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    Latency and power optimization in terahertz UAV-assisted vehicular networks across diverse atmospheric profile conditions
    (Springer, 2025) Korpe, Enis; Akkas, Mustafa Alper; Ozturk, Yavuz
    Terahertz (THz) communication has emerged as a key technology for high-speed wireless networks, particularly in scenarios where conventional frequency bands fail to meet growing data demands. With its potential for ultra-low latency, broad bandwidth, and robust connectivity, THz communication offers a suitable infrastructure for intelligent transportation systems and autonomous vehicles, especially within Vehicle-to-Everything (V2X) and Unmanned Aerial Vehicle (UAV) communication networks. This study aims to optimize THz communication between UAVs and ground vehicles under varying atmospheric conditions. Specifically, an artificial intelligence (AI)-based scheme is proposed to simultaneously minimize latency and transmission power while maintaining a sufficient signal-to-noise ratio (SNR) for successful communication. The proposed method integrates a dual-objective Particle Swarm Optimization (PSO) algorithm with the Line-by-Line Radiative Transfer Model (LBLRTM), which accurately models atmospheric absorption characteristics. Designed for critical scenarios such as emergency response operations, the scheme dynamically determines UAV positions and transmission powers to ensure both energy efficiency and low-latency communication. Simulation results demonstrate that the proposed approach achieves sufficient SNR levels and low latency across all atmospheric models. These findings highlight the potential of the AI-based approach to enhance energy efficiency and ensure sustainable connectivity in THz-enabled networks for time-sensitive applications.
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    Öğe
    Measurement of important tribocorrosion properties of titanium implant and assessment with digital image processing
    (Pamukkale Univ, 2025) Irmak, Emrah; Korpe, Enis
    Titanium implants are mechanical systems where tribocorrosion is frequently observed at the interface between the implant and the abutment alloy. In this paper, important parameters in terms of tribocorrosion such as abrasion coefficient, abrasion volume loss and corrosion rate were determined experimentally in a laboratory environment by preparing a sufficient number ofsamples obtained from the field for this material (Titanium-Ti6Al4V), which is actively used in surgeries. Comprehensive analysis of these mechanical systems in body-like environments contributes to a better understanding of the material loss caused by abrasion and corrosion interactions occurring at the interface between the implant and the abutment alloy. The samples were subjected to dry sliding wear with the pin-on-disc system in accordance with the relevant standards for a certain number of cycles, during which abrasion volume loss and friction coefficient were measured simultaneously. The results of these experiments were examined to evaluate the degree to which titanium is resistant to material loss due to abrasion and corrosion in body implants. It was found that the abrasion coefficient decreased by 51% when 10 N load was applied by 22% when 20 N load was applied, and by 2% when 30 N load was applied. The samples screws were exposed to 15% more corrosive abrasion and it was found that they had 6% higher corrosion rate in electrochemical corrosion test. Additionally, the morphological features of the abraided and corroded surfaces of Ti6Al4V alloy were analyzed and interpreted using scanning electron microscopy (SEM) and digital image processing techniques.
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    Performance evaluation of vehicular communication in terahertz band
    (Slovak Univ Technology, 2024) Korpe, Enis; Akkas, Mustafa Alper; Sokullu, Radosveta
    The Terahertz (THz) band is seen as one of the potentially essential technologies to meet the data throughput requirements of terabits per second (Tbits) in future networks. Considering vehicular communication in particular, the current vehicular communication technologies cannot cope with the rapidly increasing data traffic. To deliver increased capacity and data rate with reduced latency, new technologies and methodologies are therefore required. It is recognized that one possible technology to meet these needs is THz technology. Since the change in distance between vehicles due to their speed affects THz communication, channel modeling was carried out for single-lane and multi-lane vehicular communication scenarios in this study. The system's performance was also examined. Performance metrics were determined as path loss, signal-to-noise ratio (SNR), capacity and bit error rate (BER). While performing these analyses, the absorption of THz waves is taken into account and the High-Resolution Transmission Molecular Absorption Database (HITRAN) was used to model it. As a result, the most appropriate circumstances for successful vehicular communication have been identified and studied.
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    Swarm intelligence-inspired localization and power control for terahertz (THz) UAV-vehicle networks
    (Elsevier, 2025) Korpe, Enis; Akkas, Mustafa Alper; Ozturk, Yavuz
    In recent years, terahertz (THz) communication has gained significant attention as a transformative technology for high-speed wireless networks, addressing the limitations of conventional frequency bands in meeting the escalating demand for data transmission. THz communication is particularly critical in vehicle-to-everything (V2X) and unmanned aerial vehicle (UAV)-based communication networks, where ultra-low latency, high bandwidth, and reliable connectivity are essential. Operating in the frequency spectrum between the microwave and infrared bands, THz communication offers the potential for multi-gigabit data transmission rates, rendering it a promising enabler for next-generation intelligent transportation systems, autonomous vehicles, and UAV-supported applications. Furthermore, artificial intelligence (AI) emerges as a pivotal tool to enhance the reliability and efficiency of THz-based V2X and UAV communication networks by enabling the prediction of network traffic patterns and mobility dynamics. This study introduces a swarm intelligence-based AI approach designed to optimize system performance by minimizing latency and transmission power requirements while ensuring the required signal-to-noise ratio (SNR) within a UAV-assisted vehicular network operating in the THz band. The proposed methodology employs a dual-objective optimization framework that balances latency and transmission power within a predefined communication time frame. Comparative analysis is conducted between a baseline network with randomly distributed UAVs and a network employing UAV deployment guided by the proposed AI scheme. Also, the performance of proposed method is compared with existing swarm intelligence algorithms. Performance metrics, including SNR and latency, are evaluated to assess the system's efficacy. The channel modeling process leverages the Line-by-Line Radiative Transfer Model (LBLRTM) to characterize the propagation environment in the UAV-assisted vehicular network.