Design of reconfigurable fractal antenna using pin diode switch for wireless applications

International audienceIn this article, a frequency reconfigurable fractal patch antenna using pin diodes is proposed and studied. The antenna structure has been designed on FR-4 low-cost substrate material of relative permittivity εr = 4.4, with a compact volume of 30×30×0.8 mm3. The bandwidth and resonance frequency of the antenna design will be increased when we exploit the fractal iteration on the patch antenna. This antenna covers some service bands such as: WiMAX, m-WiMAX, WLAN, C-band and X band applications. The simulation of the proposed antenna is carried out using CST microwave studio. The radiation pattern and S parameter are further presented and discussed

A compact CPW-Fed hexagonal antenna with a new fractal shaped slot for UWB communications

International audienceIn the present paper, a simple and compact a coplanar waveguide (CPW)-Fed hexagonal antenna has been presented. The proposed antenna is composed of a new fractal shaped slot with a hexagonal patch fed. The total size of the presented antenna is 14.5×16.5 mm 2 , which is designed on Rogers RO4350B substrate and having dielectric constant ε r =3.66, a thickness of h=1.524 and loss tangent of 0.004. The impedance bandwidth, defined by -10 dB reflection coefficient. Hence, the simulated results get a proper agreement with an impedance bandwidth of 2.98 GHz to 11.4 GHz. The investigated antenna is suitable for UWB applications. The design validation of the fractal antenna has been achieved by using CST Microwave studio

Identification of groundwater potential zones using remote sensing, GIS, machine learning and electrical resistivity tomography techniques in Guelma basin, northeastern Algeria

In this research we assess and map groundwater potential in the Guelma Basin (northeastern Algeria) using an approach combining remote sensing, GIS, statistical and machine learning models. Four models were used including the frequency ratio model with both conventional (CFR) and modified (MFR) versions, the decision tree (DT), and the random forest (RF). For this purpose, firstly, thirteen hydro-geo-morphological variables influencing groundwater potential have been mapped using GIS and remote sensing techniques including elevation, slope, aspect, topographic wetness index, slope Length and Steepness factor, profile curvature, plan curvature, drainage density, distance to river, lineament and fault density, distance to faults and lineaments, lithology, and land use/land cover. Secondly, the groundwater potential was assessed and mapped based on the four models using the training data. Finally, the obtained groundwater potential maps of the four models have been validated using two approaches: (i) a statistical approach based on the receiver operating characteristics curves (ROC); (ii) a geophysical approach by interpreting the electrical resistivity tomography (ERT) results. The validation process gives the Random Forest method as the most accurate. The obtained map by this model is the main finding of this research, where the very high groundwater potential class occupies 8.25%. It is located mostly in the Guelma plain centre and in the northern part of the study area. The used approach and the obtained results may serve for water resource managers to improve groundwater resource planning and to resolve regional scale issues in this area or elsewhere