Sliding sampling and successive variational mode decomposition CNN-BiLSTM-attention based fault detection and early warning method for DC microgrid. [PDF]
Dai Y, Wang M, Zhang L, Wang S, Jiang Z.
europepmc +1 more source
On‐Chip Photonic Neural Network Architectures
This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source
Zero sequence currents in AC lines caused by transients in adjacent DC lines
openaire +1 more source
Cascading Spin‐Orbitronic Terahertz Emission in Ferromagnet/Nonmagnet Bilayers
While the initial generation mechanism of picosecond orbital currents remains elusive, we reveal a cascading spin–orbital transport mechanism that induces optically driven terahertz emission in ferromagnet/nonmagnet heterostructures. Using a ferromagnet with strong spin–orbit coupling, we identify a thickness‐driven transition from spin‐dominated to ...
Younghun Kim +7 more
wiley +1 more source
Smart technique for calculating fault current model parameters using short circuit current measurements. [PDF]
Mahmoud RA, Malik OP, Fayek WM.
europepmc +1 more source
Micromachined Double‐Membrane Mechanically Tunable Metamaterial for Thermal Infrared Filtering
Herein, a mechanically tunable double‐layer plasmonic metamaterial leveraging the extraordinary optical transmission effect observed in subwavelength arrays of openings within thin metal layers is presented. The concept is experimentally validated by integrating the proposed metamaterial structure into an electrostatic parallel‐plate actuator to create
Oleg Bannik +7 more
wiley +1 more source
Sequential monitoring and control of a silicon photonic coherent beam adder and analyzer. [PDF]
De Gaetano S +6 more
europepmc +1 more source
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source
Research on an islanding detection method suitable for distributed generation grid-connection complex system. [PDF]
Sun W, Yu S, Jiang Z.
europepmc +1 more source
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
wiley +1 more source

