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Institutional influences on healthcare service innovation: Lessons from German rehabilitation clinics
No full textPrIcosa: High-Precision 3D Camera Calibration with Non-Overlapping Field of Views
Get PDFMulti-camera systems are being used more and more frequently, from autonomous mobile robots to intelligent visual servoing cells. Determining the pose of the cameras to each other very accurately is essential for many applications. However, choosing the most suitable calibration object geometry and utilizing it as effectively as possible still remains challenging. Disadvantageous geometries provide only subpar datasets, increasing the need for a larger dataset and decreasing the accuracy of the calibration results. Moreover, an unrefined calibration method can lead to worse accuracies even with a good dataset. Here, we introduce a probabilistic method to increase the accuracy of 3D camera calibration. Furthermore, we analyze the effects of the calibration object geometry on the data properties and the resulting calibration accuracy for the geometries cube and icosahedron. The source code for this project is available at GitHub (Nova, 2024)
Automatized End Mill Wear Inspection Using a Novel Illumination Unit and Convolutional Neural Network
Get PDFEnsuring cutting tools are in optimal condition is essential for achieving peak machining performance, given their direct impact on both workpiece quality and process efficiency. However, accurately assessing wear on end mills, especially those with complex geometries, pose a significant challenge due to their reflective surfaces and varied wear patterns. Presented here is a novel method that addresses this challenge by employing a customized illumination unit in conjunction with a convolutional neural network (CNN) for end mill wear analysis. This innovative approach involves utilizing the specially designed illumination unit to capture high-quality images, enabling precise examination of material wear on helically shaped end mills. Notably, this method is tailored to illuminate reflective surfaces and represents a pioneering application in the realm of wear testing.We validate the viability of this approach by employing CNN-based models to segment wear on complex-shaped end mills coated with titanium carbonitride (TiCN) and titanium nitride (TiN). We achieved remarkable mean Intersection over Union (mIoU) results in wear detection on a test dataset: 0.99 for tool segmentation, 0.78 for abnormal wear, and 0.71 for normal wear segmentation
The tension of usable safety, security and privacy
Get PDFLocal disasters such as the Ahr Valley flood in Germany, the international backdrop of the Russo-Ukrainian War, or the global impact of the COVID-19 pandemic place high demands on the people and organisations that are involved in these situations and contexts to save lives, mitigate damage, provide comfort, or organise reconstruction. Novel technologies are constantly making their way into everyday life, such as artificial intelligence, big data, decentralised networks, internet of things, or virtual reality. Their adaptation, acceptance, usability, usefulness, and legal framework conditions for safety-critical systems must be researched and tested thoroughly. In this special issue, we investigate the use of computer-based solutions in areas and situations of direct relevance to people’s lives and well-being (Usable Safety), as well as contributions to user-oriented resilience concepts of sociotechnical systems concerning potential attacks (Usable Security) and data protection mechanisms (Usable Privacy)
Holistic evaluation and optimization of multilevel inverter designs for electric vehicle applications
Get PDFTo advance the development of multilevel inverters (MLIs) for electric vehicle applications, this study introduces novel asymmetric MLI (AMLI) configurations featuring buffer modules to enhance efficiency. A comprehensive comparative analysis of 125 distinct inverter systems is conducted, integrating five different microtopologies and 25 representative symmetrical MLI (SMLI) and AMLI systems. Unlike previous studies, this work employs a successive design process with a graph-based approach to systematically minimize conduction losses. Furthermore, experimental loss measurements ensure practical relevance. By applying Pareto optimization with cost, energy losses, and total harmonic distortion as objective functions, the study identifies the most promising MLI systems among all considered ones. While the cascaded H-bridge MLI emerges as the most cost-effective solution, specific SMLI configurations with 12 or 18 battery cells per module and AMLI designs featuring buffer modules exhibit lower inverter losses. In both cases, the incorporation of microtopologies that enable parallel operation leads to a remarkable reduction in inverter losses by more than 30 % compared to the least efficient MLI systems. Finally, a comparative assessment against a conventional B6-bridge SiC inverter highlights the significant advantages of these optimized MLI configurations in terms of efficiency and system performance
Applying Extended Object Tracking for Self-Localization of Roadside Radar Sensors
Get PDFIntelligent Transportation Systems (ITS) can benefit from roadside 4D mmWave radar sensors for large-scale traffic monitoring due to their weatherproof functionality, long sensing range and low manufacturing cost. However, the localization method using external measurement devices has limitations in urban environments. Furthermore, if the sensor mount exhibits changes due to environmental influences, they cannot be corrected when the measurement is performed only during the installation. In this paper, we propose self-localization of roadside radar data using Extended Object Tracking (EOT). The method analyses both the tracked trajectories of the vehicles observed by the sensor and the aerial laser scan of city streets, assigns labels of driving behaviors such as "straight ahead", "left turn", "right turn" to trajectory sections and road segments, and performs Semantic Iterative Closest Points (SICP) algorithm to register the point cloud. The method exploits the result from a down stream task -- object tracking -- for localization. We demonstrate high accuracy in the sub-meter range along with very low orientation error. The method also shows good data efficiency. The evaluation is done in both simulation and real-world tests
Towards AI-enabled Cyber Threat Assessment in the Health Sector
Get PDFCyber attacks on the healthcare industry can have tremendous consequences and the attack surface expands continuously. In order to handle the steadily rising workload, an expanding amount of analog processes in healthcare institutions is digitized. Despite regulations becoming stricter, not all existing infrastructure is sufficiently protected against cyber attacks. With an increasing number of devices and digital processes, the system and network landscape becomes more complex and harder to manage and therefore also more difficult to protect. The aim of this project is to introduce an AI-enabled platform that collects security relevant information from the outside of a health organization, analyzes it, delivers a risk score and supports decision makers in healthcare institutions to optimize investment choices for security measures. Therefore, an architecture of such a platform is designed, relevant information sources are identified, and AI methods for relevant data collection, selection, and risk scoring are explored
Adaptive Filter Bank Based on Independent Component Analysis for Harmonic, Inter-Harmonic and Sub-Harmonic Extraction
No full text3D‐Printing with Steel: Additive Manufacturing of a Bridge in situ
Get PDFAdditive manufacturing (AM) plays an increasing role in the production of complex structures in steel construction. Robot‐guided Gas Shielded Metal Arc Welding (GMAW), known as Wire and Arc Additive Manufacturing (WAAM), is suitable for this purpose. At TU Darmstadt, a small pedestrian bridge in shell form was designed. It was completely additively manufactured on site with a welding robot over a creek. This paper presents selected aspects of this project. The focus is particularly on the preliminary strength investigations carried out and the process sequences required for homogenous manufacturing. The paper concludes with a consideration of the implementation on site
