A bandwidth enhancement of chamfered square Ultrawideband (UWB) monopole textile antenna with truncated ground plane for breast cancer detection is presented in this paper. The overall dimensions of 28.5 x 28.5 x 3.34 mm3, covering a super bandwidth of range between 2.23 and 18.24 GHz is obtained. A total impedance bandwidth (<-10 dB) of 16.01 GHz is achieved with a total efficiency of 93.54% and realized gain of 12.95 dBi at 9.3 GHz.
A quadruple band with L-slotted multiple-input-multiple-output (MIMO) square dielectric resonator antenna (SDRA) for fifth generation (5G) applications at the sub-6 GHz band is presented, which can cover 5G new radio band N77 (3.3–4.2) GHz and N79 (4.4–5) GHz. The proposed structure consists of a single SDRA mounted on a substrate excited by an aperture slot underneath dielectric resonators (DR)s. The performance of SDRA is improved by introducing L-shaped slot on the central part of DRA. Results show that the MIMO SDRA antenna achieves S11<-10 dB and S21<=-15 dB for all resonant frequencies at 3.5 GHz, 4 GHz, 4.6 GHz, and 5 GHz, indicating good performance of the antenna at the desired frequencies. The maximum realized gain is 5.61 dB and 5.01 dB at port 1, 4 GHz and port 2, 4.6 GHz, respectively. The radiation efficiencies are acceptable for all resonant frequencies. Moreover, the proposed antenna design achieved good envelop correlation coefficient (ECC) and diversity gain
Fifth Generation (5G) is the next evolution of mobile communication that will provide seamless and massive high speed connectivity to the society. Paralleled with the rise of 5G, it is foreseen that wearable devices particularly wearable antenna will be the significant end node for wearable devices in Millimeter Wave (mmWave) frequency bands. Thus, this paper discusses the new development of the 5G sub-6 GHz and mmWave wearable antenna, introduces the research results of the 5G mmWave wearable antenna in recent years, and addresses the key challenges in the development trend of the development trend of the 5G mmWave wearable antenna.
The Fifth Generation (5G) communication technology will deliver faster data speeds and support numerous new applications such as virtual and augmented reality. The additional need for a larger number of 5G base stations has sparked widespread public concerns about their possible negative health impacts. This review analyzes the latest research on electromagnetic exposure on humans, with particular attention to its effect on cognitive performance, well-being, physiological parameters, and Electroencephalography (EEG). While most of their results indicated no changes in cognitive function, physiological parameters, or overall well-being, the strength of the EEG alpha wave is noticed to vary depending on various aspects of cognitive functions. However, the available studies have not investigated the health effects resulting from exposure from the 5G mobile phone and base station antennas from 700 MHz to 30 GHz on the cognitive performance, well-being subjective symptoms, human physiologic
The current practice of adjusting hearing aids (HA) is tiring and time-consuming for both patients and audiologists. Of hearing-impaired people, 40–50% are not satisfied with their HAs. In addition, good designs of HAs are often avoided since the process of fitting them is exhausting. To improve the fitting process, a machine learning (ML) unsupervised approach is proposed to cluster the pure-tone audiograms (PTA). This work applies the spectral clustering (SP) approach to group audiograms according to their similarity in shape. Different SP approaches are tested for best results and these approaches were evaluated by Silhouette, Calinski-Harabasz, and Davies-Bouldin criteria values. Kutools for Excel add-in is used to generate audiograms’ population, annotated using the results from SP, and different criteria values are used to evaluate population clusters. Finally, these clusters are mapped to a standard set of audiograms used in HA characterization. The results indicated that gr