An adaptive frequency-hopping detection for slowly-varying fading dispersive channels.

Frequency hopping (FH) signals have been widely used to improve performance against frequency selective fading phenomenon of underwater channels. However, the channel is slowly varying in regard to changes in weather conditions, and thus the conventional FH detection transmitting signals with fixed frequency cannot guarantee good detection performance in the dynamic underwater environment. To overcome the performance degradation in slowly-varying fading dispersive channels, this paper proposes an adaptive frequency-hopping (AFH) target detection method.

Microwave Imaging of Anisotropic Objects by Artificial Intelligence Technology.

In this paper, we present the microwave imaging of anisotropic objects by artificial intelligence technology. Since the biaxial anisotropic scatterers have different dielectric constant components in different transverse directions, the problems faced by transverse electronic (TE) polarization waves are more complex than those of transverse magnetic (TM) polarization waves. In other words, measured scattered field information can scarcely reconstruct microwave images due to the high nonlinearity characteristic of TE polarization.

Fabrications of the Flexible Non-Enzymatic Glucose Sensors Using Au-CuO-rGO and Au-CuO-rGO-MWCNTs Nanocomposites as Carriers.

A flexible, non-enzymatic glucose sensor was developed and tested on a polyethylene terephthalate (PET) substrate. The sensor's design involved printing Ag (silver) as the electrode and utilizing mixtures of either gold-copper oxide-modified reduced graphene oxide (Au-CuO-rGO) or gold-copper oxide-modified reduced graphene oxide-multi-walled carbon nanotubes (Au-CuO-rGO-MWCNTs) as the carrier materials. A one-pot synthesis method was employed to create a nanocomposite material, consisting of Au-CuO-rGO mixtures, which was then printed onto pre-prepared flexible electrodes.