Results 161 to 170 of about 264,463 (296)
This paper is part of the conference proceedings from the 22nd International Symposium on Air Breathing ...
Domingos, David Carlos +2 more
core
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
Increased Work of Breathing due to Tracheomalacia in Neonates. [PDF]
Gunatilaka CC +8 more
europepmc +1 more source
This paper is part of the conference proceedings from the 22nd International Symposium on Air Breathing ...
Bae, Jinhyun +3 more
core
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang +3 more
wiley +1 more source
Effect of Swept Stator on Fan Tone Noise of Turbofan Engine
This paper is part of the conference proceedings from the 22nd International Symposium on Air Breathing ...
Hano, Hiroki +3 more
core
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
Imposed work of breathing of 16 neonatal CPAP-devices using different mechanisms of CPAP generation. [PDF]
Sterzik H +9 more
europepmc +1 more source
This paper is part of the conference proceedings from the 22nd International Symposium on Air Breathing ...
Martelli, Francesco +2 more
core
Predicting Performance of Hall Effect Ion Source Using Machine Learning
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source

