Sami Barmada
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View article: Unilateral EMG-Guided Botulinum Toxin for Retrograde Cricopharyngeus Dysfunction: A Prospective Clinical and Neurophysiological Study
Unilateral EMG-Guided Botulinum Toxin for Retrograde Cricopharyngeus Dysfunction: A Prospective Clinical and Neurophysiological Study Open
Retrograde cricopharyngeus dysfunction (R-CPD) is a recently recognized condition characterized by the inability to burp, typically accompanied by gurgling noises, bloating, and flatulence. Percutaneous botulinum neurotoxin (BoNT) injectio…
View article: A deep learning based lightning location system
A deep learning based lightning location system Open
The paper presents a new approach for lightning location and peak current estimation based on Deep Learning (DL) algorithms. The basic idea is to use the time domain waveforms of the overvoltages induced by lightning strikes on transmissio…
View article: A Deep Learning Based Prediction of Specific Absorption Rate Hot‐Spots Induced by Broadband Electromagnetic Devices
A Deep Learning Based Prediction of Specific Absorption Rate Hot‐Spots Induced by Broadband Electromagnetic Devices Open
The rapid growth of wearable electromagnetic devices has raised concerns about the potential health effects of electromagnetic fields, particularly due to their interaction with biological tissues. The key parameter for assessing these eff…
View article: A STacked Adaptive Residual PINN (STAR-PINN) Approach to 2D Time-Domain Magnetic Diffusion in Nonlinear Materials
A STacked Adaptive Residual PINN (STAR-PINN) Approach to 2D Time-Domain Magnetic Diffusion in Nonlinear Materials Open
This work explores the use of Physics-Informed Neural Networks (PINNs) and a newly proposed approach, called the STacked Adaptive Residual PINN (STAR-PINN), to solve magnetic diffusion problems in the magneto quasi static regime. The study…
View article: Synthesis of Boundary Conditions in Polygonal Magnetic Domains Using Deep Neural Networks
Synthesis of Boundary Conditions in Polygonal Magnetic Domains Using Deep Neural Networks Open
In this paper, the authors approach the problem of boundary condition synthesis (also defined as field continuation) in a doubly connected domain by the use of a Neural Network-based approach. In this innovative method, given a field probl…
View article: Maintain Power Transmission and Efficiency Tracking Using Variable Capacitors for Dynamic WPT Systems
Maintain Power Transmission and Efficiency Tracking Using Variable Capacitors for Dynamic WPT Systems Open
This study introduces a new method for real-time efficiency tracking and stable output power of Dynamic Wireless Power Transfer (DWPT) systems using variable capacitors. A preliminary detailed discussion and an analysis of the DWPT system …
View article: Enhanced prediction of transformers vibrations under complex operating conditions
Enhanced prediction of transformers vibrations under complex operating conditions Open
Vibrations occurring in transformer are a physical phenomenon that can be used for condition monitoring, since when the amount of vibrations changes significantly, a faulty condition is in progress (or is incipient). Consequently, vibratio…
View article: Analysis of current distribution and termination conditions in 2D metasurfaces
Analysis of current distribution and termination conditions in 2D metasurfaces Open
Purpose The purpose of this paper is to gain a better understanding on how metasurfaces behave, in terms of currents in each unit cell. A better knowledge of their behavior could lead to an ad-hoc design for specific applications. Design/m…
View article: Open-Ended Coaxial Probe for Effective Reconstruction of Biopsy-Excised Tissues’ Dielectric Properties
Open-Ended Coaxial Probe for Effective Reconstruction of Biopsy-Excised Tissues’ Dielectric Properties Open
Dielectric characterization is extremely promising in medical contexts because it offers insights into the electromagnetic properties of biological tissues for the diagnosis of tumor diseases. This study introduces a promising approach to …
View article: Lightning Location and Peak Current Estimation From Lightning-Induced Voltages on Transmission Lines With a Machine Learning Approach
Lightning Location and Peak Current Estimation From Lightning-Induced Voltages on Transmission Lines With a Machine Learning Approach Open
In this article, a machine-learning-based model for the regression of cloud-to-ground lightning location and peak current from time-domain waveforms of lightning-induced voltage measurements on overhead transmission lines is presented. A p…
View article: Physics-informed Neural Networks for the Resolution of Analysis Problems in Electromagnetics
Physics-informed Neural Networks for the Resolution of Analysis Problems in Electromagnetics Open
Learning from examples is the golden rule in the construction of behavioral models using neural networks (NN). When NN are trained to simulate physical equations, the tight enforcement of such laws is not guaranteed by the training process…
View article: Machine Learning for the Design and the Simulation of Radiofrequency Magnetic Resonance Coils: Literature Review, Challenges, and Perspectives
Machine Learning for the Design and the Simulation of Radiofrequency Magnetic Resonance Coils: Literature Review, Challenges, and Perspectives Open
Radiofrequency (RF) coils for magnetic resonance imaging (MRI) applications serve to generate RF fields to excite the nuclei in the sample (transmit coil) and to pick up the RF signals emitted by the nuclei (receive coil). For the purpose …
View article: A Source Identification Problem in Magnetics Solved by Means of Deep Learning Methods
A Source Identification Problem in Magnetics Solved by Means of Deep Learning Methods Open
In this study, a deep learning-based approach is used to address inverse problems involving the inversion of a magnetic field and the identification of the relevant source, given the field data within a specific subdomain. Three different …
View article: A Novel Hybrid Boundary Element—Physics Informed Neural Network Method for Numerical Solutions in Electromagnetics
A Novel Hybrid Boundary Element—Physics Informed Neural Network Method for Numerical Solutions in Electromagnetics Open
In this contribution the authors propose a hybrid Boundary Element Method – Physics Informed Neural Networks (BEM – PINN) approach, to be used for the resolution of partial differential equations arising when formulating boundary-value pro…
View article: Model-based Control of a Glass Melting Furnace
Model-based Control of a Glass Melting Furnace Open
This paper derives practical dynamic models for the glass industrial manufacturing process to be then included in model-based control solutions. In particular, the first section of the plant, that is, the glass melting furnace is investiga…
View article: Optimal Metamaterial Configuration for Magnetic Field Shielding in Wireless Power Transfer Systems
Optimal Metamaterial Configuration for Magnetic Field Shielding in Wireless Power Transfer Systems Open
This paper investigates the use of a metamaterial slab for magnetic field shielding in a low-frequency inductive power transfer (IPT) system. In particular, three different configurations of metamaterial slabs are considered, which are def…
View article: Introducing energy into marine environments: A lab-scale static magnetic field submarine cable simulation and its effects on sperm and larval development on a reef forming serpulid
Introducing energy into marine environments: A lab-scale static magnetic field submarine cable simulation and its effects on sperm and larval development on a reef forming serpulid Open
Non-chemical sources of anthropogenic environmental stress, such as artificial lights, noise and magnetic fields, are still an underestimate factor that may affect the wildlife. Marine environments are constantly subjected to these kinds o…
View article: Learning-Based Approaches to Current Identification from Magnetic Sensors
Learning-Based Approaches to Current Identification from Magnetic Sensors Open
Direct measurement of electric currents can be prevented by poor accessibility or prohibitive technical conditions. In such cases, magnetic sensors can be used to measure the field in regions adjacent to the sources, and the measured data …
View article: On the Spiral Resonator Arrays Size Analysis for Misalignment Compensation in Wireless Power Transfer Systems
On the Spiral Resonator Arrays Size Analysis for Misalignment Compensation in Wireless Power Transfer Systems Open
In this study the authors aim to use a metasurface as an additional component of a two-coil Wireless Power Transfer (WPT) system and to provide a robustness analysis to misalignment between the transmitter and the receiver coils. The analy…
View article: Impact of Nearby Lightning Strikes on Wireless Power Transfer Ground Assembly
Impact of Nearby Lightning Strikes on Wireless Power Transfer Ground Assembly Open
Direct hits from Lightning Strikes (LS) are commonly recognized as dangerous events for open air installations, but also the much more frequent case of LS hitting nearby can cause overvoltage potentially damaging connected circuits, if not…
View article: Spiral Resonator Arrays for Misalignment Compensation in Wireless Power Transfer Systems
Spiral Resonator Arrays for Misalignment Compensation in Wireless Power Transfer Systems Open
In this contribution, the authors focus on the use of a metasurface (physically implemented as a 2D array of spiral resonators) as an additional component of a two-coil Wireless Power Transfer (WPT) system, with the aim of increasing the r…
View article: Electromagnetic interferences susceptibility analysis for a metasurface‐modified wireless power transfer system
Electromagnetic interferences susceptibility analysis for a metasurface‐modified wireless power transfer system Open
The use of magnetic metasurfaces in Wireless Power Transfer systems is becoming a popular research topic: they have proven to be a valid approach to increase the performances (in terms of power transfer) and improve the overall EMC propert…
View article: Optimal Terminations of 2-D Meta-Surfaces for Uniform Magnetic Field Applications
Optimal Terminations of 2-D Meta-Surfaces for Uniform Magnetic Field Applications Open
This paper investigates the possibility of obtaining a uniform magnetic field close to a 2D metamaterial made of magnetically coupled resonant circuits. The magnetic field is controlled by terminating the boundary of the meta-surface with …
View article: Deep Neural Network-Based Electro-Mechanical Optimization of Electric Motors
Deep Neural Network-Based Electro-Mechanical Optimization of Electric Motors Open
In this contribution the authors use a Deep Neural Network based approach for the optimization of an electric motor, taking into account both electromagnetic and mechanical constraints, i.e. approaching the problem from the multiphysics po…
View article: Two‐port network compact representation of resonator arrays for wireless power transfer with variable receiver position
Two‐port network compact representation of resonator arrays for wireless power transfer with variable receiver position Open
Summary This paper presents an equivalent circuit characterization of an array of resonators for wireless power transfer (WPT) applications. These apparatuses are composed of magnetically coupled resonant coils acting as a transmitter whic…
View article: Editorial Chairs Preface
Editorial Chairs Preface Open
was held in a virtual format from October 24th to October 26th 2022.It was originally scheduled to be held in Denver, Colorado, USA; but due to the uncertainty related to the pandemic, the organizing committee decided to host it as a virtu…
View article: Deep learning as a tool for inverse problems resolution: a case study
Deep learning as a tool for inverse problems resolution: a case study Open
Purpose This study aims to investigate the possible use of a deep neural network (DNN) as an inverse solver. Design/methodology/approach Different models based on DNNs are designed and proposed for the resolution of inverse electromagnetic…
View article: A Regularized Procedure to Generate a Deep Learning Model for Topology Optimization of Electromagnetic Devices
A Regularized Procedure to Generate a Deep Learning Model for Topology Optimization of Electromagnetic Devices Open
The use of behavioral models based on deep learning (DL) to accelerate electromagnetic field computations has recently been proposed to solve complex electromagnetic problems. Such problems usually require time-consuming numerical analysis…
View article: Fault Prediction and Early-Detection in Large PV Power Plants Based on Self-Organizing Maps
Fault Prediction and Early-Detection in Large PV Power Plants Based on Self-Organizing Maps Open
In this paper, a novel and flexible solution for fault prediction based on data collected from Supervisory Control and Data Acquisition (SCADA) system is presented. Generic fault/status prediction is offered by means of a data driven appro…