Browsing by Author "Eltokhy, Amira"

Now showing 1 - 3 of 3

Four ports MIMO printed antenna with high isolation for UWB and X-band systems
(Cambridge University Press, 2023-11) Ibrahim, Ahmed A; Eltokhy, Amira; Daw, Ahmed Fawzy
In this work, a compact size 4 ports multiple input multiple output (MIMO) slot antenna with the connected ground for Ultra-Wide Band (UWB) and X band applications is introduced and discussed. The single antenna is a cross-shaped slot antenna in the ground plane and a 50 Ω microstrip line with a small L-stub is used to feed the antenna on the other side. The suggested MIMO antenna has four identical elements arranged to be orthogonal to each other to enhance the MIMO system performance. The antenna elements are connected with a small strip to compose the proposed connected ground antennas. The suggested MIMO antenna has an overall size of 47 mm × 47 mm. The antenna has tested and simulated bandwidth with S11 < −10 dB extended from 4– 14 GHz and has isolation greater than 20 dB between ports without utilizing the decoupling elements and with good consistency between results. The MIMO antenna has peak gain and efficiency, envelope correlation coefficient, diversity gain, and channel capacity loss of 5.6 dBi and 80%, <5 × 10–3, 10 dB, and <0.4 bit/s/Hz, respectively which prove that our antenna can be suggested for the UWB MIMO applications.
Integration of 5.8GHz Doppler Radar and Machine Learning for Automated Honeybee Hive Surveillance and Logging
(IEEE, 25/06/2021) Aldabashi, Nawaf; Williams, Sam; Eltokhy, Amira; Palmer, Edward; Cross, Paul; Palego, Cristiano
A 5.8GHz Doppler radar was used to monitor free flying honeybees entering and leaving their hive at a 2m distance. Free falling metal spheres of different size and materials were first used, along with radar cross section (RCS) simulations, for calibration of an in house continuous-wave (CW) radar system. The system was then applied to extract the RCS of free flying honeybees (n=164) at 5.8GHz, which fills a gap in the literature and was found to be in the range of-55 to-60dBsm ± 3dBsm. The Doppler radar was hence integrated with machine learning (ML) techniques to autonomously discriminate the incoming and outgoing flights of honeybees. A neural network built through a random forest algorithm and processing of the data as Line Spectral Pairs (LSPs) achieved a maximum accuracy of 87.83% with a Binary Cross Entropy loss of 0.4274 when interpreting hive departure/entrance events. © 2021 IEEE.
An Overview of the Development of Speaker Recognition Techniques for Various Applications
(Engineering and Technology Publishing, 2022-08) Mohamed, Amira; Eltokhy, Amira; Zekry, Abdelhalim
Speech Enhancement (SE) is a significant research issue in audio signal processing where the goal is to enhance the clarity and quality of speech signals corrupted by noise. Because of its different applications, it becomes a compelling research topic nowadays. The focus of this paper is dedicated to one of these applications which is Speaker recognition. In this paper, the fundamentals and applications of speaker recognition are discussed. A brief study on the performance and the recognition accuracy of different speaker modeling techniques has been conducted. Furthermore, while there have been several studies about the technologies used in speaker recognition, there have been few studies about the applications of speaker recognition, and none of them considers combining or linking the applications and technology in the same study. This overview demonstrates the various technologies that can be used to achieve speaker recognition applications. It aims to give a new perspective of the existing technologies uses in various applications. The paper concludes with discussions on future trends and research opportunities in this area. © 2022 Journal of Communications and 2022 by the authors.