Search Results (2,330)

Frequency-Modulated Continuous-Wave (FMCW) Laser Detection and Ranging (LiDAR) systems are widely used due to their high accuracy and resolution. Nevertheless, conventional distance extraction methods often lack robustness in noisy and complex environments. To address this limitation, we propose a deep learning-based signal extraction framework that integrates a Dual Convolutional Neural Network (DCNN) with a Transformer model. The DCNN extracts multi-scale spatial features through multi-layer and pointwise convolutions, while the Transformer employs a self-attention mechanism to capture global temporal dependencies of the beat-frequency signals. The proposed DCNN–Transformer network is evaluated through beat-frequency signal inversion experiments across distances ranging from 3 m to 40 m. The experimental results show that the method achieves a mean absolute error (MAE) of 4.1 mm and a root-mean-square error (RMSE) of 3.08 mm. These results demonstrate that the proposed approach provides stable and accurate predictions, with strong generalization ability and robustness for FMCW LiDAR systems. Full article

Grout voids in external tendons of post-tensioned bridges are a critical issue, as they may result in the corrosion of the steel strands and significantly reduce tendon strength. Therefore, preventing tendon failure necessitates thorough inspection for these voids during both construction and operation. Terahertz electromagnetic wave testing is an effective method for detecting voids between the protective duct and the grout in external tendons, as terahertz waves can penetrate through the protective duct. This study introduces a D-band electronic frequency-modulated continuous-wave terahertz A-scanner for enhanced real-time inspection. The proposed method offers key advantages such as miniaturization, cost-effectiveness, and robustness, while providing effective detection of voids beneath the duct in external tendons. It is indicated that voids with a thickness of approximately 2.5 mm or greater can be detected using the D-band THz A-scanner. Full article

Background/Objectives: Race-based cardiac screening criteria in sports cardiology, including the “Black athlete’s heart” concept, assume biological distinctions that may not reflect physiological reality. This systematic review evaluates whether geographic ancestry provides more clinically relevant predictors of cardiac adaptation than racial categorization. Methods: PubMed was searched (January 2005–July 2025) for studies examining cardiac adaptations in athletes by ethnicity. Data extraction captured demographics, geographic origin, cardiac assessments, and outcomes. Narrative synthesis was employed due to methodological heterogeneity. Results: Forty-seven studies (n = 66,130) revealed substantial within-race heterogeneity. The “Black athlete repolarization variant” prevalence ranged from 1.8% (Brazilian) to 30% (Ghanaian) Black athletes. Left ventricular wall thickness >12 mm (normal <11 mm) occurred in 7.1% of Black versus 0.4% of White athletes, yet varied significantly within Black populations—10.8 ± 1.2 mm in Sub-Saharan versus 9.4 ± 1.1 mm in African-American athletes (p < 0.001). Relative wall thickness ≥0.44 (normal ≤0.42) was presented in 43% of West/Middle African, 23% of East African, and 7% of White athletes. T-wave inversion showed four-fold variation within Black populations (3.6–8.5% West African versus 0.5–2.0% African-American/Caribbean). Current International Criteria demonstrated inequitable specificity: 3.3% false-positive rate in Black versus 1.4% in White athletes. Conclusions: Geographic ancestry explains more cardiac variation than racial categories, supporting contemporary understanding of race as a sociopolitical construct. The persistent diagnostic disparities in ECG screening specificity highlight the need for reform. Transitioning toward protocols incorporating continental origin, anthropometric factors, and social determinants of health—while eliminating terminology like “Black athlete’s heart”—represents an important step toward achieving equity in cardiovascular care for diverse athletic populations. Full article

Coating degradation monitoring is increasingly important in offshore industries, where protective layers ensure corrosion prevention and structural integrity. In this context, coating thickness estimation provides critical information. The ultrasound pulse-echo technique is widely used for non-destructive testing (NDT), but closely spaced acoustic interfaces often produce overlapping echoes, which complicates detection and accurate isolation of each layer’s thickness. In this study, analysis of the pulse-echo signal from a coated sample has shown that the front-coating reflection affects each main backwall echo differently; by comparing two consecutive backwall echoes, we can cancel the acquisition system’s impulse response and isolate the propagation path-related information between the echoes. This work introduces an ultrasound echo-based methodology for estimating coating thickness by first obtaining the impulse response of the test medium (reflectivity sequence) through a deconvolution model, developed using two consecutive backwall echoes. This is followed by an enhanced detection of coating layer thickness in the reflectivity function using a 1D convolutional neural network (1D-CNN) trained with synthetic signals obtained from finite-difference time-domain (FDTD) simulations with k-Wave MATLAB toolbox (v1.4.0). The proposed approach estimates the front-side coating thickness in steel samples coated on both sides, with coating layers ranging from $60\mathsf{\mu }$m to $740\mathsf{\mu }$m applied over 5 mm substrates and under varying coating and steel properties. The minimum detectable thickness corresponds to approximately $\mathit{\lambda }/5$ for an 8 MHz ultrasonic transducer. On synthetic signals, where the true coating thickness and speed of sound are known, the model achieves an accuracy of approximately $8\mathsf{\mu }$m. These findings highlight the strong potential of the model for reliably monitoring relative thickness changes across a wide range of coatings in real samples. Full article

Radio spectrum planning has become increasingly important, since the radio spectrum is a scarce resource. Moreover, the utilization of millimeter wave (mmWave) frequencies with fifth-generation (5G) standards has made radio planning more compelling. Considering their different strengths and weaknesses, it is essential to know when mmWave frequencies should be selected in radio planning. In this paper, an approach with edge learning is developed to provide smart spectrum recommendations on which frequency bands should be used for a region. Using the proposed approach, radio spectrum planning can be carried out more efficiently, especially for the frequency ranges of mmWave communications. The proposed approach is designed with a distributed structure, based on awareness of the environment and ambient intelligence. This approach can be performed for each transmission point considering the environment information of the related coverage area. As a result, radio spectrum planning can be conducted for an entire region with the proposed system. The results show that this study both enhances overall user satisfaction and provides reasonable recommendations to operators in the transition to mmWave usage. Thus, the developed approach can be utilized for 5G and beyond communications. Specifically, this methodology is based on applying supervised ML algorithms to a synthetically generated dataset, and the best model achieves around 80% classification accuracy, demonstrating the feasibility of the approach. These quantitative results confirm its practicality and provide a concrete baseline for future studies. Full article

This paper investigates the channel performance through a high-gain, circularly polarized microstrip patch antenna that is developed for contemporary wireless communication systems. The proposed antenna creates two orthogonal modes for circular propagation with slightly varying resonance frequencies by using a cross line and truncations to circulate surface currents. Compactness, reduced surface wave losses, and enhanced impedance bandwidth are made possible by the coaxial probe feed, periodic electromagnetic gap (EBG) slots, and fractal patch geometry. For in-phase reflection and beam focusing, a specially designed single-layer metasurface (MTS) reflector with an 11 × 11 circular aperture array is placed 20 mm behind the antenna. A log-normal shadowing model was used to test the antenna in real-world scenarios, and the results showed a strong correlation between the model predictions and actual data. At up to 250 m, the polarization-agile, high-gain antenna demonstrated reliable performance across a variety of channel conditions, enabling accurate characterization of the Channel Quality Indicator (CQI), Signal-to-Noise Ratio (SNR), and Reference Signal Received Power (RSRP). By combining cutting-edge antenna architecture with an empirical channel performance study, this research presents a compact, affordable, and fabrication-friendly solution for increased wireless coverage and efficiency. Full article

A compact fork-shaped four-element multiple-input multiple-output (MIMO) antenna system with wide bandwidth for 5G millimeter-wave (mmWave) applications is presented. The antenna elements are arranged orthogonally to achieve a compact footprint of $20\times 26{\mathrm{mm}}^2$. To enhance the gain, a frequency selective surface (FSS) is placed above the MIMO system, providing an average gain improvement of 1.5 dB across the entire operating band and achieving a peak gain of 7.5 dB at 41 GHz. The proposed design operates in the Ka-band (22–46 GHz), making it well suited for 5G communications. The antenna exhibits an isolation greater than 20 dB and radiation efficiency exceeding 80% across the band. Moreover, key MIMO performance metrics, including diversity gain (DG ≈ 10) and envelope correlation coefficient (ECC < 0.05), meet the required standards. A prototype of the proposed system was fabricated and measured, with the experimental results showing good agreement with simulations. Full article

This work presents a closed-form approximation to the symbol error probability (SEP) for cross-quadrature amplitude modulation (cross-QAM) schemes over $\mathit{\kappa }$–$\mathit{\mu }$ fading channels. The proposed formulation enables accurate performance evaluation while avoiding computationally expensive numerical integration. The analysis covers millimeter-wave (mmWave) frequencies at 55, 60, and 65 GHz, under both line-of-sight (LoS) and non-line-of-sight (nLoS) conditions, and for multiple transmitter–receiver polarization configurations. A key contribution of this work is the experimental validation of the theoretical expression with real channel-measurement data, which confirms the applicability of the $\mathit{\kappa }$–$\mathit{\mu }$ model in realistic mmWave scenarios. Furthermore, we perform a detailed parametric study to quantify the influence of $\mathit{\kappa }$ and $\mathit{\mu }$ on adaptive modulation performance, providing practical insights for 5G and future 6G systems. The proposed framework bridges theoretical analysis and experimental validation, offering a computationally efficient and robust tool for the design and evaluation of advanced modulation schemes in generalized fading environments. Full article

In the marine salt spray environment, steel fiber reinforced concrete (SFRC) structures are often subjected to accelerated durability degradation, primarily due to chloride-induced corrosion. To address this issue, polypropylene (PP) fibers were incorporated to partially replace steel fibers in the formulation of hybrid fiber reinforced concrete (HFRC), thereby enhancing its resistance to chloride corrosion. The results demonstrate that all HFRC mixtures achieved a compressive strength of approximately 65 MPa at 28 d. After 200 d of salt spray exposure, the compressive strength of the HFRC containing PP fibers decreased at a significantly slower rate than that of the control group (M0) incorporating sole steel fibers, with the former still meeting the high-strength concrete standard (>60 MPa). Regardless of the exposure duration to salt spray, the wave velocity of the HF series remained higher than that of M0. This suggests that the PP fibers play a significant role in preserving the matrix’s compactness, effectively mitigating deterioration caused by chloride corrosion. Furthermore, after 200 d of exposure, the peak chloride content, critical corrosion depth, and chloride diffusion coefficient of HF2 were 0.58%, 16 mm, and 1.24 × 10⁻¹² m²/s, respectively, all of which were lower than those of the other specimens. This demonstrates that incorporating 0.3 vol% PP fibers most effectively enhances the chloride corrosion resistance of HFRC. Full article

Background: Perianal Crohn’s disease (pCD) is one of the most disabling complications of inflammatory bowel disease, characterized by fistulas and abscesses that demand precise imaging for diagnosis, treatment planning, and follow-up. Magnetic resonance imaging (MRI) is considered the reference standard, but endoanal ultrasound (EAUS) with high-frequency 360° probes provide a readily available, cost-effective, and repeatable alternative. Methods: We performed a narrative review of the literature, evaluating studies on the EAUS technique, diagnostic applications, distinguishing features of Crohn’s-related fistulas, and comparative analyses with MRI. Consensus documents and structured reporting initiatives were also included. Results: EAUS provides high-resolution visualization of the anal sphincter complex and intersphincteric space, enabling the reliable detection of fistulas and abscesses. Characteristic features such as tract width > 4 mm, bifurcation, hyperechoic debris, the Crohn’s Ultrasound Fistula Sign (CUFS), and the rosary sign assist in differentiating Crohn’s from cryptoglandular fistulas. EAUS is well-suited for serial monitoring, perioperative seton guidance, and therapeutic decision-making. Emerging tools such as Doppler and shear wave elastography provide additional information on activity and fibrosis. MRI remains indispensable for supralevator disease, deep pelvic sepsis, and standardized activity indices. Comparative studies indicate similar sensitivity for simple fistulas, with MRI superior in complex cases; combining both modalities maximizes accuracy. Conclusions: EAUS is a practical and repeatable imaging tool that complements MRI in the multidisciplinary management of perianal Crohn’s disease. Advances such as 3D imaging, contrast enhancement, and elastography may enable validated activity scoring—for example, a future PEACE (Perianal Endosonographic Activity in Chron’s Evaluation) Index—further strengthening its role in longitudinal care. Full article

We present a novel disposable electrochemical biosensor for highly sensitive and selective glucose detection, employing gold-modified screen-printed electrodes combined with square wave (SWV) and linear sweep voltammetry (LSV). The sensor integrates recombinant corn-derived manganese peroxidase with glucose oxidase, bovine serum albumin, and gold nanoparticles to enhance stability and signal transduction. Glucose detection by LSV covered 0.001–6.5 mM (R² = 0.9913; LOD = 0.50 µM), while SWV achieved a broader range of 0.0006–6.5 mM (R² = 0.998; LOD = 0.29 µM). The sensor demonstrated excellent selectivity, showing minimal interference from common electroactive species including caffeine, aspartame, and ascorbic acid, and provided rapid responses, making it ideal for point-of-care and food monitoring applications. Full article

This paper presents an intelligent design framework for a high-performance 26 GHz MIMO antenna array tailored to 5G applications, built upon a compact single-element patch. The 11.5 mm × 11.5 mm × 1.6 mm microstrip patch on FR4 exhibits near-unity electrical length, an ultra-deep return loss (S11 < −40 dB at 26 GHz), and a wide operational bandwidth from 24.4 to 31.2 GHz (6.8 GHz, ~26.2%). A two-element array, spaced at λ/2, is first augmented with a inspired metamaterial (MTM) unit cell whose dimensions are optimized via a Multi-Layer Perceptron (MLP) model to maximize gain (+2 dB) while preserving S11. In the second phase, a closed-square parasitic ring is introduced between the elements; its side length, thickness, and position are predicted by a Random Forest (RF) model with Bayesian optimization to minimize mutual coupling (S12) from −25 dB to −58 dB at 26 GHz without significantly degrading S11 (remains below −25 dB). Full-wave simulations and anechoic chamber measurements confirm the ML predictions. The close agreement among predicted, simulated, and measured S-parameters validates the efficacy of the proposed AI-assisted optimization methodology, offering a rapid and reliable route to next-generation millimeter-wave MIMO antenna systems. Full article

The emergence of 6G wireless systems marks a paradigm shift toward intelligent, context-aware networks that can adapt in real-time to their environment. Within this landscape, Sensing-Assisted Communication (SAC) emerges as a key enabler, integrating perception into the communication control loop to enhance reliability, beamforming accuracy, and system responsiveness. Unlike prior surveys that treat SAC as a subfunction of Integrated Sensing and Communication (ISAC), this work offers the first dedicated review of SAC in Millimeter-Wave (mmWave) and Sub-Terahertz (Sub-THz) systems, where directional links and channel variability present core challenges. SAC encompasses a diverse set of methods that enable wireless systems to dynamically adapt to environmental changes and channel conditions in real time. Recent studies demonstrate up to 80% reduction in beam training overhead and significant gains in latency and mobility resilience. Applications include predictive beamforming, blockage mitigation, and low-latency Unmanned Aerial Vehicle (UAV) and vehicular communication. This review unifies the SAC landscape and outlines future directions in standardization, Artificial Intelligence (AI) integration, and cooperative sensing for next-generation wireless networks. Full article

Pipelines are extensively used in offshore equipment. Accurate and non-destructive measurement of hoop stress conditions within pipes is critical for ensuring the integrity of offshore structures. However, the existing technology to measure the hoop stress of the pipeline needs to planarize the surface of the pipeline, which greatly limits the detection efficiency. This study proposes a method for pipeline hoop stress measurement using a planar longitudinal critically refracted (LCR) probe, based on correcting LCR wave-propagation paths, which solves the problem of pipeline planarization in pipeline hoop stress measurement. First, a linear relationship between stress variations and ultrasonic time-of-flight changes in the material was established based on the acoustoelastic effect. Finite element analysis was then used to construct an acoustic simulation model for the hoop direction of the pipeline. Simulation results showed that LCR waves propagated within a wedge as quasi-plane waves and, upon oblique incidence into the pipeline, traveled along the chordal direction. Furthermore, using ray tracing methods, a mapping relationship between the pipeline geometry and the ultrasonic propagation path was established. Based on this, the LCR pipeline hoop stress measurement (LCR-HS) method was proposed. Finally, a C-shaped ring was employed to verify the measurement accuracy of the LCR-HS method. Experimental results indicated that the measurement error decreased with increasing pipe diameter and fell below 8% when the diameter exceeded 400 mm. This method enables precise measurement of hoop stress on curved surfaces by revealing the hoop propagation behavior of LCR waves in pipelines. The findings provide a technical reference for evaluating pipeline stress states, which is of significant importance for assessment of pipeline integrity. Full article

A ceramic-based wideband capacitive-fed patch-loaded multi-layered rectangular dielectric resonator antenna (CFPL-ML-RDRA) with a compact form factor is proposed in this paper. The proposed antenna is composed of two ceramic substrates and a polymer as an adhesive. A capacitive-fed metallic patch structure is located on the top side of the bottom ceramic substrate. This novel structure generates two distinct resonant modes: the fundamental resonant mode of the RDRA and a hybrid resonant mode, which was confirmed through electric field (E-field) analysis and parametric studies. By merging these two resonant modes, the proposed antenna achieves a wide impedance bandwidth of 5.5 GHz, sufficient to cover the fifth-generation (5G) millimeter-wave (mmWave) frequency bands n257, n258, and n261 (5.25 GHz), while reducing the height of the DRA by 38.5% compared to the conventional probe-fed RDRA (PF-RDRA). Additionally, the 4 dBi realized gain bandwidth of the proposed CFPL-ML-RDRA is 5.4 GHz, which is 28.6% broader than that of the conventional PF-RDRA. To experimentally verify the antenna’s performance, the CFPL-ML-RDRA mounted on a test printed circuit board with a small ground size of 3.2 × 3.2 mm² was fabricated and characterized. The measured data align well with the simulated data. Furthermore, excellent antenna array performance was achieved based on array simulations. Therefore, the proposed antenna structure is well-suited for 5G mmWave mobile applications. Full article