Quick and accurate structural damage detection is essential for maintaining the safety and integrity of infrastructure, especially following natural disasters. Traditional methods of damage assessment, which rely on manual inspections, can be labor-intensive and subject to human error. This paper introduces a hybrid deep learning model that combines the capabilities of ResNet50 and GoogLeNet, further enhanced by a convolutional block attention module (CBAM), proposed to improve both the accuracy and performance in detecting structural damage. For training purposes, a diverse dataset of images depicting both structural damage cases and undamaged cases was used. To further enhance the robustness, data augmentation techniques were also employed. In this research, precision, recall, F1-score, and accuracy were employed to evaluate the effectiveness of the introduced hybrid deep learning model. Our findings indicate that the hybrid deep neural network introduced in this study significantly outperformed standalone architectures such as ResNet50 and GoogLeNet, making it a highly effective solution for applications in disaster response and infrastructure maintenance.

This article introduces a miniaturized antenna for 5G-II band millimeter-wave communication. The antenna’s performance is meticulously examined through comprehensive simulations carried out using CST Microwave Studio, employing an FR-4 substrate with dimensions measuring 12 × 14 × 1.6 mm³. The proposed design exhibits exceptional qualities, featuring an impressive impedance bandwidth of 70.4% and a remarkable return loss of −35 dBi. The operational frequency range of this antenna extends from 16.2 GHz to 33.8 GHz, featuring a central frequency of 25 GHz, positioning it effectively within the 5G-II Band. The antenna consistently maintains polar patterns throughout this spectrum, which guarantees dependable and efficient performance. It showcases a substantial gain of 3.85 dBi and an impressive efficiency rating of 82.9%. Renowned for its versatility, this antenna is well suited for a diverse range of applications, including but not limited to Ka band, Ku band, 5G-II bands, and various other purposes in microwaves.

A circular compact ultra‐wideband antenna for 5G microwave applications

This article presents a novel S/C/X band antenna specifically designed for 5G and beyond applications. The antenna's performance is thoroughly analyzed through comprehensive simulations using CST Microwave Studio on an FR-4 substrate, measuring 10λ × 14λ × 0.014λ (where λ is calculated at a lower resonance frequency). The proposed design displays remarkable characteristics, boasting an outstanding impedance bandwidth of 124% and an impressive return loss of −38 dBi. Its operational frequency ranges from 2.8 to 12 GHz, with a central frequency of 7.4 GHz. Throughout this range, the antenna maintains stable polar patterns, ensuring consistent and efficient performance with a wide gain of 3.98 dBi and an impressive efficiency of 84.2%. This antenna proves to be well-suited for diverse applications, including S-band: 3.1–4.2 GHz, C-band: 4.4–5.0 GHz, X-band: 8.0–12.0 GHz, and 5G and beyond communication. The innovative features of this S/C/X band antenna offer significant potential for advancing wireless communication technologies.