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Digital Twin Networks (DTNs) are emerging as a key enabler for the robust optimization and lifecycle management of next-generation networks. However, current DTN approaches still rely heavily on manual design, implementa...

This paper proposes an innovative model-free deep reinforcement learning-based controller (RL-C) for a grid-connected 5-level packed-U-cell (PUC5) multilevel inverter (MLI). The controller is designed to deliver a high-q...

Dairy farms increasingly deploy sensor networks that generate high-frequency behavioral and spatial data, yet translating these multimodal streams into actionable welfare insights remains a key challenge. This study pres...

Efficient UAV path planning in large and dynamic environments requires adaptive strategies that account for varying regional importance. Traditional coverage or Reinforcement Learning-based methods often suffer from redu...

Autonomous microrobotic navigation in life sciences is highly challenging due to environmental disturbances, unpredictable phenomena, diverse obstacles, and dynamic changes. These significantly limit motion of microrobot...

The transport industry has recently shown significant interest in unmanned surface vehicles (USVs), specifically for port and inland waterway transport. These systems can improve operational efficiency and safety, which ...