Search Results (424)

Silicone oil-based magnetic liquids containing carbon nanotubes (CNTs) were prepared using an in situ chemical coprecipitation method. The surface modification of Fe₃O₄/CNT composite particles was carried out by using three silane coupling agents: γ-aminopropyltriethoxysilane (550), γ-methacryloxypropyltrimethoxysilane (570), and phenyltrimethoxysilane (7030). Infrared Spectroscopy (IR), Transmission Electron Microscopy (TEM), and X-ray Diffraction (XRD) were used to confirm the successful doping of CNTs and the effective coating of the coupling agents. The rheological behavior of the magnetic liquids was systematically studied using an Anton Paar Rheometer. The results show that viscosity decreases exponentially with increasing temperature (fitting the Arrhenius equation), increases and tends to saturate with rising magnetic field intensity, and exhibits shear-thinning characteristics with increasing shear rate. Among the samples, Fe₃O₄@7030 has the best visco-thermal performance due to the benzene ring structure, which reduces the symmetry of the molecular chains. In contrast, Fe₃O₄@570 shows the most significant magneto-viscous effect (viscosity variation of 161.4%) as a result of the long-chain structure enhancing the steric hindrance of the magnetic dipoles. Full article

Static Priority-based Multiple Access (SPMA) is an emerging and promising wireless MAC protocol which is widely used in Unmanned Aerial Vehicle (UAV) networks. UAV (Unmanned Aerial Vehicle) networks, also known as drone networks, refer to a system of interconnected UAVs that communicate and collaborate to perform tasks autonomously or semi-autonomously. These networks leverage wireless communication technologies to share data, coordinate movements, and optimize mission execution. In SPMA, traffic arriving at the UAV network node can be divided into multiple priorities according to the information timeliness, and the packets of each priority are stored in the corresponding queues with different thresholds to transmit packet, thus guaranteeing the high success rate and low latency for the highest-priority traffic. Unfortunately, the multi-priority queue scheduling of SPMA deprives the packet transmitting opportunity of low-priority traffic, which results in unfair conditions among different-priority traffic. To address this problem, in this paper we propose the method of Adaptive Credit-Based Shaper with Reinforcement Learning (abbreviated as ACBS-RL) to balance the performance of all-priority traffic. In ACBS-RL, the Credit-Based Shaper (CBS) is introduced to SPMA to provide relatively fair packet transmission opportunity among multiple traffic queues by limiting the transmission rate. Due to the dynamic situations of the wireless environment, the Q-learning-based reinforcement learning method is leveraged to adaptively adjust the parameters of CBS (i.e., idleslope and sendslope) to achieve better performance among all priority queues. The extensive simulation results show that compared with traditional SPMA protocol, the proposed ACBS-RL can increase UAV network throughput while guaranteeing Quality of Service (QoS) requirements of all priority traffic. Full article

Machine learning techniques have revolutionized physical layer security (PLS) and provided opportunities for optimizing the performance and security of modern communication systems. In this study, we propose the first machine learning-assisted random communication system (ML-RCS). It comprises a pretrained decision tree (DT)-based receiver that extracts binary information from the transmitted random noise carrier signals. The ML-RCS employs skewed alpha-stable ($\alpha$-stable) noise as a random carrier to encode the incoming binary bits securely. The DT model is pretrained on an extensively developed dataset encompassing all the selected parameter combinations to generate and detect the $\alpha$-stable noise signals. The legitimate receiver leverages the pretrained DT and a predetermined key, specifically the pulse length of a single binary information bit, to securely decode the hidden binary bits. The performance evaluations included the single-bit transmission, confusion matrices, and a bit error rate (BER) analysis via Monte Carlo simulations. The fact that the BER reached 10⁻³ confirms the ability of the proposed system to establish successful secure communication between a transmitter and legitimate receiver. Additionally, the ML-RCS provides an increased data rate compared to previous random communication systems. From the perspective of security, the confusion matrices and computed false negative rate of 50.2% demonstrate the failure of an eavesdropper to decode the binary bits without access to the predetermined key and the private dataset. These findings highlight the potential ability of unconventional ML-RCSs to promote the development of secure next-generation communication devices with built-in PLSs. Full article

Terahertz (THz) frequencies, spanning from 0.1 to 1 THz, are poised to play a pivotal role in the development of future 6G wireless communication systems. These systems aim to utilize photonic technologies to enable ultra-high data rates—on the order of terabits per second—while maintaining low latency and high efficiency. In this work, we present a novel photonic method for generating sub-THz vector signals within the THz band, employing a semiconductor optical amplifier (SOA) and phase modulator (PM) to create an optical frequency comb, combined with in-phase and quadrature (IQ) modulation techniques. We demonstrate, both through simulation and experimental setup, the generation and successful transmission of a 0.1 THz vector. The process involves driving the PM with a 12.5 GHz radio frequency signal to produce the optical comb; then, heterodyne beating in a uni-traveling carrier photodiode (UTC-PD) generates the 0.1 THz radio frequency signal. This signal is transmitted over distances of up to 30 km using single-mode fiber. The resulting 0.1 THz electrical vector signal, modulated with quadrature phase shift keying (QPSK), achieves a bit error ratio (BER) below the hard-decision forward error correction (HD-FEC) threshold of ${3.8 \times 10}^{-3}$. To the best of our knowledge, this is the first experimental demonstration of a 0.1 THz photonic vector THz wave based on an SOA and a simple PM-driven optical frequency comb. Full article

To address the issues of bulky structure and complex transmission systems in current transplanters, a compact, electric-driven automatic transplanter was designed. Using pepper plug seedlings as the test subject, this study investigated plug tray dimensions and planting patterns. According to the design requirement that the width of the single-row transplanter must be less than 62.5 cm, a three-dimensional transplanter model was constructed. The transplanter comprises a coaxially installed dual-layer seedling conveying device and a sector-expanding automatic seedling picking and depositing device. The structural dimensions, drive configurations, and driving forces of the transplanter were also determined. Finally, the circuit and pneumatic system were designed, and the transplanter was assembled. Both bench and field tests were conducted to select the optimal working parameters. The test results demonstrated that the seedling picking and depositing mechanism met the required operational efficiency. In static seedling picking and depositing tests, at three transplanting speeds of 120 plants/min, 160 plants/min, and 200 plants/min, the success rates of seedling picking and depositing were 100%, 100%, and 97.5%, respectively. In the field test, at three transplanting speeds of 80 plants/min, 100 plants/min, and 120 plants/min, the transplanting success rates were 94.17%, 90.83%, and 88.33%, respectively. These results illustrate that the compact, electric-driven seedling conveying and picking and depositing devices meet the operational demands of automatic transplanting, providing a reference for the miniaturization and electrification of transplanters. Full article

This article first constructs a multi-layer deep learning neural network to help understand the structural characteristics of communication data, thereby learning complex functions and obtaining the predicted network values. At the same time, signal transmission is achieved through the interconnection of neurons, the representation performance of which is enhanced through activation functions; this completes the modeling of IoT communication models. Then, we use the analytic hierarchy process to construct a deep learning autoencoder and extract the feature elements of network communication reliability parameters. Finally, we use the obtained total reliability indicators as features for automatic coding and evaluate the mapping relationship between indicators. The results show that the success rates of handovers in deep leaning-based IoT communication based are all greater than 99.6%. The predicted transmission rate can reach a maximum of 99.5%, achieving error free communication output and improving fidelity. Full article

This paper proposes a deeply integrated model called CAS-GNN, aiming to solve the collaborative path-planning problem for multi-agent vehicles operating in dynamic environments. Our proposed model integrates CAS-UNet and Graph Neural Network (GNN), and, by introducing a dynamic edge enhancement module and a dynamic edge weight update module, it improves the accuracy of obstacle boundary recognition in complex scenarios and adaptively changes the influence of different edges during the information transmission process. We generate data through online trajectory optimization to enhance the model’s adaptability to dynamic environments. Simulation results show that our proposed CAS-GNN model has good performance in path planning. In a dynamic scenario involving six vehicles, our model achieved a success rate of 92.8%, a collision rate of 0.0836%, and a trajectory efficiency of 64%. Compared with the traditional A-GNN model, our proposed CAS-GNN model improves the planning success rate by 2.7% and the trajectory efficiency by 8%, while reducing the collision rate by 23%. Full article

Traditional cryptographic systems face critical vulnerabilities posed by the rapid advancement of quantum computing, particularly concerning key exchange mechanisms and the quality of entropy sources for random number generation. To address these challenges, this paper proposes a multi-layered, quantum-resistant hybrid cryptographic architecture. First, to ensure robust data confidentiality and secure key establishment, the architecture employs AES-256 (Advanced Encryption Standard-256) for data encryption and utilizes the Kyber Key Encapsulation Mechanism (KEM), which is based on the Learning With Errors (LWE) problem, for secure key exchange. Second, to further bolster overall security by establishing a high-quality cryptographic foundation, we design a TRNG (true random number generator) system based on a multi-level Ring Oscillator (RO) architecture (employing 5, 7, 9, and 11 inverter stages), which provides a reliable and high-quality entropy source. Third, to enable intelligent and adaptive security management, we introduce FA-Kyber (Flow-Adaptive Kyber), a dual-trigger key exchange framework facilitating dynamic key management strategies. Experimental evaluations demonstrate that our implementation exhibits robust performance, achieving an encrypted data transmission throughput of over 550 Mbps with an average end-to-end latency of only 3.14 ms and a key exchange success rate of 99.99% under various network conditions. The system exhibits excellent stability under network congestion, maintaining 86% of baseline throughput under moderate stress, while adaptively increasing the key rotation frequency to enhance security. This comprehensive approach strikes an optimal balance between performance and post-quantum resilience for sensitive communications. Full article

This study presents a new intelligent aquatic farming surveillance system that tackles real-time monitoring challenges in the industry. The main technical break-throughs of this system are evident in four key aspects: First, it achieves the smooth integration of remotely operated vehicles (ROVs), sensors, and real-time data transmission. Second, it uses a mobile communication architecture with buoy relay stations for distributed edge computing. This design supports future upgrades to Beyond 5G and satellite networks for deep-sea applications. Third, it features a multi-terminal control system that supports computers, smartphones, smartwatches, and centralized hubs, effectively enabling monitoring anytime, anywhere. Fourth, it incorporates a cost-effective modular design, utilizing commercial hardware and innovative system integration solutions, making it particularly suitable for farms with limited resources. The data indicates that the system’s 4G connection is both stable and reliable, demonstrating excellent performance in terms of data transmission success rates, control command response delays, and endurance. It has successfully processed 324,800 data transmission events, thoroughly validating its reliability in real-world production environments. This system integrates advanced technologies such as the Internet of Things, mobile communications, and multi-access control, which not only significantly enhance the precision oversight capabilities of marine farming but also feature a modular design that allows for future expansion into satellite communications. Notably, the system reduces operating costs while simultaneously improving aquaculture efficiency, offering a practical and intelligent solution for small farmers in resource-limited areas. Full article

Massive multiple input–multiple output (M-MIMO) is a promising and pivotal technology in contemporary wireless communication systems that can effectively enhance link reliability and data throughput, especially in uplink scenarios. Even so, the receiving end requires more computational complexity to reconstitute the signal. This problem has emerged in fourth-generation (4G) MIMO system; with the dramatic increase in demand for devices and data in beyond-5G (B5G) systems, this issue will become yet more obvious. To take into account both complexity and signal-revested capability at the receiver, this study uses the matrix iteration method to avoid the staggering amount of operations produced by the inverse matrix. Then, we propose a highly efficient multi-user detector (MUD) named hybrid SOR-based Chebyshev acceleration (CHSOR) for the uplink of M-MIMO orthogonal frequency-division multiplexing (OFDM) and universal filtered multi-carrier (UFMC) waveforms, which can be promoted to B5G developments. The proposed CHSOR scheme includes two stages: the first consists of successive over-relaxation (SOR) and modified successive over-relaxation (MSOR), combining the advantages of low complexity of both and generating a better initial transmission symbol, iteration matrix, and parameters for the next stage; sequentially, the second stage adopts the low-cost iterative Chebyshev acceleration method for performance refinement to obtain a lower bit error rate (BER). Under constrained evaluation settings, Section (Simulation Results and Discussion) presents the results of simulations performed in MATLAB version R2022a. Results show that the proposed detector can achieve a 91.624% improvement in BER performance compared with Chebyshev successive over-relaxation (CSOR). This is very near to the performance of the minimum mean square error (MMSE) detector and is achieved in only a few iterations. In summary, our proposed CHSOR scheme demonstrates fast convergence compared to previous works and as such possesses excellent BER and complexity performance, making it a competitive solution for uplink M-MIMO B5G systems. Full article

Unmanned Underwater Vehicles (UUVs) play an irreplaceable role in marine exploration, environmental monitoring, and national defense. The UUV depends on underwater acoustic communication (UAC) technology to enable reliable data transmission and support efficient collaboration. As the complexity of UUV missions has increased, secure UAC has become a critical element in ensuring successful mission execution. However, underwater channels are inherently characterized by high error rates, limited bandwidth, and signal interference. These problems severely limit the efficacy of traditional security methods and expose UUVs to the risk of data theft and signaling attacks. Cryptography-based security methods are important means to protect data, effectively balancing security requirements and resource constraints. They provide technical support for UUVs to build secure communication. This paper systematically reviews key advances in cryptography-based secure UAC technologies, focusing on three main areas: (1) efficient authentication protocols, (2) lightweight cryptographic algorithms, and (3) fast cryptographic synchronization algorithms. By comparing the performance boundaries and application scenarios of various technologies, we discuss the current challenges and critical issues in underwater secure communication. Finally, we explore future research directions, aiming to provide theoretical references and technical insights for the further development of secure UAC technologies for UUVs. Full article

In this paper, we investigate a covert communication system with a full-duplex decode-and-forward (DF) relay and introduce a user-relaying scheme that maximizes the covert rate while ensuring the covertness requirement. In our system model, Alice (transmitter) sends regular data to Carol (regular user) and occasionally embeds covert data for Bob (covert user). Meanwhile, Willie (warden) monitors for covert transmissions. Carol assists Alice by acting as a full-duplex DF relay, decoding both data types via successive interference cancellation and relaying covert data using phase steering and power allocation to confuse Willie. Our proposed scheme adopts a novel approach in which the covert data received by Willie is perfectly canceled, optimizing Alice’s and Carol’s transmissions to maximize the covert rate while keeping Willie’s detection probability below a given threshold. Full article

As Industry 5.0 progresses, the demand for zero-touch configuration in industrial automation and smart manufacturing is increasing. This paper proposes a dynamic configuration management framework for Time-Sensitive Networking (TSN), aiming to address the challenges of flexibility and adaptability in dynamic network environments. A zero-touch configuration model is presented for TSN by incorporating a Delay-Aware Shortest Path Search (DASPS) algorithm to improve scheduling success rates. Simulation results demonstrate the ability of the framework to reconfigure networks within 2.67 milliseconds. The DASPS algorithm achieves a scheduling success rate of 70.22% for 1000 TSN flows, in contrast to only 22.23% achieved by the Shortest Path Search (SPS) algorithm. The proposed model effectively adapts to dynamic network changes, guaranteeing real-time data transmission. To further evaluate system adaptability, path entropy is introduced as a metric to quantitatively assess the balance of scheduling outcomes under topological changes. In the event of link failures, path entropy experiences a sharp decline but rapidly recovers after reconfiguration, demonstrating the system’s strong self-healing capability. Full article

This study evaluated the relationship between the microstructure, photoluminescence, and photocatalytic properties of newly synthesized nanostructured phosphor materials. The combustion method was used to create samples of down-converting SrGd₂O₄ doped with Dy³⁺ ions (1, and 7 at%) and up-converting SrGd₂O₄ co-doped with varying quantities of Yb³⁺ ions (2, and 6 at%) and a constant quantity of Ho³⁺ ions (1 at%). Transmission electron microscopy (TEM) revealed the existence of porous agglomerated round-shaped particles, with the size around 150 nm, arranged in network-like structures. Energy dispersive X-ray spectroscopy (EDS) confirmed the presence of all structural elements and their homogeneous distribution throughout the particles. The presence of specific emission peaks associated with Dy³⁺ or Ho³⁺ dopant ions was demonstrated by luminescent measurement. The degradation processes of specific organic dyes (methylene blue for up-converters and rhodamine B for down-converters) under simulated sun irradiation were used to investigate photocatalytic activity. A reduction in dye concentration in aqueous solutions was measured using UV/Vis absorption spectroscopy. The results showed a successful dye breakdown rate after 4 h, and aliquots of the working solutions were obtained at precise intervals. Additionally, the results indicated that samples with the highest luminescence intensity exhibited superior photocatalytic activity, suggesting a significant promise for usage as multifunctional materials. Full article

Hydrogel patches have gained significant attention in wound healing applications as they are similar to hydrogel dressings due to their moisture-retentive properties, biocompatibility, and ability to promote tissue regeneration. In this study, gelatin-based hydrogels crosslinked with genipin and incorporated with hyaluronic acid (HA) were developed to enhance mechanical stability, swelling behavior, and structural integrity. Fourier transform infrared (FTIR), thermogravimetric (TGA), and energy-dispersive X-ray (EDX) analyses were conducted and confirmed successful crosslinking and good thermal stability, ensuring hydrogel durability under physiological conditions. The optimized hydrogel (GE_HA_GNP) exhibited a sufficient water vapor transmission rate (WVTR), swelling ratio, and contact angle, allowing for effective wound exudate absorption and hydration maintenance, which is essential for accelerated healing. The findings demonstrate that the crosslinked hydrogels were able to maintain a WVTR of 500 to 1500 gm⁻² day⁻¹, a contact angle of >40°, and a swelling ratio of 700–1000%. The combination of genipin as a crosslinker and the addition of HA significantly improved the mechanical properties and biocompatibility of the hydrogels, making them promising candidates for an alternative treatment for atopic dermatitis and a potential wound dress-ing. Furthermore, the hydrogel patches show potential for future drug delivery appli-cations, with further studies required to evaluate their antimicrobial properties and long-term clinical performance. Full article