Jan ED - Yurish, Sergey Y. T1 - A Code Generation Framework for Indoor Robot Applications Based on Building Information Modeling (BIM) T2 - Automation, Robotics & Communications for Industry 4.0/5.0: Proceedings of the 6th Winter IFSA Conference on Automation, Robotics & Communications for Industry 4.0/5.0/6.0 (ARCI' 2026) 25-27 February 2026 Salzburg, Austria N2 - We present BIM2Robot, a framework connecting the digital planning world (Building Information Modeling) with real-world robotics. The aim of the tools we developed is to convert building data from IFC building plans (Industry Foundation Classes) such that autonomous robots can use them for navigation and task planning. Conventional robotics systems rely on hard-coded maps or proprietary data. In the BIM2Robot framework, we generate a robot-compatible building model automatically from existing BIM data. This model describes rooms, walls, doors, and connections allowing robots to understand their environment, move around in it, and carry out useful missions. Besides the data transformation tools, our software framework comprises a graphical user interface which allows for interactive planning, path visualization and remote process control. The generated building model can be used directly by ROS-compliant robots or in robot simulation environments, forming a basis for navigation, perception, and interaction. The manual post-processing of the generated robot motion plans is supported at GUI- and also at code-level. Y1 - 2026 UR - https://www.researchgate.net/profile/Sergey-Yurish/publication/401427390_Automation_Robotics_Communications_for_Industry_405060/links/69a567ae16faea00ba9b9b02/Automation-Robotics-Communications-for-Industry-40-50-60.pdf#page=41 SN - 978-84-09-82030-6 SP - 40 EP - 44 PB - IFSA ER - TY - CHAP A1 - Bachir, Hussein A1 - Weikl, Simone T1 - Identifying Cyclist Riding Styles Using Drone-Based Trajectory Data and Volatility Clustering in Free-Flow Traffic Conditions T2 - 2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), 18-21. November 2025, Gold Coast, Australia N2 - Cycling is increasingly promoted as a sustainable and healthy urban transportation mode. However, understanding cyclists' behavior remains underdeveloped compared to car drivers' behavior research. This paper proposes a two-level unsupervised clustering framework to identify cyclist riding styles in free flow conditions from drone-recorded trajectory data. The first level classifies local riding behavior at the timestamp level using riding volatility measures. The second level identifies overall cyclist behavior through clustering entropy measures, mean rotation fluctuation and surrounding traffic density at the trajectory level. The method was applied to a dataset of 284 trajectories and 100,000 data points from a 500-meter urban road segment in Munich, Germany and revealed two riding patterns on both levels: stable and volatile. The findings highlight the influence of road design clarity and behavioral variability and provide a foundation for cyclist-focused behavior and infrastructure analysis. Y1 - 2025 SN - 979-8-3315-2418-0 U6 - https://doi.org/10.1109/ITSC60802.2025.11423140 SP - 233 EP - 240 PB - IEEE ER - TY - CHAP A1 - Norbisrath, Ulrich A1 - Rossi, Bruno A1 - Jubeh, Ruben A1 - Heydarov, Araz T1 - Multi-Stage Testing for Open Source IoT Frameworks T2 - 2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 5-8. October 2025, Vienna N2 - The Internet of Things (IoT) has rapidly evolved, integrating networked intelligence into a web of things, servers, and cloudlets. Although there are various tools and approaches for software testing, the broader field of IoT testing presents unique challenges due to the heterogeneity of devices, large-scale deployments, dynamic environments, and real-time needs. This paper presents our approach to developing a multi-stage testing framework for the IoTempower framework, addressing the challenges of testing a versatile and evolving open-source Internet-of-Things framework used extensively in educational settings and beyond. The framework incorporates compilation testing, integration testing, and system testing with a focus on regression testing. This multi-stage testing approach allows us to validate the framework’s functionality at various granularities, from the correct compilation of individual drivers to the seamless interaction of deployed hardware. This approach aims to proactively identify and prevent regressions, facilitating the integration of new features and enhancements without losing our scope of providing a real hands-on IoT experience in the classroom. Y1 - 2025 SN - 979-8-3315-3358-8 U6 - https://doi.org/10.1109/SMC58881.2025.11343478 SP - 4685 EP - 4690 PB - IEEE ER - TY - CHAP A1 - Barik, Ranjan Kumar A1 - Rawat, Vikram Singh A1 - Manna, Subhrajit A1 - Bandyopadhyay, Ayan Kumar A1 - Hausladen, Matthias A1 - Asgharzade, Ali A1 - Schreiner, Rupert T1 - On Chip Electron Gun Design Using Silicon Tip Field Emitter Array T2 - 2025 IEEE Microwaves, Antennas, and Propagation Conference (MAPCON), 14-18. Dezember 2025, Kochi, India N2 - Silicon based silicon tip array emitter has developed at OTH Regensburg, Germany. This array emitter is the basis for development of a novel electron gun. This field emitter electron sources were fabricated using laser-micromachining technique followed by MEMS technology. In this work, the design and development of electron gun using complete silicon structure is reported. The goal of this work is to develop electron gun using less effort, easy and hassle free technique. Y1 - 2025 SN - 979-8-3315-3722-7 U6 - https://doi.org/10.1109/MAPCON65020.2025.11426578 PB - IEEE ER - TY - CHAP A1 - Michel, Johanna A1 - Krenkel, Lars ED - Dillmann, Andreas ED - Heller, Gerd ED - Krämer, Ewald ED - Breitsamter, Christian ED - Wagner, Claus ED - Krenkel, Lars T1 - Towards Experimental Validation of Models of Shear-Induced Aerosol Generation in the Human Respiratory System T2 - New Results in Numerical and Experimental Fluid Mechanics XV : Contributions to the 24th STAB/DGLR Symposium, Regensburg, Germany, 2024 N2 - Numerical modeling is a valuable tool to research shear-induced aerosol generation inside the human respiratory system. While the volume of fluid method and Eulerian wall film models have been used to predict the stripping of particles from the mucus film, sufficient validation data is lacking. Here, we present an experimental method to create such validation data. A film of mucus mimetic hydrogel with an initial thickness of 1 mm covering the floor of a rectangular channel (75.5 mm 25.5 mm 3 mm) was exposed to an airflow with a flow rate of 9.5 and 21.6 L/min. The number of created particles and the emergence of waves on the mucus surface were measured. Shear-induced aerosol generation was triggered successfully and caused an increase of mean particle flow. Different wave profiles were observed at varying film depths. Y1 - 2026 SN - 978-3-032-11114-2 U6 - https://doi.org/10.1007/978-3-032-11115-9_13 SP - 135 EP - 144 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Pointner, Daniel A1 - Kranz, Michael A1 - Wagner, Maria Stella A1 - Haus, Moritz A1 - Lehle, Karla A1 - Krenkel, Lars T1 - Automated deep learning based detection of cellular deposits on clinically used ECMO membrane lungs JF - Frontiers in Bioinformatics N2 - Introduction: Despite the promising application of extracorporeal membrane oxygenation (ECMO) in the treatment of critically ill patients, coagulation-associated technical complications, primarily clot formation and critical bleeding, remain a major challenge during ECMO therapy. The deposition of nucleated cells on the surface has been shown, yet the role of these cells towards complication development is still matter of ongoing research. In particular, the membrane lung (MemL) is prone to clot formation. Therefore, the investigation of nuclear deposits on its hollow-fibers may provide insights for a better understanding of the cellular mechanisms involved in the development of ECMO complications. Methods: To support current research, this study aimed to develop a deep learning–based tool for the automated detection and quantitative analysis of nuclear depositions on MemL hollow-fiber mats. A customized fluorescence microscopy workflow, combined with a semi-automated iterative labeling strategy, was used to generate a high-quality dataset for model training. Results: Six configurations of instance segmentation models were evaluated, with a Mask R-CNN with ResNet 101 backbone using dilated convolution providing the most balanced performance in both nuclei count and area accuracy. Compared with U-Net–based approaches such as Cellpose or StarDist, the proposed model demonstrated superior segmentation of overlapping and low-intensity nuclei, maintaining accuracy even in densely packed cellular regions. Discussion: We present an automated image analysis tool for clinically used MemLs, which exhibit complex three-dimensional hollow-fiber architectures and irregular cellular deposits that challenge conventional tools. A dedicated graphical user interface enables streamlined detection, morphometric analysis, and spatial clustering of nuclei, establishing a reproducible workflow for high-throughput analysis of fluorescence microscopy images. This approach eliminates labor-intensive manual counting and facilitates large-scale studies on cell-fiber interactions and disease-related correlations. Y1 - 2026 U6 - https://doi.org/10.3389/fbinf.2026.1771574 N1 - Corresponding author der OTH Regensburg: Daniel Pointner, Lars Krenkel VL - 6 PB - Frontiers ER - TY - GEN A1 - Pöhlmann, Kendra T1 - Bildung für Nachhaltige Entwicklung – Achtsamkeit als Future Skill N2 - Das Poster beleuchtet die Rolle von Achtsamkeit als zentrale Zukunftskompetenz im Kontext von Bildung für nachhaltige Entwicklung (BNE). Ausgangspunkt ist die Annahme, dass nachhaltige Transformation nicht allein durch Wissen über die Sustainable Development Goals (SDGs) gelingt, sondern maßgeblich innere Kompetenzen erfordert, wie sie in den Inner Development Goals (IDGs) beschrieben werden. Achtsamkeit wird dabei als grundlegender Baustein von Selbst- und Reflexionskompetenz verstanden und bildet die Voraussetzung für Fähigkeiten wie Perspektivenwechsel, Ambiguitätstoleranz und verantwortungsvolles Handeln. Das Poster integriert verschiedene Kompetenzrahmen (Future Skills, IDGs, Rounder Sense of Purpose) und zeigt deren konzeptionelle Schnittmengen auf. Es argumentiert, dass Achtsamkeit nicht nur individuelle Entwicklung unterstützt, sondern als Hebel für kollektive Transformationsprozesse wirkt. Für die Hochschullehre ergibt sich daraus die Implikation, Achtsamkeit systematisch in fachliche Kontexte zu integrieren, um Studierende zur aktiven Mitgestaltung nachhaltiger Entwicklung zu befähigen. KW - Bildung für nachhaltige Entwicklung; Transformationskompetenz; innere Entwicklung Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-90168 ER - TY - GEN A1 - Pöhlmann, Kendra T1 - Diversity: Important, Fair, and Sustainable – But Often Overlooked in AI Applications N2 - In the era of digital transformation, the intersection of sustainability and AI has emerged as a critical area of research. My poster delves into the intricate relationship between these two domains, highlighting their potential to shape a more equitable and sustainable future. One significant facet of this is diversity. But diversity, as a vital component of the social dimension of sustainability, is frequently sidelined in the discourse surrounding digitalization and AI, despite its potential to synergize with these technologies in forging a fairer and more sustainable world. Digital solutions frequently lack inclusivity and emancipation, exacerbating disparities in access and opportunity. AI tools, likewise, often perpetuate bias and inequality by being trained on homogeneous datasets, overlooking factors such as gender, ability, and ethnicity. To address this oversight, it is imperative to incorporate diversity and sustainability education into the training of future IT specialists and AI engineers. Developing ethical awareness and the ability to critically reflect on biases within AI systems is essential to avoid reproducing biases and stereotypical thinking. This is why it is imperative to emphasizes the urgency of recognizing diversity as a key enabler of fairness and sustainability within the digital transformation landscape. KW - Digital Transformation; Diversity; Sustainability Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-90156 ER - TY - GEN A1 - Pöhlmann, Kendra T1 - Diversity: Important, fair, and sustainable – but often overlooked in AI applications N2 - In the era of digital transformation, the intersection of sustainability and AI has emerged as a critical area of research. My research delves into the intricate relationship between these two domains, highlighting their potential to shape a more equitable and sustainable future. One significant facet of this is diversity. But diversity, as a vital component of the social dimension of sustainability, is frequently sidelined in the discourse surrounding digitalization and AI, despite its potential to synergize with these technologies in forging a fairer and more sustainable world. Digital solutions frequently lack inclusivity and emancipation, exacerbating disparities in access and opportunity. AI tools, likewise, often perpetuate bias and inequality by being trained on homogeneous datasets, overlooking factors such as gender, ability, and ethnicity. To address this oversight, it is imperative to incorporate diversity and sustainability education into the training of future IT specialists and AI engineers. Developing ethical awareness and the ability to critically reflect on biases within AI systems is essential to avoid reproducing biases and stereotypical thinking. This is why my research emphasizes the urgency of recognizing diversity as a key enabler of fairness and sustainability within the digital transformation landscape. KW - Diversity; Digital Transformation; Sustainability Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-90170 ER - TY - GEN A1 - Pöhlmann, Kendra T1 - Research Based Spin-Offs: Understanding the specifics of Best Performers N2 - This presentation investigates the success factors of research-based spin-offs, with a particular focus on the differences between best and worst performers. Based on an empirical study of German spin-offs originating from public research institutions, key influencing factors such as team size, degree of innovation, market conditions, and the role of the parent organization are analyzed. The findings indicate that spin-off success is shaped by a combination of entrepreneurial, technological, and contextual factors, and varies depending on the applied performance measure (e.g., growth, financial performance, or technological output). The study provides nuanced insights into the mechanisms of successful knowledge and technology transfer and derives implications for both research institutions and founders. KW - Research-based spin-offs; technology transfer; success factors Y1 - 2012 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-90181 ER - TY - GEN A1 - Pöhlmann, Kendra T1 - Similarities and Differences of Research-based and Corporate Spin-offs: Theoretical Thoughts, Research Design and Expected Implications N2 - This presentation explores the similarities and differences between research-based spin-offs and corporate spin-offs, addressing a key gap in the entrepreneurship and innovation literature. While both types of ventures aim at commercializing knowledge and generating economic value, they emerge from distinct institutional contexts and may therefore rely on different success factors. Building on existing research on research-based spin-offs, the study develops a comparative conceptual framework that integrates perspectives from the resource-based view and industrial economics. It examines dimensions such as founder characteristics, motivation structures, knowledge bases, and relationships with parent organizations. The proposed research design aims to systematically contrast both spin-off types and assess the transferability of established success factors. The paper contributes to a more differentiated understanding of spin-off heterogeneity and derives implications for improving commercialization processes in both academic and corporate contexts. KW - Spin-offs; Knowledge Transfer; Commercialization Process Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-90198 ER - TY - THES A1 - Bachl, Hannes T1 - Initial 5G synchronisation using a time-domain correlator N2 - The following Bachelor’s thesis explores the implementation of a fre- quency correlator in the time-domain as required for the initial synchro- nisation in 5G mobile networks. Exact time domain synchronisation is required for modern mobile networks to allow reconstruction of the em- ployed physical modulations schemes without producing excessive amounts of interference. This is the first step in the discovery process of mobile radio cells. Initial the theoretical foundations of time synchronisation mechanisms as used in 5G networks are explored, including the physical modulation schemes employed. The different implementations of the synchronisa- tion algorithms are considered and a single algorithm is chosen for im- plementation. The chosen algorithm is then implemented and the implementation and findings are discussed. The hardware basis for the implementation is a Xilinx RFSoC, a high speed FPGA with associated analog-to-digital con- verts designed for RF signal processing. Finally there will be a discussion of possible optimisations and problems encountered during implementation. Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-89048 CY - Regensburg ER - TY - JOUR A1 - Stenglein, Anna A1 - Appelt, Andreas T1 - Einsatz der Thermographie als Steuerungsinstrument im Asphaltbau – Erkenntnisse aus Erprobungsstrecken mit temperaturabgesenktem Asphalt JF - Straße und Autobahn N2 - Die Sicherstellung homogener Einbautemperaturen ist eine zentrale Voraussetzung für eine dauerhafte Asphaltbefestigung. Dieser Beitrag stellt Ergebnisse aus der wissenschaftlichen Begleitung zweier Erprobungsstrecken zum Einsatz von temperaturabgesenktem Walzasphalt vor. Mithilfe von Thermoscannern wurden die Oberflächentemperaturen des eingebauten Mischguts flächendeckend erfasst und georeferenziert ausgewertet. Die Analyse zeigt, dass insbesondere Lkw-Wechselstellen, Fertigerstillstände und komplexe Einbausituationen zu ausgeprägten Temperaturgradienten führen. Bei temperaturabgesenkten Asphalten wirkt sich dies aufgrund des eingeschränkten Verdichtungszeitfensters besonders kritisch aus. Die Untersuchungen verdeutlichen, dass Thermoscans über ihre dokumentierende Funktion hinaus als wirksames Instrument der bauprozessintegrierten Qualitätskontrolle eingesetzt werden können. Sie unterstützen die Ausführung, indem thermisch bedingte Schwachstellen frühzeitig erkannt und gezielte Anpassungen im Bauprozess ermöglicht werden. Darüber hinaus werden die Abschiebetechnik und ihre Eignung als Alternative zur Kipptechnik mit Beschicker hinsichtlich Temperaturhomogenität und logistischer Randbedingungen bewertet. T2 - Use of thermography as a control tool in asphalt construction – findings from test sections with temperature-reduced asphalt Y1 - 2026 UR - https://www.kirschbaum.de/fachzeitschriften/strasse-und-autobahn/strasse-und-autobahn/aktuelles-heft-47-1.html#c12609 U6 - https://doi.org/10.53184/STA3-2026-3 VL - 77 IS - 3 SP - 182 EP - 191 PB - Kirschbaum Verlag GmbH 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 - Examining Reliance Patterns on AI Advice in Medical Imaging: a Mixed-Methods Randomized Crossover Experiment N2 - Background: Artificial intelligence (AI) holds significant potential to support diagnostic decision-making; however, evidence regarding its clinical utility remains mixed. Often, the collaboration between clinicians and AI systems does not surpass the individual performance of unaided humans or standalone AI. Yet, currently, the mechanisms that limit human-AI synergy are poorly understood. This study examined the impact of AI advice on diagnostic decision-making among experts and novices, focusing on reliance patterns. Methods: We used a mixed-methods crossover experimental design with a think-aloud and an eye-tracking study arm. Participants were 50 task experts (radiologists) and 75 novices (non-radiologist physicians and medical trainees) from 10 countries. They reviewed 50 head CT scans and every case was examined in three time-separate sessions in randomized order. In each session, participants were exposed to different experimental conditions: (a) control, no AI prediction; (b) basic advice, AI prediction without annotations; and (c) XAI advice, AI prediction with scan annotations. For each case, participants had to determine if the patients had an intracranial hemorrhage (ICH). The main outcomes were diagnostic performance, confidence in the diagnosis, case reading time, and AI advice usefulness ratings. Findings: Both overreliance on incorrect advice and underreliance on correct advice occurred. Underreliance was associated with high uncertainty and, in absolute terms, had a more detrimental impact on diagnostic performance than overreliance. Correct XAI advice reduced underreliance, improved performance (OR=1·84, p<0·0001), and confidence (b=0·15, p<0·0001), particularly when reviewing more difficult cases with ICH. Surprisingly, correct XAI did not reduce reading time (b=1·81, p=0·0713). XAI was perceived as more useful than basic AI advice (b=0·12, p=0·0029), especially among novices. Interpretation: The occurrence of both under- and overreliance highlights the need for efficient counterstrategies beyond classic XAI methods to foster appropriate reliance and synergy. Y1 - 2026 U6 - https://doi.org/10.31219/osf.io/4wv8j_v3 ER - TY - INPR A1 - Achhammer, Anton A1 - Fioriti, Davide A1 - Patonia, Aliaksei A1 - Sterner, Michael T1 - The impact of hydrogen underground storage on fair partnerships: a GIS-based integration of salt caverns into PyPSA-Earth N2 - The increasing demand for hydrogen in Europe and the development of cross-border infrastructure, such as the SoutH2 Corridorconnecting Tunisia, Italy, Austria, and Germany, underscore the importance for hydrogen storage solutions to ensure supplysecurity and competitive pricing. Without storage, producers face increased market dependency, as electrolyzers require con-tinuous operation to remain economically viable. At the same time, storage offers opportunities to strengthen domestic valuechains by securing hydrogen supply for local industries. To assess the system-level impact of underground hydrogen storageand its implications for hydrogen partnerships, we integrate GIS-based salt cavern potentials into PyPSA-Earth and apply theframework to Tunisia. Salt caverns are currently largely considered the most economical option for large-scale hydrogen storage,offering operational flexibility. Underground storage is represented as an endogenously optimised, regionally constrained option,enabling a direct comparison between scenarios with and without geological storage under identical demand, technology, andpolicy assumptions.Our results show that underground hydrogen storage enables seasonal balancing at multi-terawatt-hour scale, reshaping hydro-gen system design. Storage availability substitutes most aboveground hydrogen tank capacity, improves electrolyser utilisation,and reduces levelised hydrogen production costs by approximately 0.10 € kg−1. Moreover, it decouples hydrogen production fromshort-term electricity variability and export demand, enhancing supply stability and export competitiveness.Beyond the Tunisian case, the findings underscore the strategic role of geological storage in international hydrogen trade. Byincreasing resilience and reducing cost volatility, underground hydrogen storage strengthens the position of exporting regionsand supports more balanced and sustainable hydrogen partnerships. KW - Energy Transition KW - Hydrogen export KW - hydrogen underground storage KW - Hydrogen prices KW - salt caverns KW - Power-to-X KW - PyPSA-Earth Y1 - 2026 U6 - https://doi.org/10.2139/ssrn.6307406 PB - SSRN ER - TY - INPR A1 - Falter, Thomas T1 - Werkstattbericht: Erfahrungen aus der Zusammenarbeit mit KI-Agenten für individualisiertes Lernen N2 - DDer Artikel reflektiert praxisbasiert und philosophisch die Zusammenarbeit von Menschen mit KI-Agenten – insbesondere im Kontext des Lernens von Skills auf Experten-Level im Hochschulbereich. Am Beispiel der Entwicklung des KI-unterstützten Multiagentensystem LASSI, das Lernen unterstützt, wird eine Lernreise in drei Phasen erzählt – vom produktiven Staunen über die Verschiebung von Autorenschaft bis hin zur Übernahme von Verantwortung. Die Perspektiven von Entwickler, Professor und Studierenden zeigen, wie sich Mensch-Agenten-Systeme durch Zusammenarbeit verändern. Ergänzend werden drei philosophische Dimensionen – Embodied Knowledge, Enhanced Technologies und Embedded Ethics – herangezogen, um Potenziale und Risiken dieser Systeme zu beleuchten: Was passiert, wenn Intelligenz entkörperlicht, menschliche Fähigkeiten an Technologien ausgelagert und Werte kodiert werden? Der Text plädiert dafür, Agenten nicht als neutrale Werkzeuge, sondern als Mitgestalter im Soziotechnischen System Bildung zu begreifen. In der Schlussbetrachtung wird die Hochschule als Denkwerkstatt skizziert, die durch KI ihre Rolle neu definieren muss: weg vom Prüfungsbetrieb hin zu einem Raum für Urteilskraft und Selbstreflexion. Lernen mit und von Agenten heißt: Lernen neu denken – gemeinsam gestalten. Y1 - 2026 U6 - https://doi.org/10.13140/RG.2.2.20204.63360 ER - TY - JOUR A1 - Brunner, Philipp A1 - Vogl, Stefanie T1 - Extracting Product Improvement Insights from Social Media Comments Using Machine Learning: a Case Study in the Automotive Industry JF - Machine Learning and Knowledge Extraction N2 - This paper presents a scalable machine learning pipeline for extracting actionable, product-related insights from user-generated social media comments. Leveraging sentence embeddings from SBERT and unsupervised clustering (k-Means and agglomerative), the approach structures informal and noisy comments from Instagram and YouTube into topic groups intended to support thematic analysis. A case study on feedback regarding BMW vehicles, comprising more than 26,000 comments, illustrates how the pipeline can reveal recurring user concerns, such as design critiques, usability issues, and technology-related expectations, even in short and unstructured social media comments. The proposed pipeline operates without labeled data or manual annotation, enabling scalable application and transferability across product categories and industries. By transforming large-scale, unstructured consumer feedback into interpretable themes, the pipeline provides product teams with an efficient and structured basis for data-driven product development and improvement. KW - social media mining; sentence embeddings; unsupervised clustering; product feedback analysis; SBERT; natural language processing Y1 - 2026 U6 - https://doi.org/10.3390/make8020042 VL - 8 IS - 2 PB - MDPI ER - TY - JOUR A1 - Wallner, M. A1 - Gutbrod, Max A1 - Rauber, David A1 - Ebigbo, Alanna A1 - Probst, Andreas A1 - Palm, Christoph A1 - Messmann, Helmut A1 - Roser, David T1 - KI-gestützte Detektion und Segmentierung von Magenkarzinomen in westlichen endoskopischen Bilddaten anhand eines fine-tuned Deep-Learning Ansatzes JF - Zeitschrift für Gastroenterologie N2 - Diese vorläufige monozentrische Studie zeigt, dass ein aus einem Barrett-Ösophagus-KI-System feinjustiertes Deep-Learning-Modell Magenkarzinome in westlichen multimodalen endoskopischen Bilddaten zuverlässig detektieren und präzise segmentieren kann. Die hohe Segmentierungsgenauigkeit und Detektionssensitivität über verschiedene Bildmodalitäten hinweg unterstreichen die Machbarkeit eines pathologiegestützten KI-Ansatzes auch in einer westlichen Niedriginzidenzpopulation. Aufgrund der ausschließlichen Verwendung von Bildern mit sichtbaren Tumoren lassen sich keine Aussagen zur Spezifität treffen; eine Übertragbarkeit auf Screening- oder Mischkollektive ist daher limitiert. Weitere Studien mit a) größerem Datensatz inklusive Videodaten, b) externer Validierung an einer multizentrischen westlichen Kohorte, sowie c) Anwendung und Prüfung an nicht-neoplastischen Vergleichsbildern oder anderen Pathologien sind erforderlich. Nach unserem Kenntnisstand zählt dieses System zu den ersten in einer westlichen Population entwickelten endoskopischen KI-Ansätzen zur Magenkarzinomdetektion, und zu wenigen, die vollständige ESD-präparatbasierte Referenzdaten für Training und Validierung nutzen. Y1 - 2026 U6 - https://doi.org/10.1055/s-0046-1817751 VL - 64 IS - 03 SP - e64 EP - e65 PB - Thieme ER - TY - JOUR A1 - Tan, Jing Jie A1 - Schreiner, Rupert A1 - Hausladen, Matthias A1 - Asgharzade, Ali A1 - Edler, Simon A1 - Bartsch, Julian A1 - Bachmann, Michael A1 - Schels, Andreas A1 - Kwan, Ban-Hoe A1 - Ng, Danny Wee-Kiat A1 - Hum, Yan-Chai T1 - SiMiC: Context-aware silicon microstructure characterization using attention-based convolutional neural networks for field-emission tip analysis JF - Journal of Vacuum Science & Technology B N2 - Accurate characterization of silicon microstructures is essential for advancing microscale fabrication, quality control, and device performance. Traditional analysis using scanning electron microscopy (SEM) often requires labor-intensive, manual evaluation of feature geometry, limiting throughput and reproducibility. In this study, we propose SiMiC: Context-aware Silicon Microstructure Characterization Using Attention-based Convolutional Neural Networks for Field-Emission Tip Analysis. By leveraging deep learning, our approach efficiently extracts morphological features—such as size, shape, and apex curvature—from SEM images, significantly reducing human intervention while improving measurement consistency. A specialized dataset of silicon-based field-emitter tips was developed, and a customized convolutional neural network architecture incorporating attention mechanisms was trained for multiclass microstructure classification and dimensional prediction. Comparative analysis with classical image processing techniques demonstrates that SiMiC achieves high accuracy while maintaining interpretability. The proposed framework establishes a foundation for data-driven microstructure analysis directly linked to field-emission performance, opening avenues for correlating emitter geometry with emission behavior and guiding the design of optimized cold-cathode and SEM electron sources. The related dataset and algorithm repository that could serve as a baseline in this area can be found at https://research.jingjietan.com/?q=SIMIC. KW - Field emitter arrays KW - Quality assurance KW - Convolutional neural network KW - Deep learning KW - Image processing KW - Machine learning KW - Cold cathodes KW - Scanning electron microscopy KW - Electron sources KW - Chemical elements Y1 - 2025 U6 - https://doi.org/10.1116/6.0005068 VL - 43 IS - 6 PB - AVS ER - TY - JOUR A1 - Weiherer, Maximilian A1 - von Riedheim, Antonia A1 - Brébant, Vanessa A1 - Egger, Bernhard A1 - Palm, Christoph T1 - Learning Neural Parametric 3D Breast Shape Models for Metrical Surface Reconstruction From Monocular RGB Videos JF - Machine Learning for Biomedical Imaging (MELBA) N2 - We present a neural parametric 3D breast shape model and, based on this model, introduce a low-cost and accessible 3D surface reconstruction pipeline capable of recovering accurate breast geometry from a monocular RGB video. In contrast to widely used, commercially available yet expensive 3D breast scanning solutions and existing low-cost alternatives, our method requires neither specialized hardware nor proprietary software and can be used with any device that is able to record RGB videos. The key building blocks of our pipeline are a state-of-the-art, off-the-shelf Structure-from-Motion pipeline, paired with a parametric breast model for robust surface reconstruction. Our model, similarly to the recently proposed implicit Regensburg Breast Shape Model (iRBSM), leverages implicit neural representations to model breast shapes. However, unlike the iRBSM, which employs a single global neural Signed Distance Function (SDF), our approach—inspired by recent state-of-the-art face models—decomposes the implicit breast domain into multiple smaller regions, each represented by a local neural SDF anchored at anatomical landmark positions. When incorporated into our surface reconstruction pipeline, the proposed model, dubbed liRBSM (short for localized iRBSM), significantly outperforms the iRBSM in terms of reconstruction quality, yielding more detailed surface reconstruction than its global counterpart. Overall, we find that the introduced pipeline is able to recover high-quality and metrically correct 3D breast geometry within an error margin of less than 2 mm. Our method is fast (requires less than six minutes), fully transparent and open-source, and together with the model publicly available at https://rbsm.re-mic.de/local-implicit. KW - 3D Reconstruction KW - Shape Modeling Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-89791 IS - MELBA–BVM 2025 Special Issue SP - 95 EP - 114 PB - Melba ER - TY - CHAP A1 - Bielmeier, Benno A1 - Ramsauer, Ralf A1 - Yoshida, Takahiro A1 - Mauerer, Wolfgang T1 - From Tracepoints to Timeliness: a Semi-Markov Framework for Predictive Runtime Analysis T2 - IEEE 31th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), 20-22 August 2025, Singapore N2 - Detecting and resolving violations of temporal constraints in real-time systems is both, time-consuming and resource-intensive, particularly in complex software environments. Measurement-based approaches are widely used during development, but often are unable to deliver reliable predictions with limited data. This paper presents a hybrid method for worst-case execution time estimation, combining lightweight runtime tracing with probabilistic modelling. Timestamped system events are used to construct a semi-Markov chain, where transitions represent empirically observed timing between events. Execution duration is interpreted as time-to-absorption in the semi-Markov chain, enabling worst-case execution time estimation with fewer assumptions and reduced overhead. Empirical results from real-time Linux systems indicate that the method captures both regular and extreme timing behaviours accurately, even from short observation periods. The model supports holistic, low-intrusion analysis across system layers and remains interpretable and adaptable for practical use. Y1 - 2025 U6 - https://doi.org/10.1109/RTCSA66114.2025.00021 SP - 114 EP - 125 PB - IEEE ER - TY - JOUR A1 - Feilner, Markus A1 - Ramsauer, Ralf T1 - Open-Source-Wissenschaftler bereiten Software für das Quantencomputing vor JF - Linux-Magazin N2 - Um Software und Architekturen für das Quantencomputing zu entwickeln, zu definieren und zu testen, braucht man keinen Quantencomputer. Weil die teuer und rar sind, entschieden sich Wissenschaftler der OTH Regensburg dafür, sie einfach zu virtualisieren – mit messbarem Erfolg. KW - Linux KW - Quantencomputing KW - QuantumVM Y1 - 2025 UR - https://www.linux-magazin.de/ausgaben/2025/08/quantencomputing/ VL - 25 IS - 08 PB - Deloitte ER - TY - CHAP A1 - Schmidbauer, Lukas A1 - Riofrío, Carlos A. A1 - Heinrich, Florian A1 - Junk, Vanessa A1 - Schwenk, Ulrich A1 - Husslein, Thomas A1 - Mauerer, Wolfgang T1 - Path Matters: Industrial Data Meet Quantum Optimization T2 - 2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August - 05 September 2025, Albuquerque N2 - Real-world optimization problems must undergo a series of transformations before becoming solvable on current quantum hardware. Even for a fixed problem, the number of possible transformation paths-from industry-relevant formulations through binary constrained linear programs (BILPs), to quadratic unconstrained binary optimization (QUBO), and finally to a hardware-executable representation-is remarkably large. Each step introduces free parameters, such as Lagrange multipliers, encoding strategies, slack variables, rounding schemes or algorithmic choices-making brute-force exploration of all paths intractable. In this work, we benchmark a representative subset of these transformation paths using a realworld industrial production planning problem with industry data: the optimization of work allocation in a press shop producing vehicle parts. We focus on QUBO reformulations and algorithmic parameters for both quantum annealing (QA) and the Linear Ramp Quantum Approximate Optimization Algorithm (LR-QAOA). Our goal is to identify a reduced set of effective configurations applicable to similar industrial settings. Our results show that QA on D-Wave hardware consistently produces near-optimal solutions, whereas LR-QAOA on IBM quantum devices struggles to reach comparable performance. Hence, the choice of hardware and solver strategy significantly impacts performance. The problem formulation and especially the penalization strategy determine the solution quality. Most importantly, mathematically-defined penalization strategies are equally successful as hand-picked penalty factors, paving the way for automated QUBO formulation. Moreover, we observe a strong correlation between simulated and quantum annealing performance metrics, offering a scalable proxy for predicting QA behavior on larger problem instances. Y1 - 2025 U6 - https://doi.org/10.1109/QCE65121.2025.00230 SP - 2101 EP - 2111 PB - IEEE ER - TY - JOUR A1 - Franz, Maja A1 - Schönberger, Manuel A1 - Strobl, Melvin A1 - Kühn, Eileen A1 - Streit, Achim A1 - Zurita, Pía A1 - Diefenthaler, Markus A1 - Mauerer, Wolfgang T1 - From Hope to Heuristic: Realistic Runtime Estimates for Quantum Optimisation in NHEP JF - EPJ Web of Conferences; 27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024) N2 - Noisy Intermediate-Scale Quantum (NISQ) computers, despite their limitations, present opportunities for near-term quantum advantages in Nuclear and High-Energy Physics (NHEP) when paired with specially designed quantum algorithms and processing units. This study focuses on core algorithms that solve optimization problems through the quadratic Ising or Quadratic Unconstrained Binary Optimisation model, specifically Quantum Annealing and the Quantum Approximate Optimisation Algorithm (QAOA). In particular, we estimate runtimes and scalability for the task of particle Track Reconstruction (TR), a key computing challenge in NHEP, and investigate how the classical parameter space in QAOA, along with techniques like a Fourieranalysis based heuristic, can facilitate future quantum advantages. The findings indicate that lower frequency components in the parameter space are crucial for effective annealing schedules, suggesting that heuristics can improve resource efficiency while achieving near-optimal results. Overall, the study highlights the potential of NISQ computers in NHEP and the significance of co-design approaches and heuristic techniques in overcoming challenges in quantum algorithms. Y1 - 2025 U6 - https://doi.org/10.1051/epjconf/202533701282 N1 - Corresponding author der OTH Regensburg: Maja Franz VL - 337 PB - EDP Sciences ER - TY - INPR A1 - Franz, Maja A1 - Strobl, Melvin A1 - Chaichenets, Leonid A1 - Kühn, Eileen A1 - Streit, Achim A1 - Mauerer, Wolfgang T1 - Out of Tune: Demystifying Noise-Effects on Quantum Fourier Models N2 - Variational quantum algorithms have received substantial theoretical and empirical attention. As the underlying variational quantum circuit (VQC) can be represented by Fourier series that contain an exponentially large spectrum in the number of input features, hope for quantum advantage remains. Nevertheless, it remains an open problem if and how quantum Fourier models (QFMs) can concretely outperform classical alternatives, as the eventual sources of non-classical computational power (for instance, the role of entanglement) are far from being fully understood. Likewise, hardware noise continues to pose a challenge that will persist also along the path towards fault tolerant quantum computers. In this work, we study VQCs with Fourier lenses, which provides possibilities to improve their understanding, while also illuminating and quantifying constraints and challenges. We seek to elucidate critical characteristics of QFMs under the influence of noise. Specifically, we undertake a systematic investigation into the impact of noise on the Fourier spectrum, expressibility, and entangling capability of QFMs through extensive numerical simulations and link these properties to training performance. The insights may inform more efficient utilisation of quantum hardware and support the design of tailored error mitigation and correction strategies. Decoherence imparts an expected and broad detrimental influence across all Ansätze. Nonetheless, we observe that the severity of these deleterious effects varies among different model architectures, suggesting that certain configurations may exhibit enhanced robustness to noise and show computational utility. Y1 - 2025 U6 - https://doi.org/10.48550/arXiv.2506.09527 ER - TY - JOUR A1 - Maschek, Stefan Raimund A1 - Schwittalla, Jürgen A1 - Franz, Maja A1 - Mauerer, Wolfgang T1 - Make Some Noise! Measuring Noise Model Quality in Real-World Quantum Software JF - Proceedings of the IEEE International Conference on Quantum Software (QSW), 07-12 July 2025, Helsinki N2 - Noise and imperfections are among the prevalent challenges in quantum software engineering for current NISQ systems. They will remain important in the post-NISQ area, as logical, error-corrected qubits will be based on software mechanisms. As real quantum hardware is still limited in size and accessibility, noise models for classical simulation-that in some cases can exceed dimensions of actual systems-play a critical role in obtaining insights into quantum algorithm performance, and the properties of mechanisms for error correction and mitigation. We present, implement and validate a tunable noise model building on the Kraus channel formalism on a large scale quantum simulator system (Qaptiva). We use empirical noise measurements from IBM quantum (IBMQ) systems to calibrate the model and create a realistic simulation environment. Experimental evaluation of our approach with Greenberger-Horne-Zeilinger (GHZ) state preparation and QAOA applied to an industrial usecase validate our approach, and demonstrate accurate simulation of hardware behaviour at reasonable computational cost. We devise and utilise a method that allows for determining the quality of noise models for larger problem instances than is possible with existing metrics in the literature. To identify potentials of future quantum software and algorithms, we extrapolate the noise model to future partially fault-tolerant systems, and give insights into the interplay between hardware-specific noise modelling and hardware-aware algorithm development. KW - Industrial Application KW - Noise Model KW - Quantum Computing Y1 - 2025 U6 - https://doi.org/10.1109/QSW67625.2025.00010 PB - IEEE ER - TY - JOUR A1 - Strobl, Melvin A1 - Franz, Maja A1 - Kühn, Eileen A1 - Mauerer, Wolfgang A1 - Streit, Achim T1 - QML-Essentials: A Framework for Working with Quantum Fourier Models JF - Proceedings of the IEEE International Conference on Quantum Software (QSW), 07-12 July 2025, Helsinki N2 - In this work, we propose a framework in the form of a Python package, specifically designed for the analysis of Quantum Machine Learning models. This framework is based on the PennyLane simulator and facilitates the evaluation and training of Variational Quantum Circuits. It provides additional functionality ranging from the ability to add different types of noise to the classical simulation, over different parameter initialisation strategies, to the calculation of expressibility and entanglement for a given model. As an intrinsic property of Quantum Fourier Models, it provides two methods for calculating the corresponding Fourier spectrum: one via the Fast Fourier Transform and another analytical method based on the expansion of the expectation value using trigonometric polynomials. It also provides a set of predefined approaches that allow a fast and straightforward implementation of Quantum Machine Learning models. With this framework, we extend the PennyLane simulator with a set of tools that allow researchers a more convenient start with Quantum Fourier Models and aim to unify the analysis of Variational Quantum Circuits. Y1 - 2025 U6 - https://doi.org/10.1109/QSW67625.2025.00035 SP - 238 EP - 243 PB - IEEE ER - TY - INPR A1 - Höß, Nicole A1 - Paradis, Carlos A1 - Kazman, Rick A1 - Mauerer, Wolfgang T1 - Oops!... I did it again. Conclusion (In-)Stability in Quantitative Empirical Software Engineering: A Large-Scale Analysis N2 - Context: Mining software repositories is a popular means to gain insights into a software project's evolution, monitor project health, support decisions and derive best practices. Tools supporting the mining process are commonly applied by researchers and practitioners, but their limitations and agreement are often not well understood. Objective: This study investigates some threats to validity in complex tool pipelines for evolutionary software analyses and evaluates the tools' agreement in terms of data, study outcomes and conclusions for the same research questions. Method: We conduct a lightweight literature review to select three studies on collaboration and coordination, software maintenance and software quality from high-ranked venues, which we formally replicate with four independent, systematically selected mining tools to quantitatively and qualitatively compare the extracted data, analysis results and conclusions. Results: We find that numerous technical details in tool design and implementation accumulate along the complex mining pipelines and can cause substantial differences in the extracted baseline data, its derivatives, subsequent results of statistical analyses and, under specific circumstances, conclusions. Conclusions: Users must carefully choose tools and evaluate their limitations to assess the scope of validity in an adequate way. Reusing tools is recommended. Researchers and tool authors can promote reusability and help reducing uncertainties by reproduction packages and comparative studies following our approach. Y1 - 2026 U6 - https://doi.org/10.48550/arXiv.2510.06844 ER - TY - INPR A1 - Periyasamy, Maniraman A1 - Ufrecht, Christian A1 - Scherer, Daniel D. D. A1 - Mauerer, Wolfgang T1 - CutReg: A loss regularizer for enhancing the scalability of QML via adaptive circuit cutting N2 - Whether QML can offer a transformative advantage remains an open question. The severe constraints of NISQ hardware, particularly in circuit depth and connectivity, hinder both the validation of quantum advantage and the empirical investigation of major obstacles like barren plateaus. Circuit cutting techniques have emerged as a strategy to execute larger quantum circuits on smaller, less connected hardware by dividing them into subcircuits. However, this partitioning increases the number of samples needed to estimate the expectation value accurately through classical post-processing compared to estimating it directly from the full circuit. This work introduces a novel regularization term into the QML optimization process, directly penalizing the overhead associated with sampling. We demonstrate that this approach enables the optimizer to balance the advantages of gate cutting against the optimization of the typical ML cost function. Specifically, it navigates the trade-off between minimizing the cutting overhead and maintaining the overall accuracy of the QML model, paving the way to study larger complex problems in pursuit of quantum advantage Y1 - 2025 U6 - https://doi.org/10.48550/arXiv.2506.14858 ER - TY - CHAP A1 - Ramsauer, Ralf A1 - Bielmeier, Benno A1 - Mauerer, Wolfgang T1 - Towards Real-World System-Level Integration of Quantum Accelerators: A Hardware/Software Co-Design Approach T2 - INFORMATIK; Lecture Notes in Informatics (LNI); GI Quantum Computing Workshop. Potsdam. 16.–19. September 2025 N2 - This work-in-progress explores architectural and systemic foundations for integrating quantum accelerators into heterogeneous computing environments. We propose and implement a modular architecture where Quantum Processing Units (QPUs) operate as peripheral devices, supporting pulse-level control interfaces and high-level circuit execution offloading, while internally managing compilation, transpilation, and scheduling. To enable efficient quantum-classical orchestration, we introduce a Quantum Abstraction Layer (QAL) at the operating system level to enable seamless communication, resource management, and integration with existing software frameworks. Our two-step design approach begins with validating the architecture through simulations in virtualised environments. We then implement an FPGA-based surrogate supporting both result- and timing-accurate modes, enabling full-stack emulation and performance evaluation in the absence of physical quantum hardware. This platform supports extensible and rapid prototyping, Hardware/Software Co-Design, and allows for investigations on the practical quantum advantage under realistic system-level constraints of various use cases. We aim for applicability by hardware vendors, facilitating early development even before physical quantum processors are available. Y1 - 2025 U6 - https://doi.org/10.18420/inf2025_158 SP - 1761 EP - 1765 PB - Gesellschaft für Informatik e.V. ER - TY - INPR A1 - Ramsauer, Ralf A1 - Mauerer, Wolfgang T1 - Towards System-Level Quantum-Accelerator Integration N2 - Quantum computers are often treated as experimental add-ons that are loosely coupled to classical infrastructure through high-level interpreted languages and cloud-like orchestration. However, future deployments in both, high-performance computing (HPC) and embedded environments, will demand tighter integration for lower latencies, stronger determinism, and architectural consistency, as well as to implement error correction and other tasks that require tight quantum-classical interaction as generically as possible. We propose a vertically integrated quantum systems architecture that treats quantum accelerators and processing units as peripheral system components. A central element is the Quantum Abstraction Layer (QAL) at operating system kernel level. It aims at real-time, low-latency, and high-throughput interaction between quantum and classical resources, as well as robust low-level quantum operations scheduling and generic resource management. It can serve as blueprint for orchestration of low-level computational components "around" a QPU (and inside a quantum computer), and across different modalities. We present first results towards such an integrated architecture, including a virtual QPU model based on QEMU. The architecture is validated through functional emulation on three base architectures (x86_64, ARM64, and RISC-V), and timing-accurate FPGA-based simulations. This allows for a realistic evaluation of hybrid system performance and quantum advantage scenarios. Our work lays the ground for a system-level co-design methodology tailored for the next generation of quantum-classical computing. Y1 - 2025 U6 - https://doi.org/10.48550/arXiv.2507.19212 ER - TY - CHAP A1 - Safi, Hila A1 - Niedermeier, Christoph A1 - Mauerer, Wolfgang T1 - TWiDDle: Twirling and Dynamical Decoupling, and Crosstalk Noise Modeling T2 - 2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August - 05 September 2025, Albuquerque N2 - Crosstalk remains a major source of correlated error in quantum systems, yet lacks a precise, community-wide definition - hindering systematic analysis and mitigation. This paper introduces a model-driven approach to crosstalk characterisation through three architecture-inspired noise models: (1) simultaneous two-qubit gate execution, (2) shared qubit interference, and (3) proximity-induced noise from shared control or readout hardware. These models act as both diagnostic tools and building blocks for crosstalk-aware quantum programming. We assess their impact across a broad benchmark suite - quantum simulation, Grover's algorithm, and fault-tolerant primitives like surface, Shor, and Steane codes - and evaluate two mitigation techniques: dynamical decoupling and Pauli twirling. While both are discussed in literature, only dynamical decoupling consistently enhances fidelity across noise types. Our work links low-level noise effects to high-level software engineering, underscoring the role of hardware-software co-design in scalable quantum computing. Model-based, hardware-aware design flows and composable noise abstractions improve error mitigation and program portability. Integrating such strategies into the toolchain is essential for building resilient quantum programs under realistic noise conditions. Y1 - 2025 U6 - https://doi.org/10.1109/QCE65121.2025.10313 SP - 162 EP - 168 PB - IEEE ER - TY - JOUR A1 - Schmidbauer, Lukas A1 - Lobe, Elisabeth A1 - Schaefer, Ina A1 - Mauerer, Wolfgang T1 - It’s Quick to be Square: Fast Quadratisation for Quantum Toolchains JF - ACM Transactions on Quantum Computing N2 - Many of the envisioned use-cases for quantum computers involve optimisation processes. While there are many algorithmic primitives to perform the required calculations, all eventually lead to quantum gates operating on quantum bits, with an order as determined by the structure of the objective function and the properties of target hardware. When the structure of the problem representation is not aligned with structure and boundary conditions of the executing hardware, various overheads degrading the computation may arise, possibly negating any possible quantum advantage. Therefore, automatic transformations of problem representations play an important role in quantum computing when descriptions (semi-)targeted at humans must be cast into forms that can be “executed” on quantum computers. Mathematically equivalent formulations are known to result in substantially different non-functional properties depending on hardware, algorithm and detail properties of the problem. Given the current state of noisy intermediate-scale quantum (NISQ) hardware, these effects are considerably more pronounced than in classical computing. Likewise, efficiency of the transformation itself is relevant because possible quantum advantage may easily be eradicated by the overhead of transforming between representations. In this paper, we consider a specific class of higher-level representations, that is, PUBOs, and devise novel automatic transformation mechanisms into widely used QUBOs that substantially improve efficiency and versatility over the state of the art. In addition, we conduct a comprehensive investigation of industry-relevant problem formulations and their conversion into a quantum-specific representation, identifying significant obstacles in scaling behaviour and demonstrating how these can be circumvented. KW - Algorithmic optimisation KW - Graphs KW - Performance KW - Pseudo Boolean Function Y1 - 2026 U6 - https://doi.org/10.1145/3800943 N1 - Preprint ebenfalls auf OPUS veröffentlicht: https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/7937 VL - 7 IS - 2 PB - ACM ER - TY - CHAP A1 - Schmidbauer, Lukas A1 - Mauerer, Wolfgang T1 - SAT Strikes Back: Parameter and Path Relations in Quantum Toolchains T2 - Proceedings of the IEEE International Conference on Quantum Software (QSW), 07-12 July 2025, Helsinki N2 - In the foreseeable future, toolchains for quantum computing should offer automatic means of transforming a high level problem formulation down to a hardware executable form. Thereby, it is crucial to find (multiple) transformation paths that are optimised for (hardware specific) metrics. We zoom into this pictured tree of transformations by focussing on k-SAT instances as input and their transformation to QUBO, while considering structure and characteristic metrics of input, intermediate and output representations. Our results can be used to rate valid paths of transformation in advance—also in automated (quantum) toolchains. We support the automation aspect by considering stability and therefore predictability of free parameters and transformation paths. Moreover, our findings can be used in the manifesting era of error correction (since considering structure in a high abstraction layer can benefit error correcting codes in layers below). We also show that current research is closely linked to quadratisation techniques and their mathematical foundation. KW - Pseudo Boolean Function KW - PUBO KW - Quantum Software KW - QUBO KW - SAT Y1 - 2025 U6 - https://doi.org/10.1109/QSW67625.2025.00021 SP - 104 EP - 115 PB - IEEE ER - TY - CHAP A1 - Schönberger, Manuel A1 - Trummer, Immanuel A1 - Mauerer, Wolfgang T1 - Hybrid Mixed Integer Linear Programming for Large-Scale Join Order Optimisation T2 - Proceedings of the VLDB Endowment N2 - Finding optimal join orders is among the most crucial steps to be performed by query optimisers. Though extensively studied in data management research, the problem remains far from solved: While query optimisers rely on exhaustive search methods to determine ideal solutions for small problems, such methods reach their limits once queries grow in size. Yet, large queries become increasingly common in real-world scenarios, and require suitable methods to generate efficient execution plans. While a variety of heuristics have been proposed for large-scale query optimisation, they suffer from degrading solution quality as queries grow in size, or feature highly sub-optimal worst-case behavior, as we will show. We propose a novel method based on the paradigm of mixed integer linear programming (MILP): By deriving a novel MILP model capable of optimising arbitrary bushy tree structures, we address the limitations of existing MILP methods for join ordering, and can rely on highly optimised MILP solvers to derive efficient tree structures that elude competing methods. To ensure optimisation efficiency, we embed our MILP method into a hybrid framework, which applies MILP solvers precisely where they provide the greatest advantage over competitors, while relying on more efficient methods for less complex optimisation steps. Thereby, our approach gracefully scales to extremely large query sizes joining up to 100 relations, and consistently achieves the most robust plan quality among a large variety of competing join ordering methods. Y1 - 2026 U6 - https://doi.org/10.14778/3778092.3778097 VL - 19 IS - 3 SP - 348 EP - 360 PB - VLDB Endowment ER - TY - CHAP A1 - Thelen, Simon A1 - Mauerer, Wolfgang T1 - Predict and Conquer: Navigating Algorithm Trade-Offs with Quantum Design Automation T2 - 2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August - 05 September 2025, Albuquerque N2 - Combining quantum computers with classical compute power has become a standard means for developing algorithms and heuristics that are, eventually, supposed to beat any purely classical alternatives. While in-principle advantages for solution quality or runtime are expected for increasingly many approaches, substantial challenges remain: Non-functional properties like runtime or solution quality of many suggested approaches are not yet fully understood, and need to be explored empirically. This, in turn, makes it unclear which approach is best suited for a given problem. Accurately predicting behaviour and properties of quantum-classical algorithms opens possibilities for software abstraction layers, which in turn can automate decisionmaking for algorithm selection and parametrisation. While such techniques find frequent use in classical high-performance computing, they are still mostly absent from quantum software toolchains. In this paper, we present a methodology (accompanied by a reproducible reference implementation) to perform algorithm selection based on desirable non-functional requirements. This greatly simplifies decision-making processes for end users. Based on meta-information annotations at the source code level, our framework traces key characteristics of quantum-classical heuristics and algorithms, and uses this information to predict the most suitable approach and its parameters for given computational challenges and their non-functional requirements. As combinatorial optimisation is a very extensively studied aspect of quantumclassical systems, we perform a comprehensive case study based on numerical simulations of algorithmic approaches to implement and validate our ideas. We develop statistical models to quantify the influence of various factors on non-functional properties, and establish predictions for optimal algorithmic choices without manual user effort. We argue that our methodology generalises to problem classes beyond combinatorial optimisation, such as Hamiltonian optimisation, and lays a foundation for integrated software layers for quantum design automation. KW - Design automation KW - Heuristic algorithms KW - Optimization KW - Prediction algorithms KW - Quantum Computing KW - Runtime KW - Software KW - Software algorithms KW - Source coding KW - Standards Y1 - 2025 U6 - https://doi.org/10.1109/QCE65121.2025.00071 SP - 591 EP - 602 PB - IEEE CY - Los Alamitos, USA ER - TY - CHAP A1 - Krüger, Tom A1 - Mauerer, Wolfgang T1 - Quantum Dark Magic: Efficiency of Intermediate Non-Stabiliserness T2 - 2025 IEEE International Conference on Quantum Computing and Engineering (QCE), 30 August- 05 September 2025, Albuquerque N2 - While quantum systems are know to possess inherent computational advantages over classical computers, constructing algorithms that harness such advantage remains an open challenge. Non-stabiliserness (i.e., traversal of states outside the Clifford orbit), is a necessary condition, as de-quantisation is otherwise possible. Nevertheless, an excess of non-stabiliserness is also known to not be advantageous. In this paper, we present an approach to understanding the efficient use of non-stabiliser states by tracking their behaviour across various algorithms. Our techniques reveal different efficiencies in the use of non-stabiliserness, leading us to hypothesise that greater classical optimisation degrees of freedom can introduce unnecessary non-stabiliser consumption, which becomes costly with error correction. Y1 - 2025 U6 - https://doi.org/10.1109/QCE65121.2025.10461 SP - 592 EP - 593 PB - IEEE ER - TY - INPR A1 - Eichenseher, Vincent A1 - Franz, Maja A1 - Wolff, Christian A1 - Mauerer, Wolfgang T1 - Pattern or Not? QAOA Parameter Heuristics and Potentials of Parsimony N2 - Structured variational quantum algorithms such as the Quantum Approximate Optimisation Algorithm (QAOA) have emerged as leading candidates for exploiting advantages of near-term quantum hardware. They interlace classical computation, in particular optimisation of variational parameters, with quantum-specific routines, and combine problem-specific advantages -- sometimes even provable -- with adaptability to the constraints of noisy, intermediate-scale quantum (NISQ) devices. While circuit depth can be parametrically increased and is known to improve performance in an ideal (noiseless) setting, on realistic hardware greater depth exacerbates noise: The overall quality of results depends critically on both, variational parameters and circuit depth. Although identifying optimal parameters is NP-hard, prior work has suggested that they may exhibit regular, predictable patterns for increasingly deep circuits and depending on the studied class of problems. In this work, we systematically investigate the role of classical parameters in QAOA performance through extensive numerical simulations and suggest a simple, yet effective heuristic scheme to find good parameters for low-depth circuits. Our results demonstrate that: (i) optimal parameters often deviate substantially from expected patterns; (ii) QAOA performance becomes progressively less sensitive to specific parameter choices as depth increases; and (iii) iterative component-wise fixing performs on par with, and at shallow depth may even outperform, several established parameter-selection strategies. We identify conditions under which structured parameter patterns emerge, and when deviations from the patterns warrant further consideration. These insights for low-depth circuits may inform more robust pathways to harnessing QAOA in realistic quantum compute scenarios. Y1 - 2026 U6 - https://doi.org/10.48550/arXiv.2510.08153 ER - TY - INPR A1 - Gierisch, Vincent A1 - Mauerer, Wolfgang T1 - QEF: Reproducible and Exploratory Quantum Software Experiments N2 - Commercially available Noisy Intermediate-Scale Quantum (NISQ) devices now make small hybrid quantum-classical experiments practical, but many tools hide configuration or demand ad-hoc scripting. We introduce the Quantum Experiment Framework (QEF): A lightweight framework designed to support the systematic, hypothesis-driven study of quantum algorithms. Unlike many existing approaches, QEF emphasises iterative, exploratory analysis of evolving experimental strategies rather than exhaustive empirical evaluation of fixed algorithms using predefined quality metrics. The framework's design is informed by a comprehensive review of the literature, identifying principal parameters and measurement practices currently reported in the field. QEF captures all key aspects of quantum software and algorithm experiments through a concise specification that expands into a Cartesian product of variants for controlled large-scale parameter sweeps. This design enables rigorous and systematic evaluation, as well as precise reproducibility. Large sweeps are automatically partitioned into asynchronous jobs across simulators or cloud hardware, and ascertain full hyper-parameter traceability. QEF supports parameter reuse to improve overall experiment runtimes, and collects all metrics and metadata into a form that can be conveniently explored with standard statistical and visualisation software. By combining reproducibility and scalability while avoiding the complexities of full workflow engines, QEF seeks to lower the practical barriers to empirical research on quantum algorithms, whether these are designed for current NISQ devices or future error-corrected quantum systems. Y1 - 2026 U6 - https://doi.org/10.48550/arXiv.2511.04563 ER - TY - JOUR A1 - Weigert, Alexander A1 - Galka, Stefan A1 - Dünnweber, Jan A1 - Meißner, Sebastian A1 - Riege, Jacob A1 - Böck, Hendrik A1 - Wagner, Martin T1 - Simulationsframework mit Anordnungsalgorithmus von Petri-Netzen JF - Zeitschrift für wirtschaftlichen Fabrikbetrieb N2 - Die serienmäßige Produktion von Elektrolysezellen befindet sich im Anfangsstadium, sodass belastbare Erfahrungen für standardisierte Produktionssysteme fehlen. Die Planung ist daher durch hohe Unsicherheit geprägt. Unterschiedliche Gestaltungsmöglichkeiten der Produktionssysteme müssen frühzeitig bewertet und ihre Leistungsfähigkeit mit dynamischen Methoden, wie der Simulation, abgesichert werden. Anhand eines von den Autoren entwickelten Simulationsframeworks mit automatisierter Modellgenerierung auf Basis der Petri-Netz-Logik zeigt dieser Beitrag die Möglichkeit der Simulation von Produktionssystemen in der Planung. Ein besonderes Leistungsmerkmal des Frameworks ist, dass zunächst unübersichtlich generierte Modelle mit einem Graphenalgorithmus so angeordnet werden, dass ihre Funktionsweise aus der Darstellung nachvollziehbar wird. KW - Continuous Simulation; Framework; Automated Simulation Model Generation; Graph-Layout-algorithm; Petri-Net Y1 - 2026 U6 - https://doi.org/10.1515/zwf-2026-1035 VL - 121 IS - 3 SP - 125 EP - 130 PB - DeGruyter ER - TY - JOUR A1 - Stadler, Anselm A1 - Mohr, Christa T1 - Zwischen Simulation und Realität : Digitale Lernräume in der Pflegeausbildung JF - PADUA N2 - Digitale Lernräume wie Virtual und Augmented Reality verändern die Pflegeausbildung grundlegend. Das europäische Projekt VReduMED, getragen von Partnern aus fünf zentraleuropäischen Ländern, entwickelt immersive Lernformate, die den Theorie-Praxis-Transfer stärken und Lehrende wie Lernende in der digitalen Transformation unterstützen. Der Beitrag zeigt Ansatzpunkte, Ergebnisse und Perspektiven. Y1 - 2026 U6 - https://doi.org/10.1024/1861-6186/a000910 VL - 21 IS - 1 SP - 33 EP - 35 PB - Hogrefe ER - TY - GEN ED - Handels, Heinz ED - Breininger, Katharina ED - Deserno, Thomas M. ED - Maier, Andreas ED - Maier-Hein, Klaus H. ED - Palm, Christoph ED - Tolxdorff, Thomas T1 - Bildverarbeitung für die Medizin 2026 : Proceedings, German Conference on Medical Image Computing, Lübeck March 15–17, 2026 N2 - Die Konferenz "BVM – Bildverarbeitung für die Medizin" ist seit vielen Jahren als die nationale Plattform für den Austausch von Ideen und die Diskussion der neuesten Forschungsergebnisse im Bereich der Medizinischen Bildverarbeitung und der Künstlichen Intelligenz (KI) etabliert. Auch 2026 haben (junge) Wissenschaftler*innen, Industrie und Anwender*innen diesen Austausch vertieft. Die Beiträge dieses Bandes – die meisten davon in englischer Sprache – umfassen alle Bereiche der medizinischen Bildverarbeitung, insbesondere die Bildgebung und -akquisition, Segmentierung und Analyse, Registrierung, Visualisierung und Animation, computerunterstützte Diagnose sowie bildgestützte Therapieplanung und Therapie. Hierbei kommen Methoden des maschinellen Lernens, der biomechanischen Modellierung sowie der Validierung und Qualitätssicherung zum Einsatz. KW - Bildverarbeitung KW - Computerunterstützte Medizin KW - Bildgebendes Verfahren KW - Bildanalyse KW - Deep Learning Y1 - 2026 SN - 978-3-658-51099-2 U6 - https://doi.org/10.1007/978-3-658-51100-5 SN - 1431-472X PB - Springer Vieweg CY - Wiesbaden ER - TY - CHAP A1 - Gutbrod, Max A1 - Rauber, David A1 - Palm, Christoph ED - Handels, Heinz ED - Breininger, Katharina ED - Deserno, Thomas M. ED - Maier, Andreas ED - Maier-Hein, Klaus H. ED - Palm, Christoph ED - Tolxdorff, Thomas T1 - Improving Generalization in Mitotic Cell Detection via Domain Transformations T2 - Bildverarbeitung für die Medizin 2025: Proceedings, German Conference on Medical Image Computing, Lübeck March 15-17, 2026 N2 - We address domain generalization (DG) in mitotic-cell (MC) detection by combining a β-variational autoencoder (VAE) for domain transformations with feature-space alignment together with an object detector. The β-VAE synthesizes domain-transformed images, and the detector is trained to map originals and their transformed counterparts to equal representations. On the MIDOG++ dataset, this approach improves out-of-domain detection F1 scores by 7 and 3 percentage points compared to the color-variation augmentation and stain-normalization baselines. Results further suggest that morphology shifts hinder generalization more than stain shifts. KW - Künstliche Intelligenz KW - Bildverarbeitung Y1 - 2026 U6 - https://doi.org/10.1007/978-3-658-51100-5_71 SP - 362 EP - 367 PB - Springer Vieweg CY - Wiesbaden ER - TY - GEN A1 - Klausmann, Leonard A1 - Rueckert, Tobias A1 - Rauber, David A1 - Maerkl, Raphaela A1 - Yildiran, Suemeyye R. A1 - Gutbrod, Max A1 - Palm, Christoph ED - Handels, Heinz ED - Breininger, Katharina ED - Deserno, Thomas M. ED - Maier, Andreas ED - Maier-Hein, Klaus H. ED - Palm, Christoph ED - Tolxdorff, Thomas T1 - Abstract: DIY Challenge Blueprint BT - from organization to technical implementation in Biomedical Image Analysis T2 - Bildverarbeitung für die Medizin 2025: Proceedings, German Conference on Medical Image Computing, Lübeck March 15-17, 2026 N2 - The high cost of challenge platforms prevents many people from organizing their own competitions. The do-it-yourself (DIY) challenge blueprint [1] allows you to host your own biomedical AI benchmark challenge. Our DIY approach circumvents the current constraints of commercial challenge platforms. A sovereign, extensible and cost-efficient deployment is provided via containerised, identity-managed and reproducible pipelines. Focus lies on GDPR-compliant hosting via infrastructure-as-code, automated evaluation, modular orchestration, and role-based identity and access management. The framework integrates Docker-based execution and standardised interfaces for task definitions, dataset curation and evaluation. All in all it is designed to be flexible and modular, as demonstrated in the MICCAI 2024 PhaKIR challenge [2, 3]. In this case study, different medical tasks on a multicentre laparoscopic dataset with framewise labels for phases and spatial annotations for instruments across fulllength videos were supported. This case study empirically validates the DIY challenge blueprint as a reproducible and customizable challenge-hosting infrastructure. The full code can be found at https://github.com/remic-othr/PhaKIR_DIY. KW - Bildverarbeitung Y1 - 2026 U6 - https://doi.org/10.1007/978-3-658-51100-5_27 SP - 131 EP - 131 PB - Springer Vieweg CY - Wiesbaden ER - TY - JOUR A1 - de Souza Júnior, Luis Antonio A1 - Pacheco, André Georghton Cardoso A1 - Oliveira dos Santos, Thiago A1 - Fogos da Rocha, Wyctor A1 - Bouzon, Pedro Henrique A1 - Palm, Christoph A1 - Papa, João Paulo T1 - LiwTERM-r: a Revised Lightweight Transformer-based Model for Multimodal Skin Lesion Detection Robust to Incomplete Input JF - Journal of the Brazilian Computer Society N2 - As the most common type of cancer in the world, skin cancer accounts for approximately 30% of all diagnosed tumor-based lesions. Early diagnosis can reduce mortality and prevent disfiguring in different skin regions. With the application of machine learning techniques in recent years, especially deep learning, promising results in this task could be achieved, presenting studies demonstrating that the combination of patients’ clinical anamneses and images of the injured lesion is essential for improving the correct classification of skin lesions. Despite that, meaningful use of anamneses with multiple collected images of the same skin lesion is mandatory, requiring further investigation. Thus, this project aims to contribute to developing multimodal machine learning-based models to solve the skin lesion classification problem by employing a lightweight transformer model that is robust to missing clinical information input. As a main hypothesis, models can be fed by multiple images from different sources as input along with clinical anamneses from the patient’s historical evaluations, leading to a more factual and trustworthy diagnosis. Our model deals with the not-trivial task of combining images and clinical information concerning the skin lesions in a lightweight transformer architecture that does not demand high computation resources or even all the information from the anamneses but still presents competitive classification results. KW - Deep learning KW - Skin Lesion Detection KW - Transformers KW - Lightweight Architectures Y1 - 2026 U6 - https://doi.org/10.5753/jbcs.2026.5871 VL - 32 IS - 1 PB - Brazilian Computer Society ER - TY - GEN A1 - Stadler, Sebastian A1 - Cornet, Henriette A1 - Huang, Danqing A1 - Frenkler, Fritz ED - Jung, Timothy ED - tom Dieck, M. Claudia ED - Rauschnabel, Philipp A. T1 - Designing Tomorrow’s Human-Machine Interfaces in Autonomous Vehicles: an Exploratory Study in Virtual Reality T2 - Augmented Reality and Virtual Reality: Changing Realities in a Dynamic World N2 - Technical advances in the automotive industry strive in the direction of full automation. However, besides advantages like improving traffic and fuel efficiency, people do not always trust Autonomous Vehicles (AVs) to make critical decisions. With the ultimate goal of reducing anxiety of passengers of AVs, this explorative study (i) proposes possible design concepts and variants for Human-Machine Interfaces (HMI) for passengers inside the AV using a requirements catalogue, (ii) evaluates the HMI concepts and variants thanks to an experience simulation in Virtual Reality (VR), and (iii) derives the most suitable HMI concept and refines it based on observations of participants’ behaviours during the experience simulation in VR, as well as questionnaires and interviews. The results show that the HMI concepts help passengers to reduce anxiety in the AV. Overall, VR turned out to be a suitable tool for this exploratory study. Further work will focus on testing HMI concepts in a variety of more complex scenarios to ensure user acceptance. Y1 - 2020 SN - 978-3-030-37869-1 U6 - https://doi.org/10.1007/978-3-030-37869-1_13 SP - 151 EP - 160 PB - Springer ER - TY - INPR A1 - Waas, Thomas A1 - Brockmann, R. A1 - Weise, Wolfram T1 - Deeply bound pionic states and the effective pion mass in nuclear systems N2 - We show that the s-wave pion-nuclear potential which reproduces the deeply bound pionic states in Pb, recently discovered at GSI, is remarkably close to the one constructed directly from low energy theorems based on chiral symmetry. Converting this information into an effective pion mass we find $m_\pi^\star/m_\pi\simeq 1.13$ in the center of the Pb nucleus, and $m_\pi^\star/m_\pi\simeq 1.07$ in symmetric nuclear matter. Y1 - 1997 U6 - https://doi.org/10.48550/arXiv.hep-ph/9704397 N1 - Der Aufsatz wurde peer-reviewed veröffentlicht und ist ebenfalls in diesem Repositorium verzeichnet unter: https://opus4.kobv.de/opus4-oth-regensburg/frontdoor/index/index/docId/8893 ER - TY - JOUR A1 - Stadler, Anselm A1 - Geiger, Andrea A1 - Mohr, Christa T1 - Lernen in digitalen Realitäten : XR als Chance für die Pflegebildung JF - PADUA N2 - Extended Reality (XR) eröffnet neue Möglichkeiten,den Theorie-Praxis-Transfer in der Pflege zu ver-bessern. Der Beitrag zeigt, wie Virtual Reality (VR),Augmented Reality (AR) und Mixed Reality (MR)Lernprozesse unterstützen, welche pädagogischenKompetenzen Lehrende benötigen und welche He-rausforderungen bei der Implementierung zu be-achten sind. Y1 - 2026 U6 - https://doi.org/10.1024/1861-6186/a000922 N1 - Dazugehöriges Literaturverzeichnis: https://doi.org/10.35096/othr/pub-8895 VL - 21 IS - 2 SP - 79 EP - 81 PB - Hogrefe ER - TY - JOUR A1 - Schulz, Carsten A1 - Graneß, Henry A1 - Weinzierl, Stefan A1 - Nicklas, Johannes T1 - Eigenvalue perturbation in drivetrain analysis and redesign JF - Multibody System Dynamics N2 - The optimisation of the dynamic behavior of drive systems often involves targeted modifications of the system characteristics. Structural and parametric modifications are used to satisfy the constraints of the dynamic requirements. However, many optimisations are still achieved by intuition or parameter variations, even though more streamlined and easy-to-implement tools such as the eigenvalue perturbation method are available. In this article, the eigenvalue perturbation method in the form of an eigenvalue sensitivity analysis is used to efficiently optimise the dynamic behavior for two different use cases using different optimisation measures. This paper demonstrates how eigenvalue perturbation theory can efficiently optimise drivetrain dynamics by systematically modifying system parameters. Two case studies show how eigenvalue sensitivity analysis achieves targeted frequency shifts to avoid resonances: (1) adapting shaft stiffness and control parameters in a torsional drivetrain, and (2) adjusting structural modifications in a wind turbine bedplate. The study introduces the eigenvector tensor product as a weighting matrix, identifying key parameters for effective redesign. Compared to conventional parameter studies, this method enables precise control over system dynamics with minimal computational effort, making it highly applicable for vibration mitigation and drivetrain optimisation. Y1 - 2026 U6 - https://doi.org/10.1007/s11044-026-10155-8 SN - 1384-5640 N1 - Corresponding author der OTH Regensburg: Carsten Schulz PB - Springer Nature ER - TY - CHAP A1 - Weinzierl, Stefan A1 - Schulz, Carsten T1 - Digitaler Zwilling einer Doppelschlag-Verlitzmaschine : Digital twin of a double twist stranding machine T2 - 5. VDI-Fachtagung Schwingungen 2025 N2 - Die Methode der Mehrkörpersimulation und die Finite-Elemente-Methode gewinnen aufgrund immer leistungsfähigerer Rechentechnik in Forschung und Entwicklung zunehmend an Bedeutung. Heutzutage können komplexe Systeme mit diesen Methoden virtuell simuliert und multiphysikalisch untersucht werden. Insbesondere im Entwicklungsprozess führt deren Einsatz aufgrund der damit verbundenen Zeit- und Kosteneinsparungen zu einem entscheidenden Wettbewerbsvorteil. Im Rahmen dieser Arbeit wird ein digitaler Zwilling einer bestehenden Doppelschlag-Verlitzmaschine erstellt. Ziel ist die virtuelle Durchführung von Untersuchungen und Schwingungsanalysen. Die wichtigsten Komponenten werden mit flexiblen Eigenschaften unter der Verwendung der Finite-Elemente-Methode integriert, um die Schwingungsfähigkeit des Systems zu simulieren. Um die Effizienz der Simulation zu erhöhen, werden die flexiblen Körper auf ein modales Ersatzmodell reduziert. Darüber hinaus wird die Nachgiebigkeit der Lagerpunkte durch Streifigkeitsmatrizen abgebildet und analysiert. Für die Untersuchung des Hochlaufs und des Dauerbetriebes mit unterschiedlichen Maschinenkonfigurationen wurde ein Auswerteverfahren entwickelt, das die Reproduzierbarkeit und den Vergleich zwischen den einzelnen Tests ermöglicht. Abschließend erfolgt durch den Abgleich mit realen Messungen die Validierung des digitalen Zwillings, wodurch dessen Qualität gesichert und die Vergleichbarkeit zur realen Maschine gewährleistet wird. Y1 - 2025 SN - 9783181024638 U6 - https://doi.org/10.51202/9783181024638-271 SP - 271 EP - 288 PB - VDI Verlag ER - TY - CHAP A1 - Pfingsten, Andrea ED - Kopkow, Christian ED - Elsner, Bernhard T1 - Pain Neuroscience Education bei chronischen Schmerzen T2 - Physiotherapie evidenzbasiert Band 2 KW - Schmerz KW - chronischer Schmerz KW - Physiotherapie KW - Edukation KW - Neuroscience Y1 - 2026 SN - 978-3-45125-6 SP - 93 EP - 95 PB - Elsevier CY - München ER - TY - GEN A1 - Stadler, Anselm A1 - Sattler, Andrea A1 - Mohr, Christa T1 - Literaturliste zum Artikel: Lernen in digitalen Realitäten T2 - Lernen in digitalen Realitäten. XR als Chance für die Pflegebildung. PADUA (2026), 21(2), 10.1024/1861-6186/a000922 N2 - Dies ist das vollständige Literaturverzeichnis zum Zeitschriftenartikel "Lernen in digitalen Realitäten". Y1 - 2026 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-88958 N1 - Nachweis zur Veröffentlichung ebenfalls auf OPUS: https://opus4.kobv.de/opus4-oth-regensburg/admin/document/index/id/8952 ER - TY - PAT A1 - Hummel, Helmut A1 - Lechner, Alfred T1 - Miniaturized on-line trace analysis [Patentschrift] N2 - The invention relates to a measuring apparatus comprising an apparatus for forming a liquid optical waveguide having a substrate (1) having an at least partially curved closed microchannel (2) having a low-refractive coating (13), whereby there is formed in the substrate (1) at least one feed line (6) for supplying liquid, and whereby there is provided at least at one end of the closed microchannel (2) an apparatus for coupling light axially into the closed microchannel and/or for coupling light axially out of the closed microchannel (2), further comprising a light source (4), a light detector (5), and a first liquid pump (9) which supplies a sample liquid (7) to the closed microchannel (2) via the at least one feed line (6, 6a). Y1 - 2015 UR - https://depatisnet.dpma.de/DepatisNet/depatisnet?action=bibdat&docid=US000008948563B2&zd=1#zd ER - TY - JOUR A1 - Jain, Brijnesh A1 - Schultz, David T1 - Asymmetric learning vector quantization for efficient nearest neighbor classification in dynamic time warping spaces JF - Pattern Recognition N2 - The nearest neighbor method together with the dynamic time warping (DTW) distance is one of the most popular approaches in time series classification. This method suffers from high storage and computation requirements for large training sets. As a solution to both drawbacks, this article extends learning vector quantization (LVQ) from Euclidean spaces to DTW spaces. The proposed generic LVQ scheme uses asymmetric weighted averaging as update rule. We theoretically justify the asymmetric LVQ scheme via subgradient techniques and by the margin-growth principle. In addition, we show that the decision boundary of two prototypes from different classes is piecewise quadratic. Empirical results exhibited superior performance of asymmetric generalized LVQ (GLVQ) over other state-of-the-art prototype generation methods for nearest neighbor classification. Y1 - 2018 U6 - https://doi.org/10.1016/j.patcog.2017.10.029 VL - 76 SP - 349 EP - 366 PB - Elsevier ER -