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Design of a dynamic and self adapting system, supported with artificial intelligence, machine learning and real time intelligence for predictive cyber risk analytics in extreme environments, cyber risk in the colonisation of Mars
This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real time intelligence in edge computing.
An Application of Network Lasso Optimization For Ride Sharing Prediction
Ride sharing has important implications in terms of environmental, social and individual goals by reducing carbon footprints, fostering social interactions and economizing commuter costs.
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