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Lorenz Dingeldein
While the growth of unmanned aerial vehicle (UAV) usage over the next few years is indisputable, cooperative operation strategies for UAV swarms have gained great interest in the research community. Mission capabilities increase while contingencies can b...
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Adele H. Marshall and Aleksandar Novakovic
As the world moves into the exciting age of Healthcare 4.0, it is essential that patients and clinicians have confidence and reassurance that the real-time clinical decision support systems being used throughout their care guarantee robustness and optima...
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Yufeng Huang, Jun Tao, Gang Sun, Hao Zhang and Yan Hu
In this study, a prognostics and health management (PHM) framework is proposed for aero-engines, which combines a dynamic probability (DP) model and a long short-term memory neural network (LSTM). A DP model based on Gaussian mixture model-adaptive densi...
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Mihaela Mitici and Ingeborg de Pater
Remaining-useful-life prognostics for aircraft components are central for efficient and robust aircraft maintenance. In this paper, we propose an end-to-end approach to obtain online, model-based remaining-useful-life prognostics by learning from cluster...
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Austin D. Lewis and Katrina M. Groth
Dynamic Bayesian networks (DBNs) represent complex time-dependent causal relationships through the use of conditional probabilities and directed acyclic graph models. DBNs enable the forward and backward inference of system states, diagnosing current sys...
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Andrea Nesci, Andrea De Martin, Giovanni Jacazio and Massimo Sorli
Recent trend in the aeronautic industry is to introduce a novel prognostic solution for critical systems in the attempt to increase vehicle availability, reduce costs, and optimize the maintenance policy. Despite this, there is a general lack of literatu...
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