Results 181 to 190 of about 224,256 (277)
Short-term load forecasting using a metaheuristic optimized temporal fusion transformer with decomposition technique. [PDF]
Chandrasekaran R, Paramasivan SK.
europepmc +1 more source
This paper explores the forecasting performances of several non-linear models, namely GARCH, EGARCH, APARCH used with three distributions, namely the Gaussian normal, the Student-t and Generalized Error Distribution (GED).
Guidi, Francesco
core
Solid‐state nanopores are used to interrogate dendrimer‐peptide conjugates with systematically varied peptide loading. Single‐particle ionic current signatures reveal how ligand density modulates deformability, transport pathways, and electromechanical coupling during translocation.
Chaoming Gu +7 more
wiley +1 more source
Xenes for Sustainable Energy: A Roadmap From First‐Principles Design to Practical Deployment
Emerging 2D Xenes are advancing from theoretical predictions toward practical energy‐storage and conversion technologies through the integration of first‐principles modelling, experimental synthesis, electrochemical validation, and AI‐assisted materials design, enabling accelerated discovery of high‐performance and sustainable electrochemical systems ...
Onur Karaman, Ceren Karaman
wiley +1 more source
Accuracy of heart rate measurement using AirPods Pro 3 during graded treadmill exercise: A laboratory-based validation study. [PDF]
Doherty C +6 more
europepmc +1 more source
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu +8 more
wiley +1 more source
An optimization-driven hierarchical deep learning approach using the Gray Langurs algorithm for data-driven seismic activity prediction. [PDF]
Shabrawy M +3 more
europepmc +1 more source
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding +5 more
wiley +1 more source
Fully automated artificial intelligence-based echocardiographic analysis substantially reduces workflow time while preserving measurement accuracy: a pilot study. [PDF]
Sun J +8 more
europepmc +1 more source
ABSTRACT Real‐time insight into local chemistry is critical for reliable part quality in additive manufacturing, especially laser powder bed fusion (PBF‑LB/M), where rapid thermal cycles and localized evaporation can undermine part performance. Optical emission spectroscopy (OES) offers non‑intrusive, in situ plume monitoring, but detection geometry ...
Philipp Gabriel +4 more
wiley +1 more source

