In this study, we compare the retrieval results for the dielectric properties of verified oil slick, acquired using airborne multifrequency synthetic aperture radar. A polarimetric two-scale model was used to invert the radar imagery by first employing solely the co-polarization channels, and then by employing the co-polarization channels in conjunction with the cross-polarization channels, and ...

Artificial intelligent systems often model the solutions of typical machine learning problems, inspired by biological processes, because of the biological system is faster and much adaptive than deep learning. The utility of bio-inspired learning methods lie in its ability to discover unknown patterns, and its less dependence on mathematical modeling or exhaustive training. In this paper, we propose ...

The spatial and temporal characterization of trapped charged particle trajectories in magnetospheres has been extensively studied in dipole magnetic field structures. Such studies have allowed the calculation of spatial quantities, such as equatorial loss cone size as a function of radial distance, the location of the mirror points along particular field lines (<i>L</i>‐shells) as a function of the ...

In this paper, we test and evaluate policy gradient reinforcement learning for automated blood glucose control in patients with Type 1 Diabetes Mellitus. Recent research has shown that reinforcement learning is a promising approach to accommodate the need for individualized blood glucose level control algorithms. The motivation for using policy gradient algorithms comes from the fact that adaptively ...

Robust and reliable classification of sea ice types in synthetic aperture radar (SAR) images is needed for various operational and environmental applications. Previous studies have investigated the class-dependent decrease in SAR backscatter intensity with incident angle (IA); others have shown the potential of textural information to improve automated image classification. In this work, we investigate ...

Considering a coherent microscopy setup, influences of the substrate below the sample in the imaging performances are studied, with a focus on high refractive index substrate such as silicon. Analytical expression of 3D full-wave vectorial point spread function, i.e. the dyadic Green's function is derived for the optical setup together with the substrate. Numerical analysis are performed in order ...

Fram Strait, the deepest gateway to the Arctic Ocean, is strongly influenced by eddy dynamics. Here we analyse the output from two eddy-resolving models (ROMS – Regional Ocean Modeling System; FESOM – Finite-Element Sea-ice Ocean Model) with around 1 km mesh resolution in Fram Strait, with a focus on their representation of eddy properties and dynamics. A comparison with mooring observations shows ...

Image denoising or artefact removal using deep learning is possible in the availability of supervised training dataset acquired in real experiments or synthesized using known noise models. Neither of the conditions can be fulfilled for nanoscopy (super-resolution optical microscopy) images that are generated from microscopy videos through statistical analysis techniques. Due to several physical ...

Photonic-chip-based light illumination has recently found applications in optical microscopy and nanoscopy methodologies. The photonic chip removes the dependency on imaging objective lenses to generate the required illumination patterns for different microscopy methods. Until now, all the reported chip-based optical microscopy methods exploit the evanescent field present on top of a waveguide surface ...

Multiple signal classification algorithm (MUSICAL) exploits temporal fluctuations in fluorescence intensity to perform super-resolution microscopy by computing the value of a super-resolving indicator function across a fine sample grid. A key step in the algorithm is the separation of the measurements into signal and noise subspaces, based on a single user-specified parameter called the threshold. ...