Self‐Sensing Artificial‐Muscle‐Empowered Humanlike Perception, Interaction, and Positioning
The proposed self‐sensorized artificial muscle (SSAM) can sense its length change as small as 0.01 mm via a seamlessly integrated multi‐segment induction coil. The SSAM provides accurate length information regardless of its loadings, driving pressure, or muscle design, adequate for robust data‐driven feedback control.
Houping Wu +6 more
wiley +1 more source
Epidemiological and Clinical Profile of Patients With Non-traumatic Subarachnoid Hemorrhage in a Brazilian Referral Hospital. [PDF]
Ballestero M +3 more
europepmc +1 more source
OFDM for optical wireless systems under severe clipping conditions
Ali Waqar Azim +2 more
openalex +2 more sources
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai +3 more
wiley +1 more source
Effects of intraoperative hypercapnia on postoperative brain functional network connectivity and cognitive function in adult patients undergoing Clipping Intracranial Aneurysm. [PDF]
Jiao F, Li G, Bian W.
europepmc +1 more source
[Newspaper clipping: Bailey named president of Texas Stonewall]
David Webb
openalex +1 more source
A note on clipping experiments to estimate fish production in culture operations [PDF]
K Alagaraja, M Vijaya Gupta
openalex
Memory‐Reduced Convolutional Neural Network for Fast Phase Hologram Generation
This article reports a lightweight convolutional neural network framework using INT8 quantization to efficiently generate 3D computer‐generated holograms from a single 2D image. The quantized model reduces memory usage and computational cost, accelerates inference speed, and maintains high output quality, enabling real‐time holographic display on low ...
Chenliang Chang +6 more
wiley +1 more source
[Clipping: Homosexuality still questioned by the military]
Philip Shenon
openalex +1 more source
This work presents a deep learning model to autonomously recognize and classify the secretion retention into three levels for patients receiving invasive mechanical ventilation, achieving 89.08% accuracy. This model can be implemented to ventilators by edge computing, whose feasibility is approved.
Shuai Wang +6 more
wiley +1 more source

