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Tianlei Fu, Lianwu Guan, Yanbin Gao and Chao Qin
This paper investigates an anticipatory activation anti-windup approach based on Linear Active Disturbance Rejection Control (LADRC) to address the influences of accelerated saturation on the actuators in a Miniaturized Inertial Stabilized Platform (MISP...
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Danilo Pau, Andrea Pisani and Antonio Candelieri
In the context of TinyML, many research efforts have been devoted to designing forward topologies to support On-Device Learning. Reaching this target would bring numerous advantages, including reductions in latency and computational complexity, stronger ...
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Fátima Trindade Neves, Manuela Aparicio and Miguel de Castro Neto
In the rapidly evolving landscape of urban development, where smart cities increasingly rely on artificial intelligence (AI) solutions to address complex challenges, using AI to accurately predict real estate prices becomes a multifaceted and crucial tas...
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Fan Lin, Dengjie Chen, Cheng Liu and Jincheng He
This study pioneered a non-destructive testing approach to evaluating the physicochemical properties of golden passion fruit by developing a platform to analyze the fruit?s electrical characteristics. By using dielectric properties, the method accurately...
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Andrea D?Ambrosio and Roberto Furfaro
This paper demonstrates the utilization of Pontryagin Neural Networks (PoNNs) to acquire control strategies for achieving fuel-optimal trajectories. PoNNs, a subtype of Physics-Informed Neural Networks (PINNs), are tailored for solving optimal control pr...
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