: This paper presents the design of a compact tri-band monopole antenna for wireless applications operating below 8 GHz, employing split-ring resonators (SRRs) to enhance performance. The antenna is realized in two phases, resulting in an offset-fed monopole structure with strategically positioned SRR elements. The antenna operates at three distinct frequencies: 5.34 GHz, 7.64 GHz, and 7.94 GHz, with corresponding operational bandwidths of 5.25-5.40 GHz, 7.43-7.73 GHz, and 7.87-8.15 GHz, offering bandwidths of 150 MHz, 302 MHz, and 280 MHz, respectively. The return losses at these frequencies are –16.66 dB, –15.39 dB, and –18.71 dB. Surface current analysis reveals multiple modal excitations across the three bands, confirming efficient multi-frequency operation. The antenna exhibits a stable gain between 2.5 and 3.8 dBi, indicating sufficient directionality for multi-standard communication systems, such as WLAN, ISM, and satellite uplink. The proposed antenna design successfully balances high performance with structural simplicity and compact dimensions. These characteristics make it suitable for a variety of wireless communication applications, where size and multi-band functionality are critical. The use of SRRs contributes to enhanced bandwidth and performance, while the offset-fed monopole configuration ensures broad compatibility with diverse wireless standards. The design achieves a practical and effective solution for future communication systems requiring compact yet high-performance antenna structures.
TL;DR: This study provides a thorough examination of parametric and generative design processes for 3D printing applications, evaluating their techniques, industrial uses, benefits, problems and future potential.
: The integration of parametric and generative design approaches into cloud-based computer-aided design (CAD) and computer-aided manufacturing (CAM) platforms is transforming contemporary product development, especially in 3D printing applications. Parametric design prioritizes c…
TL;DR: A Reliable Resource Placement with Migration Function (MF) method to reduce the outage in SC communications is proposed and reduces outage time by 13.79%, network overload by 14.04% and improves the response ratio by 13.41% for the maximum network load.
: Smart City (SC) development with technological aspects depends on wireless communication and intelligent networks such as the Internet of Things (IoT). Wireless networks and IoT interconnect resources and projects them to be ubiquitous for various applications and user services…
TL;DR: An Adaptive Binary Genetic Algorithm (A-BGA) is developed that introduces population-diversity-driven dynamic crossover and mutation rates, and reformulates the fitness as a bi-objective trade-off between prediction RMSE and feature cardinality to form a comprehensive framework that enhances prediction efficiency and uncertainty modeling.
: As the share of renewable energy in power systems continues to grow, improving prediction accuracy has become critical for enhancing system flexibility and reducing operational costs. In this paper, we propose two novel optimization methods tailored for renewable energy predict…
TL;DR: A conditional generative adversarial networks method that integrates the machine learning with the deep learning to detect the hardware Trojans injected in Register-Transfer Level code and it contributes to enhancing the security and trustworthiness of ICs against hardware Trojan attacks.
: Hardware Trojan (HT) can compromise the security of a system by changing the integrated circuit (IC) functionality and reducing the system ꞌ s reliability. To handle this issue, machine learning has been widely used to analyze the datasets extracted from circuits to detect hard…
: Accurate demand forecasting of railway freight car components is critical for effective material planning under condition-based maintenance (CBM). Traditional forecasting methods often fail to capture nonlinear patterns and perform poorly with small and uncertain datasets. This…
TL;DR: A new intrusion detecting framework is presented in this paper that is based on a combination of a Domain-adaptive Gated Deep Belief Network (DomG-DeNet) and an enhanced optimization method known as Builder-on-Zebra Recurrent Dropout Optimization (BoZ-RDO).
: Due to the rapid growth of the modern network infrastructures and the rise in the sophistication of the attacks by criminals based on networks, intrusion detection system (IDS) has become a crucial component in offering network security. The common machine learning and the exis…