Results 181 to 190 of about 517,528 (292)

Predicting copper leaching from slag: an interpretable machine learning approach under oxidative sulfuric acid conditions. [PDF]

RSC Adv
Kim SJ, Kang SS, Pae KN, Pak SI, Jo HI, Kim RJ.   +5 more
europepmc   +1 more source

Modeling and Characterization of a Self‐Sensing Soft Hydraulic Muscle

Advanced Intelligent Systems, EarlyView.
This article presents the self‐sensing soft hydraulic muscle (SSHM), a novel soft actuator capable of simultaneously sensing force and length without external sensors. A comprehensive model accurately predicts SSHM behavior, validated experimentally with minimal errors. Using propylene glycol enhances durability and reduces hysteresis.
Nhu An Phan, Phuong Linh Dao, Duc Tu Vu, The Doan Le, Sy Trung Ngo, Minh Tri Phan, T. Thang Vo‐Doan, Ke Wu, Mai Thanh Thai   +8 more
wiley   +1 more source

Erratum to: Clinical feasibility of the ESCRS IOL power calculator. [PDF]

J Cataract Refract Surg
Pomberger L, Tasch L, Mayer-Xanthaki C, Reifeltshammer SA, Bolz M, Hirnschall N.   +5 more
europepmc   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

A Range-Aware Attention Framework for Meteorological Visibility Estimation. [PDF]

Sensors (Basel)
Lo WL, Wong KW, Hsung RTC, Chung HSH, Fu H, Tsang HSH, Zhu TY.   +6 more
europepmc   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Real-world federated learning for brain imaging scientists. [PDF]

Front Digit Health
Denissen S, Laton J, Grothe M, Vaneckova M, Uher T, Kudrna M, Horáková D, Baijot J, Penner IK, Kirsch M, Motýl J, De Vos M, Chén OY, Van Schependom J, Sima DM, Nagels G.   +15 more
europepmc   +1 more source

Predicting Crystal Structures and Ionic Conductivities in Li3 YCl6−x Brx Halide Solid Electrolytes Using a Fine‐Tuned Machine Learning Interatomic Potential

Advanced Intelligent Systems, EarlyView.
This study refines the Crystal Hamiltonian Graph Network to predict energies, structures, and lithium‐ion dynamics in halide electrolytes. By generating ordered structural models and using an iterative fine‐tuning workflow, we achieve near‐ab initio accuracy for phase stability and ionic transport predictions.
Jonas Böhm, Aurélie Champagne
wiley   +1 more source

Dynamic machine learning approach for workload prediction in cloud environments. [PDF]

Sci Rep
Nashaat M, Moussa W, Rizk R, Saber W.
europepmc   +1 more source

Economy of Touch : Task‐Driven Information Selection in Electrical Impedance Tomography‐based Tactile Robotic Sensing

Advanced Intelligent Systems, EarlyView.
Electrical impedance tomography (EIT) tactile skins enable multiplexed measurements that trade sensing speed against information richness. This work introduces an economy‐of‐touch framework that treats tactile sensing as an information‐budgeting problem.
Xiaoxian Xu, David Hardman, Fumiya Iida
wiley   +1 more source