Results 191 to 200 of about 25,724 (259)
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 +4 more
wiley +1 more source
Autonomous AI‐Driven Design for Skin Product Formulations
Advanced Intelligent Discovery, EarlyView.This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang +5 more
wiley +1 more source
Online Gambling of Pure Chance: Wager Distribution, Risk Attitude, and Anomalous Diffusion. [PDF]
Sci Rep, 2019 Wang X, Pleimling M.
europepmc +1 more source
Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction
Advanced Intelligent Discovery, EarlyView.Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong +4 more
wiley +1 more source
Inferring Active Noise Characteristics from the Paired Observations of Anomalous Diffusion. [PDF]
Polymers (Basel), 2018 Saito T, Sakaue T.
europepmc +1 more source
Advanced Intelligent Discovery, EarlyView.Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley +1 more source
Protein motion in the nucleus: from anomalous diffusion to weak interactions. [PDF]
Biochem Soc Trans, 2018 Woringer M, Darzacq X.
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 +8 more
wiley +1 more source
Non-Linear Langevin and Fractional Fokker-Planck Equations for Anomalous Diffusion by Lévy Stable Processes. [PDF]
Entropy (Basel), 2018 Anderson J, Moradi S, Rafiq T.
europepmc +1 more source
AI &Innovation, EarlyView.ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury +2 more
wiley +1 more source