Artificial Intelligence-Based Decision Support System for UAV Control in a Simulated Environment. [PDF]
Sujecki P, Frąszczak D.
europepmc +1 more source
Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network
We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang +16 more
wiley +1 more source
Safe and adaptive control of non-stationary stochastic systems via Lyapunov-constrained distributional reinforcement learning. [PDF]
Khaniki MAL, Mirzaee M, Moradi E.
europepmc +1 more source
Pre‐Curved Everting Robots With Embedded Steering Intelligence Fabricated by CO2 Laser Welding
Design and experimental demonstration of a laser welded growing robot for anatomically guided navigation. The robot follows an aortic arch phantom entering the branchiocephalic branch through steering by design. The figure shows the physical phantom setup, CAD defined weld geometry and full robot eversion.
Brandon Saldarriaga +5 more
wiley +1 more source
Deep Learning-Based Intelligent Resource Management for Renewable Energy Engineering Projects. [PDF]
Yao Y.
europepmc +1 more source
Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 more
wiley +1 more source
Object-centric diffusion policies for real-world robotic-arm imitation learning. [PDF]
Kasu PR, Um D.
europepmc +1 more source
An agentic AI‐driven decision‐support framework for prosumers is proposed, integrating PV generation, load profiling, and multihorizon optimization within a four‐agent architecture. The approach significantly reduces grid dependence, enhances self‐sufficiency and prevents system oversizing.
Adela BÂRA, Simona‐Vasilica OPREA
wiley +1 more source
A vibration control method for chatter mitigation in milling process based on sliding mode control and reinforcement learning. [PDF]
Paul S.
europepmc +1 more source
Neuro‐evolution can boost machine‐learning optimization of chiral metasurfaces. By integrating the NEAT algorithm into a deep‐learning framework, we enable the efficient design of visible‐spectrum chiroptical responses. NEAT autonomously evolves neural‐network architectures and weights, reducing manual tuning.
Davide Filippozzi, Arash Rahimi‐Iman
wiley +1 more source

