Search Results (65)

This study proposes a dual-element wideband circularly polarized (CP) slot-integrated multiple-input multiple-output (MIMO) antenna with an X-notch square-shaped artificial magnetic conductor (AMC) for dedicated short-range communications (DSRC) applications. The proposed antenna design consists of two substrate layers separated by an air gap. The upper layer features a dual-element coplanar waveguide-fed slot antenna and a defected ground structure decoupling isolator, while the lower layer comprises an 8 × 8 array of X-notch square-shaped elemental units, functioning as an AMC reflector. Characteristic mode analysis shows that circular polarization is produced by the dominant orthogonal mode pair (modes J₅ and J₆), whose modal significance exceeds 0.92 and whose characteristic angle separation is 82° around the 5.9 GHz DSRC band. An I-shaped slot embedded in the ground plane of the upper layer serves as a defected ground structure isolator to suppress mutual coupling between antenna elements. Meanwhile, the X-notch square AMC reflector enhances radiation characteristics and antenna gain. The measured return loss bandwidth and axial ratio bandwidth are 32% (4.72–6.61 GHz) and 21.18% (5.2–6.45 GHz), respectively. The dual-element antenna scheme achieves high isolation exceeding 19 dB, with a maximum gain of 8.6 dBic at 5.9 GHz. The envelop correlation coefficient remains below 0.003, while the diversity gain exceeds 9.98 dB. Full article

Automatic modulation classification (AMC) is a fundamental technique in wireless communication systems, as it enables the identification of modulation schemes at the receiver without prior knowledge, thereby promoting efficient spectrum utilization. Recent advancements in deep learning (DL) have significantly enhanced classification performance by enabling neural networks (NNs) to learn complex decision boundaries directly from raw signal data. However, many existing NN-based AMC methods employ deep or specialized network architectures, which, while effective, tend to involve substantial structural complexity. To address this issue, we present a simple NN architecture that utilizes features derived from Hankelized matrices to extract informative signal representations. In the proposed approach, received signals are first transformed into Hankelized matrices, from which informative features are extracted using singular value decomposition (SVD). These features are then fed into a compact, fully connected (FC) NN for modulation classification across a wide range of signal-to-noise ratio (SNR) levels. Despite its architectural simplicity, the proposed method achieves competitive performance, offering a practical and scalable solution for AMC tasks at the receiver in diverse wireless environments. Full article

Orthogonal time–frequency space (OTFS) modulation has emerged as a promising technology to alleviate the effects of the Doppler shifts in high-mobility environments. As a prerequisite to demodulation and signal processing, automatic modulation classification (AMC) is essential for OTFS systems. However, a very limited number of works have focused on this issue. In this paper, we propose a novel AMC approach for OTFS systems. We build a dual-stream convolutional neural network (CNN) model to simultaneously capture multi-domain signal features, which substantially enhances recognition accuracy. Moreover, we propose a differentiated embedded pilot structure that incorporates information about distinct modulation schemes to further improve the separability of modulation types. The results of the extensive experiments carried out show that the proposed approach can achieve high classification accuracy even under low signal-to-noise ratio (SNR) conditions and outperform the state-of-the-art baselines. Full article

This work presents a novel dual-polarized antenna array tailored for Internet of Things (IoT) applications, specifically designed to operate in the millimeter-wave (mm-wave) spectrum within the frequency range of 30–60 GHz. Leveraging printed ridge gap waveguide (PRGW) technology, the antenna ensures robust performance by eliminating parasitic radiation from the feed network, thus significantly enhancing the reliability and efficiency required by IoT communication systems, particularly for smart cities, autonomous vehicles, and high-speed sensor networks. The proposed antenna achieves superior radiation characteristics through a cross-shaped magneto-electric (ME) dipole backed by an artificial magnetic conductor (AMC) cavity and electromagnetic bandgap (EBG) structures. These features suppress surface waves, reduce edge diffraction, and minimize back-lobe emissions, enabling stable, high-quality IoT connectivity. The antenna demonstrates a wide impedance bandwidth of 24% centered at 30 GHz and exceptional isolation exceeding 40 dB, ensuring interference-free dual-polarized operation crucial for densely populated IoT environments. Fabrication and testing validate the design, consistently achieving a gain of approximately 13.88 dBi across the operational bandwidth. The antenna’s performance effectively addresses the critical requirements of emerging IoT systems, including ultra-high data throughput, reduced latency, and robust wireless connectivity, essential for real-time applications such as healthcare monitoring, vehicular communication, and smart infrastructure. Full article

With the rapid development of Wi-Fi 6/6E and dual-band wireless systems, there is an increasing demand for compact antennas with balanced high-gain performance across both 2.4 GHz and 5 GHz bands. However, most existing dual-band metasurface antennas face challenges in uneven gain distribution between lower/higher-frequency bands and structural miniaturization. This paper proposes a high-gain dual-band metasurface antenna based on an artificial magnetic conductor (AMC) array, which has a significant advantage in miniaturization and improving antenna performance. Two types of dual-band AMC structures are applied to design the metasurface antenna. The optimal antenna with dual-slot AMC array operates in the 2.42–2.48 GHz and 5.16–5.53 GHz frequency bands, with a 25% size reduction compared to the reference dual-band U-slot antenna. Meanwhile, high gains of 7.65 dBi and 8 dBi are achieved at 2.4 GHz and 5 GHz frequency bands, respectively. Experimental results verify stable radiation gains across the operation bands, where the total efficiency remains above 90%, agreeing well with the simulation results. This research provides an effective strategy for high-gain and dual-band metasurface antennas, offering a promising solution for integrated modern wireless systems such as Wi-Fi 6, Bluetooth, and MIMO technology. Full article

The Finite Difference Time-Domain (FDTD) method is a powerful tool for electromagnetic field analysis. In this work, we develop a variation of the algorithm to accurately calculate antenna, microwave circuit, and target scattering problems. To improve efficiency, a single-field (SF) FDTD method is proposed as a numerical solution to the time-domain Helmholtz equations. New formulas incorporating resistors and voltage sources are derived for the SF-FDTD algorithm, including hybrid implicit–explicit and weakly conditionally stable SF-FDTD methods. The correctness of these formulas is verified through numerical simulations of a newly designed dual-band wearable antenna with an artificial magnetic conductor (AMC) structure. A novel antenna fed by a coplanar waveguide with a compact size of 15.6 × 20 mm² has been obtained after being optimized through an artificial intelligent method. A double-layer, dual-frequency AMC structure is designed to improve the isolation between the antenna and the human body. The simulation and experiment results with different bending degrees show that the antenna with the AMC structure can cover two frequency bands, 2.4 GHz–2.48 GHz and 5.725 GHz–5.875 GHz. The gain at 2.45 GHz and 5.8 GHz reaches 5.3 dBi and 8.9 dBi, respectively. The specific absorption rate has been reduced to the international standard range. In particular, this proposed SF-FDTD method can be extended to analyze other electromagnetic problems with fine details in one or two directions. Full article

Accurate forecasting is crucial for enhancing the flexibility and controllability of power grids. Traditional forecasting methods mainly focus on modeling based on a single data source, which leads to an inability to fully capture the underlying relationships in wind power data. In addition, current models often lack dynamic adaptability to data characteristics, resulting in lower prediction accuracy and reliability under different time periods or weather conditions. To address the aforementioned issues, an ultra-short-term hybrid probabilistic prediction model based on MultiFusion, ChronoNet, and adaptive Monte Carlo (AMC) is proposed in this paper. By combining multi-source data fusion and a multiple-gated structure, the nonlinear characteristics and uncertainties of wind power under various input conditions are effectively captured by this model. Additionally, the AMC method is applied in this paper to provide comprehensive, accurate, and flexible ultra-short-term probabilistic predictions. Ultimately, experiments are conducted on multiple datasets, and the results show that the proposed model not only improves the accuracy of deterministic prediction but also enhances the reliability of probabilistic prediction intervals. Full article

Despite advancements in direct sensing technologies, accurately capturing complex wave–structure interactions remain a significant challenge in ship and ocean engineering. Ensuring the safety and reliability of floating structures requires precise monitoring of dynamic water interactions, particularly in extreme sea conditions. Recent developments in computer vision and artificial intelligence have enabled advanced image-based sensing techniques that complement traditional measurement methods. This study investigates the application of Computerized Video Analysis (CVA) for water surface tracking in maritime experimental tests, marking the first exploration of digitalized experimental video analysis at the Australian Maritime College (AMC). The objective is to integrate CVA into laboratory data acquisition systems, enhancing the accuracy and robustness of wave interaction measurements. A novel algorithm was developed to track water surfaces near floating structures, with its effectiveness assessed through a Wave Energy Converter (WEC) experiment. The method successfully captured wave runup interactions with the hull form, operating alongside traditional sensors to evaluate spectral responses at a wave height of 0.4 m. Moreover, its application in irregular wave conditions demonstrated the algorithm’s capability to reliably detect the waterline across varying wave heights and periods. The findings highlight CVA as a reliable and scalable approach for improving safety assessments in maritime structures. Beyond controlled laboratory environments, this method holds potential for real-world applications in offshore wind turbines, floating platforms, and ship stability monitoring, contributing to enhanced structural reliability under operational and extreme sea states. Full article

This study investigates the influence of nano-sized reinforcements on aluminum matrix composites’ mechanical and tribological properties. Microstructural analysis revealed that introducing nanoparticles led to grain refinement, reducing the grain size from 129.7 μm to 41.3 μm with 2 wt.% TiO₂ addition. Furthermore, ultrasonic-assisted squeeze casting of AA6061 composites reinforced with TiO₂ and Al₂O₃ resulted in a 52% decrease in grain size, demonstrating nano-reinforcements’ effectiveness in refining the matrix structure. Despite these advantages, the high surface energy of nanoparticles causes agglomeration, which can undermine composite performance. However, ultrasonic-assisted stir casting reduced agglomeration by approximately 80% compared to conventional stir casting, and cold isostatic pressing improved dispersion uniformity by 27%. The incorporation of nano-reinforcements such as SiC, Al₂O₃, and TiC significantly enhanced the material properties, with hardness increasing by ~30% and ultimate tensile strength improving by ~80% compared to pure Al. The hardness of nano-reinforced composites substantially rose from 83 HV (pure Al) to 117 HV with 1.0 vol.% CNT reinforcement. Additionally, TiC-reinforced AA7075 composites improved hardness from 94.41 HB to 277.55 HB after 10 h of milling, indicating a nearly threefold increase. The wear resistance of Al-Si alloys was notably improved, with wear rates reduced by up to 52%, while the coefficient of friction decreased by 20–40% with the incorporation of graphene and CNT reinforcements. These findings highlight the potential of nano-reinforcements in significantly improving the mechanical and tribological performance of n-AMCs, making them suitable for high-performance applications in aerospace, automotive, and structural industries. Full article

The scattering of reinforcement plays a crucial role in the microstructure and properties of metal matrix composites. In this study, an aluminum matrix composite (AMC) was reinforced by 10 wt% TiO₂ (Al-10TiO₂), with an average particle size of a submicron, combined with a different content of graphitic carbon nitride (g-C₃N₄), which was fabricated by shift-speed ball milling (SSBM) combined with multi-pass friction stir processing (FSP). In addition to the high hardness of TiO₂, g-C₃N₄ has functional groups to promote in situ reactions. SSBM improves the distribution of reinforcement, refines grain size, and reduces the structural destruction of g-C₃N₄. The in situ reaction was achieved after multi-pass FSP at a high rotational speed and low travel speeds, which can promote uniform dispersion and grain refinement. Moreover, the g-C₃N₄ shows the efficient enhancement of strength while maintaining the elongation of AMC. Because the exfoliation of g-C₃N₄ under the effect of processing reduces the agglomeration of TiO₂, boosts the flattening of Al, and enhances interface integration with the base metal. In situ phases can reduce the generation of coarse phases and improve interfacial bonding ability to enhance mechanical properties. The maximum tensile strength has been found at about 172.5 MPa in the Al-10TiO₂ containing 1 wt% g-C₃N₄, which was enhanced by 34% compared to that of the Al-10TiO₂. The tensile strength increases when the g-C₃N₄ content increases from 0 to 1 wt%, but then reduces with a further increase of content. The hardness was increased by 50.2%, 60.2%, and 35% with a g-C₃N₄ content of 0.5, 1, and 2 wt% compared to AMCs without reinforcement, respectively. According to the test, the enhancement mechanism is mainly attributed to Orowan, grain refinement strengthening, and load transfer of scattered reinforcement. In summary, the utilization of hybrid reinforcements successfully enhances the microstructure and mechanical properties. Full article

Wearable communication technologies necessitate antenna designs that harmonize ergonomic compatibility, reliable performance, and minimal interaction with human tissues. However, high specific absorption rate (SAR) levels, limited radiation efficiency, and challenges in integration with flexible materials have significantly constrained widespread deployment. To address these limitations, this manuscript introduces a novel wearable cavity-backed substrate-integrated waveguide (SIW) antenna augmented with artificial magnetic conductor (AMC) structures. The proposed architecture is meticulously engineered using diverse textile substrates, including cotton, jeans, and jute, to synergistically integrate SIW and AMC technologies, mitigating body-induced performance degradation while ensuring safety and high radiation efficiency. The proposed design demonstrates significant performance enhancements, achieving SAR reductions to 0.672 W/kg on the spine and 0.341 W/kg on the forelimb for the cotton substrate. Furthermore, the AMC-backed implementation attains ultra-low reflection coefficients, as low as −26.56 dB, alongside a gain improvement of up to 1.37 dB, culminating in a total gain of 7.09 dBi. The impedance bandwidth exceeds the ISM band specifications, spanning 150 MHz (2.3–2.45 GHz). The design maintains remarkable resilience and operational stability under varying conditions, including dynamic bending and proximity to human body models. By substantially suppressing back radiation, enhancing directional gain, and preserving impedance matching, the AMC integration optimally adapts the antenna to body-centric communication scenarios. This study uniquely investigates the dielectric and mechanical properties of textile substrates within the AMC-SIW configuration, emphasizing their practicality for wearable applications. This research sets a precedent for wearable antenna innovation, achieving an unprecedented balance of flexibility, safety, and electromagnetic performance while establishing a foundation for next-generation wearable systems. Full article

Aluminum matrix composites (AMCs) are designed to enhance the performance of conventional aluminum alloys for engineering applications at both room and elevated temperatures. However, the dynamic phase-specific deformation behavior and load-sharing mechanisms of AMCs at elevated temperatures have not been extensively studied and remain unclear. Here, in situ neutron diffraction experiments are employed to reveal the phase-specific structure evolution of additively manufactured Al6061+TiC composites under compressive loading at 250 °C. It is found that the addition of a small amount of nano-size TiC significantly alters the deformation behavior and increases the strength at 250 °C in comparison to the as-printed Al6061. Unlike the two-stage behavior observed in Al6061, the Al6061+TiC composites exhibit three stages during compression triggered by changes in the interphase stress states. Further analysis of Bragg peak intensity and broadening reveals that the presence of TiC alters the dislocation activity during deformation at 250 °C by influencing dislocation slip planes and promoting dislocation accumulation. These findings provide direct experimental observations of the phase-specific dynamic process in AMCs under deformation at an elevated temperature. The revealed mechanisms provide insights for the future design and optimization of high-performance AMCs. Full article

Aluminum matrix composites (AMCs) with hetero-grains exhibit high strength with good ductility. A trimodal grain structure composed of ultrafine grains (UFGs), fine grains (FGs) and coarse grains (CGs) prevents the pre-mature cracking of hetero-zone boundaries in conventional bimodal grain structures; thus, it is favored by AMCs. However, the design of the size and distribution of hetero-domains in trimodal AMCs is tough, with complicated multi-scale deformation mechanisms. This study tunes the distribution of FG domains elaborately via altering the volume fraction of FG from 10 vol.% to 60 vol.% and investigates the distribution effect of FG domains on strength–ductility synergy. The optimized 2024 Al matrix composites with 30 vol.% FG exhibited a tensile strength of over 700 MPa and an elongation of 7.5%, respectively, realizing a good combination of high strength and ductility. This work enlightens the heterostructure design with a balance between heterogeneous deformation induced (HDI) strain hardening and high-content soft phase induced strain homogenization. Full article

This paper presents a wideband dual-polarized dipole antenna structure operating at 1.7–3.8 GHz (76.4%). For a traditional 4G dipole antenna that covers the band 1.71–2.69 GHz, it is difficult to maintain the satisfactory impedance matching and normal stable radiation patterns within the 5G sub-6 GHz band 3.3–3.8 GHz, mainly due to the fixed antenna height no longer being a quarter-wavelength. To solve this, a connected-ring-shaped metasurface structure is proposed and deployed to operate as an artificial magnetic conductor (AMC). As a result, stable antenna radiation patterns are obtained within the whole band 1.7–3.8 GHz. For verification, this wideband dipole antenna using AMC is implemented and tested. The measured results show that the proposed antenna has an impedance bandwidth of 80.7% (1.7–4.0 GHz). It has an average measured in-band realized gain of $7.0\pm 1.0$ dBi and a stable $70\pm 5$ half power beam width (HPBW) within the 4G/5G-sub 6GHz bands 1.71–2.69 GHz and 3.3–3.8 GHz. Full article

The development of anticancer drugs based on zinc-dependent histone deacetylase inhibitors (HDACi) has acquired great practical significance over the past decade. The most important HDACi characteristics are selectivity and strength of inhibition since they determine the mechanisms of therapeutic action. For in-cell testing of the selectivity of de novo-synthesized HDACi, Western blot analysis of the level of acetylation of bona fide protein substrates of HDACs of each class is usually used. However, the high labor intensity of this method prevents its widespread use in inhibitor screening. We developed an in-cell high-throughput screening method based on the use of three subtype-selective fluorogenic substrates of the general structure Boc-Lys(Acyl)-AMC, which in many cases makes it possible to determine the selectivity of HDACi at the class level. However, we found that the additional inhibitory activity of HDACi against metallo-β-lactamase domain-containing protein 2 (MBLAC2) leads to testing errors. Full article