Search Results (1,704)

This paper focuses on the issue of unmodeled dynamics and large-range parametric uncertainties in air-breathing hypersonic vehicles (AHV), proposing an adaptive dynamic surface control method based on radial basis function (RBF) neural networks. First, the hypersonic longitudinal model is transformed into a strict-feedback control system with model uncertainties. Then, based on backstepping control theory, adaptive dynamic surface controllers incorporating RBF neural networks are designed separately for the velocity and altitude channels. The proposed controller achieves three key functions: (1) preventing “differential explosion” through low-pass filter design; (2) approximating uncertain model components and unmodeled dynamics using RBF neural networks; (3) enabling real-time adjustment of controller parameters via adaptive methods to accomplish online estimation and compensation of system uncertainties. Finally, stability analysis proves that all closed-loop system signals are semi-globally uniformly bounded (SGUB), with tracking errors converging to an arbitrarily small residual set. The simulation results indicate that the proposed control method reduces steady-state error by approximately 20% compared to traditional controllers. Full article

The objective of this work was to study the possibility of upgrading the control system of the drum shear mechanism by using neural network PI controllers to improve the efficiency of the sheet-metal cutting process. The developed detailed model of the mechanism, including a dual DC electric drive with three subordinate control loops for the voltage of the thyristor converter, current and speed of the motors, a 6-mass kinematic system with viscoelastic connections as well as a model of the metal cutting process, made it possible to uncover that the interaction of electric drives with the mechanical part leads to significant speed fluctuations during the cutting process, which worsens the quality of the sheet-metal edge. A modified system of current and speed controllers with built-in three-layer fitting neural networks as nonlinear components of proportional-integral channels is proposed. An algorithm for the fast learning of neural controllers using the gradient descent method in each cycle of calculating the controller signal is also proposed. The developed neuro-regulators make it possible to reduce the amplitude of speed fluctuations during the cutting process by four times, ensuring the effective damping of oscillations and reducing the duration of transient processes to 0.1 s. Full article

To address the issues of insufficient detector target size and high system complexity in infrared bionic compound-eye systems, this paper designs a miniaturized cooled medium-wave infrared curved bionic compound-eye optical system specifically for large target surface detectors and develops a proof-of-concept prototype for verification. The system comprises three components: (1) a curved multi-aperture array, which consists of 61 sub-apertures with an entrance pupil diameter of 5 mm and a focal length of 10 mm; (2) a cooled planar detector; and (3) a relay imaging system, which adopts secondary imaging technology and achieves the matching between the array and detector with only six infrared lenses. The fill factor is introduced to analyze light energy utilization efficiency, providing a theoretical basis for improving the system’s signal-to-noise ratio and spatial information collection capability; meanwhile, the focal length distribution and pupil matching are analyzed to ensure the system’s optical performance. The system operates within the 3.7–4.8 μm wavelength band, with a total focal length of 3.08 mm, F-number of 2, and field of view reaching 108°. Simulations demonstrate that all sub-aperture imaging channels have MTF values greater than 0.47 at 33.3 lp/mm, with distortion less than 3%. Imaging test results verify that the system possesses excellent imaging performance. Full article

Fostering and steering New-Quality Productivity (NQP) to underwrite the sustainable development of the Economic–Social–Environmental System (ESES) in ethnic-minority regions is both an intrinsic requirement and a strategic fulcrum for advancing modernization at the sub-national level. Despite growing policy attention, county-level evidence on how NQP translates into sustainability outcomes—and through which mechanisms—remains insufficient. Embedding NQP within a region-specific sustainability framework, this study first articulates the theoretical channels through which NQP can transform and sustain ethnic areas. It then exploits panel data covering 67 ethnic counties in Sichuan Province from 2005 to 2024 and applies benchmark regressions, multiple-mediator models, and spatial Durbin specifications to identify the mechanisms and impact footprints of NQP. Three core findings emerge: (1) NQP exerts a robust, positive effect on ESE sustainability that varies across geography, development stages, and sectoral structures. (2) Technological innovation, industrial upgrading, and optimized resource allocation all transmit NQP’s influence, with industrial upgrading displaying the strongest mediating power. (3) NQP generates positive spatial spillovers that extend its sustainability dividends to neighboring ethnic counties. These results sharpen the academic understanding of the NQP–sustainability nexus in ethnic contexts, expand NQP assessment frameworks, and furnish county-level policymakers with evidence to design differentiated strategies that align NQP cultivation with broader goals of regionally inclusive and sustainable development. Full article

Massive machine-type communications (mMTC) in future 6G networks will involve a vast number of devices with sporadic traffic. Grant-free access has emerged as an effective strategy to reduce the access latency and processing overhead by allowing devices to transmit without prior permission, making accurate active user detection and channel estimation (AUDCE) crucial. In this paper, we investigate the joint AUDCE problem in wideband massive access systems. We develop an innovative channel prior model that captures the dual correlation structure of the channel using three state variables: active indication, channel supports, and channel values. By integrating Markov chains with coupled Gaussian distributions, the model effectively describes both the structural and numerical dependencies within the channel. We propose the correlated hybrid message passing (CHMP) algorithm based on Bethe free energy (BFE) minimization, which adaptively updates model parameters without requiring prior knowledge of user sparsity or channel priors. Simulation results show that the CHMP algorithm accurately detects active users and achieves precise channel estimation. Full article

This numerical investigation employs a two-dimensional unsteady Reynolds-averaged Navier–Stokes (URANS) approach with the k-ω SST turbulence model to systematically evaluate the impact of bleed-feed channel geometry (with three width variations: 0.2D, 0.25D, and 0.3D) on double feedback fluidic oscillator performance. The focus is on improving oscillation frequency and heat transfer while reducing pressure drop, which are critical parameters in fluidic oscillator-driven jet impingement cooling applications. Addressing these challenges is essential to enhance cooling performance, minimize energy consumption, and enable reliable thermal management in advanced engineering systems. The study analyzes key performance parameters, including oscillation frequency, pressure drop, and heat transfer characteristics, comparing channel-enhanced designs against a baseline smooth oscillator. Results demonstrate that incorporating a bleed-feed channel significantly enhances performance, with the 0.3D width emerging as optimal, delivering a 150% increase in oscillation frequency and a 3.2% reduction in pressure drop compared to the smooth design. These improvements are attributed to the channel’s ability to strengthen feedback flow, thereby accelerating jet switching while minimizing energy losses. Thermally, the 0.3D configuration achieves a 7.3% higher Nusselt number than the smooth oscillator, resulting from combined effects of higher oscillation frequency (intensifying boundary layer disruption) and increased jet momentum from reinforced feedback flow. The progressive performance enhancement across the three channel widths (0.2D to 0.3D) reveals clear geometry–performance relationships. These findings provide valuable insights for optimizing fluidic oscillator designs in applications requiring high-frequency oscillations and targeted cooling, such as electronics or gas turbine blade cooling. Full article

At present, most oilfields in China have entered the late, high-water-cut stage, commonly facing declining single-well productivity and increasingly pronounced reservoir heterogeneity. Prolonged waterflooding has further exacerbated permeability contrast, yielding complex, hard-to-produce residual-oil distributions. Accordingly, the development of efficient enhanced oil recovery (EOR) technologies has become a strategic priority and an urgent research focus in oil and gas field development. Weak gels, typical non-Newtonian fluids, exhibit both viscous and elastic responses, and their distinctive rheology shows broad application potential for crude oil extraction in porous media. Targeting medium–high-permeability reservoirs with high water cut, this study optimized and evaluated a weak gel system. Experimental results demonstrate that the optimized weak gel system achieves remarkable oil displacement performance. The one-dimensional dual-sandpack flooding tests yielded a total recovery of 72.26%, with the weak gel flooding stage contributing an incremental recovery of 14.52%. In the physical three-dimensional model experiments, the total recovery reached 46.12%, of which the weak gel flooding phase accounted for 16.36%. Through one-dimensional sandpack flow experiments and three-dimensional physical model simulations, the oil displacement mechanisms and synergistic effects of the optimized system in heterogeneous reservoirs were systematically elucidated from macro to micro scales. The optimized system demonstrates integrated synergistic performance during flooding, effectively combining mobility control, displacement, and oil-washing mechanisms. Macroscopically, it effectively strips residual oil in high-permeability zones via viscosity enhancement and viscoelastic effects, efficiently blocks high-permeability channels, diverts flow to medium-permeability regions, and enhances macroscopic sweep efficiency. Microscopically, it mobilizes residual oil via normal stress action and a filamentous transport mechanism, improving oil-washing efficiency and increasing ultimate oil recovery. This study demonstrates the technical feasibility and practical effectiveness of the optimized weak gel system for enhancing oil recovery in heterogeneous reservoirs, providing critical technical support for the efficient development of medium–high-permeability reservoirs with high water cut. Full article

In the context of urban extreme weather events, the efficacy of the “emergency language” employed by governments and public institutions on social media in effectively reaching and guiding the public in a timely manner necessitates a quantifiable evaluation framework. An indicator system was constructed on the basis of Hovland’s persuasion theory. This system comprised five input characteristics (word count/structural clarity, first/second-person perspective, emotional appeal, evidence and framing, and media format) along with three output indicators (reposts, comments, and likes). A data envelopment analysis (DEA) model that is oriented towards output was employed, with disseminators being categorized into four distinct decision-making units: central mainstream media, other government media, local government media, and other media. It is imperative to note that the outputs were subjected to a process of normalization through the implementation of a scale factor. The data were sourced from the Weibo platform within the specified time window, which was from 10:00 on 24 July 2025, to 12:00 on 19 August 2025, with a sample size of 744. The findings revealed substantial disparities in technical efficiency across different disseminator types. A subset of local government media demonstrated a technical efficiency ≈ 1.00 yet low scale efficiency. Posts exhibiting clear structures, actionable points, and accompanying images or videos achieved higher cross-efficiency scores. It is therefore evident that the proposed DEA model provides a benchmark for maximizing dissemination effectiveness under given information characteristics. It is recommended that posting frequencies be maintained at consistent intervals during periods of heightened activity, that a template structure be adopted in accordance with the “fact–action–assistance channel” model, and that the proportion of rich media content be augmented. Full article

Three-dimensional holographic imaging technology is increasingly applied in biomedical detection, materials science, and industrial non-destructive testing. Achieving high-resolution, large-field-of-view, and high-speed three-dimensional imaging has become a significant challenge. This paper proposes and implements a three-dimensional holographic imaging method based on trillion-frame-frequency all-optical multiplexing. This approach combines spatial and temporal multiplexing to achieve multi-channel partitioned acquisition of the light field via a two-dimensional diffraction grating, significantly enhancing the system’s imaging efficiency and dynamic range. The paper systematically derives the theoretical foundation of holographic imaging, establishes a numerical reconstruction model based on angular spectrum propagation, and introduces iterative phase recovery and image post-processing strategies to optimize reproduction quality. Experiments using standard resolution plates and static particle fields validate the proposed method’s imaging performance under static conditions. Results demonstrate high-fidelity reconstruction approaching diffraction limits, with post-processing further enhancing image sharpness and signal-to-noise ratio. This research establishes theoretical and experimental foundations for subsequent dynamic holographic imaging and observation of large-scale complex targets. Full article

This paper addresses the issue of existing research that fails adequately capture the spatiotemporal nonstationarity caused by the building of occlusion and flight dynamics in air-to-ground channels from unmanned aerial vehicles (UAVs) in urban scenarios. This study focuses on the angular-altitude correlations of three key metrics: path loss (PL), shadow fading, and the Ricean K-factor. A dynamic path-loss model incorporating the look-down angle is proposed, an exponential decay model for the shadow-fading standard deviation is constructed, and a model for the angle-dependent variation of the Ricean K-factor is established based on line-of-sight probability. Simulations were conducted in two urban-geometry scenarios using WinProp to evaluate the combined effects of flight altitude and elevation angle. The results indicate that path loss decreases and subsequently stabilizes with increasing elevation angle, the shadow-fading standard deviation decreases significantly, and the Ricean K-factor increases with angle and saturates at high angles, in agreement with theoretical predictions. These models are more adaptable to UAV mobility scenarios than traditional fixed exponential models and provide a useful basis for UAV link planning and system optimization in urban environments. Full article

The rapid spread of unmanned aerial vehicles (UAVs) has created new challenges for airspace security, as drones are increasingly used for surveillance, smuggling, and potentially for attacks near critical infrastructure. A key difficulty lies in reliably distinguishing UAVs from visually similar birds in electro-optical surveillance channels, where complex backgrounds and visual noise often increase false alarms. To address this, we investigated recent YOLO architectures and developed an enhanced model named YOLOv12-ADBC, incorporating an adaptive hierarchical feature integration mechanism to strengthen multi-scale spatial fusion. This architectural refinement improves sensitivity to subtle inter-class differences between drones and birds. A dedicated dataset of 7291 images was used to train and evaluate five YOLO versions (v8–v12), together with the proposed YOLOv12-ADBC. Comparative experiments demonstrated that YOLOv12-ADBC achieved the best overall performance, with precision = 0.892, recall = 0.864, mAP50 = 0.881, mAP50–95 = 0.633, and per-class accuracy reaching 96.4% for drones and 80% for birds. In inference tests on three video sequences simulating realistic monitoring conditions, YOLOv12-ADBC consistently outperformed baselines, achieving a detection accuracy of 92.1–95.5% and confidence levels up to 88.6%, while maintaining real-time processing at 118–135 frames per second (FPS). These results demonstrate that YOLOv12-ADBC not only surpasses previous YOLO models but also offers strong potential as the optical module in multi-sensor fusion frameworks. Its integration with radar, RF, and acoustic channels is expected to further enhance system-level robustness, providing a practical pathway toward reliable UAV detection in modern airspace protection systems. Full article

An integrated QR-based identification and multi-participant quiz system is developed for classroom and competition scenarios. It reduces the check-in latency, removes fixed buzz-in timing, and lifts hardware-imposed limits on the participant count. On the software side, a MATLAB-R2022b-based module integrates the generation and recognition of linear barcodes and QR Codes, enabling fast, accurate acquisition of contestant information while reducing the latency and error risk of manual entry. On the hardware side, control circuits for compulsory and buzz-in modules are designed and simulated in Multisim-14.3. To accommodate diverse scenarios, the team-versus-team buzz-in mode is extended to support two- or three-member teams. Functional tests demonstrate the stable display of key states—including contestant identity, buzz-in priority group ID, and response duration. Compared with typical MCU-channel-based designs, the proposed system relaxes hardware-channel constraints, decoupling the participant count from fixed input channels. It also overcomes fixed-timing limitations by supporting scenario-dependent configuration. The Participant Information Registration subsystem achieved a mean accuracy of 86.7% and a mean per-sample computation time of 14 ms. The 0–99 s configurable timing aligns with question difficulty and instructional procedures. It enhances fairness, adaptability, and usability in formative assessments and competition-based learning. Full article

With the rapid development of unmanned aerial vehicle (UAV) technology, quadrotor UAVs have demonstrated extensive application potential in various fields. However, due to parameter uncertainties and strong coupling, the flight attitude of quadrotors is prone to external disturbances, posing challenges for achieving precise control and stable flight. In this paper, we address the tracking control problem under unknown command rate variations by proposing a Modified Linear Active Disturbance Rejection Control (LADRC) strategy, aiming to enhance flight stability and anti-disturbance capability in complex environments. First, based on the attitude dynamics model of quadrotors, an LADRC technique is adopted to realize three-channel decoupling-free control. By integrating a parameter estimator, the proposed method can compensate unknown disturbances in real time, thereby improving the system’s anti-disturbance ability and dynamic response performance. Second, to further enhance system robustness, a linear extended state observer (LESO) is designed to accurately estimate the tracking error rate and total disturbances. Additionally, a Levant differentiator is introduced to replace the traditional differentiation component for optimizing the response speed of command rate. Finally, a modified LADRC controller incorporating error rate estimation is constructed. Simulation results validate that the proposed scheme maintains good tracking accuracy under high-frequency disturbances, providing an effective solution for stable UAV flight in complex scenarios. Compared with traditional control methods, the modified LADRC strategy exhibits significant advantages in tracking performance, anti-disturbance capability, and dynamic response. This research not only offers a novel perspective and solution for quadrotor control problems but also holds important implications for improving UAV performance and reliability in practical applications. Full article

To address the limitations of traditional acoustic experimental equipment, such as large volume, discrete modules, and complex operation, this paper proposes and implements a set of digital portable acoustic teaching systems. The hardware component is based on an FPGA, enabling a highly integrated design for signal source excitation and multi-channel synchronous acquisition. It supports the output of various signals, including pulses, sine waves, chirps, and arbitrary waveforms. The software component is developed based on the Qt framework, offering cross-platform compatibility and excellent graphical interaction capabilities. It supports signal configuration, data acquisition, real-time processing, result visualization, and historical playback, establishing a closed-loop experimental workflow of signal excitation–synchronous acquisition–real-time processing–data storage–result visualization. The system supports both local USB connection and remote TCP operation modes, accommodating scenarios such as real-time classroom experiments and cross-regional collaborative teaching. The verification results of three typical experiments, namely, multi-media sound velocity measurement, TDOA hydrophone positioning, and remote acoustic detection, demonstrate that the system performs well in terms of measurement accuracy, positioning stability, and the feasibility of remote detection. This study demonstrates the technical advantages and engineering adaptability of a digital teaching platform in acoustic experimental education. It provides a scalable system solution for cross-regional hybrid teaching models and practice-oriented education under the framework of emerging engineering disciplines. Future work will focus on expanding experimental scenarios, enhancing system intelligence, and improving multi-user collaboration capabilities, aiming to develop a more comprehensive and efficient platform to support acoustic teaching. Full article

Unmanned aerial vehicle (UAV)-assisted wireless communication systems often employ the carrier aggregation (CA) technique to alleviate the issue of insufficient bandwidth. However, in high-mobility UAV communication scenarios, the dynamic channel characteristics pose significant challenges to channel estimation (CE). Given these challenges, this paper proposes a line-of-sight (LoS) and echo sensing-based CE scheme for CA-enabled UAV-assisted communication systems. Firstly, LoS sensing and echo sensing are employed to obtain sensing-assisted prior information, which refines the CE for the primary component carrier (PCC). Subsequently, the path-sharing property between the PCC and secondary component carriers (SCCs) is exploited to reconstruct SCC channels in the delay-Doppler (DD) domain through a three-stage process. The simulation results demonstrate that the proposed method effectively enhances the CE accuracy for both the PCC and SCCs. Furthermore, the proposed scheme exhibits robustness against parameter variations. Full article