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Electromagnetic Fields

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Electromagnetic Wave Absorption in the Human Head: A Virtual Sensor Based on a Deep-Learning Model.

Sensors (Basel, Switzerland)
Determining the amount of electromagnetic wave energy absorbed by the human body is an important issue in the analysis of wireless systems. Typically, numerical methods based on Maxwell's equations and numerical models of the body are used for this p...

Machine learning-assisted antenna modelling for realistic assessment of incident power density on non-planar surfaces above 6 GHz.

Radiation protection dosimetry
In this paper, the analysis of exposure reference levels is performed for the case of a half-wavelength dipole antenna positioned in the immediate vicinity of non-planar body parts. The incident power density (IPD) spatially averaged over the spheric...

Electromagnetic interference elimination via active sensing and deep learning prediction for radiofrequency shielding-free MRI.

NMR in biomedicine
At present, MRI scans are typically performed inside fully enclosed radiofrequency (RF) shielding rooms, posing stringent installation requirements and causing patient discomfort. We aim to eliminate electromagnetic interference (EMI) for MRI with no...

Mammography using low-frequency electromagnetic fields with deep learning.

Scientific reports
In this paper, a novel technique for detecting female breast anomalous tissues is presented and validated through numerical simulations. The technique, to a high degree, resembles X-ray mammography; however, instead of using X-rays for obtaining imag...

Energy controls wave propagation in a neural network with spatial stimuli.

Neural networks : the official journal of the International Neural Network Society
Nervous system has distinct anisotropy and some intrinsic biophysical properties enable neurons present various firing modes in neural activities. In presence of realistic electromagnetic fields, non-uniform radiation activates these neurons with ene...

Deep learning-based near-field effect correction method for Controlled Source Electromagnetic Method and application.

PloS one
Addressing the impact of near-field effects in the Controlled Source Electromagnetic Method(CSEM) has long been a focal point in the realm of geophysical exploration. Therefore, we propose a deep learning-based near-field correction method for contro...

Fuzzy-Based Bioengineering System for Predicting and Diagnosing Diseases of the Nervous System Triggered by the Interaction of Industrial Frequency Electromagnetic Fields.

Critical reviews in biomedical engineering
The study aims to enhance the standard of medical care for individuals working in the electric power industry who are exposed to industrial frequency electromagnetic fields and other relevant risk factors. This enhancement is sought through the integ...

Robust EMI elimination for RF shielding-free MRI through deep learning direct MR signal prediction.

Magnetic resonance in medicine
PURPOSE: To develop a new electromagnetic interference (EMI) elimination strategy for RF shielding-free MRI via active EMI sensing and deep learning direct MR signal prediction (Deep-DSP).

A Comparative Analysis of Explainable Artificial Intelligence Models for Electric Field Strength Prediction over Eight European Cities.

Sensors (Basel, Switzerland)
The widespread propagation of wireless communication devices, from smartphones and tablets to Internet of Things (IoT) systems, has become an integral part of modern life. However, the expansion of wireless technology has also raised public concern a...

AI-based forecasting of dynamic behaviors of Ag and ZnO nanoparticles-enhanced milk in an electromagnetic channel with exponential heating: dairy decontamination.

The European physical journal. E, Soft matter
Electromagnetic plates can be used to heat milk and other dairy products rapidly and uniformly. The use of electromagnetic fields enables precise thermal control, which is crucial for safe pasteurization while retaining the nutritional and sensory qu...