DEEP REINFORCEMENT LEARNING BASED ONLINE LIFTING PATH PLANNING FOR TOWER CRANES IN UNKNOWN DYNAMIC ENVIRONMENTS

Deep reinforcement learning based online lifting path planning for tower cranes in unknown dynamic environments

Lifting path planning is critical for the safety and efficiency of tower cranes operating in dynamic construction environments.This paper proposes a lifting path planner to efficiently generate safe and smooth lifting paths for tower cranes in an unknown construction environment through a deep reinforcement learning (DRL) method.Based on the Twin-D

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An infant with unexplained multiple rib fractures occurring during treatment in a neonatal intensive care unit

It is generally believed that trauma from child abuse or bone fragility from diseases such DRESSES as osteogenesis imperfecta accounts for most cases of multiple rib fractures.We report an infant with unexplained fractures from the right 3rd rib through to the 8th rib who had undergone resection of a large cervical tumor and had been admitted to a

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Formulating evidence-based design guidelines for therapeutic gardens tailored to elderly populations: a synthesis of reminiscence and preference studies

Gardens emerge as powerful catalysts for enhancing the well-being of the older generation.The design of a garden plays a significant role in engagement with such an environment.The investigation aimed to determine features integral to the garden for older adults to be applied as design guidelines for therapeutic gardens serving the elderly.A mixed

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