OPUS - Publikationenserver der Technischen Hochschule Nürnberg Georg Simon Ohm
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SSegRef2Surf — Near Real-Time Photogrammetric Flood Monitoring and Refinement of Classified Water Surfaces
No full textEffective response to flood events requires high-resolution, frequently updated data on flooded areas for comprehensive flood risk assessments. Unmanned aerial vehicles (UAVs) equipped with conventional camera systems and classification based on orthophotos from photogrammetric postprocessing and artificial intelligence are widely used to detect flooded areas. However, these methods often involve time-intensive pre- and postprocessing steps and fail to incorporate geometric factors such as elevation data and water depths. This study introduces SSegRef2Surf, a novel tool that integrates classified flood raster data with terrain information. SSegRef2Surf refines and optimizes coarse raster classifications by filling shadowed areas and correcting misclassified regions. This tool reduces data requirements for AI training and minimizes postprocessing time, enabling near real-time flood monitoring. All processes necessary for SSegRef2Surf were optimized through sensitivity and accuracy analyses to reduce postprocessing duration to a minimum. A comparison of the SSegRef2Surf results with two-dimensional (2D) numerical model results for a flood event revealed discrepancies in the 2D model, caused by inaccuracies in the underlying terrain data. This comparison showed that 30% of the flooded areas identified in the 2D numerical results were incorrect, while missing areas (11%) were added. This highlights the significant potential of SSegRef2Surf for near real-time flood monitoring and traceability of flood events, as combining UAVs’ high-frequency surveying capabilities with SSegRef2Surf allows for more effective validation and optimization of 2D models
Mini-grid performance in Sub-Saharan Africa: case studies from Tsumkwe and Gam, Namibia
No full textThis paper investigates the performance analysis and operational challenges of mini-grids in Sub-Saharan Africa, focusing on the Tsumkwe and Gam mini-grids, the only officially recognized mini-grids in Namibia. The study addresses a critical gap in understanding mini-grid efficiency, technical difficulties, and future potential. The key research questions focus on assessing mini-grid performance, identifying technical and operational challenges, quantifying the relationship between electricity demand and supply, and providing recommendations for enhancing rural electrification through mini-grids. These insights are crucial for evaluating the effectiveness of mini-grids in the African context and understanding their role in advancing rural electrification. By using a mixed-method approach, the research combines quantitative and qualitative data to offer a comprehensive analysis of these two mini-grid systems of Namibia. The data collected from 2017 to 2022 include metrics on energy supply, consumption, photovoltaic generation, community load, and meteorological conditions. Qualitative insights were gathered through field visits, surveys, and interviews with mini-grid operators, allowing for a thorough examination of community perspectives, operational issues, and technical performance. The findings reveal that the Tsumkwe mini-grid has seen a decline in efficiency due to maintenance problems and battery overheating, while the Gam mini-grid, initially oversized, now struggles with increased demand and new connections. This study provides the first detailed technical insights, identifies consumer archetypes, and evaluates the energy dynamics of mini-grids in Namibia. Recommendations include improved maintenance protocols, advanced battery management, and enhanced data monitoring. By analyzing Tsumkwe and Gam, this paper offers valuable lessons for mini-grid development in Sub-Saharan Africa, stressing the need for continuous evaluation and strategic improvements to achieve sustainable rural electrification
Ausbildung im Bereich der empirischen Sozialforschung im Studium der Sozialen Arbeit. Ein Scoping Review
No full textGame Audio: Error UI Sound
No full textUser Interface Sound, welcher im Rahmen meiner Bachelorarbeit "Design and Evaluation of User Interface Sounds in Computergames" im SoSe 2025 entstanden ist
From Hybrid to AI-First Innovation Management
No full textThe rise of generative Artificial Intelligence (AI) in traditionally human domains of creativity signifies a profound development in product innovation management. In this article, we investigate the evolving role of innovation managers, emphasizing a transition from problem-solving to sense-making and decision-making. Additionally, we delve into organizational strategies for effective AI integration, advocating for systematic experimentation, comprehensive training, and the development of AI-first innovation frameworks for new product development (NPD). Ultimately, we propose a paradigm shift to AI-first creative processes, where AI is not merely an extension but the foundational mechanism of the innovation workflow
Entwicklung und Gestaltung von Sound Drones für Computerspiele
No full textIm Rahmen einer Bachelorarbeit wurde in der Unreal-Engine mit dem relativen neuen Metasounds-Modul ein modularer Synthesizer nachgebildet, der zum einen eine sogenannte Sound-Drone für das Computerspiel erzeugt, und zum anderen eine interaktive Musik umsetzt, welche positionsabhängig die gespielte Notenskala (Dur, Moll, doppelt Harmonische Skala) des Stückes anpasst
Lichttechnik: Licht und Beleuchtung III
No full textDie verschiedenen Arten von Lichtquellen werden aufgezeigt. Dabei spielt ebenso die Lichtsteuerung eine wichtige Nebenrolle, auf die kurz eingegangen wird (DMX512, ArtNet, etc.). Zudem wird auf die Lichtführung eingegangen. Darunter fallen Themen wie Lichtrichtungen, Lichteinfall und Schattenwirkung wie auch die Ausleuchtung von Personen oder die Drei- und Vierpunktausleuchtung. Zudem wird auf das Lichtdesign für Film-, Theater-, Bühnen- und TV-Umgebungen eingegangen