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In today's world, the significance of reducing energy consumption globally is increasing, making it imperative to prioritize energy efficiency in 5th-generation (5G) networks. However, it is crucial to ensure that these energy-saving measures do not compromise the Key Performance Indicators (KPIs), such as user experience, quality of service (QoS), or other important aspects of the network. Advanced wireless technologies have been integrated into 5G network designs at multiple network layers to address this difficulty. The integration of emerging technology trends, such as machine learning (ML), which is a subset of artificial intelligence (AI), and AI's rapid improvements have made the integration of these trends into 5G networks a significant topic of research. The primary objective of this survey is to analyze AI's integration into 5G networks for enhanced energy efficiency. By exploring this intersection between AI and 5G, we aim to identify potential strategies and techniques for optimizing energy consumption while maintaining the desired network performance and user experience. [ABSTRACT FROM AUTHOR]

The intersection of cybersecurity and opportunistic networks has ushered in a new era of innovation in the realm of wireless communications. In an increasingly interconnected world, where seamless data exchange is pivotal for both individual users and organizations, the need for efficient, reliable, and sustainable networking solutions has never been more pressing. Opportunistic networks, characterized by intermittent connectivity and dynamic network conditions, present unique challenges that necessitate innovative approaches for optimal performance and sustainability. This paper introduces a groundbreaking paradigm that integrates the principles of cybersecurity with opportunistic networks. At its core, this study presents a novel routing protocol meticulously designed to significantly outperform existing solutions concerning key metrics such as delivery probability, overhead ratio, and communication delay. Leveraging cybersecurity's inherent strengths, our protocol not only fortifies the network's security posture but also provides a foundation for enhancing efficiency and sustainability in opportunistic networks. The overarching goal of this paper is to address the inherent limitations of conventional opportunistic network protocols. By proposing an innovative routing protocol, we aim to optimize data delivery, minimize overhead, and reduce communication latency. These objectives are crucial for ensuring seamless and timely information exchange, especially in scenarios where traditional networking infrastructures fall short. By large-scale simulations, the new model proves its effectiveness in the different scenarios, especially in terms of message delivery probability, while ensuring reasonable overhead and latency. [ABSTRACT FROM AUTHOR]

This study investigates the impact of shear reinforcement amount and arrangement on the shear capacity of shallow/wide RC beams. Seven specimens of shallow/wide beams with different ultimate shear reinforcement stress (µ.Fys), longitudinal spacing to depth ratio (S/d), and transversal spacing to depth ratio (S'/d) were tested under a monotonic three-point bending test. All the specimens were designed to fail at shearing. The results showed that the shear reinforcement was fully functioning until it yielded; also, the amount of shear reinforcement had the major impact on the shear capacity; in addition, the transverse spacing had more influence on the shear capacity than the longitudinal spacing. The measured shear capacities were compared to six design codes, in which the results ranged from 95% to 110%, with the Japanese code (JSCE) being the closest to the experimental results. Two AI-based predicting equations, "Genetic Programming" (GP) and "Evolutionary Polynomial Regression" (EPR), were also compared to the experimental, with accuracies of 78% and 86% of the measured capacities, respectively. Initial stiffness, final stiffness, dissipated energy, and ductility were all discussed for the seven specimens, with ultimate shear reinforcement stress being the most impactful on the total shear capacity of the wide beams. [ABSTRACT FROM AUTHOR]