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interconnected computing nodes, actuators and sensors, communicating over networks, to achieve complex functionalities, at both slow and fast timeframes, and at different safety criticalities. Future connectivity
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differences in biodiversity over space and changes through time, and the relevance of these to conservation planning and management. Students will tackle specific questions regarding the distribution and
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development of protocols for commercial deployment (supported by Detectronic ). There will be significant opportunities for personal development including a residential programme at Ashorne Hill to further
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. To fill in this gap, in collaboration with industrial partners, the research will develop novel Machine Learning and Computer Vision methods for detecting and localising. These will be used to develop
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will enable the advanced monitoring and computing techniques of power systems, as well as to create a resilient control and operation for both energy network and distributed energy sources. This PhD
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complexity, classical control techniques cannot be easily applied because of computational bottlenecks or an absence of suitable prediction models. Distributed control approaches have been conceived to handle
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-homogeneously distributed on every heat transfer surface along with different surface defects. These features have a strong impact on boiling conditions but are mostly overlooked in available CFD models. Ideal
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spectrometry to compare submicron particulate emissions from the different reactors using different fuels and operating regimes. This will consider the particle size spectra, particle measurement programme