Publikationsserver der Ostbayerischen Technischen Hochschule Regensburg
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Investigation of Influencing Factors on the Measurement Signal of a CMOS Image Sensor for Measuring Field Emission Currents
No full textPhotodissociation-Driven Photoacoustic Spectroscopy with UV-LEDs for Ozone Detection
No full textThis study presents the development and evaluation of a UV-LED based photoacoustic (PA) measurement system for ozone (O3) detection to demonstrate its potential for low-cost and accurate sensing while for the first time addressing the importance of photodissociation for PA signal generation for O3 in the UV range. With a detection limit of 7.9 ppbV, the system exhibits a significant advancement over state-of-the-art UV-PA O3 detection and is on par with laser-based setups. Following a novel discussion of the PA signal arising from photodissociation and its products, cross-sensitivity effects due to environmental factors such as temperature and gas composition were systematically analyzed. A digital twin driven compensation for these influences was implemented and evaluated. Despite the challenges associated with modeling the effects of H2O and CO2, the PA system shows considerable potential, though further studies in real world applications must be conducted
OpenMIBOOD: Open Medical Imaging Benchmarks for Out-Of-Distribution Detection
No full textThe 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, near-OOD, 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 OOD detection 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 this https URL
A Transformer-Based Framework for Anomaly Detection in Multivariate Time Series
No full textThis paper introduces a comprehensive Transformer-based architecture for anomaly detection in multivariate time series. Using self-attention, the framework efficiently processes high-dimensional sensor data without extensive feature engineering, enabling early detection of unusual patterns to prevent critical system failures. In a subsequent laboratory setup, the framework will be applied using fuzzing techniques to induce anomalies in an Electronic Control Unit, while monitoring side channels, such as temperature, voltage, and Controller Area Network messages. The overall structure of the architecture, as well as the necessary preprocessing steps, such as temporal aggregation and classification
up to the optimization of the hyperparameters of the model, are presented. The evaluation of the model architecture with the postulated restrictions shows that the model handles anomaly scenarios in the dataset robustly. It is necessary to evaluate the extent to which the model can be used in practical applications in areas, such as cloud environments or the industrial Internet of Things. Overall, the results highlight the potential of Transformer models for the automated and reliable monitoring of complex time series data for deviations
Does the Tool Matter? Exploring Some Causes of Threats to Validity in Mining Software Repositories
No full textSoftware repositories are an essential source of information for software engineering research on topics such as project evolution and developer collaboration. Appropriate mining tools and analysis pipelines are therefore an indispensable precondition for many research activities. Ideally, valid results should not depend on technical details of data collection and processing. It is, however, widely acknowledged that mining pipelines are complex, with a multitude of implementation decisions made by tool authors based on their interests and assumptions. This raises the questions if (and to what extent) tools agree on their results and are interchangeable. In this study, we use two tools to extract and analyse ten large software projects, quantitatively and qualitatively comparing results and derived data to better understand this concern. We analyse discrepancies from a technical point of view, and adjust code and parametrisation to minimise replication differences. Our results indicate that despite similar trends, even simple metrics such as the numbers of commits and developers may differ by up to 500%. We find that such substantial differences are often caused by minor technical details. We show how tool-level and data post-processing changes can overcome these issues, but find they may require considerable efforts. We summarise identified causes in our lessons learned to help researchers and practitioners avoid common pitfalls, and reflect on implementation decisions and their influence in ensuring obtained data meets explicit and implicit expectations. Our findings lead us to hypothesise that similar uncertainties exist in other analysis tools, which may limit the validity of conclusions drawn in tool-centric research
Was macht die Kunst mit der Welt?
No full textDer Beitrag bestimmt die Kunst als eine spezifische, feierliche Praxis des Kommunizierens mit der Welt, nicht über die Welt. Dies wird zunächst anhand ihrer Präsenz bei Festen und Feiern, dann auch anhand ihrer autonomen öffentlichen und privaten Vollzugsformen aufgezeigt. Solche Kommunikation mit der Welt hat existenzielle Bedeutung für Menschen und lässt sich daher mit der etablierten Vorstellung einer spielerischen Zweckfreiheit des Ästhetischen nicht erfassen. Kunst ist vielmehr eine Praxis existenziellen ästhetischen Sorgens um das menschliche Dasein in der Welt. In dieser Eigenschaft trifft sie sich mit den ebenfalls von einem existenziellen Sorgen um dieses Dasein motivierten Nachhaltigkeitszielen der Vereinten Nationen, in deren Rahmen sie durch ihren spezifischen Weltbezug eine bildungsbedeutsame Funktion entfalten kann. Die folgenden Ausführungen fassen die in meiner Monographie Ästhetisches Sorgen (Zürner, C. (2020). Ästhetisches Sorgen. Eine Theorie der Kunst. Bielefeld: transcript.) dargelegte Kunsttheorie zusammen und perspektivieren sie im Hinblick auf das Thema dieses Sammelbandes
UCSM: Dataset of U-Shaped Parametric CAD Geometries and Real-World Sheet Metal Meshes for Deep Drawing
No full textThe development of machine learning (ML) applications in deep drawing is hindered by limited data availability and the absence of open-access benchmarks for validating novel approaches, including domain generalization over distinct geometries. This paper addresses these challenges by introducing a comprehensive U-shaped dataset tailored to this manufacturing process. Our U-Channel sheet metal (UCSM) dataset combines 90 real-world meshes with an infinite number of synthetic geometry samples generated from four parametric Computer-Aided Design (CAD) models, ensuring extensive geometry variety and data quantity. Additionally, a ready-to-use dataset for drawability assessment and segmentation is provided. Leveraging CAD and mesh data sources bridges the gap between sparse data availability and ML requirements. Our analysis demonstrates that the proposed parametric models are geometrically valid, and real-world and synthetic data complement each other effectively, providing robust support for ML model development. While the dataset is confined to U-shaped, thin-walled, deep drawing scenarios, it considerably aids in overcoming data scarcity. Thereby, it facilitates the validation and comparison of new geometry-generalizing ML methodologies in this domain. By providing this benchmark dataset, we enhance the comparability and validation of emerging methods for ML advancements in sheet metal forming
Die Nachhaltigkeitsziele der UN im Spiegel der Wissenschaft : Beispiele aus der Sozial- und Gesundheitsforschung
No full textDas Tableau der Nachhaltigkeitsziele der Vereinten Nationen fordert alle gesellschaftlichen Akteure heraus. Soll die globale Transformation in eine ressourcenorientierte Weltzivilisation gelingen, muss auch die Wissenschaft einen Beitrag für eine nachhaltige Entwicklung leisten. Der vorliegende Band konzentriert sich dabei auf die Perspektive der Sozial- und der Gesundheitswissenschaften. Er zeigt an vielen Beispielen, wie durch innovative Forschung die Probleme einzelner Nachhaltigkeitsziele analysiert, die Zielerreichung unterstützt und Zielkonflikte bearbeitet werden können
Exoskelettale Unterstützung in der Pflege - eine Untersuchung der Muskelaktivität, des Hüftflexionswinkels und des subjektiven Belastungsempfinden bei einem simulierten Transfer.
No full textDie dargestellten Ergebnisse weisen darauf hin, dass das in der Studie verwendete passive rückenunterstützende Exoskelett die (wahrgenommene) körperliche Belastung beim dynamischen Transfer eines 45 kg schweren Dummys potenziell reduzieren kann und sich der maximale Hüftgelenksflexionswinkel mit Exo verkleinert. Dieses Ergebnis deckt sich mit bereits publizierten Studienergebnissen von Arbeitsaufgaben im Bereich des Hebens und Tragens von Gegenständen aus der Logisti