Publikationsserver der Ostbayerischen Technischen Hochschule Regensburg
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Bildverarbeitung für die Medizin 2026 : Proceedings, German Conference on Medical Image Computing, Lübeck March 15–17, 2026
No full textDie Konferenz "BVM – Bildverarbeitung für die Medizin" ist seit vielen Jahren als die nationale Plattform für den Austausch von Ideen und die Diskussion der neuesten Forschungsergebnisse im Bereich der Medizinischen Bildverarbeitung und der Künstlichen Intelligenz (KI) etabliert. Auch 2026 haben (junge) Wissenschaftler*innen, Industrie und Anwender*innen diesen Austausch vertieft. Die Beiträge dieses Bandes – die meisten davon in englischer Sprache – umfassen alle Bereiche der medizinischen Bildverarbeitung, insbesondere die Bildgebung und -akquisition, Segmentierung und Analyse, Registrierung, Visualisierung und Animation, computerunterstützte Diagnose sowie bildgestützte Therapieplanung und Therapie. Hierbei kommen Methoden des maschinellen Lernens, der biomechanischen Modellierung sowie der Validierung und Qualitätssicherung zum Einsatz
Oops!... I did it again. Conclusion (In-)Stability in Quantitative Empirical Software Engineering: A Large-Scale Analysis
No full textContext: Mining software repositories is a popular means to gain insights into a software project's evolution, monitor project health, support decisions and derive best practices. Tools supporting the mining process are commonly applied by researchers and practitioners, but their limitations and agreement are often not well understood.
Objective: This study investigates some threats to validity in complex tool pipelines for evolutionary software analyses and evaluates the tools' agreement in terms of data, study outcomes and conclusions for the same research questions.
Method: We conduct a lightweight literature review to select three studies on collaboration and coordination, software maintenance and software quality from high-ranked venues, which we formally replicate with four independent, systematically selected mining tools to quantitatively and qualitatively compare the extracted data, analysis results and conclusions.
Results: We find that numerous technical details in tool design and implementation accumulate along the complex mining pipelines and can cause substantial differences in the extracted baseline data, its derivatives, subsequent results of statistical analyses and, under specific circumstances, conclusions.
Conclusions: Users must carefully choose tools and evaluate their limitations to assess the scope of validity in an adequate way. Reusing tools is recommended. Researchers and tool authors can promote reusability and help reducing uncertainties by reproduction packages and comparative studies following our approach
Hybrid Mixed Integer Linear Programming for Large-Scale Join Order Optimisation
No full textFinding optimal join orders is among the most crucial steps to be performed by query optimisers. Though extensively studied in data management research, the problem remains far from solved: While query optimisers rely on exhaustive search methods to determine ideal solutions for small problems, such methods reach their limits once queries grow in size. Yet, large queries become increasingly common in real-world scenarios, and require suitable methods to generate efficient execution plans. While a variety of heuristics have been proposed for large-scale query optimisation, they suffer from degrading solution quality as queries grow in size, or feature highly sub-optimal worst-case behavior, as we will show.
We propose a novel method based on the paradigm of mixed integer linear programming (MILP): By deriving a novel MILP model capable of optimising arbitrary bushy tree structures, we address the limitations of existing MILP methods for join ordering, and can rely on highly optimised MILP solvers to derive efficient tree structures that elude competing methods. To ensure optimisation efficiency, we embed our MILP method into a hybrid framework, which applies MILP solvers precisely where they provide the greatest advantage over competitors, while relying on more efficient methods for less complex optimisation steps. Thereby, our approach gracefully scales to extremely large query sizes joining up to 100 relations, and consistently achieves the most robust plan quality among a large variety of competing join ordering methods
Development of a continuous fiber-reinforced 3D printing process with a 6-axis robot arm: Process design and equipment
No full textThe utilisation of 3D printing processes in the fabrication of continuous fiber-reinforced composites confers a multitude of advantages, in particular flexible design based on structural requirements. In order to achieve greater flexibility, there is a necessity for 3D printing systems that allow for customisable material selection and fiber positioning. This paper presents the design of a robot-based 3D printing system that incorporates an in-situ impregnation line and flexibility regarding the machine code generation for fiber positioning. The development of the system enabled the attainment of an average fiber volume content of up to 37.12%. In the tensile tests, material characteristics up to E1 = 24.7 GPa and strength of up to RM1 = 0.51 GPa were determined
Stephan Rixen / Eva Maria Welskop-Deffaa (Hrsg.): Klimasozialpolitik. Der Klimaschutz-Beschluss des Bundesverfassungsgerichts und seine Folgen
No full textErich Schützendorf, Jürgen Datum: Anderland entdecken, erleben, begreifen. Ein Reise-führer in die Welt von Menschen mit Demenz.
No full textGerd Grampp: Lernort Wohnung. Befähigung als Assistenzleistung in der Eingliederungshilfe.
No full textModel order reduction for unbounded second-order vibroacoustic systems using infinite elements and Dirichlet-to-Neumann map
No full textThis work addresses the efficient numerical simulation of time-harmonic vibroacoustic problems in unbounded domains, with a focus on fluid-structure interaction. The underlying mathematical model is a second-order dynamical system arising from the coupling of structural and acoustic domains, incorporating material damping effects, relevant in structural acoustics and noise control applications. A central novelty of the proposed method is its unified computational framework that supports two distinct strategies for treating unbounded fluid domains: (1) non-local absorbing boundary conditions based on Dirichlet-to-Neumann map, and (2) infinite elements, which extend the computational domain rather than truncate it. Both approaches are integrated into a consistent formulation that enables flexible and accurate modeling of exterior wave propagation. To efficiently evaluate frequency-domain transfer functions, the method employs model order reduction using the Padé-via-Lanczos technique. While this algorithm typically targets first-order systems, the present approach uses a Schur complement strategy to reduce the second-order system in a way that maintains computational efficiency and storage requirements comparable to first-order formulations. Importantly, the framework seamlessly embeds both interior structural damping and the additional dissipation introduced by the acoustic-domain truncation into the model-order reduction process. The exterior acoustic field is represented via spherical harmonic expansions, with expansion coefficients computed from the reduced system. Numerical results demonstrate the method’s accuracy, efficiency, and scalability, making it well-suited for high-fidelity vibroacoustic analysis in unbounded domains
Bayerische Regionalkonferenz an der OTH Regensburg
No full textKann ein flexibilisierter Einsatz der Stromverbraucher zur Netzentlastung in kritischen Zeitpunkten beitragen und wie ist der aktuell häufig genannte Begriff des „zellulären Ansatzes“ in diesem Zusammenhang zu verstehen? Am 21. September 2018 waren zahlreiche Partner des Projektes C/sells sowie Vertreterinnen und Vertreter von Umweltschutzorganisationen und aus der Politik an der OTH Regensburg zu Gast, um diesen Fragen nachzugehen und mit Experten zu diskutieren
LiwTERM-r: a Revised Lightweight Transformer-based Model for Multimodal Skin Lesion Detection Robust to Incomplete Input
No full textAs the most common type of cancer in the world, skin cancer accounts for approximately 30% of all diagnosed tumor-based lesions. Early diagnosis can reduce mortality and prevent disfiguring in different skin regions. With the application of machine learning techniques in recent years, especially deep learning, promising results in this task could be achieved, presenting studies demonstrating that the combination of patients’ clinical anamneses and images of the injured lesion is essential for improving the correct classification of skin lesions. Despite that, meaningful use of anamneses with multiple collected images of the same skin lesion is mandatory, requiring further investigation. Thus, this project aims to contribute to developing multimodal machine learning-based models to solve the skin lesion classification problem by employing a lightweight transformer model that is robust to missing clinical information input. As a main hypothesis, models can be fed by multiple images from different sources as input along with clinical anamneses from the patient’s historical evaluations, leading to a more factual and trustworthy diagnosis. Our model deals with the not-trivial task of combining images and clinical information concerning the skin lesions in a lightweight transformer architecture that does not demand high computation resources or even all the information from the anamneses but still presents competitive classification results