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Mobile Edge Computing (MEC) has emerged as a promising computing paradigm to support emerging high-performance applications by deploying resources at the network edge. However, most existing MEC
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-urban accessibility to health and socioeconomic outcomes. It will: Challenge the fixed-threshold paradigm by introducing the concept of the “N-minute city,” where N is a time variable that differs across
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Medical imaging is central to the diagnosis and management of lung and abdominal diseases, including lung cancer, pneumonia, liver disease, and gastrointestinal disorders. In real clinical workflows
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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Project Description The next generation of signal processing, computing and artificial intelligence (AI) technologies will be unlocked by the close integration of electronics and photonics
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pathway to overcome the limitations of polymer-based membranes, offering superior thermal and chemical stability, enhanced mechanical robustness, and the potential for operation across wider temperature and
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algorithms that combine Reinforcement Learning techniques like Partially Observable Markov Decision Processes (POMDPs) with cognitive inference modules capable of modelling human beliefs, intentions, and goals
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of light. [1][2] This emerging technology holds enormous potential, offering routes towards new forms of highly parallelised information processing (optical computing), point-of-care diagnostics, next