This study presents a high-efficiency circular microstrip patch antenna designed for radio frequency identification (RFID) applications simulation results illustrate the performance of a circular microstrip patch antenna operating at 900 MHz. Microstrip antennas are renowned for their ability to meet the requirements of compact, lightweight designs, ensuring compatibility, and ease of integration. This research focuses on the development of a circular microstrip antenna, formed as a circular patch on a 0.035 mm thick FR-4 substrate. The design was realized using a substrate with a relative permittivity (εr) of 4.3, a loss tangent (tan δ) of 0.021 and a substrate height (h) of 1.6 mm. The antenna dimensions are small, measuring 58×45 mm, with a circular patch radius of 17 mm. The antenna operates over a frequency range from 0.5 GHz to 2 GHz. Key performance parameters include a return loss of -49.8 dB, a wide bandwidth of 150 MHz, a voltage standing wave ratio (VSWR) of 1.009, a gain of 2.161 dB, and a directivity of 2.200 dBi. Antenna design and simulation were carried out using computer simulation technology (CST) Studio Suite Software, specifically adapted to RFID applications.

1×2 microstrip patch antennas array for mm-waves 5G application

Wind energy is a critical component of the global shift to renewable energy sources, with significant growth driven by the need to reduce carbon emissions. Accurate wind speed prediction is crucial for increasing wind energy output since it directly influences wind farm design and performance. The purpose of this study is to compare two artificial neural network (ANN) models for predicting wind speed in Dakhla City, a place with a high wind energy potential. The first model is a multilayer perceptron (MLP) trained with the backpropagation algorithm, while the second is a nonlinear autoregressive with exogenous inputs (NARX) model, a form of recurrent neural network (RNN) noted for its ability to handle time-series data more well. The comparative analysis results show that the NARX model outperforms the MLP model in terms of wind speed forecast accuracy. The NARX model achieved a near-perfect regression coefficient (R) of 0.9998 and a root mean square error (RMSE) of 1.02899, indicating that it can represent complex, nonlinear wind speed patterns. These findings indicate that the NARX model could be a beneficial tool for increasing the efficiency of Dakhla City’s wind energy infrastructure, assisting the region in meeting its renewable energy ambitions.

Journal of Nano- and Electronic Physics. Scientific journal. ISSN: 2077-6772. Journal abbreviation: J. Nano- Electron. Phys. No page charges. All articles are freely available on-line. Issued 4 times per year. Publisher: Sumy State University. (Sumy, Ukraine)

Design monopole antenna of ultra-wideband high bandwidth and high efficiency for ground penetrating radar application