Search Results (1,145)

With the prevalence of telemedicine and digital diagnosis, the security and integrity of medical images transmitted over open networks have become critical issues. To effectively defend against malicious tampering and ensure the reliability of diagnostic information, this study proposes a block-based image authentication and tamper detection framework (KPP-BA). This framework integrates key-dependent pixel permutation, hash-based message authentication code (HMAC)-SHA256 hash verification, and a parity-based 3-LSB minimal distortion embedding strategy. The core innovation lies in utilizing pseudo-random pixel permutation to disrupt spatial correlation within blocks, thereby effectively resisting collage and statistical analysis attacks. Furthermore, by combining the avalanche effect of HMAC-SHA256 with hybrid bit-plane feature extraction, the proposed method ensures extremely high sensitivity to subtle tampering. Experimental results on a dataset comprising 300 medical images demonstrate that the proposed method maintains superior visual quality while ensuring security, achieving an average Peak Signal-to-Noise Ratio (PSNR) of 54.15 of 0.5 bit per pixel (bpp). Moreover, against various tampering attacks—including masking, copy–paste, circle masking, and collage—the method exhibits exceptional detection capabilities with an average detection accuracy of 99.99%. Compared with seven state-of-the-art methods, the proposed framework demonstrates significant advantages in both image fidelity and tamper localization precision, validating its feasibility and robustness for secure medical image transmission applications. Full article

In today’s manufacturing industry, work-related musculoskeletal disorders (WMSDs) remain among the most prevalent occupational health issues. Collaborative robots (cobots) represent a promising technology to address this challenge. Consequently, ergonomics assessment in human–robot collaboration (HRC) has gained increasing attention in recent years. This study investigates the feasibility of using a coupled digital twin system consisting of a digital human model (DHM) and a cobot digital twin to assess detailed ergonomic parameters such as muscle activations and joint reaction forces in an HRC task. Selected parameters are used to develop an ergonomics map that condenses the effects of human–robot interaction into a single scalar value for each working position in the coronal plane in front of the user. The ergonomics mapping approach is presented, key influencing factors are identified, and critical workspace design implications are discussed. Full article

The performance of the aircraft anti-skid braking system is critical to the ground operational safety of an aircraft. Conventional Pressure Bias Modulation (PBM) can suffer from deep skidding under low runway friction coefficients or low aircraft speeds. To address these issues, a composite control strategy based on Gaussian Quantum Particle Swarm Optimization (GQPSO) is proposed. This strategy employs the GQPSO algorithm for offline Proportional–Integral–Derivative (PID) parameter optimization, followed by real-time adaptive scheduling through a lookup table to accommodate varying speed domains and runway conditions. Simultaneously, by integrating the main-wheel dynamics model and friction characteristics, a runway identification function based on a Back Propagation Neural Network (BPNN) is designed to provide runway status information. The stability of the controller is verified via phase-plane analysis and Monte Carlo simulation. Subsequently, comparative Hardware-in-the-Loop (HIL) tests are conducted among PBM, PSO-PID, and the proposed GQPSO-PID controller under various runway conditions. The experimental results demonstrate that this composite controller can adapt to different speed domains and runway conditions, stably track the target slip ratio, effectively suppress skidding, and significantly improve braking efficiency, as well as exhibiting excellent robustness and control performance. Full article

The in-plane shear performance of carbon fiber-reinforced polymer (CFRP) composites is critical for structural design but is challenged by significant property scatter. This study aims to achieve individualized prediction of the complete shear stress–strain curve for each composite specimen using only a single early-stage digital image correlation (DIC) strain field. Systematic in-plane shear tests were conducted on 45 laminated carbon fiber/epoxy specimens with synchronized full-field DIC data and macroscopic load–displacement records. A lightweight encoder–decoder convolutional neural network was developed, taking a single DIC strain contour map at 0.2% global strain as input and mapping it directly to the full-range stress–strain curve up to failure for that specific specimen. Data augmentation and Dropout regularization mitigated the small-sample challenge. The proposed model achieved strong predictive performance across the five-fold cross-validation yielded a mean R² of 0.926 ± 0.022 and a mean RMSE of 6.37 ± 1.14 MPa for stress. Individual specimen predictions on the test set yielded an average R² of 0.945, with a minimum of 0.821, confirming robust capability across scattered properties. Residual analysis elucidated error characteristics across deformation stages. This research provides a novel paradigm for non-destructive, early-stage individualized assessment of composite mechanical properties, with applications in structural health monitoring and probabilistic design. Full article

Anterior cruciate ligament (ACL) injuries remain a leading cause of morbidity in athletic populations, with 70–80% occurring through non-contact mechanisms driven by biomechanical risk factors including knee valgus (>10°), low knee flexion (<30°), tibial internal rotation (>20°), and loading asymmetry (>15°), yet implementation of evidence-based neuromuscular training (which reduces injury risk by 50–70%) remains limited due to barriers in identifying at-risk individuals through accessible field-based screening. This narrative review synthesizes motion analysis technologies spanning laboratory-based optical systems (marker-based), wearable inertial measurement units (IMUs), computer vision and marker-less pose estimation, force plate and pressure-sensitive insole systems, and integrated drone-based field assessment platforms to address this critical gap. We present a three-tier clinical screening framework that progresses from basic anthropometric and single-plane video analysis to multi-modal biomechanical assessment using real-time kinematic feedback. As an illustrative example of emerging field-deployable technology, an integrated drone-based motion capture and smart insole system combining 4K video capture, AI-driven 3D motion reconstruction, and plantar pressure mapping is described to demonstrate how laboratory-quality biomechanical assessment can be achieved in ecologically valid field settings. This evidence-based review addresses current gaps between laboratory research and practical field deployment, with emphasis on cost-effectiveness, accessibility, and clinical utility for ACL injury prevention in diverse sporting environments. Full article

This paper presents a novel design approach for mitigating the adverse effects of antenna mountings on the radiation pattern of GNSS antennas. By employing a resistive structure integrated into the ground plane, the proposed solution suppresses unwanted edge diffraction and near-field reflections caused by nearby mounting hardware. The design is developed using the concept of tapered resistive sheets and optimized using a customized cost function that accounts for pattern degradation across multiple realistic mounting configurations, ensuring robust performance under varying installation conditions. The resulting structure is fabricated using additive manufacturing (AM), enabling precise realization of complex resistive profiles with tailored surface impedance. Comprehensive validation through both electromagnetic simulations and experimental measurements demonstrates significant improvements in radiation pattern stability and reduced sensitivity to near-field objects, particularly in critical GNSS bands such as E5a/L5 and E1/L1. The results demonstrate that the proposed structure significantly enhances antenna reliability and calibration integrity in real-world deployments, offering a practical, hardware-based solution to a persistent challenge in high-precision GNSS systems. Full article

Trust evaluation in Industrial Internet of Things (IIoT) edge networks must account for both device behavior and the operational importance of industrial assets. Existing models often apply uniform scoring rules, which may limit their response to semantic attacks and whitewashing behavior while increasing the processing burden on edge devices. This paper presents an Asset-Aware Resilient Trust (ART) framework. ART separates dynamic behavioral credibility from physical asset criticality through a dual-plane architecture. Cross-layer evidence is collected from communication, identity, physical, and semantic interactions. A Fuzzy Triggered-Entropy Weight Method (Fuzzy T-EWM) recalculates evidence weights only when the observed fluctuation exceeds a preset threshold. Trust scores are updated using a Fast-Drop Slow-Rise rule, together with a tolerance margin for routine network jitter. The simulation results show that ART detects stealthy False Data Injection attacks, limits trust recovery after whitewashing behavior, and reduces accumulated computational overhead by 76.4% compared with the Standard EWM baseline. The credibility-weighted aggregation mechanism also limits collusive recommendation manipulation during cold-start evaluation. These results support differentiated trust regulation for IIoT edge networks. Full article

The nanoindentation analysis of zirconium carbide (ZrC) has been studied through molecular dynamics simulations, focusing on various factors such as temperature, stoichiometric ratio, and crystal orientation. The findings show that as temperature increases, both the critical pop-in load and the maximum load decrease, while atomic strain, von Mises stress, and residual indentation depth increase. High temperatures facilitate the nucleation and propagation of 1/2<110> dislocations, which enhance the material’s ability to undergo plastic deformation. Both indentation hardness and Young’s modulus decrease linearly as temperature rises or the concentration of C vacancy increases. For stoichiometric ZrC, as the temperature rises from 10 K to 2100 K, the hardness decreases from 45.04 GPa to 20.36 GPa, and Young’s modulus drops from 396.28 GPa to 254.45 GPa. At 10 K, when the C/Zr ratio is reduced to 0.5, the hardness and Young modulus decrease to 25.32 GPa and 192.09 GPa, respectively. This reduction is attributed to the weakening of Zr-C bonds, which also reduces stress concentration. At elevated temperatures, the impact of C vacancies on the nanoindentation process diminishes due to the thermal softening of the substrate, which lessens the effects of vacancy-induced softening. Regarding anisotropy, Young’s modulus at room temperature decreases from 383.39 GPa on the (001) plane to 335.93 GPa on the $(1\stackrel{\mathrm{-}}{1}0)$ plane, and it reduces further to 303.31 GPa on the $(1\stackrel{\mathrm{-}}{1}1)$ plane; hardness shows a similar decreasing trend. This trend is primarily due to differences in slip systems, surface energies, and the angles between the plane normal and the Zr-C bond axis located directly beneath the surface atoms. Overall, these results may provide theoretical support for the processing and application of ZrC. Full article

With deep coal mining in China, high in situ stress frequently causes severe floor deformation, bolt-cable support failure, and excessive floor heave, which critically threaten mine safety. In this study, we use physical experiments, numerical simulation, and theoretical analysis to explore how hydraulic fractures with different azimuth angles affect stress transfer in roadways under floor dynamic pressure. Prefabricated fractures simulate weak planes induced by hydraulic fracturing. Uniaxial compression tests and PFC2D fluid–solid coupling simulations analyze mechanical properties, failure modes, acoustic emission behavior, and stress distribution. Results show that fracture azimuth significantly controls rock damage and failure modes. As the angle increases from 0° to 90°, failure changes from gradual degradation to sudden instability. Peak strength first decreases then increases, reaching the minimum at 22.5°, while roadway damage is minimal at 45°. Small-angle fractures lead to shear failure with clear precursors, and large-angle fractures cause sudden tensile failure. Hydraulic fractures form directional stress-relief zones and enable effective stress transfer and pressure relief. The results support parameter optimization of hydraulic fracturing and stability control for deep roadways under floor dynamic pressure. Full article

The qualification of additively manufactured (AM) components produced from engineering polymers poses unique challenges, particularly when evaluating mechanical properties according to ASTM D638. The application of high-performance thermoplastics, such as ULTEM™ 9085 and ULTEM™ 1010, frequently relies on manufacturer-provided datasheets for qualification. However, existing datasheets do not provide guidance specific to articles printed in the XY plane, which can be complicated by failures that initiate at microstructural anomalies rather than being driven by intrinsic material behavior. The objective of this study was to investigate the performance and qualification of ULTEM 9085™, examined according to ASTM D638, and pursue improvements through refined print parameters. A significant improvement in strength and conforming failures was achieved with modest adjustments to the print settings. For Type 1 samples printed with ±45° infill, gage section failures improved from only 5% to 100%, while samples with 0/90° infill achieved 80%. Correspondingly, the ultimate tensile strength increased from 49 ± 2 MPa to 61 ± 2 MPa and from 53 ± 3 MPa to 63 ± 6 MPa, respectively. These results underscore the critical role of process parameters, including contour overlap, in qualifying polymer AM materials, and their contribution to the performance and reliability of printed components. Full article

The squat is a critical component of numerous rehabilitation and functional assessment protocols, playing a significant role in enhancing athletic performance and activities of daily living. Although some of the characteristics gathered during the squat need additional confirmation, Kinovea provides a free two-dimensional squat motion analysis tool that is simple to use in clinical practice. This analytical, cross-sectional reliability study aimed to evaluate the intra-rater and test–retest reliability (with a 20 min interval between performances) of loaded squat kinematics in a sample of women using Kinovea. Twenty women performed a loaded back squat; intra-rater reliability was assessed by re-analyzing the same video one week apart, and test–retest reliability was assessed across two performances separated by 20 min. The results showed good to excellent intra-rater reliability (ICC: 0.75–0.99; SEM: 0.16 cm to 5.14°; MDC: 0.44 cm to 14.24°), and moderate to excellent test–retest reliability (ICC: 0.64–0.98; SEM: 0.36 cm to 14.29°; MDC: 0.99 cm to 39.61°). Variables tracked in the sagittal plane showed high precision. Conversely, the head angle and knee angle in the frontal plane exhibited greater variability, reflected by higher SEM and MDC values. In conclusion, Kinovea is a reliable and accessible tool for clinical kinematic assessment of the squat, particularly in the sagittal plane parameters. However, due to the elevated measurement error observed in head angles and frontal-plane knee dynamics, the integration of 3D motion capture is recommended over 2D digital protocols for these variables. Full article

Investigation of the drill–rock interaction mechanism is fundamental to the design and optimization of drilling engineering. Existing theoretical studies have primarily focused on intact and homogeneous rock formations, whereas analytical studies of drilling in jointed rock masses remain limited. To address this issue, this study examines the drilling behavior of jointed rock masses and analyzes the forces acting on the drill bit during joint crossing. It is proposed that the non-uniform distribution of rock at the borehole bottom generates an additional longitudinal torque on the drill bit within the vertical plane. Based on whether this torque is considered, both static and dynamic mechanical models for drilling across a joint interface are established. Using parametric analyses, the evolution of weight on bit (WOB) and torque under the two modeling approaches is investigated, together with their sensitivity to differences in mechanical properties of rocks on either side of the joint. The results show that when the drill bit penetrates from hard rock into soft rock across a joint interface, both WOB and torque continuously decrease if longitudinal torque is neglected. In contrast, when longitudinal torque is considered, WOB and torque first increase and then decrease. The longitudinal torque increases both drilling parameters, with maximum increments in WOB and torque reaching 56.0% and 2.8%, respectively, indicating a more pronounced influence on WOB. As the mechanical-property differences between rocks on either side of the joint increase, the relative increments of WOB and torque, which characterize load fluctuation magnitude, initially increase and then gradually stabilize. The critical increments at stabilization are 0.73 for the internal friction angle and 7.17 for cohesion. These findings indicate that WOB and torque variations during joint crossing increase with increasing strength contrast across the joint interface, and that differences in internal friction angle exert a greater influence than cohesion. This study is primarily theoretical, and the proposed models are preliminarily validated through comparison with results in the literature. The developed analytical models reveal the drill–rock interaction mechanisms during drilling in jointed rock masses, clarify the influence of longitudinal torque on drilling parameters, introduce quantitative indices characterizing WOB and torque fluctuations, and establish their relationships with mechanical-property contrasts across joint interfaces. The findings provide a theoretical basis for interpreting drilling responses induced by geological discontinuities, evaluating jointed rock masses, and optimizing drilling parameter design. Full article

Rockfall from slope unstable rock masses is a typical geological hazard induced by brittle failure, with abrupt occurrence, limited macroscopic deformation before failure, and a short warning lead time. Conventional static analysis methods are useful for design-stage stability checks, but they cannot continuously capture structural-plane damage or update the stability state in real time. Dynamic evaluation based on structural dynamics links measurable parameters such as natural frequency, damping ratio, mode shape, vibration trajectory, wave velocity, and energy dissipation to the degradation of structural planes. This review synthesizes the dynamic behavior mechanism, parameter system, theoretical models, sensing technologies, and engineering applications for slope unstable rock masses. Different from previous reviews that mainly summarize rockfall monitoring or conventional slope stability analysis, this paper organizes the literature by failure mode, monitoring scale, model assumptions, field validation, uncertainty sources, and engineering applicability. The single-degree-of-freedom models for sliding-, toppling-, and falling-type rock masses, multi-block chain-collapse models, and data-physics dual-driven surrogate models are compared critically. Contact monitoring based on MEMS sensors, non-contact LDV monitoring, acoustic emission, microseismic monitoring, coda wave interferometry, and cloud-edge early-warning architectures are further reviewed. Key challenges include field-scale validation under heterogeneous and anisotropic geological conditions, environmental compensation, robust threshold calibration, and probabilistic linkage between dynamic indicators and failure probability. The review provides guidance for selecting dynamic evaluation models, designing field monitoring systems, and developing full-life-cycle digital-twin platforms for rockfall risk mitigation. Full article

Magnetic skyrmions have emerged as promising candidates for next-generation nanomagnetic devices owing to their stability, nanoscale size, and efficient manipulability. In this work, we demonstrate the deterministic creation of skyrmions using a single ultrafast laser pulse in a thin ferromagnetic film. Through micromagnetic simulations, we model the effect of a focused picosecond laser pulse on a Pt/Co-based multilayer with interfacial Dzyaloshinskii–Moriya interaction (DMI). We find that above a threshold laser fluence, or equivalently, a critical pulse duration, a stable 25 nm Néel-type skyrmion diameter is created at low temperature under a modest out-of-plane magnetic field. Our results demonstrate that skyrmions can be written deterministically by a single picosecond laser pulse, eliminating the need for multiple exposures or electrical stimuli. This work systematically identifies the ultrafast excitation and material-parameter ranges that enable stable solitary skyrmion nucleation in experimentally realistic magnetic multilayers. This can be a foundation for photonic-spintronic integration, enabling optical data writing and magnetic storage, offering a pathway toward ultrafast, energy-efficient, and contactless control of topological spin states for future memory and logic applications. Full article

With the transition to deep coal mining, the transparent detection of hidden geological hazards in the floor strata is fundamental for production safety. In mine seismic exploration, gliding waves—inhomogeneous plane waves propagating along the coal–rock interface—offer a unique advantage for penetrating high-velocity floors via the skin effect, overcoming the total reflection limitations of conventional in-seam waves. This study investigates the propagation laws and anomaly response characteristics of floor gliding waves using super-critical incidence theory and high-order staggered-grid finite difference simulations. The results demonstrate that the apparent velocities of gliding P and S-waves are bounded by those of the coal and host rock, exhibiting minimal dispersion. Quantitative analysis using a penetration depth model reveals that while penetration depth is frequency-dependent—with lower frequencies providing deeper reach—high-frequency components remain essential for high-resolution imaging. Crucially, the proposed method was validated through a field Case Study at the 11123 working face. By utilizing a specialized deep-hole excitation strategy to ensure super-critical incidence, the inversion successfully identified a hidden fault extending up to 60 m below the floor, which was subsequently confirmed by rock roadway excavation. These findings establish a robust physical basis for designing underground floor-detection systems and provide a significant theoretical reference for addressing detection blind spots in deep mining environments. Full article