@article{BedburKampsSchmiedt, author = {Bedbur, Stefan and Kamps, Udo and Schmiedt, Anja Bettina}, title = {A flexible model of ordered random variables for non-metallic inclusions in steels and related statistical inference}, series = {Applied Mathematical Modelling}, volume = {149}, journal = {Applied Mathematical Modelling}, publisher = {Elsevier}, issn = {0307-904X}, doi = {10.1016/j.apm.2025.116284}, pages = {15}, abstract = {In a data set of non-metallic inclusion sizes in samples from engineering steel, common order statistics fail to serve as a suitable model for ascendingly ordered measurements within single samples. Therefore, a flexible model of ordered random variables is proposed, which allows for changes of distributions described by model parameters. Joint maximum likelihood estimation of these parameters and the shape parameter of an underlying left-truncated Weibull distribution is considered, and a model test is developed for the null-hypothesis of common order statistics being an adequate model. To overcome small data situations, a link-function approach is examined in order to reduce the number of involved model parameters as well as to propose to use a link-function parameter as a material indicator. An asymptotic test is provided to check for the presence of a linear link function, and tests for hypotheses about two link-function parameters are studied. Moreover, the construction of simultaneous confidence regions for the link-function parameters as well as of confidence bands for the entire graph of the link function are presented. Throughout, the findings are applied to the real metallurgical data set. Similar problems and data structures arise in other fields of material science and applications such as geology.}, language = {en} } @article{SchmiedtEmpacherKamps, author = {Schmiedt, Anja B. and Empacher, Christina and Kamps, Udo}, title = {One- and two-sided prediction intervals for future Pareto record values with applications}, series = {Journal of Statistical Theory and Applications}, journal = {Journal of Statistical Theory and Applications}, publisher = {Springer}, issn = {2214-1766}, doi = {10.1007/s44199-025-00119-w}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-81605}, pages = {26}, abstract = {Based on upper record values in a series of observations over time from a Pareto distribution, an exact and several approximate one-sided and two-sided prediction intervals for the next record value (or for another future record value) to appear are studied and compared by means of an extensive simulation study. The performances of the prediction intervals are evaluated and recommendations are proposed for what method should be used in a given situation with respect to the form of the prediction interval on the one hand and to the tail behaviour on the other. The proposed methods are applied to insurance, environmental and sports data, where the respectively fitted Pareto distributions show a different tail behaviour. As a result, it is seen that although the number of observed record values in the presented real data applications is rather small, as it is usually the case, the selected prediction intervals are of practical use.}, language = {en} } @article{DotterHaugSchnelletal., author = {Dotter, Caroline and Haug, Sonja and Schnell, Rainer and Raptis, Georgios and Weber, Karsten}, title = {Sharing health data for research purposes: results of a population survey in Germany}, series = {BMC health services research}, volume = {25}, journal = {BMC health services research}, publisher = {BMC}, doi = {10.1186/s12913-025-12706-9}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-81622}, pages = {9}, abstract = {BACKGROUND: Increased use of health data has the potential to improve both health care and health policies. Several recent policy initiatives at the European and German legislative levels aim to increase the primary and secondary use of health data. However, little is known about general population views on health data access for research. Most studies are based on subsets defined by specific illnesses. METHODS: We commissioned a national computer-assisted dual-frame telephone survey (landline and mobile). Logit estimation models were used to identify predictors of willingness to provide access to health data to different organizations (universities in Germany, universities worldwide, German government organizations, pharmaceutical companies). RESULTS: A high willingness to share health data for research purposes is observed, depending on the specific data recipient. The willingness is highest for research at universities in Germany and German governmental organizations, and lowest regarding research by pharmaceutical companies. The main drivers for sharing health data are the level of trust in public institutions, the respondents' assessment of the seriousness and likelihood of data misuse, and the level of digital literacy. Age, gender, and level of education have small effects and do not determine the willingness to share health data for all organizations. CONCLUSION: We present evidence from a random sample of the German population. The results indicate widespread support among the population for providing access to health data for research purposes. Similar to findings in other countries, the willingness depends strongly on the recipient of the data. This paper evaluates the impact of various determinants - identified in previous qualitative and quantitative research - on the willingness of the German population to share health data. While previous studies have found that patients are generally more willing to share health data, we found that the presence of a medical precondition does not translate into respondents' unequivocal support for health data sharing. We identify privacy concerns, general trust, and digital literacy as key factors influencing the willingness to share health data. Therefore, policymakers and stakeholders need to ensure and communicate the necessary privacy protection measures to increase the willingness of the German population to share health data.}, language = {en} } @inproceedings{SchwaegerlUhrig, author = {Schw{\"a}gerl, Felix and Uhrig, Sabrina}, title = {Tool Support for the Evaluation of Matching Algorithms in the Eclipse Modeling Framework}, series = {Proceedings of the 1st International Conference on Model-Driven Engineering and Software Development, February 19-21, 2013, in Barcelona, Spain, Vol. 1}, booktitle = {Proceedings of the 1st International Conference on Model-Driven Engineering and Software Development, February 19-21, 2013, in Barcelona, Spain, Vol. 1}, publisher = {SciTePress - Science and and Technology Publications}, isbn = {978-989-8565-42-6}, issn = {2184-4348}, doi = {10.5220/0004310801010110}, pages = {101 -- 110}, abstract = {In the field of model-driven development, sophisticated support for comparing model versions is urgently needed. Unfortunately, algorithms for model matching have been rarely evaluated so far. This paper deals with two extensions to the Eclipse Modeling Framework (EMF) that facilitate the evaluation of matching algorithms for EMF models, with the goal to combine user involvement and automated testing in the evaluation process. First a tree editor is presented that allows for the manual and semi-automated creation of match models which formalize the intended matching result. Second a benchmarking procedure is implemented which - given the intended match and the actual results of matching algorithms - automatically derives the number of a and b errors in a target-performance comparison. These results are valuable for drawing conclusions about the specific qualities of matching algorithms or for finding an adequate set of parameters for a configurable algorithm.}, language = {en} } @inproceedings{BuchmannSchwaegerl, author = {Buchmann, Thomas and Schw{\"a}gerl, Felix}, title = {Using Meta-code Generation to Realize Higher-order Model Transformations}, series = {Proceedings of the 8th International Joint Conference on Software Technologies, July 29-31, 2013, in Reykjav{\´i}k, Iceland, Vol. 1}, booktitle = {Proceedings of the 8th International Joint Conference on Software Technologies, July 29-31, 2013, in Reykjav{\´i}k, Iceland, Vol. 1}, publisher = {SciTePress - Science and and Technology Publications}, isbn = {978-989-8565-68-6}, doi = {https://doi.org/10.5220/0004522305360541}, pages = {536 -- 541}, abstract = {Model-driven engineering is a wide-spread paradigm in modern software engineering. During the last couple of years, many tools and languages have been developed, which are especially designed for model transformations — a discipline which is needed in many model-driven engineering approaches. While most of the existing model-to-model tools and languages are tailored towards batch transformations for specific model instances, they lack support for generic transformation problems, where the metamodel is unknown beforehand. In this paper we present a two-step meta-code generation approach that derives a metamodel-specific modelto- model transformation from a model-to-text transformation. The approach has been successfully applied to the problem of product derivation in model-driven software product lines.}, language = {en} } @article{WinterArtingerBoecketal., author = {Winter, Lina and Artinger, Annalena and B{\"o}ck, Hendrik and Ramakrishnan, Vignesh and Reible, Bruno and Albin, Jan and Sch{\"u}ffler, Peter J. and Raptis, Georgios and Brochhausen, Christoph}, title = {Developing a smart and scalable tool for histopathological education—PATe 2.0}, series = {Journal of Pathology Informatics}, volume = {20}, journal = {Journal of Pathology Informatics}, publisher = {Elsevier}, issn = {2153-3539}, doi = {10.1016/j.jpi.2025.100535}, abstract = {Digital microscopy plays a crucial role in pathology education, providing scalable and standardized access to learning resources. In response, we present PATe 2.0, a scalable redeveloped web-application of the former PATe system from 2015. PATe 2.0 was developed using an agile, iterative process and built on a microservices architecture to ensure modularity, scalability, and reliability. It integrates a modern web-based user interface optimized for desktop and tablet use and automates key workflows such as whole-slide image uploads and processing. Performance tests demonstrated that PATe 2.0 significantly reduces tile request times compared to PATe, despite handling larger tiles. The platform supports open formats like DICOM and OpenSlide, enhancing its interoperability and adaptability across institutions. PATe 2.0 represents a robust digital microscopy solution in pathology education enhancing usability, performance, and flexibility. Its design enables future integration of research algorithms and highlights it as a pivotal tool for advancing pathology education and research.}, language = {en} } @misc{Weber, author = {Weber, Karsten}, title = {K{\"u}nstliche Intelligenz als vielschichtige Herausforderung}, language = {de} } @techreport{BhardwajHauerMueckeetal., type = {Working Paper}, author = {Bhardwaj, Prakhar and Hauer, Franziska and M{\"u}cke, Vanessa and Dotter, Caroline and Haug, Sonja and Weikl, Simone and Weber, Karsten}, title = {Recording and understanding multi- and intermodal mobility - a review}, address = {Regensburg}, doi = {10.35096/othr/pub-8742}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-87427}, pages = {25}, abstract = {The transition to sustainable mobility requires detailed knowledge of actual mobility behavior. Recording mobility behavior through conventional, aggregated, or retrospective survey methods (e.g., counting stations, travel diaries) may yield incomplete insights. In addition, these methods are often expensive, prone to error, or not scalable. The aim of this literature review is to provide a systematic overview of the current state of the literature on recording and analysis of individual mobility data and, based on this, to identify possible research gaps and potential. The exploratory literature review includes social science surveys on multi- and intermodal mobility behavior, as well as an overview of possible ways to analyze travel data. The focus of the latter is on identifying relevant data sources and methodological approaches for segmentation, identification of transport mode, and trip purpose determination. Results from recent studies show that sensor-based data collection alone is not sufficient to fully and accurately map mobility behavior. One possible solution is a "best-of-both-worlds" approach that combines passive, automatic mobility data collection via smartphone sensors with targeted user corrections and additions ("human-in-the-loop") within an app. The literature review shows that this approach yields the best data quality. Combining mobility surveys with passive collection of mobility data provides a comprehensive, accurate, and complete overview of mobility behavior.}, language = {en} } @misc{HauerHaugScharfetal., author = {Hauer, Franziska and Haug, Sonja and Scharf, Anna and Schultz, Maximilian and Weber, Karsten}, title = {Quantitative Befragung zu K{\"u}nstlicher Intelligenz f{\"u}r Nichtregierungsorganisationen -Fragebogen und Codebuch}, address = {Regensburg}, doi = {10.35096/othr/pub-8706}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-87066}, pages = {25}, abstract = {K{\"u}nstliche Intelligenz (KI) stellt ein wichtiges Thema der Digitalisierung dar und hat das Potenzial viele Arbeitsfelder grundlegend zu ver{\"a}ndern. Mit dem Einsatz von KI wird die Hoffnung verbunden durch Automatisierung Zeit und Geld zu sparen. Dies k{\"o}nnte besonders interessant f{\"u}r Organisationen sein, die wenig Ressourcen zur Verf{\"u}gung haben, da sie nicht gewinnorientiert oder ehrenamtlich arbeiten. Dazu z{\"a}hlen Nichtregierungsorganisationen (NRO), die einen wichtigen Bestandteil der Zivilgesellschaft darstellen. Aufgrund der komplexer werdenden Arbeit von NROs scheint KI M{\"o}glichkeiten zur Bew{\"a}ltigung aktueller und zuk{\"u}nftiger Herausforderungen zu bieten. {\"U}ber den Einsatz von KI in NROs ist derzeit jedoch wenig bekannt. Es wurde eine quantitative Querschnittstudie deutscher Nichtregierungsorganisationen (NRO) zum Thema KI durchgef{\"u}hrt. Der Web-Survey baut auf den Erkenntnissen des Scoping Reviews und der qualitativen Interviews auf und vertieft den Einblick in die Bereiche aktuelle Nutzung von KI, Wissenstand in den Organisationen sowie vorhandene und noch ben{\"o}tigte Ressourcen. Daf{\"u}r wurden 343 NROs verschiedener Gr{\"o}ßen und Handlungsfelder befragt und die Ergebnisse quantitativ analysiert.}, language = {de} } @techreport{BhardwajHauerMueckeetal., type = {Working Paper}, author = {Bhardwaj, Prakhar and Hauer, Franziska and M{\"u}cke, Vanessa and Dotter, Caroline and Haug, Sonja and Weikl, Simone and Weber, Karsten}, title = {Multi- und intermodale Mobilit{\"a}t erfassen und verstehen - eine Literatur{\"u}bersicht}, address = {Regensburg}, doi = {10.35096/othr/pub-8741}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-87415}, pages = {24}, abstract = {Die Transformation zu nachhaltiger Mobilit{\"a}t erfordert eine detaillierte Erfassung des tats{\"a}chlichen Mobilit{\"a}tsverhaltens, was durch herk{\"o}mmliche, aggregierte oder retrospektive Erhebungsmethoden (z.B. Z{\"a}hlstellen, Wegetageb{\"u}cher) nicht vollst{\"a}ndig gelingt. Zudem sind diese Methoden oft teuer, fehleranf{\"a}llig oder nicht nachhaltig skalierbar. Ziel dieser Literatur{\"u}bersicht ist es, einen systematischen {\"U}berblick {\"u}ber den aktuellen Forschungsstand zur Erhebung und Analyse individueller Mobilit{\"a}tsdaten zu geben und darauf aufbauend m{\"o}gliche Forschungsl{\"u}cken sowie Potentiale zu identifizieren. Die explorative Literaturrecherche umfasst sozialwissenschaftliche Erhebungen zu multi- und intermodalem Mobilit{\"a}tsverhalten, sowie einen {\"U}berblick {\"u}ber Analysem{\"o}glichkeiten von Wegedaten. Der Fokus liegt auf der Identifikation relevanter Datenquellen und methodischer Ans{\"a}tze zur Segmentierung, Verkehrsmittelerkennung und Wegezweckbestimmung. Ergebnisse aus aktuellen Studien verdeutlichen, dass ausschließlich sensorgest{\"u}tzte Datenerhebungen bisher nicht ausreichen, um Mobilit{\"a}tsverhalten vollumf{\"a}nglich und pr{\"a}zise abzubilden. Eine m{\"o}gliche L{\"o}sung ist ein "Best-of-both-worlds-Ansatz, der die passive, automatische Mobilit{\"a}tsdatenerfassung via Smartphone-Sensorik mit gezielten Nutzerkorrekturen und Erg{\"a}nzungen ("Human-in-the-Loop") innerhalb einer App kombiniert. Die Literaturauswertung zeigt, dass auf diesem Weg die beste Datenqualit{\"a}t gewonnen werden kann. Durch die Kombination von Mobilit{\"a}tsbefragung mit passiver Erhebung von Mobilit{\"a}tsdaten kann ein umfassender, m{\"o}glichst vollst{\"a}ndiger und korrekter {\"U}berblick {\"u}ber das Mobilit{\"a}tsverhalten gewonnen werden.}, language = {de} } @inproceedings{FranzWinkerGroppeetal., author = {Franz, Maja and Winker, Tobias and Groppe, Sven and Mauerer, Wolfgang}, title = {Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation}, series = {2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 15-20 September 2024, Montreal, QC, Canada}, booktitle = {2024 IEEE International Conference on Quantum Computing and Engineering (QCE), 15-20 September 2024, Montreal, QC, Canada}, publisher = {IEEE}, doi = {10.1109/QCE60285.2024.00055}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-76877}, pages = {409 -- 420}, abstract = {Identifying optimal join orders (JOs) stands out as a key challenge in database research and engineering. Owing to the large search space, established classical methods rely on approximations and heuristics. Recent efforts have successfully explored reinforcement learning (RL) for JO. Likewise, quantum versions of RL have received considerable scientific attention. Yet, it is an open question if they can achieve sustainable, overall practical advantages with improved quantum processors. In this paper, we present a novel approach that uses quantum reinforcement learning (QRL) for JO based on a hybrid variational quantum ansatz. It is able to handle general bushy join trees instead of resorting to simpler left-deep variants as compared to approaches based on quantum(-inspired) optimisation, yet requires multiple orders of magnitudes fewer qubits, which is a scarce resource even for post-NISQ systems. Despite moderate circuit depth, the ansatz exceeds current NISQ capabilities, which requires an evaluation by numerical simulations. While QRL may not significantly outperform classical approaches in solving the JO problem with respect to result quality (albeit we see parity), we find a drastic reduction in required trainable parameters. This benefits practically relevant aspects ranging from shorter training times compared to classical RL, less involved classical optimisation passes, or better use of available training data, and fits data-stream and low-latency processing scenarios. Our comprehensive evaluation and careful discussion delivers a balanced perspective on possible practical quantum advantage, provides insights for future systemic approaches, and allows for quantitatively assessing trade-offs of quantum approaches for one of the most crucial problems of database management systems.}, language = {en} } @article{KruegerMauerer, author = {Kr{\"u}ger, Tom and Mauerer, Wolfgang}, title = {Out of the Loop: Structural Approximation of Optimisation Landscapes and non-Iterative Quantum Optimisation}, series = {Quantum}, volume = {9}, journal = {Quantum}, publisher = {Verein zur F{\"o}rderung des Open Access Publizierens in den Quantenwissenschaften}, doi = {10.22331/q-2025-11-06-1903}, pages = {32}, abstract = {The Quantum Approximate Optimisation Algorithm (QAOA) is a widely studied quantum-classical iterative heuristic for combinatorial optimisation. While QAOA targets problems in complexity class NP, the classical optimisation procedure required in every iteration is itself known to be NP-hard. Still, advantage over classical approaches is suspected for certain scenarios, but nature and origin of its computational power are not yet satisfactorily understood. By introducing means of efficiently and accurately approximating the QAOA optimisation landscape from solution space structures, we derive a new algorithmic variant of unit-depth QAOA for two-level Hamiltonians (including all problems in NP): Instead of performing an iterative quantum-classical computation for each input instance, our non-iterative method is based on a quantum circuit that is instance-independent, but problem-specific. It matches or outperforms unit-depth QAOA for key combinatorial problems, despite reduced computational effort. Our approach is based on proving a long-standing conjecture regarding instance-independent structures in QAOA. By ensuring generality, we link existing empirical observations on QAOA parameter clustering to established approaches in theoretical computer science, and provide a sound foundation for understanding the link between structural properties of solution spaces and quantum optimisation.}, language = {de} } @inproceedings{SchoenbergerTrummerMauerer, author = {Sch{\"o}nberger, Manuel and Trummer, Immanuel and Mauerer, Wolfgang}, title = {Large-Scale Multiple Query Optimisation with Incremental Quantum(-Inspired) Annealing}, series = {Proceedings of the ACM on Management of Data}, volume = {3}, booktitle = {Proceedings of the ACM on Management of Data}, number = {4}, publisher = {ACM}, doi = {10.1145/3749171}, pages = {25}, abstract = {Multiple-query optimization (MQO) seeks to reduce redundant work across query batches. While MQO offers opportunities for dramatic performance improvements, the problem is NP-hard, limiting the sizes of problems that can be solved on generic hardware. We propose to leverage specialized hardware solvers for optimization, such as Fujitsu's Digital Annealer (DA), to scale up MQO to problem sizes formerly out of reach. We present a novel incremental processing approach that combines classical computation with DA acceleration. By efficiently partitioning MQO problems into sets of partial problems, and by applying a dynamic search steering strategy that reapplies initially discarded information to incrementally process individual problems, our method overcomes capacity limitations, and scales to extremely large MQO instances (up to νm1000 queries). A thorough and comprehensive empirical evaluation finds our method substantially outperforms existing approaches. Our generalisable framework lays the ground for other database use-cases on quantum-inspired hardware, and bridges towards future quantum accelerators.}, language = {en} } @unpublished{KoesterPorkertVolbert, author = {K{\"o}ster, Dominik and Porkert, Florian and Volbert, Klaus}, title = {Multi-Day Scheduling for Electric Vehicle Routing: A Novel Model and Comparison Of Metaheuristics}, doi = {10.48550/arXiv.2512.21346}, pages = {6}, abstract = {The increasing use of electric vehicles (EVs) requires efficient route planning solutions that take into account the limited range of EVs and the associated charging times, as well as the different types of charging stations. In this work, we model and solve an electric vehicle routing problem (EVRP) designed for a cross-platform navigation system for individual transport. The aim is to provide users with an efficient route for their daily appointments and to reduce possible inconveniences caused by charging their EV. Based on these assumptions, we propose a multi-day model in the form of a mixed integer programming (MIP) problem that takes into account the vehicle's battery capacity and the time windows of user's appointments. The model is solved using various established metaheuristics, including tabu search (TS), adaptive large neighborhood search (ALNS), and ant colony optimization (ACO). Furthermore, the performance of the individual approaches is analyzed using generated ensembles to estimate their behavior in reality and is compared with the exact results of the Google OR-Tools solver. 6 pages, 5 figures}, language = {en} } @unpublished{KruegerMauerer, author = {Kr{\"u}ger, Tom and Mauerer, Wolfgang}, title = {Out of the Loop: Structural Approximation of Optimisation Landscapes and non-Iterative Quantum Optimisation}, pages = {20}, abstract = {The Quantum Approximate Optimisation Algorithm (qaoa) is a widely studied quantum-classical iterative heuristic for combinatorial optimisation. While qaoa targets problems in complexity class NP, the classical optimisation procedure required in every iteration is itself known to be NP-hard. Still, advantage over classical approaches is suspected for certain scenarios, but nature and origin of its computational power are not yet satisfactorily understood. By introducing means of efficiently and accurately approximating the qaoa optimisation landscape from solution space structures, we derive a new algorithmic variant: Instead of performing an iterative quantum-classical computation for each input instance, our non-iterative method is based on a quantum circuit that is instance-independent, but problem-specific. It matches or outperforms unit-depth qaoa for key combinatorial problems, despite reduced computational effort. Our approach is based on proving a long-standing conjecture regarding instance-independent structures in qaoa. By ensuring generality, we link existing empirical observations on qaoa parameter clustering to established approaches in theoretical computer science, and provide a sound foundation for understanding the link between structural properties of solution spaces and quantum optimisation.}, language = {en} } @incollection{Mauerer, author = {Mauerer, Wolfgang}, title = {Quantum Software = Quantum minus Software?}, series = {Dagstuhl Reports : Quantum Software Engineering : Report from Dagsthul Seminar 24512}, volume = {14}, booktitle = {Dagstuhl Reports : Quantum Software Engineering : Report from Dagsthul Seminar 24512}, number = {12}, editor = {Ali, Shaukat and Barzen, Johanna and Delgado, Andrea and M{\"u}ller, Hausi A. and Murillo, Juan Manuel}, publisher = {Dagstuhl Publishing}, doi = {10.4230/DagRep.14.12.63}, url = {http://nbn-resolving.de/urn:nbn:de:0030-drops-230469}, pages = {73 -- 74}, abstract = {The Dagstuhl Seminar 24512 on "Quantum Software Engineering" was held from December 15 to 20, 2024. It brought together 26 participants from industry and academia from 13 different countries, including senior and junior researchers as well as practitioners in the field of Quantum Software Engineering. The aim of the seminar was to advance software engineering methods and tools for the engineering of hybrid quantum systems by promoting personal interaction and open discussion among researchers who are already working in this emerging area of knowledge. The first day of the seminar was devoted to the topic "When software engineering meets quantum mechanics", while the second day focused on "Quantum software engineering and its challenges." During both days, 16 invited presentations were given. The rest of the seminar was organized into three working groups to address the topics "Quantum Software Design, Modelling and Architecturing", "Adaptive Hybrid Quantum Systems", and "Quantum Software Quality Assurance". The seminar was a very fruitful experience for all participants both in terms of scientific outcomes and in terms of the personal relationships that were generated to jointly address future experiences.}, language = {en} } @unpublished{CenkoWeimannRaptis, author = {Cenko, Egidia and Weimann, Thure Georg and Raptis, Georgios}, title = {Navigating the DiGA Jungle: A Taxonomy and Archetypal Framework of the German Digital Therapeutics Landscape}, doi = {10.64898/2025.12.30.25343225}, pages = {26}, abstract = {Digital therapeutics (DTx) are patient-facing apps designed to support individuals in their daily lives. Therefore, they have thepotential to revolutionize healthcare by empowering and engaging patients to become active players in their own care. Despitethe increasing adoption of DTx in national healthcare systems, research on their design remains limited. The present studyintroduces "DiGATax", a taxonomy designed to categorize and analyze DTx, including perspectives on content, interventiondelivery logic and technology, as well as the patient's interface, consolidating and expanding upon prior taxonomic work.Based on n = 44 applications retrieved from the German DiGA directory that demonstrated positive health outcomes, thetaxonomy is supported by empirical evidence. Additionally, the study contributes by presenting an archetype frameworkof DTx derived from a taxonomy-based cluster analysis. Further analyses offer insights into specific combinations of DTxcharacteristics across archetypes, the user interface as a key factor in their acceptance, and potential links between DTxdesign and health-related and user engagement outcomes. By offering new insights into DTx design, this study contributestowards more organized research and reporting, ultimately paving the way for the development of effective solutions. It alsomarks a further step towards Meta-DTx, which aim to align patient care for multimorbid patients under one umbrella.}, language = {en} } @inproceedings{StadlerSeitz, author = {Stadler, Sebastian and Seitz, Marie Sophie}, title = {When algorithms design: a comparative study pits an AI-generated application against a manual application in a competition of user experience and user-friendliness}, series = {Proceedings of 2025 11th international HCI and UX conference in Indonesia, 5 + 6. December 2025, Bali (CHIuXiD)}, booktitle = {Proceedings of 2025 11th international HCI and UX conference in Indonesia, 5 + 6. December 2025, Bali (CHIuXiD)}, publisher = {IEEE}, doi = {10.1109/CHIuXiD68326.2025.11323819}, pages = {55 -- 60}, abstract = {The rapid growth of artificial intelligence has enabled automated website creation, including design, content, and SEO. This study compares an AI-generated application with a manually designed one in terms of usability and user experience. Forty-two participants evaluated efficiency, effectiveness, satisfaction, emotional responses, and behavioural patterns. The manual application outperformed the AI-generated one in most datasets, particularly in clarity, supportiveness, and comprehensibility, while speed, learnability, activation, creativity, and security showed no significant differences. Users reported more positive emotions and confident interactions with the manual application, whereas the AI application elicited uncertainty and frustration. These behavioural differences were also reflected in processing times and task completion rates, suggesting that AI-generated solutions currently struggle to meet established UX standards. Nevertheless, the AI builder demonstrated potential for rapid prototyping and low-effort website creation, offering advantages for users with limited technical skills or resources. The findings highlight both the opportunities and limitations of current AI-based web design tools and underline the importance of human-centered design expertise in achieving high-quality user experiences. Despite existing shortcomings, AI-supported tools may become increasingly viable as technology advances.}, language = {en} } @inproceedings{DuennweberLorenzBraeuetal., author = {D{\"u}nnweber, Jan and Lorenz, Marcel and Br{\"a}u, Fabian and Saito, Hiroshi and Melzer, Matthias}, title = {Driving out the Bears from the Suburbs by Means of Location Theory and Intelligent Agents}, series = {Proceedings of the ACM 12th International Conference on Animal-Computer Interaction, ACI 2025: The International Conference on Animal-Computer Interaction ; Indiana USA ; 01-04.12.2025}, booktitle = {Proceedings of the ACM 12th International Conference on Animal-Computer Interaction, ACI 2025: The International Conference on Animal-Computer Interaction ; Indiana USA ; 01-04.12.2025}, publisher = {ACM}, address = {New York, NY, USA}, isbn = {9798400721236}, doi = {10.1145/3768539.3768546}, pages = {9}, abstract = {Due to the recent surge in bear attacks, affected municipalities have taken various measures to drive out the intruders. Political considerations include, in many places, the expansion of shooting permits. More and more regional governmental authorities invest in technologies for efficient bear hunting, such as IP cameras and computer vision. From an ecological perspective, such procedures, which are all solely aimed at decreasing the bear population, are questionable, since ecosystems can benefit from a peaceful coexistence of bears with humans: Bears remove animal carcasses and thus return vital nutrients to the soil and prevent the spread of diseases. Moreover, the bears keep the deer population in check, which is advantageous for the forest vegetation. Conflicts start, once the bears intrude populated areas, which are often rural villages and suburbs with a low population density. Naturally, bears do not see humans as prey and respect their size. When the animal attacks, this happens rather for territorial or protective reasons, e. g., after an unexpected encounter with humans unsettled it. In this work, we analyze means to eradicate the danger: We dynamically apply Weiszfeld's algorithm for finding the shifting geometric median between time-windowed black bear sightings and use the results for implementing an early warning system. In addition, we weigh the spotted locations and predict the expected migration behavior between bear habitats using a simulation with intelligent agents. As a case study, we apply our software to data from Romania and Fukushima and identify the positions where bear repelling facilities should be placed most effectively.}, language = {en} } @inproceedings{GutbrodRauberWeberNunesetal., author = {Gutbrod, Max and Rauber, David and Weber Nunes, Danilo and Palm, Christoph}, title = {OpenMIBOOD: Open Medical Imaging Benchmarks for Out-Of-Distribution Detection}, series = {2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 10.-17. June 2025, Nashville}, booktitle = {2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 10.-17. June 2025, Nashville}, publisher = {IEEE}, isbn = {979-8-3315-4364-8}, doi = {10.1109/CVPR52734.2025.02410}, pages = {25874 -- 25886}, abstract = {The growing reliance on Artificial Intelligence (AI) in critical domains such as healthcare demands robust mechanisms to ensure the trustworthiness of these systems, especially when faced with unexpected or anomalous inputs. This paper introduces the Open Medical Imaging Benchmarks for Out-Of-Distribution Detection (OpenMIBOOD), a comprehensive framework for evaluating out-of-distribution (OOD) detection methods specifically in medical imaging contexts. OpenMIBOOD includes three benchmarks from diverse medical domains, encompassing 14 datasets divided into covariate-shifted in-distribution, nearOOD, and far-OOD categories. We evaluate 24 post-hoc methods across these benchmarks, providing a standardized reference to advance the development and fair comparison of OODdetection methods. Results reveal that findings from broad-scale OOD benchmarks in natural image domains do not translate to medical applications, underscoring the critical need for such benchmarks in the medical field. By mitigating the risk of exposing AI models to inputs outside their training distribution, OpenMIBOOD aims to support the advancement of reliable and trustworthy AI systems in healthcare. The repository is available at https://github.com/remic-othr/OpenMIBOOD.}, language = {en} } @article{HeinzSchildgen, author = {Heinz, Florian and Schildgen, Johannes}, title = {Experience Report: Hey LLM, Generate SQL!}, series = {Datenbank-Spektrum}, volume = {25}, journal = {Datenbank-Spektrum}, number = {2}, publisher = {Springer}, address = {Wiesbaden}, doi = {10.1007/s13222-025-00512-w}, pages = {95 -- 101}, abstract = {Large Language Models have advanced to a resourceful tool with many applications. One particularly interesting use case is the LLM-aided generation of ad-hoc database queries and the possibility of subsequent processing of the results in a way suiting the users intents. In this article, practical ways and experiences are described on how to effectively use LLMs to map a natural-language user query to an SQL query conforming to a specific database schema and post-processing the results of this query in order to, for example, create an appealing visualization. Best results are achieved under favorable circumstances, as, for example, a clean and meaningful named database schema.}, language = {en} } @inproceedings{PreissWestner, author = {Preiß, Niklas and Westner, Markus}, title = {From Agents to Copilots: a Systematic Review of Digital Assistant Technology Adoption in Proprietary Productivity Software}, series = {Annals of Computer Science and Information Systems}, volume = {43}, booktitle = {Annals of Computer Science and Information Systems}, publisher = {Polish Information Processing Society}, issn = {2300-5963}, doi = {10.15439/2025F3271}, pages = {565 -- 576}, abstract = {This study provides a systematic review of how the impact and adaptation of digital assistant technologies (DATs) are defined, operationalized, and studied, synthesizing key domains where DATs generate or are expected to generate value. Based on an analysis of 61 articles published since 2013, it identifies five main areas of impact: productivity and efficiency, business development, resource optimization, quality enhancement, and the promotion of learning and creativity. The review highlights DAT adoption across various disciplines and industries, while revealing limited longitudinal research on benefits and adaptation. Key gaps remain in understanding strategic use and sustained impact. Future research should explore longitudinal comparisons of recently introduced generative AI-driven DATs and their organizational implications. This review contributes to information systems research by structuring current knowledge on DAT adoption and outcomes, and by proposing a research agenda to support deeper exploration of their value and long-term integration.}, language = {en} } @inproceedings{KoehlerHarlWestneretal., author = {K{\"o}hler, Jessica and Harl, Maximilian Victor and Westner, Markus and Strahringer, Susanne}, title = {Can AI be a Scholar? A Systematic Review on the Role of Generative AI in Systematic Literature Reviews}, series = {2025 27th International Conference on Business Informatics (CBI), 09-12. September 2025, Lisbon, Portugal}, booktitle = {2025 27th International Conference on Business Informatics (CBI), 09-12. September 2025, Lisbon, Portugal}, publisher = {IEEE}, doi = {10.1109/CBI68102.2025.00012}, pages = {11}, abstract = {Systematic literature reviews (SLRs) are foundational for research but resource-intensive to conduct. With the rise of large language models (LLMs) such as ChatGPT, generative AI (GenAI) tools are being increasingly explored for their potential to support and transform the SLR process. This study presents a systematic review of peerreviewed articles that examine how LLM-based GenAI tools are used in different SLR phases. Following the PRISMA 2020 guidelines, we screened 1,846 publications published since January 2021 until April 2025 and selected 54 for in-depth analysis. Each study was coded by review phase, prompting approach, automation level, validation type and challenges. Our findings show that GenAI is most often used to support in the screening, search, and writing phases, typically through Basic Prompting and under human oversight. While many studies report efficiency gains, concerns remain regarding validity, transparency, and methodological rigor. Moreover, GenAI is frequently applied to isolated tasks but is rarely embedded in a structured, methodologically guided review processhighlighting the need for clearer phase-specific guidance and standards. We offer a structured, phase-specific synthesis that highlights both the promise and the current limitations of GenAI in literature reviews and thereby offer practical recommendations for the responsible use of GenAI in literature reviews.}, language = {en} } @incollection{Westner, author = {Westner, Markus}, title = {Generative AI in Business}, series = {Artificial Intelligence in Business and Engineering}, booktitle = {Artificial Intelligence in Business and Engineering}, editor = {Hofbauer, G{\"u}nter}, publisher = {Kohlhammer}, address = {Stuttgart}, isbn = {978-3-17-046742-2}, pages = {38 -- 50}, abstract = {Generative Artificial Intelligence (GenAI) is transforming industries at an unprecedented rate, offering novel opportunities for productivity and innovation. This article explores the adoption of GenAI, highlighting its accelerated uptake compared to previous technologies. Key topics include productivity gains through GenAI tools (e.g., ChatGPT, Klarna's AI assistant), challenges such as data quality and organizational readiness, and the implications for business strategy. Practical recommendations for managing generative AI adoption and maximizing its impact on both individual and organizational levels are also provided. The analysis underscores the necessity of aligning AI capabilities with customer needs and creating data-driven, adaptable business models.}, language = {en} } @unpublished{RueckertRauberMaerkletal., author = {R{\"u}ckert, Tobias and Rauber, David and Maerkl, Raphaela and Klausmann, Leonard and Yildiran, Suemeyye R. and Gutbrod, Max and Nunes, Danilo Weber and Moreno, Alvaro Fernandez and Luengo, Imanol and Stoyanov, Danail and Toussaint, Nicolas and Cho, Enki and Kim, Hyeon Bae and Choo, Oh Sung and Kim, Ka Young and Kim, Seong Tae and Arantes, Gon{\c{c}}alo and Song, Kehan and Zhu, Jianjun and Xiong, Junchen and Lin, Tingyi and Kikuchi, Shunsuke and Matsuzaki, Hiroki and Kouno, Atsushi and Manesco, Jo{\~a}o Renato Ribeiro and Papa, Jo{\~a}o Paulo and Choi, Tae-Min and Jeong, Tae Kyeong and Park, Juyoun and Alabi, Oluwatosin and Wei, Meng and Vercauteren, Tom and Wu, Runzhi and Xu, Mengya and an Wang, and Bai, Long and Ren, Hongliang and Yamlahi, Amine and Hennighausen, Jakob and Maier-Hein, Lena and Kondo, Satoshi and Kasai, Satoshi and Hirasawa, Kousuke and Yang, Shu and Wang, Yihui and Chen, Hao and Rodr{\´i}guez, Santiago and Aparicio, Nicol{\´a}s and Manrique, Leonardo and Lyons, Juan Camilo and Hosie, Olivia and Ayobi, Nicol{\´a}s and Arbel{\´a}ez, Pablo and Li, Yiping and Khalil, Yasmina Al and Nasirihaghighi, Sahar and Speidel, Stefanie and R{\"u}ckert, Daniel and Feussner, Hubertus and Wilhelm, Dirk and Palm, Christoph}, title = {Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge}, pages = {36}, abstract = {Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minimally invasive surgery (RAMIS), including surgical training, skill assessment, and autonomous assistance. However, robust performance under real-world conditions remains a significant challenge. Incorporating surgical context - such as the current procedural phase - has emerged as a promising strategy to improve robustness and interpretability. To address these challenges, we organized the Surgical Procedure Phase, Keypoint, and Instrument Recognition (PhaKIR) sub-challenge as part of the Endoscopic Vision (EndoVis) challenge at MICCAI 2024. We introduced a novel, multi-center dataset comprising thirteen full-length laparoscopic cholecystectomy videos collected from three distinct medical institutions, with unified annotations for three interrelated tasks: surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation. Unlike existing datasets, ours enables joint investigation of instrument localization and procedural context within the same data while supporting the integration of temporal information across entire procedures. We report results and findings in accordance with the BIAS guidelines for biomedical image analysis challenges. The PhaKIR sub-challenge advances the field by providing a unique benchmark for developing temporally aware, context-driven methods in RAMIS and offers a high-quality resource to support future research in surgical scene understanding.}, language = {en} } @book{WestnerStrasser, author = {Westner, Markus and Strasser, Artur}, title = {Objectives and Key Results verstehen und anwenden}, publisher = {Springer Gabler}, address = {Wiesbaden}, isbn = {978-3-658-50381-9}, doi = {10.1007/978-3-658-50382-6}, pages = {47}, abstract = {Dieses essential gibt eine strukturierte und kompakte Einf{\"u}hrung in die Objectives and Key Results-Managementmethode. Es erl{\"a}utert Herkunft, Definition und Einsatzzweck von Objectives and Key Results (OKR) und beschreibt deren zentrale Bestandteile. Leser:innen erfahren, wie gute Objectives und Key Results formuliert werden und welche Strategien sich zur erfolgreichen Implementierung eignen. Zudem werden praxisrelevante Erfolgs- und Misserfolgsfaktoren analysiert, die den Einsatz von OKR maßgeblich beeinflussen. Ein fundierter Leitfaden f{\"u}r alle, die OKR als Steuerungsinstrument in Organisationen verstehen und wirksam einsetzen m{\"o}chten.}, language = {en} } @inproceedings{SachenbacherLeucker, author = {Sachenbacher, Martin and Leucker, Martin}, title = {Towards Monitoring and Diagnosis of Quantum Digital Twins}, series = {Lecture Notes in Informatics (LNI)}, volume = {P-366}, booktitle = {Lecture Notes in Informatics (LNI)}, publisher = {Gesellschaft f{\"u}r Informatik e.V.}, address = {Bonn}, doi = {10.18420/INF2025_159}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-87546}, pages = {1767 -- 1772}, abstract = {As access to larger-scale quantum computers is still limited, it is useful to simulate quantum algorithms on specialized programmable logic hardware such as FPGAs to exploit analogies between quantum and digital circuits, and allow for analysis and efficient debugging of quantum programs. Such simulations can be viewed as digital representations of actual physical systems, commonly referred to as Digital Twins (DTs). In previous work, we applied formal methods from runtime verification to synthesize monitors capable of real-time analysis of conventional DTs. Specifically, these monitors supervise alignment with their physical counterparts and support model-based diagnosis to identify potential root causes of observed deviations. In this short paper, we present ongoing work aimed at adapting and extending our approach to hardware-based simulation and analysis of quantum software on FPGAs, with the objective of improving both accuracy and resilience.}, language = {en} } @article{HoessMauerer, author = {H{\"o}ß, Nicole and Mauerer, Wofgang}, title = {Generative KI: Vom technologischen Paradigmenwechsel zur Vision einer neuen {\"A}ra im Straßenverkehr}, series = {Straßenverkehrstechnik}, volume = {6}, journal = {Straßenverkehrstechnik}, number = {4}, publisher = {Kirschbaum Verlag GmbH}, doi = {10.53184/SVT4-2025-2}, pages = {247 -- 252}, abstract = {Generative K{\"u}nstliche Intelligenz (KI) geht bereits mit enormen Effizienzsteigerungen f{\"u}r Dom{\"a}nen einher, die von Kreativit{\"a}t profitieren. Die F{\"a}higkeit, beliebig viele realit{\"a}tsnahe Daten zu synthetisieren, bietet jedoch auch neue Potenziale f{\"u}r Anwendungen, die bisher aufgrund fehlender Datenmengen noch nicht den Sprung in die Praxis {\"u}berwunden haben. Im Straßenverkehr betrifft dies z. B. das autonome Fahren in herausfordernden Situationen. Um neue Anwendungspotenziale zu erschließen, ist es allerdings erforderlich, die grundlegende Funktionsweise der Technologie gepaart mit ihren Chancen und Herausforderungen zu verstehen. Dieser Fachbeitrag dient deshalb als erste Einf{\"u}hrung in die generative KI, indem er einen {\"U}berblick {\"u}ber zentrale Modelle, ihre grundlegenden Ideen und Funktionsweisen gibt. Darauf basierend werden typische Problemarten aufgezeigt, die mit generativer KI neu betrachtet und besser gel{\"o}st werden k{\"o}nnen - allgemein und spezifisch f{\"u}r den Straßenverkehr. Unter gleichzeitiger Betrachtung derzeitiger Limitierungen dient der Beitrag als Entscheidungshilfe f{\"u}r die Selektion passender generativer oder klassischer KI-Verfahren.}, language = {de} } @article{Schildgen, author = {Schildgen, Johannes}, title = {Individuelle Data-Warehousing-Projekte anstelle einer Abschlussklausur}, series = {Datenbank-Spektrum}, journal = {Datenbank-Spektrum}, publisher = {Springer}, issn = {1618-2162}, doi = {10.1007/s13222-025-00502-y}, pages = {4}, abstract = {Dieser Artikel berichtet {\"u}ber die Erfahrungen aus zwei Semestern, in denen Studierende der Data-Warehousing-Vorlesung individuelle Einzelprojekte bearbeitet haben. Das Projekt besteht aus f{\"u}nf Challenges: die Vorstellung der Projektidee, ein Peer-Review anderer Ideen, Datenmodellierung, ETL und analytische Queries, sowie die Erstellung eines Power BI-Dashboards.}, language = {de} } @article{SchmiedtWeiss, author = {Schmiedt, Anja and Weiß, Christian}, title = {The pair correlation function of multi-dimensional low-discrepancy sequences with small stochastic error terms}, series = {Journal of Number Theory}, volume = {259}, journal = {Journal of Number Theory}, publisher = {Elsevier}, issn = {0022-314X}, doi = {10.1016/j.jnt.2023.12.011}, pages = {422 -- 437}, abstract = {In any dimension d ≥ 2, there is no known example of a low-discrepancy sequence which possesses Poisssonian pair correlations. This is in some sense rather surprising, because low-discrepancy sequences always have β-Poissonian pair correlations for all 0 < β < 1 d and are therefore arbitrarily close to having Poissonian pair correlations (which corresponds to the case β = 1 d ). In this paper, we further elaborate on the closeness of the two notions. We show that d-dimensional Kronecker sequences for badly approximable vectors � α with an arbitrary small uniformly distributed stochastic error term generically have β = 1 d -Poissonian pair correlations.}, language = {en} } @misc{RueckertRueckertPalm, author = {R{\"u}ckert, Tobias and R{\"u}ckert, Daniel and Palm, Christoph}, title = {Corrigendum to "Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art" [Comput. Biol. Med. 169 (2024) 107929]}, series = {Computers in Biology and Medicine}, journal = {Computers in Biology and Medicine}, publisher = {Elsevier}, doi = {10.1016/j.compbiomed.2024.108027}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-70337}, pages = {1}, abstract = {The authors regret that the SAR-RARP50 dataset is missing from the description of publicly available datasets presented in Chapter 4.}, language = {en} } @article{HammerNunesHammeretal., author = {Hammer, Simone and Nunes, Danilo Weber and Hammer, Michael and Zeman, Florian and Akers, Michael and G{\"o}tz, Andrea and Balla, Annika and Doppler, Michael Christian and Fellner, Claudia and Da Platz Batista Silva, Natascha and Thurn, Sylvia and Verloh, Niklas and Stroszczynski, Christian and Wohlgemuth, Walter Alexander and Palm, Christoph and Uller, Wibke}, title = {Deep learning-based differentiation of peripheral high-flow and low-flow vascular malformations in T2-weighted short tau inversion recovery MRI}, series = {Clinical hemorheology and microcirculation}, journal = {Clinical hemorheology and microcirculation}, edition = {Pre-press}, publisher = {IOP Press}, doi = {10.3233/CH-232071}, pages = {1 -- 15}, abstract = {BACKGROUND Differentiation of high-flow from low-flow vascular malformations (VMs) is crucial for therapeutic management of this orphan disease. OBJECTIVE A convolutional neural network (CNN) was evaluated for differentiation of peripheral vascular malformations (VMs) on T2-weighted short tau inversion recovery (STIR) MRI. METHODS 527 MRIs (386 low-flow and 141 high-flow VMs) were randomly divided into training, validation and test set for this single-center study. 1) Results of the CNN's diagnostic performance were compared with that of two expert and four junior radiologists. 2) The influence of CNN's prediction on the radiologists' performance and diagnostic certainty was evaluated. 3) Junior radiologists' performance after self-training was compared with that of the CNN. RESULTS Compared with the expert radiologists the CNN achieved similar accuracy (92\% vs. 97\%, p = 0.11), sensitivity (80\% vs. 93\%, p = 0.16) and specificity (97\% vs. 100\%, p = 0.50). In comparison to the junior radiologists, the CNN had a higher specificity and accuracy (97\% vs. 80\%, p <  0.001; 92\% vs. 77\%, p <  0.001). CNN assistance had no significant influence on their diagnostic performance and certainty. After self-training, the junior radiologists' specificity and accuracy improved and were comparable to that of the CNN. CONCLUSIONS Diagnostic performance of the CNN for differentiating high-flow from low-flow VM was comparable to that of expert radiologists. CNN did not significantly improve the simulated daily practice of junior radiologists, self-training was more effective.}, language = {en} } @inproceedings{SchoenhaerlFuxenGrafetal., author = {Sch{\"o}nh{\"a}rl, Stefan and Fuxen, Philipp and Graf, Julian and Schmidt, Jonas and Hackenberg, Rudolf and Mottok, J{\"u}rgen}, title = {An Automotive Penetration Testing Framework for IT-Security Education}, series = {Cloud Computing 2022: The Thirteenth International Conference on Cloud Computing, GRIDs, and Virtualization, Special Track FAST-CSP, Barcelona, Spain, 24.-28.04.2022}, booktitle = {Cloud Computing 2022: The Thirteenth International Conference on Cloud Computing, GRIDs, and Virtualization, Special Track FAST-CSP, Barcelona, Spain, 24.-28.04.2022}, publisher = {IARIA}, address = {[Wilmington, DE, USA]}, isbn = {978-1-61208-948-5}, pages = {1 -- 6}, abstract = {Automotive Original Equipment Manufacturer (OEM) and suppliers started shifting their focus towards the security of their connected electronic programmable products recently since cars used to be mainly mechanical products. However, this has changed due to the rising digitalization of vehicles. Security and functional safety have grown together and need to be addressed as a single issue, referred to as automotive security, in the following article. One way to accomplish security is automotive security education. The scientific contribution of this paper is to establish an Automotive Penetration Testing Education Platform (APTEP). It consists of three layers representing different attack points of a vehicle. The layers are the outer, inner, and core layers. Each of those contains multiple interfaces, such as Wireless Local Area Network (WLAN) or electric vehicle charging interfaces in the outer layer, message bus systems in the inner layer, and debug or diagnostic interfaces in the core layer. One implementation of APTEP is in a hardware case and as a virtual platform, referred to as the Automotive Network Security Case (ANSKo). The hardware case contains emulated control units and different communication protocols. The virtual platform uses Docker containers to provide a similar experience over the internet. Both offer two kinds of challenges. The first introduces users to a specific interface, while the second combines multiple interfaces, to a complex and realistic challenge. This concept is based on modern didactic theory, such as constructivism and problem-based learning. Computer Science students from the Ostbayerische Technische Hochschule (OTH)Regensburg experienced the challenges as part of a special topic course and provided positive feedback.}, language = {en} } @misc{MeinikheimMendelProbstetal., author = {Meinikheim, Michael and Mendel, Robert and Probst, Andreas and Scheppach, Markus W. and Nagl, Sandra and Schnoy, Elisabeth and R{\"o}mmele, Christoph and Prinz, Friederike and Schlottmann, Jakob and Messmann, Helmut and Palm, Christoph and Ebigbo, Alanna}, title = {Einfluss von K{\"u}nstlicher Intelligenz auf die Performance von niedergelassenen Gastroenterolog:innen bei der Beurteilung von Barrett-{\"O}sophagus}, series = {Zeitschrift f{\"u}r Gastroenterologie}, volume = {61}, journal = {Zeitschrift f{\"u}r Gastroenterologie}, number = {8}, publisher = {Thieme}, address = {Stuttgart}, doi = {10.1055/s-0043-1771711}, abstract = {Einleitung Die Differenzierung zwischen nicht dysplastischem Barrett-{\"O}sophagus (NDBE) und mit Barrett-{\"O}sophagus assoziierten Neoplasien (BERN) w{\"a}hrend der endoskopischen Inspektion erfordert viel Expertise. Die fr{\"u}he Diagnosestellung ist wichtig f{\"u}r die weitere Prognose des Barrett-Karzinoms. In Deutschland werden Patient:innen mit einem Barrett-{\"O}sophagus (BE) in der Regel im niedergelassenen Sektor {\"u}berwacht. Ziele Ziel ist es, den Einfluss von einem auf K{\"u}nstlicher Intelligenz (KI) basierenden klinischen Entscheidungsunterst{\"u}tzungssystems (CDSS) auf die Performance von niedergelassenen Gastroenterolog:innen (NG) bei der Evaluation von Barrett-{\"O}sophagus (BE) zu untersuchen. Methodik Es erfolgte die prospektive Sammlung von 96 unver{\"a}nderten hochaufl{\"o}senden Videos mit F{\"a}llen von Patient:innen mit histologisch best{\"a}tigtem NDBE und BERN. Alle eingeschlossenen F{\"a}lle enthielten mindestens zwei der folgenden Darstellungsmethoden: HD-Weißlichtendoskopie, Narrow Band Imaging oder Texture and Color Enhancement Imaging. Sechs NG von sechs unterschiedlichen Praxen wurden als Proband:innen eingeschlossen. Es erfolgte eine permutierte Block-Randomisierung der Videof{\"a}lle in entweder Gruppe A oder Gruppe B. Gruppe A implizierte eine Evaluation des Falls durch Proband:innen zun{\"a}chst ohne KI und anschließend mit KI als CDSS. In Gruppe B erfolgte die Evaluation in umgekehrter Reihenfolge. Anschließend erfolgte eine zuf{\"a}llige Wiedergabe der so entstandenen Subgruppen im Rahmen des Tests. Ergebnis In diesem Test konnte ein von uns entwickeltes KI-System (Barrett-Ampel) eine Sensitivit{\"a}t von 92,2\%, eine Spezifit{\"a}t von 68,9\% und eine Accuracy von 81,3\% erreichen. Mit der Hilfe von KI verbesserte sich die Sensitivit{\"a}t der NG von 64,1\% auf 71,2\% (p<0,001) und die Accuracy von 66,3\% auf 70,8\% (p=0,006) signifikant. Eine signifikante Verbesserung dieser Parameter zeigte sich ebenfalls, wenn die Proband:innen die F{\"a}lle zun{\"a}chst ohne KI evaluierten (Gruppe A). Wurde der Fall jedoch als Erstes mit der Hilfe von KI evaluiert (Gruppe B), blieb die Performance nahezu konstant. Schlussfolgerung Es konnte ein performantes KI-System zur Evaluation von BE entwickelt werden. NG verbessern sich bei der Evaluation von BE durch den Einsatz von KI.}, language = {de} } @misc{ScheppachMendelProbstetal., author = {Scheppach, Markus W. and Mendel, Robert and Probst, Andreas and Nagl, Sandra and Meinikheim, Michael and Yip, Hon Chi and Lau, Louis Ho Shing and Chiu, Philip Wai Yan and Palm, Christoph and Messmann, Helmut and Ebigbo, Alanna}, title = {Effekt eines K{\"u}nstliche Intelligenz (KI) - Algorithmus auf die Gef{\"a}ßdetektion bei third space Endoskopien}, series = {Zeitschrift f{\"u}r Gastroenterologie}, volume = {61}, journal = {Zeitschrift f{\"u}r Gastroenterologie}, number = {08}, publisher = {Thieme}, address = {Stuttgart}, doi = {10.1055/s-0043-1771980}, pages = {e528-e529}, abstract = {Einleitung Third space Endoskopieprozeduren wie die endoskopische Submukosadissektion (ESD) und die perorale endoskopische Myotomie (POEM) sind technisch anspruchsvoll und gehen mit untersucherabh{\"a}ngigen Komplikationen wie Blutungen und Perforationen einher. Grund hierf{\"u}r ist die unabsichtliche Durchschneidung von submukosalen Blutgef{\"a}ßen ohne pr{\"a}emptive Koagulation. Ziele Die Forschungsfrage, ob ein KI-Algorithmus die intraprozedurale Gef{\"a}ßerkennung bei ESD und POEM unterst{\"u}tzen und damit Komplikationen wie Blutungen verhindern k{\"o}nnte, erscheint in Anbetracht des erfolgreichen Einsatzes von KI bei der Erkennung von Kolonpolypen interessant. Methoden Auf 5470 Einzelbildern von 59 third space Endoscopievideos wurden submukosale Blutgef{\"a}ße annotiert. Zusammen mit weiteren 179.681 nicht-annotierten Bildern wurde ein DeepLabv3+neuronales Netzwerk mit dem ECMT-Verfahren f{\"u}r semi-supervised learning trainiert, um Blutgef{\"a}ße in Echtzeit erkennen zu k{\"o}nnen. F{\"u}r die Evaluation wurde ein Videotest mit 101 Videoclips aus 15 vom Trainingsdatensatz separaten Prozeduren mit 200 vordefinierten Gef{\"a}ßen erstellt. Die Gef{\"a}ßdetektionsrate, -zeit und -dauer, definiert als der Prozentsatz an Einzelbildern eines Videos bezogen auf den Goldstandard, auf denen ein definiertes Gef{\"a}ß erkannt wurde, wurden erhoben. Acht erfahrene Endoskopiker wurden mithilfe dieses Videotests im Hinblick auf Gef{\"a}ßdetektion getestet, wobei eine H{\"a}lfte der Videos nativ, die andere H{\"a}lfte nach Markierung durch den KI-Algorithmus angesehen wurde. Ergebnisse Der mittlere Dice Score des Algorithmus f{\"u}r Blutgef{\"a}ße war 68\%. Die mittlere Gef{\"a}ßdetektionsrate im Videotest lag bei 94\% (96\% f{\"u}r ESD; 74\% f{\"u}r POEM). Die mediane Gef{\"a}ßdetektionszeit des Algorithmus lag bei 0,32 Sekunden (0,3 Sekunden f{\"u}r ESD; 0,62 Sekunden f{\"u}r POEM). Die mittlere Gef{\"a}ßdetektionsdauer lag bei 59,1\% (60,6\% f{\"u}r ESD; 44,8\% f{\"u}r POEM) des Goldstandards. Alle Endoskopiker hatten mit KI-Unterst{\"u}tzung eine h{\"o}here Gef{\"a}ßdetektionsrate als ohne KI. Die mittlere Gef{\"a}ßdetektionsrate ohne KI lag bei 56,4\%, mit KI bei 71,2\% (p<0.001). Schlussfolgerung KI-Unterst{\"u}tzung war mit einer statistisch signifikant h{\"o}heren Gef{\"a}ßdetektionsrate vergesellschaftet. Die mediane Gef{\"a}ßdetektionszeit von deutlich unter einer Sekunde sowie eine Gef{\"a}ßdetektionsdauer von gr{\"o}ßer 50\% des Goldstandards wurden f{\"u}r den klinischen Einsatz als ausreichend erachtet. In prospektiven Anwendungsstudien sollte der KI-Algorithmus auf klinische Relevanz getestet werden.}, language = {de} } @misc{ScheppachMendelMuzalyovaetal., author = {Scheppach, Markus W. and Mendel, Robert and Muzalyova, Anna and Rauber, David and Probst, Andreas and Nagl, Sandra and R{\"o}mmele, Christoph and Yip, Hon Chi and Lau, Louis Ho Shing and G{\"o}lder, Stefan Karl and Schmidt, Arthur and Kouladouros, Konstantinos and Abdelhafez, Mohamed and Walter, B. and Meinikheim, Michael and Chiu, Philip Wai Yan and Palm, Christoph and Messmann, Helmut and Ebigbo, Alanna}, title = {K{\"u}nstliche Intelligenz erh{\"o}ht die Gef{\"a}ßerkennung von Endoskopikern bei third space Endoskopie}, series = {Zeitschrift f{\"u}r Gastroenterologie}, volume = {62}, journal = {Zeitschrift f{\"u}r Gastroenterologie}, number = {09}, publisher = {Georg Thieme Verlag KG}, doi = {10.1055/s-0044-1790087}, pages = {e830}, abstract = {Einleitung: K{\"u}nstliche Intelligenz (KI)-Algorithmen unterst{\"u}tzen Endoskopiker bei der Erkennung und Charakterisierung von Kolonpolypen in der klinischen Praxis und f{\"u}hren zu einer Erh{\"o}hung der Adenomdetektionsrate. Auch bei therapeutischen Maßnahmen wie der endoskopischen Submukosadissektion (ESD) k{\"o}nne relevante anatomische Strukturen durch KI mit hoher Genauigkeit erkannt und im endoskopischen Bild in Echtzeit markiert werden. Der Effekt einer solchen Applikation auf die Gef{\"a}ßdetektion von Endoskopikern ist bislang nicht erforscht. Ziele: In dieser Studie wurde der Effekt eines KI-Algorithmus zur Echtzeit-Gef{\"a}ßmarkierung bei ESD auf die Gef{\"a}ßdetektionsrate von Endoskopikern untersucht. Methodik: 59 third space Endoskopievideos wurde aus der Datenbank des Universit{\"a}tsklinikums Augsburg extrahiert. Auf 5470 Einzelbildern dieser Untersuchungen wurde submukosale Blutgef{\"a}ße annotiert. Zusammen mit weiteren 179681 unmarkierten Bildern wurde ein DeepLabV3+ neuronales Netzwerk mit einer semi-supervised learning Methode darin trainiert, submukosale Blutgef{\"a}ße auf dem endoskopischen Bild zu erkennen und in Echtzeit einzuzeichnen. Anhand eines Videotests mit 101 Videoclips und 200 vordefinierten Blutgef{\"a}ßen wurden 19 Endoskopiker mit und ohne KI Unterst{\"u}tzung getestet. Ergebnis: Der Algorithmus erkannte in dem Videotest 93.5\% der Gef{\"a}ße in einer Detektionszeit von im Median 0,3 Sekunden. Die Gef{\"a}ßdetektionsrate von Endoskopikern erh{\"o}hte sich durch KI Unterst{\"u}tzung von 56,4\% auf 72,4\% (p<0.001). Die Gef{\"a}ßdetektionszeit reduzierte sich durch KI-Unterst{\"u}tzung von 6,7 auf 5.2 Sekunden (p<0.001). Der Algorithmus zeigte eine Rate an falsch positiven Detektionen in 4.5\% der Einzelbilder. Falsch positiv erkannte Strukturen wurde k{\"u}rzer detektiert, als richtig positive (0.7 und 6.0 Sekunden, p<0.001). Schlussfolgerung: KI Unterst{\"u}tzung f{\"u}hrte zu einer erh{\"o}hten Gef{\"a}ßdetektionsrate und schnelleren Gef{\"a}ßdetektionszeit von Endoskopikern. Ein m{\"o}glicher klinischer Effekt auf die intraprozedurale Komplikationsrate oder Operationszeit k{\"o}nnte in prospektiven Studien ermittelt werden.}, language = {de} } @misc{RoserMeinikheimMendeletal., author = {Roser, David and Meinikheim, Michael and Mendel, Robert and Palm, Christoph and Muzalyova, Anna and Rauber, David and R{\"u}ckert, Tobias and Parsa, Nasim and Byrne, Michael F. and Messmann, Helmut and Ebigbo, Alanna}, title = {Mensch-Maschine-Interaktion: Einfluss k{\"u}nstlicher Intelligenz auf das diagnostische Vertrauen von Endoskopikern bei der Beurteilung des Barrett-{\"O}sophagus}, series = {Zeitschrift f{\"u}r Gastroenterologie}, volume = {62}, journal = {Zeitschrift f{\"u}r Gastroenterologie}, number = {09}, publisher = {Georg Thieme Verlag KG}, doi = {10.1055/s-0044-1789656}, pages = {e575 -- e576}, abstract = {Ziele: Das Ziel der Studie war es, den Einfluss von KI auf die diagnostische Sicherheit (Konfidenzniveau) von Endoskopikern anhand von B{\"O}-Videos zu untersuchen und m{\"o}gliche Korrelationen mit der Untersuchungsqualit{\"a}t zu erforschen. Methodik: 22 Endoskopiker aus zw{\"o}lf Zentren mit unterschiedlicher Barrett-Erfahrung untersuchten 96 standardisierte Endoskopievideos. Die Untersucher wurden in Experten und Nicht-Experten eingeteilt und nach dem Zufallsprinzip f{\"u}r die Bewertung der Videos mit oder ohne KI eingeteilt. Die Teilnehmer wurden in zwei Gruppen aufgeteilt: Arm A bewertete zun{\"a}chst Videos ohne KI und dann mit KI, w{\"a}hrend Arm B die umgekehrte Reihenfolge einhielt. Die Untersucher hatten die Aufgabe, B{\"O}-assoziierte Neoplasien zu erkennen und ihr Konfidenzniveau sowohl mit als auch ohne KI auf einer Skala von 0 bis 9 anzugeben. Ergebnis: In Arm A erh{\"o}hte der Einsatz von KI das Konfidenzniveau bei beiden signifikant (p<0.001). Bemerkenswert ist, dass jedoch nur Nicht-Experten durch die KI eine signifikante Verbesserung der Sensitivit{\"a}t und Spezifit{\"a}t (p<0.001 bzw. p<0.05) erfuhren. W{\"a}hrend Experten ohne KI im Vergleich zu Nicht-Experten mit KI ein h{\"o}heres Konfidenzniveau aufwiesen, gab es keinen signifikanten Unterschied in der Genauigkeit. In Arm B zeigten beide Gruppen eine signifikante Abnahme des Konfidenzniveaus (p<0.001) bei gleichbleibender Genauigkeit. Dar{\"u}ber hinaus wurden in 9\% der Entscheidungen trotz korrekter KI eine falsche Wahl getroffen. Schlussfolgerung: Der Einsatz k{\"u}nstlicher Intelligenz steigerte das Konfidenzniveau sowohl bei Experten als auch bei Nicht-Experten signifikant - ein Effekt, der im Studienmodell reversibel war. Dar{\"u}ber hinaus wiesen Experten mit oder ohne KI durchweg h{\"o}here Konfidenzniveaus auf als Nicht-Experten mit KI, trotz vergleichbarer Ergebnisse. Zudem konnte beobachtet werden, dass die Untersucher in 9\% der F{\"a}lle die KI zuungunsten des Patienten ignorierten.}, language = {de} } @misc{ScheppachNunesArizietal., author = {Scheppach, Markus W. and Nunes, Danilo Weber and Arizi, X. and Rauber, David and Probst, Andreas and Nagl, Sandra and R{\"o}mmele, Christoph and Palm, Christoph and Messmann, Helmut and Ebigbo, Alanna}, title = {Intraoperative Phasenerkennung bei endoskopischer Submukosadissektion mit Hilfe von k{\"u}nstlicher Intelligenz}, series = {Zeitschrift f{\"u}r Gastroenterologie}, volume = {62}, journal = {Zeitschrift f{\"u}r Gastroenterologie}, number = {09}, publisher = {Georg Thieme Verlag KG}, doi = {10.1055/s-0044-1790084}, pages = {e828}, abstract = {Einleitung: K{\"u}nstliche Intelligenz (KI) wird in der Endoskopie des Gastrointestinaltraktes zur Erkennung und Charakterisierung von Kolonpolypen eingesetzt. Die Rolle von KI bei therapeutischen Maßnahmen wurde noch nicht eingehend untersucht. Eine intraprozedurale Phasenerkennung bei endoskopischer Submukoasdissektion (ESD) k{\"o}nnte die Erhebung von Qualit{\"a}tsindikatoren erm{\"o}glichen. Weiterhin k{\"o}nnte diese Technologie zu einem tieferen Verst{\"a}ndnis {\"u}ber die Eigenschaften der Prozedur f{\"u}hren und weiterf{\"u}hrende Applikationen zur automatischen Dokumentation oder standardisiertem Training vorbereiten. Ziele: Ziel dieser Studie war die Entwicklung eines KI Algorithmus zur intraprozeduralen Phasenerkennung bei endoskopischer Submukosadissektion. Methodik: 2071546 Einzelbilder aus 27 ESD Videos in voller L{\"a}nge wurden f{\"u}r die {\"u}bergeordneten Klassen Diagnostik, Markierung, Nadelinjektion, Dissektion und Blutung, sowie die untergeordneten Klassen Endoskop-Manipulation, Injektion und Applikation von elektrischem Strom annotiert. Mit einem Trainingsdatensatz (898440 Einzelbilder, 17 ESDs) wurde ein Video Swin Transformer mit uniformer Stichprobenentnahme trainiert und intern validiert (769523 Einzelbilder, 6 ESDs). Neben der internen Validierung wurde der Algorithmus anhand von einem separaten Testdatensatz (403583 Einzelbilder, 4 ESDs) evaluiert. Ergebnis: Der F1 Score des Algorithmus f{\"u}r alle Klassen lag in der internen Validierung bei 83\%, in dem separaten Test bei 90\%. Anhand des separaten Tests wurden true positive (TP)-Raten f{\"u}r Diagnostik, Markierung, Nadelinjektion, Dissektion und Blutung von 100\%, 100\%, 96\%, 97\% und 93\% ermittelt. F{\"u}r Endoskopmanipulation, Injektion und Applikation von Elektrizit{\"a}t lagen die TP-Raten bei 92\%, 98\% und 91\%. Schlussfolgerung: Der entwickelte Algorithmus klassifizierte ESD Videos in voller L{\"a}nge und anhand jedes einzelnen Bildes mit hoher Genauigkeit. Zuk{\"u}nftige Forschungsvorhaben k{\"o}nnten intraoperative Qualit{\"a}tsindikatioren auf Basis dieser Informationen entwickeln und eine automatisierte Dokumentation erm{\"o}glichen.}, language = {de} } @misc{ZellmerRauberProbstetal., author = {Zellmer, Stephan and Rauber, David and Probst, Andreas and Weber, Tobias and Nagl, Sandra and R{\"o}mmele, Christoph and Schnoy, Elisabeth and Palm, Christoph and Messmann, Helmut and Ebigbo, Alanna}, title = {Verwendung k{\"u}nstlicher Intelligenz bei der Detektion der Papilla duodeni major}, series = {Zeitschrift f{\"u}r Gastroenterologie}, volume = {61}, journal = {Zeitschrift f{\"u}r Gastroenterologie}, number = {08}, publisher = {Thieme}, address = {Stuttgart}, doi = {10.1055/s-0043-1772000}, pages = {e539 -- e540}, abstract = {Einleitung Die Endoskopische Retrograde Cholangiopankreatikographie (ERCP) ist der Goldstandard in der Diagnostik und Therapie von Erkrankungen des pankreatobili{\"a}ren Trakts. Jedoch ist sie technisch sehr anspruchsvoll und weist eine vergleichsweise hohe Komplikationsrate auf. Ziele In der vorliegenden Machbarkeitsstudie soll gepr{\"u}ft werden, ob mithilfe eines Deep-learning-Algorithmus die Papille und das Ostium zuverl{\"a}ssig detektiert werden k{\"o}nnen und somit f{\"u}r Endoskopiker mit geringer Erfahrung ein geeignetes Hilfsmittel, insbesondere f{\"u}r die Ausbildungssituation, darstellen k{\"o}nnten. Methodik Wir betrachteten insgesamt 606 Bilddatens{\"a}tze von 65 Patienten. In diesen wurde sowohl die Papilla duodeni major als auch das Ostium segmentiert. Anschließend wurde eine neuronales Netz mittels eines Deep-learning-Algorithmus trainiert. Außerdem erfolgte eine 5-fache Kreuzvaldierung. Ergebnisse Bei einer 5-fachen Kreuzvaldierung auf den 606 gelabelten Daten konnte f{\"u}r die Klasse Papille eine F1-Wert von 0,7908, eine Sensitivit{\"a}t von 0,7943 und eine Spezifit{\"a}t von 0,9785 erreicht werden, f{\"u}r die Klasse Ostium eine F1-Wert von 0,5538, eine Sensitivit{\"a}t von 0,5094 und eine Spezifit{\"a}t von 0,9970 (vgl. [Tab. 1]). Unabh{\"a}ngig von der Klasse zeigte sich gemittelt (Klasse Papille und Klasse Ostium) ein F1-Wert von 0,6673, eine Sensitivit{\"a}t von 0,6519 und eine Spezifit{\"a}t von 0,9877 (vgl. [Tab. 2]). Schlussfolgerung In vorliegende Machbarkeitsstudie konnte das neuronale Netz die Papilla duodeni major mit einer hohen Sensitivit{\"a}t und sehr hohen Spezifit{\"a}t identifizieren. Bei der Detektion des Ostiums war die Sensitivit{\"a}t deutlich geringer. Zuk{\"u}nftig soll das das neuronale Netz mit mehr Daten trainiert werden. Außerdem ist geplant, den Algorithmus auch auf Videos anzuwenden. Somit k{\"o}nnte langfristig ein geeignetes Hilfsmittel f{\"u}r die ERCP etabliert werden.}, language = {de} } @techreport{Schultz, author = {Schultz, Maximilian}, title = {1.Bericht f{\"u}r das Regensburg Center of Health Sciences and Technology (RCHST)}, volume = {2024}, publisher = {OTH Regensburg}, address = {Regensburg}, doi = {10.35096/othr/pub-7312}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-73125}, pages = {17}, abstract = {Der vorliegende Bericht zeigt den aktuellen Stand des Projekts „K{\"u}nstliche Intelligenz f{\"u}r Nichtregierungsorganisationen (KINiro) - Bedarf, Akzeptanz und Umsetzungsm{\"o}glichkeiten" an der OTH Regensburg am Institut f{\"u}r Sozialforschung und Technikfolgenabsch{\"a}tzung (IST). Im Projektbericht wird das Projekt KINiro mit besonderem Blick auf die Erkenntnisse und T{\"a}tigkeiten im Gesundheitswesen aufgezeigt. Das Projekt KINiro wird mit Laufzeit Januar 2023 bis Dezember 2025 durch das Bundesministerium f{\"u}r Familie, Senioren, Frauen und Jugend (BMFSFJ) gef{\"o}rdert. Eine zus{\"a}tzliche Unterst{\"u}tzung bietet das Regensburg Center of Health Sciences and Technology (RCHST)}, language = {de} } @article{RueckertRauberMaerkletal., author = {Rueckert, Tobias and Rauber, David and Maerkl, Raphaela and Klausmann, Leonard and Yildiran, Suemeyye R. and Gutbrod, Max and Nunes, Danilo Weber and Moreno, Alvaro Fernandez and Luengo, Imanol and Stoyanov, Danail and Toussaint, Nicolas and Cho, Enki and Kim, Hyeon Bae and Choo, Oh Sung and Kim, Ka Young and Kim, Seong Tae and Arantes, Gon{\c{c}}alo and Song, Kehan and Zhu, Jianjun and Xiong, Junchen and Lin, Tingyi and Kikuchi, Shunsuke and Matsuzaki, Hiroki and Kouno, Atsushi and Manesco, Jo{\~a}o Renato Ribeiro and Papa, Jo{\~a}o Paulo and Choi, Tae-Min and Jeong, Tae Kyeong and Park, Juyoun and Alabi, Oluwatosin and Wei, Meng and Vercauteren, Tom and Wu, Runzhi and Xu, Mengya and Wang, An and Bai, Long and Ren, Hongliang and Yamlahi, Amine and Hennighausen, Jakob and Maier-Hein, Lena and Kondo, Satoshi and Kasai, Satoshi and Hirasawa, Kousuke and Yang, Shu and Wang, Yihui and Chen, Hao and Rodr{\´i}guez, Santiago and Aparicio, Nicol{\´a}s and Manrique, Leonardo and Palm, Christoph and Wilhelm, Dirk and Feussner, Hubertus and Rueckert, Daniel and Speidel, Stefanie and Nasirihaghighi, Sahar and Al Khalil, Yasmina and Li, Yiping and Arbel{\´a}ez, Pablo and Ayobi, Nicol{\´a}s and Hosie, Olivia and Lyons, Juan Camilo}, title = {Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge}, series = {Medical Image Analysis}, volume = {109}, journal = {Medical Image Analysis}, publisher = {Elsevier}, issn = {1361-8415}, doi = {10.1016/j.media.2026.103945}, pages = {31}, abstract = {Reliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minimally invasive surgery (RAMIS), including surgical training, skill assessment, and autonomous assistance. However, robust performance under real-world conditions remains a significant challenge. Incorporating surgical context - such as the current procedural phase - has emerged as a promising strategy to improve robustness and interpretability. To address these challenges, we organized the Surgical Procedure Phase, Keypoint, and Instrument Recognition (PhaKIR) sub-challenge as part of the Endoscopic Vision (EndoVis) challenge at MICCAI 2024. We introduced a novel, multi-center dataset comprising thirteen full-length laparoscopic cholecystectomy videos collected from three distinct medical institutions, with unified annotations for three interrelated tasks: surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation. Unlike existing datasets, ours enables joint investigation of instrument localization and procedural context within the same data while supporting the integration of temporal information across entire procedures. We report results and findings in accordance with the BIAS guidelines for biomedical image analysis challenges. The PhaKIR sub-challenge advances the field by providing a unique benchmark for developing temporally aware, context-driven methods in RAMIS and offers a high-quality resource to support future research in surgical scene understanding.}, language = {en} } @inproceedings{SchwaegerlUhrigWestfechtel, author = {Schw{\"a}gerl, Felix and Uhrig, Sabrina and Westfechtel, Bernhard}, title = {A Graph-based Algorithm for Three-way Merging of Ordered Collections in EMF Models}, series = {Science of Computer Programming}, volume = {113}, booktitle = {Science of Computer Programming}, number = {Part 1}, doi = {10.1016/j.scico.2015.02.008}, pages = {51 -- 81}, abstract = {In EMF models, ordered collections appear as the values of multi-valued structural features. Traditional, text-based version control systems do not sufficiently support three-way merging of ordered collections inside EMF models since they cannot guarantee a consistent result. The operation three-way merging is defined as follows: based on a common base version b, two alternative versions and were developed by copying and modifying the base version. To reconcile these changes, a merged version m is to be created as a common successor of and . In this paper, we present a graph algorithm to solve the problem of three-way merging of ordered collections in EMF models. Each version of a collection can be represented by means of a linearly ordered graph. To create the merged version, these graphs are combined to a merged collection graph using set formula. To create the merged collection, a generalized topological sort is performed on the merged collection graph. Conflicts occur in case the order of elements cannot be deduced automatically; these conflicts are resolved either interactively or by default rules. We have implemented the merge algorithm in our tool BTMerge, which performs a consistency-preserving three-way merge of versions of EMF models being instances of arbitrary Ecore models. Our implementation relies on an alternative form of representing multiple versions of a collection, namely a versioned collection graph which forms a superimposition of collection versions. The algorithm presented here is purely state-based. Matching and merging of collections are clearly separated sub-problems. Insertions and deletions performed on the elements of the collection are propagated into the merged version in a consistent way. Our algorithm makes only minimal assumptions with regard to the underlying product model and thus may be applied to ordered collections inside plain text or XML files. By taking arbitrary move operations into account, the algorithm considerably goes beyond the functionality of contemporary merge tools which cannot adequately handle move operations.}, language = {en} } @inproceedings{BuchmannSchwaegerl, author = {Buchmann, Thomas and Schw{\"a}gerl, Felix}, title = {Breaking the Boundaries of Meta Models and Preventing Information Loss in Model-Driven Software Product Lines}, series = {Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering, Vol 1, 2016, Rome, Italy}, booktitle = {Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering, Vol 1, 2016, Rome, Italy}, publisher = {SCITEPRESS - Science and and Technology Publications}, doi = {10.5220/0005789100730083}, pages = {83}, abstract = {Model-driven software product line engineering is an integrating discipline for which tool support has become available recently. However, existing tools are still immature and have several weaknesses. Among others, limitations in variability, caused by meta model restrictions, and unintended information loss are not addressed. In this paper, we present two conceptual extensions to model-driven product line engineering based on negative variability, being alternative mappings and surrogates. Alternative mappings allow for unconstrained variability, mitigating meta model restrictions by virtually extending the underlying multi-variant domain model. Surrogates prevent unintended information loss during product derivation based on a contextsensitive product analysis, which can be controlled by a declarative OCL-based language. Both extensions have been implemented in FAMILE, a model-driven product line tool that is based on EMF, provides dedicated consistency repair mechanisms, and completely automates application engineering. The added value of alternative mappings and surrogates is demonstrated by a running example.}, language = {en} } @inproceedings{SchwaegerlUhrigWestfechtel, author = {Schw{\"a}gerl, Felix and Uhrig, Sabrina and Westfechtel, Bernhard}, title = {Model-based tool support for consistent three-way merging of EMF models}, series = {ACME '13, Proceedings of the workshop on ACadeMics Tooling with Eclipse}, booktitle = {ACME '13, Proceedings of the workshop on ACadeMics Tooling with Eclipse}, publisher = {ACM}, address = {New York, NY, USA}, doi = {10.1145/2491279.2491281}, abstract = {Inadequate version control has been identified as a major obstacle to the application of model-driven software engineering. In particular, sophisticated support for merging model versions is urgently needed. We present a tool for merging of EMF models which may be applied to instances of arbitrary Ecore models. The tool advances the state of the art by guaranteeing a consistent merge result. Furthermore, it detects and resolves not only context-free, but also context-sensitive conflicts. Our merge tool is model-based; it relies on EMF for its implementation. Initial experiences gained from its application confirm that the merge tool operates both accurately and efficiently.}, language = {en} } @techreport{SchwarzBockWeiss, author = {Schwarz, Philipp and Bock, Sebastian and Weiß, Martin}, title = {Abschlussbericht Projekt LeaP - Learning Poses : Posenerkennung mit Neuronalen Netzen}, address = {Regensburg}, doi = {10.35096/othr/pub-8851}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-88514}, pages = {45}, abstract = {Die Sch{\"a}tzung der 6D-Pose bekannter Objekte findet Anwendungen in der Robotik, der Luft- und Raumfahrtsteuerung und automatisierten Produktionsumgebungen. Es ist nach wie vor g{\"a}ngige Praxis, klassische Bildverarbeitungsmethoden zu verwenden, um eine hohe Pr{\"a}zision zu erreichen. Diese Methoden erfordern jedoch eine manuelle Parametrisierung der verwendeten Erkennungswerkzeuge f{\"u}r jedes einzelne Objekt. Dies wirft die Frage auf, ob maschinelle Lerntechniken, insb. convolutional neural networks, Netzwerke, so trainiert werden k{\"o}nnen, dass sie die in der Industrie geforderte Pr{\"a}zision ohne individuelle Programmierung erreichen k{\"o}nnen. Dar{\"u}ber sollen in Produktionsumgebungen Umwelteinfl{\"u}sse wie Lichtverh{\"a}ltnisse minimiert werden. Es werden verschiedene Netzstrukturen entwickelt und auf ihre Leistung bei diesem Szenario untersucht, mit 1 bis 6 Freiheitsgraden in der Aufgabenstellung und einer oder mehreren Kameras. Zus{\"a}tzlich wird ein Ansatz mit reinforcement learning entwickelt und untersucht.}, language = {de} } @misc{CurrleHaugWeber, author = {Currle, Edda and Haug, Sonja and Weber, Karsten}, title = {K{\"u}nstliche Intelligenz und Anamnese (KI-Anamnese) — Fragebogen der Trendstudie zur Akzeptanz von KI in der Anamnese in Arztpraxen in Deutschland mit Codeplan}, address = {Regensburg}, doi = {10.35096/othr/pub-8707}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-87079}, pages = {5}, abstract = {Die Studie st{\"u}tzt sich auf eine Quotenstichprobe der deutschsprachigen Bev{\"o}lkerung im Alter von 18 bis 74 Jahren. Sie wurde als L{\"a}ngsschnittstudie (Trendstudie) mit insgesamt zwei Wellen mit dem gleichen Fragebogen durchgef{\"u}hrt. Welle 1 war vom 18. bis 24. November 2024 im Feld, die zweite Befragungswelle vom 13. bis 17. November 2025. Mit der Datenerhebung wurde das Umfrageinstitut NielsenIQ-GfK beauftragt. Je 1.000 Personen wurden online im Rahmen des GfK eBUS®-Deutschland befragt. Die Teilnehmenden wurden mithilfe einer Kombination aus Online- und Offline-Methoden rekrutiert. Um eine m{\"o}glichst genaue Abbildung der Grundgesamtheit zu gew{\"a}hrleisten, wurden die Merkmale Geschlecht, Alter, Region, Haushaltsgr{\"o}ße, Ortsgr{\"o}ße sowie der Bildungsstand des Haushaltsvorstands quotiert, etwaige Abweichungen durch ein iteratives Gewichtungsverfahren ausgeglichen. Der Fragebogen besteht aus neun standardisierten Fragen; zuz{\"u}glich wurden soziodemographische Merkmale erhoben. Einzelne Fragen wurden, zum Teil {\"u}bersetzt sowie abgewandelt, aus anderen Studien {\"u}bernommen.}, language = {de} } @misc{RueckertRauberKlausmannetal., author = {Rueckert, Tobias and Rauber, David and Klausmann, Leonard and Gutbrod, Max and Rueckert, Daniel and Feussner, Hubertus and Wilhelm, Dirk and Palm, Christoph}, title = {PhaKIR Dataset - Surgical Procedure Phase, Keypoint, and Instrument Recognition [Data set]}, doi = {10.5281/zenodo.15740620}, abstract = {Note: A script for extracting the individual frames from the video files while preserving the challenge-compliant directory structure and frame-to-mask naming conventions is available on GitHub and can be accessed here: https://github.com/remic-othr/PhaKIR_Dataset. The dataset is described in the following publications: Rueckert, Tobias et al.: Comparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge. arXiv preprint, https://arxiv.org/abs/2507.16559. 2025. Rueckert, Tobias et al.: Video Dataset for Surgical Phase, Keypoint, and Instrument Recognition in Laparoscopic Surgery (PhaKIR). arXiv preprint, https://arxiv.org/abs/2511.06549. 2025. The proposed dataset was used as the training dataset in the PhaKIR challenge (https://phakir.re-mic.de/) as part of EndoVis-2024 at MICCAI 2024 and consists of eight real-world videos of human cholecystectomies ranging from 23 to 60 minutes in duration. The procedures were performed by experienced physicians, and the videos were recorded in three hospitals. In addition to existing datasets, our annotations provide pixel-wise instance segmentation masks of surgical instruments for a total of 19 categories, coordinates of relevant instrument keypoints (instrument tip(s), shaft-tip transition, shaft), both at an interval of one frame per second, and specifications regarding the intervention phases for a total of eight different phase categories for each individual frame in one dataset and thus comprehensively cover instrument localization and the context of the operation. Furthermore, the provision of the complete video sequences offers the opportunity to include the temporal information regarding the respective tasks and thus further optimize the resulting methods and outcomes.}, language = {en} } @misc{HaugCurrleWeber, author = {Haug, Sonja and Currle, Edda and Weber, Karsten}, title = {K{\"u}nstliche Intelligenz und Anamnese (KI-Anamnese) - Datens{\"a}tze Welle 1 und Welle 2 [Data set]}, doi = {10.5281/zenodo.18017447}, abstract = {Die Studie st{\"u}tzt sich auf eine Quotenstichprobe der deutschsprachigen Bev{\"o}lkerung im Alter von 18 bis 74 Jahren. Sie wurde als L{\"a}ngsschnittstudie (Trendstudie) mit insgesamt zwei Wellen mit dem gleichen Fragebogen durchgef{\"u}hrt. Welle 1 war vom 18. bis 24. November 2024 im Feld, die zweite Befragungswelle vom 13. bis 17. November 2025. Mit der Datenerhebung wurde das Umfrageinstitut NielsenIQ-GfK beauftragt. Je 1.000 Personen wurden online im Rahmen des GfK eBUS®-Deutschland befragt. Die Teilnehmenden wurden mithilfe einer Kombination aus Online- und Offline-Methoden rekrutiert. Um eine m{\"o}glichst genaue Abbildung der Grundgesamtheit zu gew{\"a}hrleisten, wurden die Merkmale Geschlecht, Alter, Region, Haushaltsgr{\"o}ße, Ortsgr{\"o}ße sowie der Bildungsstand des Haushaltsvorstands quotiert, etwaige Abweichungen durch ein iteratives Gewichtungsverfahren ausgeglichen. Der Fragebogen besteht aus neun standardisierten Fragen; zuz{\"u}glich wurden soziodemographische Merkmale erhoben. Einzelne Fragen wurden, zum Teil {\"u}bersetzt sowie abgewandelt, aus anderen Studien {\"u}bernommen.}, language = {de} } @misc{HauerSchultzHaugetal., author = {Hauer, Franziska and Schultz, Maximilian and Haug, Sonja and Weber, Karsten}, title = {K{\"u}nstliche Intelligenz in Nichtregierungsorganisationen - quantitativer Datensatz [Data set]}, doi = {10.5281/zenodo.17977270}, abstract = {K{\"u}nstliche Intelligenz (KI) stellt ein wichtiges Thema der Digitalisierung dar und hat das Potenzial viele Arbeitsfelder grundlegend zu ver{\"a}ndern. Mit dem Einsatz von KI wird die Hoffnung verbunden durch Automatisierung Zeit und Geld zu sparen. Dies k{\"o}nnte besonders interessant f{\"u}r Organisationen sein, die wenig Ressourcen zur Verf{\"u}gung haben, da sie nicht gewinnorientiert oder ehrenamtlich arbeiten. Dazu z{\"a}hlen Nichtregierungsorganisationen (NRO), die einen wichtigen Bestandteil der Zivilgesellschaft darstellen. Aufgrund der komplexer werdenden Arbeit von NROs scheint KI M{\"o}glichkeiten zur Bew{\"a}ltigung aktueller und zuk{\"u}nftiger Herausforderungen zu bieten. {\"U}ber den Einsatz von KI in NROs ist derzeit jedoch wenig bekannt. Es wurde eine quantitative Querschnittstudie deutscher Nichtregierungsorganisationen (NRO) zum Thema KI durchgef{\"u}hrt. Der Web-Survey baut auf den Erkenntnissen des Scoping Reviews und der qualitativen Interviews auf und vertieft den Einblick in die Bereiche aktuelle Nutzung von KI, Wissenstand in den Organisationen sowie vorhandene und noch ben{\"o}tigte Ressourcen. Daf{\"u}r wurden 343 NROs verschiedener Gr{\"o}ßen und Handlungsfelder befragt und die Ergebnisse quantitativ analysiert.}, language = {de} } @misc{GutbrodRauberWeberNunesetal., author = {Gutbrod, Max and Rauber, David and Weber Nunes, Danilo and Palm, Christoph}, title = {A cleaned subset of the first five CATARACTS test videos [Data set]}, doi = {10.5281/zenodo.14924735}, abstract = {This dataset is a subset of the original CATARACTS test dataset and is used by the OpenMIBOOD framework to evaluate a specific out-of-distribution setting. When using this dataset, it is mandatory to cite the corresponding publication (OpenMIBOOD (10.1109/CVPR52734.2025.02410)) and follow the acknowledgement and citation requirements of the original dataset (CATARACTS). The original CATARACTS dataset (associated publication,Homepage) consists of 50 videos of cataract surgeries, split into 25 train and 25 test videos. This subset contains the frames of the first 5 test videos. Further, black frames at the beginning of each video were removed.}, language = {en} } @article{Weber, author = {Weber, Karsten}, title = {Public images of artificial intelligence: an overview}, series = {media-culture-social communication}, journal = {media-culture-social communication}, number = {21}, publisher = {Wydawnictwo Uniwersytetu Warmińsko-Mazurskiego w Olsztynie}, address = {Olsztyn}, doi = {10.31648/mcsc.10343}, pages = {9 -- 24}, abstract = {Artificial intelligence (AI) is not only a ubiquitous topic in scholarly debates but in recent years has also received increased media and political attention. Discussions, initially strongly influenced by autonomous vehicles but currently dominated by expectations concerning generative AI such as ChatGPT, have contributed to public awareness. There are debate cycles, often characterized by a significant decline in public attention after a certain period of time, and the issue to a large extent or completely disappears from mass media's agenda; also, they are often specific to certain countries. In this paper, a cursory cross-country overview concerning studies on media representations and the public perception of AI is provided. The use of AI in healthcare will be particularly highlighted, as there are currently high expectations regarding the benefits of AI, but other areas of application will also be considered. It will be tentatively concluded that in many countries, public perception of and public attitudes toward AI often is based on superficial knowledge and even prejudices.}, language = {en} }