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archaeologists to understand AI results – Generalization and transferability analyses, considering domain adaptation and transfer learning strategies to ensure model robustness across different geographic regions
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processes for operational carbon reduction (mitigation) and simulate microclimate interventions to reduce heatwave vulnerability (adaptation). Where to apply Website https://phd.fbk.eu/calls/detail/urban
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. The goal of this PhD Thesis is to bridge these dimensions, moving beyond rigid profiles to develop adaptive, context-sensitive persona models. By integrating deep profile characteristics with real-time
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edge devices in distributed and collaborative IoT scenarios; ii) strategies for efficient and adaptive learning on-device or across a network of heterogeneous nodes while minimizing energy consumption
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storms, and simple data extrapolation breaks down exactly when it matters most. Approaches based on AI, developed for precipitation nowcasting, have strong potential for adaptation, e.g., to ionospheric