A machine learning aided (MLA) method is employed for the direct permittivity retrieval of
dispersive and non-dispersive materials. The method requires low-cost measurements since …

A machine learning (ML) approach is proposed to provide an accurate retrieval of the
dielectric properties of materials. In our earlier work, based on a semi-analytic solution of …

This work presents a real-life experiment implementing an artificial intelligence model for
detecting sub-millimeter cracks in metallic surfaces on a dataset obtained from a waveguide …

Dielectric dispersion (DD) logs acquired in subsurface geologic formations generally are
composed of conductivity (σ) and relative permittivity (ε r) measurements at four discrete …

An RFID-based passive sensor for pervasive soil moisture monitoring is proposed.
Variations in moisture cause a change in soil permittivity which in turn affects the impedance …

It is difficult to establish analytical relationships between coating parameters (type and filling
ratios of absorbent) and electromagnetic (EM) properties based on traditional trial-and-error …

Electromagnetic (EM) properties, such as electrical conductivity, dielectric permittivity, and
magnetic permeability, are dispersive in nature, such that the EM properties are functions of …

Measuring the complex permittivity of ultrathin, flexible materials with a high loss tangent
poses a substantial challenge with precision using conventional methods, and verifying the …

This paper introduces a machine learning (ML) measurement method to retrieve the
complex permittivity profile of dispersive and non-dispersive materials with high or low loss …

Permittivity is an important aspect of the design of microwave devices. In order to design
microwave devices that are more suitable for the excitation of air plasmas, this paper …