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Electromagnetic Fields

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Development of accurate human head models for personalized electromagnetic dosimetry using deep learning.

NeuroImage
The development of personalized human head models from medical images has become an important topic in the electromagnetic dosimetry field, including the optimization of electrostimulation, safety assessments, etc. Human head models are commonly gene...

Sensor-Aided EMF Exposure Assessments in an Urban Environment Using Artificial Neural Networks.

International journal of environmental research and public health
This paper studies the time and space mapping of the electromagnetic field (EMF) exposure induced by cellular base station antennas (BSA) using artificial neural networks (ANN). The reconstructed EMF exposure map (EEM) in urban environment is obtaine...

Indication of Electromagnetic Field Exposure via RBF-SVM Using Time-Series Features of Zebrafish Locomotion.

Sensors (Basel, Switzerland)
This paper introduces a novel model based on support vector machine with radial basis function kernel (RBF-SVM) using time-series features of zebrafish () locomotion exposed to different electromagnetic fields (EMFs) to indicate the corresponding EMF...

A Shapeshifting Ferrofluidic Robot.

Soft robotics
To create a miniature shapeshifting robot capable of controlled movement, subdivision, regeneration, passage through small channels, engulfment of particles, object manipulation, and flow manipulation, a droplet of magnetically responsive ferrofluid ...

Conformational changes of β-thalassemia major hemoglobin and oxidative status of plasma after in vitro exposure to extremely low-frequency electromagnetic fields: An artificial neural network analysis.

Electromagnetic biology and medicine
Electromagnetic fields (EMF) can generate reactive oxygen species and induce oxidative modifications. We investigated the effects of extremely low-frequency electromagnetic fields (ELF-EMF) on oxidative status of plasma and erythrocytes in β-thalasse...

Magnetic-resonance-based measurement of electromagnetic fields and conductivity in vivo using single current administration-A machine learning approach.

PloS one
Diffusion tensor magnetic resonance electrical impedance tomography (DT-MREIT) is a newly developed technique that combines MR-based measurements of magnetic flux density with diffusion tensor MRI (DT-MRI) data to reconstruct electrical conductivity ...

On-chip photonic diffractive optical neural network based on a spatial domain electromagnetic propagation model.

Optics express
An integrated physical diffractive optical neural network (DONN) is proposed based on a standard silicon-on-insulator (SOI) substrate. This DONN has compact structure and can realize the function of machine learning with whole-passive fully-optical m...

A stroke detection and discrimination framework using broadband microwave scattering on stochastic models with deep learning.

Scientific reports
Stroke poses an immense public health burden and remains among the primary causes of death and disability worldwide. Emergent therapy is often precluded by late or indeterminate times of onset before initial clinical presentation. Rapid, mobile, safe...

Computation of transcranial magnetic stimulation electric fields using self-supervised deep learning.

NeuroImage
Electric fields (E-fields) induced by transcranial magnetic stimulation (TMS) can be modeled using partial differential equations (PDEs). Using state-of-the-art finite-element methods (FEM), it often takes tens of seconds to solve the PDEs for comput...

A comprehensive deep learning method for empirical spectral prediction and its quantitative validation of nano-structured dimers.

Scientific reports
Nanophotonics exploits the best of photonics and nanotechnology which has transformed optics in recent years by allowing subwavelength structures to enhance light-matter interactions. Despite these breakthroughs, design, fabrication, and characteriza...