Results 121 to 130 of about 365 (210)

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
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

Advising and limiting medical treatment during phone consultation: a prospective multicentre study in HEMS settings. [PDF]

Scand J Trauma Resusc Emerg Med, 2022
Kangasniemi H, Setälä P, Huhtala H, Olkinuora A, Kämäräinen A, Virkkunen I, Tirkkonen J, Yli-Hankala A, Jämsen E, Hoppu S.   +9 more
europepmc   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Frequent users of the ambulance service in a Swedish region: a retrospective cohort study. [PDF]

Scand J Trauma Resusc Emerg Med
Alm F, Kurland L, Hugelius K.
europepmc   +1 more source

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
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, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source

On the use of Earth Observation to support estimates of national greenhouse gas emissions and sinks for the Global stocktake process: lessons learned from ESA-CCI RECCAP2. [PDF]

Carbon Balance Manag, 2022
Bastos A, Ciais P, Sitch S, Aragão LEOC, Chevallier F, Fawcett D, Rosan TM, Saunois M, Günther D, Perugini L, Robert C, Deng Z, Pongratz J, Ganzenmüller R, Fuchs R, Winkler K, Zaehle S, Albergel C.   +17 more
europepmc   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
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, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

Ambulance traffic accidents and their impact on prehospital personnel: a mixed-methods study. [PDF]

Scand J Trauma Resusc Emerg Med
Winther M, Sørensen OB, Brøchner AC, Wittrock D, Hansen PM, Knudsen JS, Nielsen LS, Wolthers SA, Nielsen LB, Christensen HC, Huniche L, Mikkelsen S, Laerkner E.   +12 more
europepmc   +1 more source

The development of emergency medical services benefit score: a European Delphi study. [PDF]

Scand J Trauma Resusc Emerg Med, 2021
Heino A, Raatiniemi L, Iirola T, Meriläinen M, Liisanantti J, Tommila M, Collaboration Group.   +6 more
europepmc   +1 more source

Human‐in‐the‐Loop Swarms: A Bionic Swarm Approach to Real‐World Soil Mapping

Advanced Intelligent Systems, EarlyView.
This article introduces the “Bionic Swarm,” a novel system that lowers the barriers to real‐world swarm validation by abstracting difficult hardware tasks to app‐guided human agents. We demonstrate the system's utility through the experimental validation of a geotechnical soil‐mapping swarm algorithm and show superior performance to baseline approaches
Petras Swissler, Mohammadali Rashidioun, Nicholas Sahu, Raaid Kabir, Ayodeji Aderibigbe, Oladoyin Kolawole   +5 more
wiley   +1 more source