Results 211 to 220 of about 6,813,126 (333)

Q-Learning-Based Pending Zone Adjustment for Proximity Classification. [PDF]

Sensors (Basel), 2023
Kwon JH, Lee SB, Kim EJ.
europepmc   +1 more source

Bandit Approach to Conflict-Free Parallel Q-Learning in View of Photonic Implementation

, 2023
Hiroaki Shinkawa, Nicolas Chauvet, André Röhm, Takatomo Mihana, Ryoichi Horisaki, Guillaume Bachelier, Makoto Naruse   +6 more
openalex   +1 more source

Low Resistance Interphase Formation at the PEO‐LiTFSI|LGPS Interface in Lithium Solid‐State Batteries

Advanced Materials Interfaces, EarlyView.
Interfacial charge transfer and low‐resistance interphase formation between PEO‐based polymer and Li10GeP2S12 solid electrolytes are investigated using multi‐electrode impedance spectroscopy and advanced analytical techniques such as XPS and ToF‐SIMS.
Ujjawal Sigar, Timo Weintraut, Sebastian L. Benz, Semih Engün, Sascha Kremer, Anja Henss, Felix H. Richter   +6 more
wiley   +1 more source

Enhancing secure IoT data sharing through dynamic Q-learning and blockchain at the edge. [PDF]

Sci Rep
Bayat M, Jamali MAJ, Abbasi M, Anari B, Akbarpour S.   +4 more
europepmc   +1 more source

Multiagent Q-Learning-Based Mobility Management for Multi-Connectivity in mmWAVE Cellular Systems. [PDF]

Sensors (Basel), 2023
Ryu SA, Kim DK.
europepmc   +1 more source

QXplore: Q-Learning Exploration by Maximizing Temporal Difference Error [PDF]

, 2019
Riley Simmons-Edler, Ben Eisner, Daniel Yang, Anthony Bisulco, Eric Mitchell, Sebastian Seung, Daniel C. Lee   +6 more
openalex  

Roll‐to‐Roll Manufacturing of Flexible Thermoelectric Semiconductors Using Low‐Level Direct‐Current Sputtering

Advanced Materials Technologies, EarlyView.
Roll‐to‐roll direct‐current sputtering enables room‐temperature manufacture of flexible bismuth telluride thermoelectric films. By identifying a low‐power deposition window that suppresses charge‐induced arcing, this work links sputtering conditions to film structure, charge transport, and thermoelectric performance, achieving a room‐temperature figure
Xudong Tao, John O'Sullivan, Kening Wan, Emiliano Bilotti, Ruy Sebastian Bonilla, Hazel E. Assender   +5 more
wiley   +1 more source

Dynamic Robot Navigation in Confined Indoor Environment: Unleashing the Perceptron-Q Learning Fusion. [PDF]

Sensors (Basel)
Denesh Babu M, Maheswari C, Priya BM.
europepmc   +1 more source

Memorability-based multimedia analytics for robotic interestingness prediction system using trimmed Q-learning algorithm. [PDF]

Sci Rep, 2023
Ali H, Gilani SO, Waris A, Shah UH, Khattak MAK, Khan MJ, Afzal N.   +6 more
europepmc   +1 more source

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

Advanced Materials Technologies, EarlyView.
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, Danny E. P. Vanpoucke, Yunus T. Aksoy, Tobias Corthouts, Maria R. Vetrano, Wim Deferme   +5 more
wiley   +1 more source