Search Results (7,242)

Fifth-generation (5G) networks enable railway digitalization but face signal degradation challenges in high-mobility environments. While the existing literature attributes degradation primarily to Doppler frequency shifts, this study presents empirical evidence challenging this paradigm. Analysis of 13.7 million 5G New Radio measurements across 370 km of Estonian railway reveals that visible cell density, not velocity, dominates signal quality degradation. Nine geographic hotspots exhibit 5.4–18.0 dB degradation at moderate velocities (54–66 km/h, mean 60.2 km/h) with zero high-speed measurements, excluding the Doppler effect as the reason behind service quality degradation. Cell complexity demonstrates a 3.25× stronger correlation with degradation (r = −0.390) than velocity (r = −0.120), consistent with automatic frequency control tracking instability under high cell ID churn rates (40–115 visible cells per location), though direct confirmation of this mechanism requires access to internal modem frequency-lock state data. Frequency band analysis shows that 700 MHz is optimal at 98.1% of locations, with a 19 dB advantage over 3.5 GHz. Degradation mechanism decomposition reveals within-cell effects (60%, 7.85 dB) and handover boundary effects (40%, 2–6 dB). The findings challenge velocity-centric optimization paradigms and recommend network planning focused on cell overlap reduction rather than Doppler compensation enhancement. Practical recommendations include 700 MHz prioritization, handover parameter optimization, and geographic targeting of identified hotspots for European railway 5G deployment. Full article

Graph Neural Networks (GNNs) have emerged as the standard for learning representations from graph-structured data. While traditional architectures relying on message-passing mechanisms excel in homophilic settings, they essentially function as fixed low-pass filters. However, this smoothing operation limits their ability to generalize to heterophilic graphs, where connected nodes often exhibit dissimilar labels and high-frequency signals are crucial for discrimination. Furthermore, existing Mixture-of-Experts (MoE) methods for graphs often suffer from local-view routing, failing to capture global structural context during expert selection. To address these challenges, this paper proposes SS-AdaMoE, a novel Spatio-Spectral Adaptive Mixture of Experts framework designed for robust node classification across diverse graph patterns. Specifically, a Dual-Domain Expert System is constructed, integrating heterogeneous spatial aggregators with learnable spectral filters based on Bernstein polynomials. This allows the model to adaptively capture arbitrary frequency responses—including high-pass and band-pass signals—which are overlooked by standard GNNs. To resolve the locality bias, a Hierarchical Global-Prior Gating Network augmented by a Linear Graph Transformer is introduced, ensuring that expert selection is guided by both local node features and global topological awareness. Extensive experiments are conducted on five benchmark datasets spanning both homophilic and heterophilic networks. The results demonstrate that SS-AdaMoE consistently outperforms baselines, achieving accuracy improvements of up to 2.65% on Chameleon and 1.41% on Roman-empire over the strongest MoE baseline, while surpassing traditional GCN architectures by margins exceeding 28% on heterophilic datasets such as Texas. These findings validate that the synergy of learnable spectral priors and global gating effectively bridges the gap between spatial aggregation and spectral filtering. Full article

This paper presents the concept of a 2D m × n waveguide-based power combiner (PC) that is scalable with respect to the operating frequency band and number of input ports. To our knowledge, this work reports the first planar (2D) power combiner, where the input waveguide ports are distributed in two spatial dimensions to form an array, rather than arranged along a single linear (1D) axis as in conventional corporate or cascaded waveguide combiners. The novelty of the approach relies on using H-plane rectangular waveguide T-junctions and low-loss polarization twisters in between vertically stacked T-junctions to facilitate scalability. The work is motivated by the aim to coherently combine the output power of multiple modified uni-traveling carrier (MUTC) terahertz (THz) waveguide photodiodes (PDs) in a 2D array configuration. In the manuscript, the design of a 2 × 2 planar waveguide power combiner for the WR3 band (220–320 GHz) is reported, and it is also shown that this block can be further extended to m × n input ports. Full-wave numerical analysis of the proposed 2 × 2 power combiner shows a return loss of 11 dB at the output port and an average transmission coefficient of about −6.5 dB, i.e., an overall power combining efficiency of ~90%. Furthermore, to enable 2D photodiode array integration, the manuscript presents a new slot-bow tie antenna integrated MUTC photodiode for radiating the optically generated THz power from each PD vertically into the rectangular waveguide. The simulation results of reflection loss and insertion loss for the slot bow-tie antenna are shown to be better than 10 dB and 1.4 dB over the full WR3 band, respectively. To prove scalability of the power combiner concept w.r.t. the number of input ports, a 2 × 4 power combiner is also analyzed. Results reveal a return loss better than 10 dB from 225 to 318 GHz and a transmission coefficient of approximately −9.7 dB at 300 GHz, i.e., a power combining efficiency of ~85%. Full article

This paper presents an ultra-miniaturized and high-quality factor embedded loaded coaxial substrate integrated waveguide (ELCSIW) filter. Integrating a substrate-integrated coaxial resonator with a capacitively loaded air cavity achieves a 99% reduction in size compared to a conventional SIW cavity. Incorporating an air gap in the capacitive loading structure significantly enhances the resonator’s quality factor. A comprehensive analysis of the miniaturization factor and quality factor in relation to cavity structure dimensions is performed. Guidelines for fabricating the highly loaded cavity are presented. To demonstrate the benefits of this technique, a two-pole band-pass filter with a 6.3% bandwidth at 1.1 GHz is designed, fabricated, and measured. The overall footprint of the filter is 10.5 mm × 20.5 mm, which is comparable to 0.07 ${\lambda }_g$× 0.14 ${\lambda }_g$. The measured insertion loss is 0.54 dB, and the upper band is spurious-free up to 7 times the resonant frequency. The exceptional performance and compactness of the loaded coaxial substrate integrated waveguide cavities highlight their immense potential for compact advanced wireless systems. Full article

This study investigates the sound insulation performance of an anechoic chamber, exploring the influence patterns of different multilayer material combinations on wall sound insulation characteristics. Based on sound transmission theory, a predictive model for multilayer material wall sound insulation was established. The finite element method was employed to simulate the sound propagation characteristics of walls and glass doors with various material combinations. After validating the simulation results through a double-room method experiment, the material combination scheme for the anechoic chamber walls and glass doors was optimized. Based on this, a 1000 mm × 1000 mm × 2300 mm soundproof room prototype was designed and constructed. Its sound insulation performance under reverberant conditions was tested using the insertion loss method and compared with simulation data. Simultaneously, a hybrid calculation method combining low-frequency finite element analysis with high-frequency statistical energy analysis enabled precise and efficient prediction of the overall sound insulation performance of the soundproof room. Research revealed that single-pane glass with thicknesses between 5 and 20 mm conformed to the mass law, with sound insulation increasing by an average of 0.8 dB per additional millimeter. The 10 mm single-pane glass emerged as the optimal choice for the soundproof room’s glass door due to its ideal thickness and excellent low-to-mid-frequency sound insulation. The optimized wall structure featured compact thickness, outstanding low-frequency sound insulation, and balanced mid-to-high-frequency performance. Simulation and experimental results for the core frequency range of 63–1000 Hz showed high consistency, which validates the reliability of the theoretical model and simulation methodology within this frequency band. The deviation of simulation results from experimental data in the frequency range above 1000 Hz is mainly caused by acoustic leakage due to experimental sealing defects, and the high-frequency simulation results are only used for trend analysis rather than conclusion support. This study identifies the optimal multi-layer material combination for soundproof rooms, providing practical material strategies for acoustic design. It also reveals the sound insulation mechanisms of multi-layer composite structures. The findings offer significant reference for optimizing soundproofing materials and structures in architectural acoustics and transportation noise control. Full article

Background: The early detection of autism spectrum disorder (ASD) is imperative for enhancing long-term developmental outcomes. Nevertheless, conventional screening methods depend on time-consuming, expert-driven behavioral assessments and are characterized by limited scalability. Automated video-based analysis provides a noninvasive and objective approach for the extraction of behavioral biomarkers from naturalistic recordings. Methods: A modular multimodal framework was developed that integrates motion-based video analysis and facial feature extraction for the purpose of ASD versus typically developing (TD) classification. The system is capable of processing RGB videos, skeleton/stickman representations, and motion trajectory streams. A comprehensive set of kinematic features was extracted, encompassing joint trajectories, velocity and acceleration profiles, posture variability, movement smoothness, and bilateral asymmetry. The repetitive stereotypical behaviors exhibited by the subjects were characterized using frequency-domain analysis via FFT within the 0.3–7.0 Hz band. Facial expression features derived from normalized face crops and landmark-based morphological descriptors were integrated as complementary modalities. The feature-level fusion process was executed subsequent to z-score normalization, and the classification procedure was conducted using a Random Forest model with stratified 5-fold cross validation. The implementation of GPU acceleration was instrumental in facilitating near real-time inference. Results: The motion-based ComplexVideos pipeline demonstrated a cross-validated accuracy of 94.2 ± 2.1% with an area under the ROC curve (AUC) of 0.93. Skeleton-based KinectStickman inputs demonstrated moderate performance, with an accuracy range of 60–80%. In contrast, facial-only models exhibited an accuracy of approximately 60%. The integration of multiple modalities through feature fusion has been demonstrated to enhance the robustness of classification algorithms and mitigate the occurrence of false negative outcomes, thereby surpassing the performance of single-modality models. The mean inference time remained below one second per video frame under standard operating conditions. Conclusions: The experimental results demonstrate that the integration of multimodal cues, including motion and facial features, facilitates the development of effective and efficient video-based screening methods for autism spectrum disorder (ASD). The proposed framework is designed to offer a scalable, extensible, and computationally efficient solution that can support early screening in clinical and remote assessment settings. Full article

Energy harvesting plays a pivotal role in enabling sustainable power supply for the Internet of Things and distributed sensor networks, particularly for low-power devices. Piezoelectric energy harvesters based on vortex-induced vibrations offer a promising solution for low-wind-speed applications, yet their performance is constrained by limited bandwidth and sensitivity to wind speed variations. This study addresses these limitations by proposing a novel multi-parameter adjustable piezoelectric energy harvester featuring an inclined cylindrical bluff body. By systematically tuning the inclination angle and installation position, the device achieves substantial performance improvements. Experimental results indicate that the optimized configuration yields a wider operational frequency band and enhanced energy conversion efficiency. Through the experimental results, we discovered the existence of the double-peak phenomenon and the plateau phenomenon. The voltage value of the second peak can reach up to 122.4% of the maximum voltage of the first peak. The duration of the maximum plateau phase can maintain between the wind speed of 2.3 m/s and 5.7 m/s. Full article

The qEEG findings of subjects with Down syndrome (DS) have not been described in the context of bipolar montage. Resting-state EEG (rsEEG) with a bipolar montage was performed in 22 young adults (26.0 ± 1.2 years) with DS but without psychiatric or neurological pathology and matched control subjects of the same sex and age, and the results were conventionally and numerically analyzed. Channels were grouped into frontal, parieto-occipital, and temporal lobes. For every channel, the power spectrum was calculated and used to compute the area for the delta, theta, alpha and beta bands and was log-transformed. Shannon’s spectral entropy (SSE) and coherence by bands were computed. Finally, we also calculated the peak frequency distribution of the alpha band. qEEG revealed alterations in the rsEEG that were not detected visually. Subjects with DS showed a significant generalized increase in the power of the delta and theta bands, along with a decrease in the power of the alpha band in the posterior half of the scalp. This alpha activity also exhibited features corresponding to older euploid subjects, showing interhemispheric asynchrony in one-third of the individuals. The beta band power was significantly increased in the frontal lobes and adjacent regions, such as the parietal and mid-temporal regions. Individuals with DS showed a generalized decrease in parieto-occipital synchronization associated with intelligence quotient. Left temporal synchronization was also lower. The synchronization of specific channel pairs was greater in subjects with DS in the frontal lobe and much lower in the occipital and temporal regions. These results indicate that alterations in band structure and synchronization in subjects with DS are highly specific and can aid in the clinical evaluation of these individuals. Full article

Electroencephalography (EEG) has become an increasingly important tool in depression research due to its ability to capture objective neurophysiological abnormalities associated with depressive disorders, offering high temporal resolution, non-invasiveness, and cost-effectiveness.However, existing methods often fail to fully exploit the multi-domain information in EEG signals, resulting in limited model generalization capabilities. This paper proposes an improved bidirectional long short-term memory (BiLSTM) model that segments continuous EEG into non-overlapping 2-s epochs and learns end-to-end from multi-channel temporal sequences. After band-pass filtering and resampling, each epoch is represented as a channel–time matrix $X\in {\mathbb{R}}^{C\times T}$ (with C = 128) and processed by a BiLSTM encoder followed by a dynamic-routing encapsulated-vector classifier. On the MODMA dataset under subject-independent five-fold cross-validation, the proposed method outperforms a set of reproduced representative baselines (SVM, EEGNet, InceptionNet, Self-attention-CNN and CNN–LSTM) and achieves 84.8% accuracy with an AUC of 0.899. We further discuss recent contemporary directions (e.g., attention/Transformer-based and emotion-aware expert models) and clarify the scope of our empirical comparisons. Furthermore, experiments comparing different frequency bands and band combinations indicate that joint multi-frequency input can enhance classification performance. This study provides an effective multi-domain fusion approach for the automatic diagnosis of depression based on EEG. Full article

Coupling interference in densely integrated high-frequency communication architectures leads to significant degradation in transmission efficiency, particularly in modern 5G and GHz-range platforms. From a mathematical perspective, mitigating such interference can be formulated as a multi-criteria optimization problem involving competing design objectives and interacting control mechanisms. In this paper, we develop an equilibrium-based optimization framework by modeling coupling suppression as a finite non-cooperative game. Isolation mechanisms are represented as strategic players whose actions are defined over constrained design spaces, while utility functions incorporate coupling minimization, insertion-loss penalties, and fabrication complexity. Under this formulation, stable mitigation strategies are characterized through Nash equilibrium conditions. To address the inherent trade-offs among performance metrics, the equilibrium computation is integrated with a Pareto multi-objective optimization scheme, yielding Nash–Pareto optimal configurations that balance electromagnetic isolation performance with implementation feasibility. Numerical full-wave simulations in the 2–12 GHz frequency band demonstrate that the proposed equilibrium solutions achieve substantial interference suppression, with reductions exceeding 30 dB compared with conventional baseline designs. The proposed framework provides a mathematically structured approach for interference mitigation and offers a generalizable methodology for multi-objective optimization in high-frequency communication systems. Full article

Collisions between over-height vehicles and low-clearance bridges cause infrastructure damage and pose safety risks. Existing detection systems rely primarily on optical sensors, which suffer from performance degradation in adverse weather conditions. This paper presents an alternative approach based on a 94 GHz millimeter-wave radar that achieves velocity-independent height measurement. The proposed technique exploits the ratio of Doppler shifts from two scattering centers on a vehicle, specifically the roof and the wheel–road interface. This ratio depends only on the measurement geometry, as the unknown vehicle velocity cancels algebraically, enabling direct height computation without speed measurement. The paper provides a closed-form height estimation model, analyzes the trade-off between frequency resolution and geometric constancy during integration, and presents experimental validation using a scaled laboratory testbed. An optical tracking system is used solely for ground-truth validation in the laboratory and is not required for operational deployment. Results across six test cases with heights ranging from 20 cm to 46 cm demonstrate an average absolute error of 0.60 cm and relative errors below 3.3 percent. A scaling analysis for representative full-scale geometries indicates that at highway speeds of 80 km/h, integration times in the millisecond range (approximately 3–18 ms for representative 20–50 m measurement standoff) are feasible; warning distance can be extended independently by upstream radar placement. The expected advantage in fog, rain, and dust is based on established W-band propagation characteristics; dedicated adverse-weather and full field validation (including multipath, clutter, and multi-vehicle scenarios) remain future work. Full article

Measurement results of train-induced vibrations are evaluated for characteristic frequencies, amplitudes and spectra, leading to a prediction which is based on transfer functions of the vehicle–track–soil system, the soil, and the building–soil system. The characteristic frequencies of train-induced vibrations are discussed following the propagation of vibrations from the source to the receiver: out-of-roundness frequencies of the wheels, the sleeper passage frequency, the vehicle–track eigenfrequency, the car-length frequency and multiples, axle-distance frequencies, bridge eigenfrequencies, the building–soil eigenfrequency, and floor eigenfrequencies. Amplitudes and spectra are compared for different train and track types, for different train speeds, and for different soft and stiff soils, where high frequencies are typically found for stiff soil and low frequencies for soft soil. The ground vibration is between the cut-on frequency due to the layering and the cut-off frequency due to the material damping of the soil, but the dominant frequency range also changes with distance from the track. The frequency band of the axle impulses due to the passing static loads obtains a signature from the axle sequence. The high amplitudes between the zeros of the axle-sequence spectrum are measured at the track, the bridge, and also in the ground vibrations, which are even dominant in the far field. A prediction software is presented, which includes all three parts: the excitation by the vehicle–track interaction, the wave transmission through the soil, and the transfer into a building. Full article

Multistatic sonar provides enhanced target detection in complex underwater environments. The wide-angle bistatic scattering characteristics of targets, particularly the bistatic reflection coefficients, are important for evaluating system performance and designing acoustic absorbing coatings. However, obtaining full-angle experimental measurements is challenging, and conventional finite-element simulations become computationally prohibitive for large structures, high frequencies, or exhaustive angle sweeps. To overcome these challenges, a fast wide-angle scattering prediction method for acoustically coated plates is proposed. The method constructs a scattering transfer matrix from the surface mesh and retrieves the equivalent source density from a small subset of scattered-pressure samples, enabling reconstruction of the full-angle scattering field and rapid extraction of reflection coefficients. The approach is demonstrated on both rigid and coated plates, with predictions compared against finite-element calculations. The results demonstrate that the proposed method accurately reproduces the bistatic reflection coefficients, including non-linear dispersion effects and interference fringes, across a wide frequency band from 100 Hz to 5 kHz. Compared to traditional FEM sweeps, this method significantly reduces computational time while maintaining high accuracy, providing an efficient tool for the design of acoustic stealth materials and laying a foundation for rapid target strength prediction of complex targets using the Planar Element Method. Full article

This paper presents a compact dual-band circularly polarized (CP) antenna designed for millimeter-wave applications at 28 and 38 GHz, which are critical for emerging 5G and beyond wireless communication systems. The single-element antenna features an ultra-small radiating patch of size 3.34 mm × 3.34 mm and overall substrate footprint of 8 mm × 16 mm, implemented on a Rogers RO3003 substrate with a relative permittivity of 3 and thickness of 0.25 mm, making it highly suitable for space-constrained millimeter-wave front-end integration. Circular polarization is successfully achieved at both bands, with measured axial ratios of 1.4 dB at 28 GHz and 2.2 dB at 38 GHz. Surface current distribution is thoroughly analyzed at both frequencies, showing proper rotation and confirming the antenna’s ability to generate strong circular polarization. The antenna also exhibits high radiation efficiency (~87% at 28 GHz and ~82% at 38 GHz) and peak realized gains of 7.5 dBi and 5.5 dBi, respectively. Measured results demonstrate excellent impedance matching, stable radiation patterns, and strong agreement with simulations. The combination of compact size, robust CP performance, and efficient radiation makes the proposed antenna a promising candidate for circularly polarized millimeter-wave systems, including 5G base stations, user equipment, and future high-frequency wireless platforms. Full article

To address the detuning sensitivity of conventional linear vibration absorbers under wide-frequency harmonic excitation and the limited effectiveness of nonlinear energy sinks (NESs) in low-energy regimes, this study investigates a bistable nonlinear energy sink (BNES) based on a negative-stiffness support. A coupled model of the primary system and the BNES is established, and the analytical steady-state amplitude–frequency relationship of the system is derived using the harmonic balance method. The accuracy of the analytical solutions is verified through numerical integration. Based on the first Lyapunov method, the instability regions of the system are identified, and the effects of system parameters on the amplitude–frequency response of the primary structure are analyzed. On this basis, a comprehensive performance index that accounts for both peak suppression and average vibration reduction over the frequency band is constructed, and an improved particle swarm optimization algorithm is employed for parameter optimization. The results demonstrate that the optimized BNES can effectively suppress isolated high-amplitude response branches and significantly reduce the response of the primary system within the resonance frequency band, exhibiting superior broadband vibration mitigation performance and enhanced stability. Full article