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this data. Clustering travel needs. To define different mobility needs and motivations based on the travel data, we apply different clustering algorithms (e.g., traditional k-means, density-based clustering
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learning algorithms, and design of optical communication networks or power consumption and energy saving. The synergies of MATCH consortium act together to enable the thirteen DCs to become the next
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normalization and integration of data from different sources, defining appropriate strategies to deal with all ethical and privacy/security requirements; Contribute to the development, validation and integration
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spanning design, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication