Results 81 to 90 of about 49,141 (264)
Advanced Science, EarlyView.Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su +13 more
wiley +1 more source
Advanced Science, EarlyView.Blood‐based amino acid patterns measured by 19F NMR reveal hidden metabolic changes in colorectal cancer. By analyzing how these amino acids interact as a network, machine learning models identify patients at higher risk of recurrence and metastasis.
Ji‐Yeon Lee +9 more
wiley +1 more source
Advanced Science, EarlyView.This study presents printed magnetoresistive sensors with a vertically aligned architecture that enables high optical transparency and mechanical flexibility. By integrating deep learning for the analysis of complex spatiotemporal signal patterns, the system further achieves intelligent multimodal interaction capabilities.
Rui Xu +11 more
wiley +1 more source
BIMLP Model Based on Deep Learning for Predicting Electrical Load Demand [PDF]
Iranian Journal of Electrical and Electronic EngineeringThe accurate prediction of electricity demand is crucial for efficient energy management and grid operation. However, the complexities of demand patterns, weather variability, and socioeconomic factors make it challenging to forecast demand with high ...
Somayeh Talebzadeh +2 more
doaj
An MLP-Based Deep Neural Network Incorporating SMOTE-Tomek Approach for Robust Prediction of Liver Disorders [PDF]
Journal of Artificial Intelligence and Data MiningLiver disorders are among the most common diseases worldwide, and their timely diagnosis and prediction can significantly improve treatment outcomes.
Elahe Moradi
doaj +1 more source
Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami
Advanced Science, EarlyView.This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning +3 more
wiley +1 more source
Prediction of Deformed Shape and Die Optimization for Hat-section Forming Using a Scalar-based ANN Surrogate and Genetic Algorithm [PDF]
한국정밀공학회지The formation of a hat-profile is significantly influenced by springback and the final cross-sectional geometry, both of which are sensitive to die profile design.
Hyun-Do Noh +4 more
doaj +1 more source
Advanced Science, EarlyView.Here, we present an optoelectronic synaptic memtransistor (OSMT) integrating photoresponsive IGZO with contact‐engineered HfO2, enabling electrically and optically tunable synaptic weights. The device demonstrates broad range of tunable conductance states and array‐level image processing, highlighting its potential for intelligent machine vision ...
Donghyun Kang +6 more
wiley +1 more source
Predicting shear capacity of Recycled Aggregate Concrete beams using Artificial Neural Network
Journal of Materials and Engineering StructuresThis study investigates the application of an Artificial Neural Network (ANNs) utilizing a Multi-Layer Perceptron (MLP) architecture to predict the shear capacity of Recycled Aggregate Concrete (RAC) beams.
Ha HOANG +3 more
doaj
Advanced Science, EarlyView.A pneumatically actuated multi‐tissue microphysiological system is integrated with AI‐based machine vision and automatic sampling and replenishment systems. The platform allows for the emulation of translationally relevant long‐term pharmacokinetic exposure scenarios for multiple weeks while enabling longitudinal monitoring of response biomarkers ...
Jibbe Keulen +15 more
wiley +1 more source