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: Optimization of Innovative Air Mobility Networks Operating Supervisor: Prof. Dr.-Ing Hartmut Fricke, Chair of Air Transport Technology and Logistics and co-supervised by at least one additional
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are being developed that provide AI-supported tools to identify suitable sources and optimize utilization decisions throughout the product life cycle. Various machine learning approaches are to be used
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finalization of the foundations of dual-tracer imaging using a GATE-based Monte Carlo simulation Implementation of the developed algorithms within our modular, C++-based and cluster optimized PET image
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