Search Results (222)

This study devised a blasting experiment to establish a dynamic quantified relationship between blasting and movement, failure, and ejection of rock masses. The experiment was conducted using the 3D digital image correlation method (3D-DIC), which provided high-speed images capturing the process of shallow-buried tunnel blasting. The study analyzed the mechanical behavior of full-section rock mass under blasting action through cross-scale image processing. Yield and elastic points were distinguished based on the time–displacement curve. Then, the spatial vector method was employed to deduce flying rock trajectory and throwing distance, enabling the subdivision of underground space based on risk assessment. The results show that the rock in the cut zone starts moving within 3 ms after initiation, ultimately exhibiting a maximum visible off-plane displacement of 215 mm. Displacements are related to delay time and distance. Different zones show distinct dominant directions of rock mass displacement. The rock mass becomes flying rocks separated from the cross-section. The initial velocity of the flying rocks ranges from 11.8 m·s⁻¹ to 29.9 m·s⁻¹. Around 85% of the flying rocks fall within the range of 0 to 40.8 m. Only 5% of the flying rocks fall outside 64.3 m. Appropriate protective measures should be taken for equipment during experiments. Full article

Broadband Capon direction-of-arrival estimation is computationally demanding because covariance processing, spatial spectrum evaluation, and steering-vector construction are repeatedly performed over multiple frequency bins and candidate directions. This study presents an efficient framework for horizontal-plane sound source azimuth estimation by combining pairwise Capon processing with recursive steering-vector generation. The array is partitioned into ordered two-microphone pairs, enabling independent $2\times 2$ covariance processing. Each pair estimates a local angle relative to its directed baseline, and the resulting constraints are fused according to the array geometry. In the implemented orthogonal cross array, both pairs lie in the horizontal plane and provide complementary components of the planar source direction. A general fusion formulation is also provided for non-orthogonal baselines and non-coincident pair midpoints. The frequency-linear phase structure of the pairwise steering vector is exploited to replace repeated trigonometric evaluations across DFT bins with recursive complex rotations. Across 80 single-source trials, the proposed method achieved an MAE of $1.88°$, an RMSE of $3.54°$, and 100% of estimates within $\pm 10°$. The steering-vector generation time decreased from 165.69 ms to 66.77 ms, while the total measured component time decreased from 172.14 ms to 70.92 ms. Additional evaluations of multi-source resolution, reverberation, moving sources, numerical stability, and irregular arrays demonstrate a practical trade-off between computational efficiency and localization robustness. Full article

Image-stitching methods for moving elongated objects require high stitching quality, efficient inference, and robustness to interference from regions outside the target object. Existing methods still have difficulty satisfying these requirements simultaneously. This paper proposes a semi-supervised deep image-stitching method for moving elongated objects. The proposed framework consists of two stages: semi-supervised registration and unsupervised reconstruction. In the semi-supervised registration stage, a semi-supervised optical-flow estimation network is used to predict the bidirectional optical flow between the input images. An object-centric spatial transformation module is then introduced to remove regions outside the moving object and warp the inputs onto a unified plane. In the unsupervised reconstruction stage, a multi-scale fusion model is used to improve the quality of the reconstructed stitched image. Correspondingly, we design a reconstruction objective function based on multi-scale feature representations. To address the lack of available datasets for this task, we construct two datasets: MEOIS-D, a synthetic dataset for generalized evaluation, and Container-D, a real-world scene-specific dataset. Extensive comparative experiments and ablation studies demonstrate the effectiveness of the proposed method. Full article

Digital holography is a powerful imaging technique for quantitative analysis in various fields of science and technology, including biomedical applications. However, the development and validation of neural network-based methods in this field are often limited by the unavailability of large, well-annotated experimental data. For example, in biological studies, the typical size of an experimental dataset is around 1000 images. In this work, we present a procedural framework for generating synthetic datasets of biological cell phase images and digital holograms. The generated datasets were tested in several key tasks of neural network applications, including cell classification, detection, and phase reconstruction from in-line holograms. High classification accuracy is achieved for both phase images and holograms, while phase reconstruction reaches high structural similarity indices. The applicability of the generated datasets is further demonstrated in complex scenarios involving multiple moving cells and multiple object planes. The proposed approach provides a flexible and scalable platform for method development, performance evaluation, and future integration with experimental holographic imaging systems. Full article

Haptic feedback has attracted significant attention in virtual reality (VR), augmented reality (AR), and teleoperation because it can provide rich tactile information of an object through skin without increasing visual load. Among the many tactile presentation methods, vibration is the most widely used, and numerous vibration actuators have been incorporated into tactile displays. For directional control, attempts have been made to generate directional acceleration within a two-dimensional plane using a single device, but the reported device produces a single-shot impact rather than continuous vibration and offers limited control of the acceleration magnitude. To address this, we focus on a shape-memory alloy (SMA) wire. The wire contracts when heated by an applied current and returns to its original length when the current is stopped. Such repeated contraction and recovery generate vibration in synchronization with a pulse current. This paper proposes a vibrator that suspends a moving part with four SMA wires to generate two-dimensional directional acceleration with a single compact device. Through driving experiments, we show that the device generates acceleration aligned with the axis of each of eight target directions spaced at 45° intervals, and that the magnitude of the acceleration can be adjusted through the duty ratio at a fixed driving frequency. The perceptual evaluation of the presented direction is left for future work. Full article

This paper presents a metrology-oriented review of vision-based displacement and deformation measurement for civil structural health monitoring (SHM), with an emphasis on field robustness and uncertainty quantification (UQ). The review focuses on image- and video-based methods that convert visual information into quantitative physical measurements, such as displacement, strain, or derived dynamic indicators. The literature is organized according to the main stages of the measurement chain: image formation, image-plane motion estimation, and geometric conversion to metric motion. Within this framework, measurement pipelines are interpreted through three levels of geometric mapping, namely, a scalar scale-factor model, a planar homography-based model, and a full Jacobian-based model. The review synthesizes major method families, including marker-based and markerless tracking, feature-based tracking, optical flow, digital image correlation (DIC), phase-based motion magnification, edge-based estimators, fixed- and moving-camera configurations, UAV-based acquisition with ego-motion compensation, hybrid vision–sensor fusion, and deep-learning-enhanced pipelines. A structured taxonomy of uncertainty sources is then presented along the processing chain, covering camera geometry and calibration, imaging noise and blur, quantization, timing and synchronization, environmental disturbances, optical turbulence and heat haze, platform motion, algorithmic failure modes, and reference-sensor uncertainty. The paper also compares UQ practices, including GUM-aligned analytical propagation, Monte Carlo methods, DIC-specific error budgets, bootstrap and resampling strategies, and probabilistic deep learning. The main contribution of this review is to connect computer-vision-based displacement pipelines with metrological requirements by explicitly linking measurement models, uncertainty sources, UQ methods, and field-validation evidence within a unified framework. A practical uncertainty-budget template is compiled to support traceable reporting across different pipelines and deployment scenarios. The paper concludes with prioritized research gaps and future directions, including standardized benchmarks and datasets, traceable UQ for moving-camera systems, multi-sensor fusion with end-to-end uncertainty propagation, long-term drift characterization, optical-turbulence and adverse-weather modeling, validated subpixel limits at extreme range, probabilistic deep learning–metrology integration, and standardized reporting practices. Full article

Background: Clinicians working with children with neuromotor impairments require sensitive measures to assess postural control and evaluate interventions. This study explored the sensitivity of a single Inertial Measurement Unit (IMU) to changes in postural control during reaching in sitting with clinician support at different segmental levels: upper thoracic, lower thoracic, lower lumbar, and no support. The effect of pelvic-stabilizing straps was examined. Methods: A single Delsys Trigno IMU sensor attached over the mid-thoracic spine recorded acceleration and angular velocity data during a reaching task in sitting in ten typically developing children. Results: Comparisons of the support levels showed a significantly lower range of accelerations in the medial–lateral and anterior–posterior directions when support was provided at the upper thoracic level compared to support at the lower lumbar level. The range of angular velocity in the sagittal and coronal planes showed progressively lower values as the level of support moved cranially. Pelvic stability straps allowed for a significantly greater range of acceleration values in all directions and a greater range of angular velocities in the sagittal and transverse planes. Conclusions: These exploratory findings suggest that IMUs may have clinical utility in postural control assessment and evaluating the effects of intervention in children with neuromotor impairment. Full article

The use of the stress intensity factor K to characterize the severity of crack tip stress fields is widespread throughout engineering. The relationship between K and the crack growth rate is then usually represented empirically by a straight line Paris law relationship on logarithmic axes. This study develops an analytical relationship between the two by linking crack growth to the accumulation of fatigue damage ahead of the moving crack tip. A stress-based fatigue model was used, with inputs from plastic 2D plane stress FE analyses representing an edge crack by a sharp semi-circular notch. Stress–distance profiles ahead of the crack tip were extracted at the maximum and minimum points of a range of fatigue loading cycles. These were then used with data from smooth specimen LCF tests to predict the build-up of fatigue damage at regularly spaced locations ahead of the crack tip and hence crack growth rates. Full da/dN–ΔK curves were generated for the nickel-based superalloy RR1000 at 20 °C with loading R-ratios of 0, −1 and 0.5. The R = 0 and R = −1 crack growth rate predictions agreed well with experimental data, as did the steeper growth rate slope calculated at R = 0.5. The method was then extended to predict overload behaviour. Full article

Background: Changes in the rearfoot calcaneal position affect the foot “arch structure” during the stance phase of gait and hence influence reactions in the plantar fascia thickness and stiffness during weight bearing. However, previous research has focused on the non-weight-bearing assessment of plantar fascia thickness (PFT) and stiffness (PFS) and has not linked these measurements to rearfoot position. Methods: This study aims to investigate if a change in the weight-bearing rearfoot position influences the PFT and PFS. A linear actuator-driven 3D-printed platform was utilised to reliably move the rearfoot through a range of frontal (F (4,12) = 19,585.8, p = 0.00) and sagittal plane angles (F (2,6) = 11,751.32, p = 0.00) whilst weight bearing. An ultrasound probe capable of shear wave elastography was incorporated into the platform for the closed-chain weight-bearing assessment of the PF. The PFT and PFS were collected for 13 (26 feet) participants (11 male, two female; age 35.62 ± 15.04; BMI: 30.31± 6.22 Kg/m²) from a convenience sample who met the inclusion criteria. Results: The data were subject to appropriate statistical, collective and cluster analysis. Individual participant data analysis showed a strong nonlinear correlation between PFT and PFS in the relaxed calcaneal position. The rearfoot sagittal plane cluster demonstrated an auxetic property in 54.3% of the group, where both the PFT and PFS increased. The frontal plane cluster demonstrated an auxetic property in 76% of the group, where the PFT increased as the PFS increased. Conclusions: The results suggest that the PF does have a specific response to changes in the rearfoot position for individuals, which, in some, can show an auxetic property. Full article

This paper investigates time-varying output formation (TVOF) tracking for heterogeneous small fixed-wing unmanned aerial vehicles (UAVs) and nonholonomic unmanned ground vehicles (UGVs). The small fixed-wing UAVs operate in three-dimensional space, and the UGVs move on a two-dimensional plane, leading to heterogeneous dynamics with nonholonomic constraints, asymmetric velocity constraints, and input saturation. To address these challenges, distributed adaptive control protocols are developed under switching directed communication topologies. Unlike existing TVOF tracking methods that require global information, the proposed protocols do not rely on the upper bound of the leader’s unknown input or the eigenvalues of the Laplacian matrix. A constructive parameter-selection algorithm is provided, and the closed-loop stability is established using Lyapunov theory. Numerical simulations involving heterogeneous UAV-UGV formations verify that the proposed method achieves TVOF tracking under random disturbance while satisfying the prescribed motion constraints. Full article

Real-time kinematic (RTK) positioning in open-pit mining environments is critically compromised by non-line-of-sight (NLOS) signals and anisotropic multipath effects induced by pit walls, haul roads, and industrial infrastructure. Conventional elevation-dependent stochastic models fail to discriminate between geometrically favorable low-elevation satellites and those subject to directional obstruction, resulting in degraded ambiguity resolution and decimeter-level positioning errors that undermine safety-critical deformation monitoring. This paper presents an adaptive RTK positioning framework utilizing azimuth-integer-based elevation masking to explicitly model site-specific obstruction geometry. The proposed method discretizes the horizontal plane into 360 integer-degree sectors, extracts minimum elevation angles per sector from 24 h line-of-sight (LOS) data, and constructs a smoothed 360°mask profile via moving-window filtering. A virtual elevation-angle transformation is introduced to normalize satellite geometry relative to the local mask, enabling adaptive down-weighting of diffraction-susceptible observations within the stochastic model without requiring multi-day satellite repeat arcs or hardware modifications. The approach was validated using 54 h of BDS data collected at eight monitoring stations within the Wangjialing open-pit mine, China. Implementation of the mask model engendered a selective 8.1% reduction in satellite participation (15.66 to 14.39 satellites) while significantly enhancing observation quality. The ambiguity validation ratio improved by 19.5% (from 9.43 to 11.27 in the experimental project), and the fix success rate increased from 92.4% to 97.2% (exceeding the 95% reliability threshold at all stations). The RMS errors in the east, north, and up directions improved by 34.8% to 65.2%, 28.7% to 77.0%, and 44.8% to 70.8%, respectively, with the most dramatic gains observed at stations subject to severe azimuthal obstruction (e.g., ZDH6 vertical RMS: from 50.7 mm to 14.8 mm). By explicitly modeling anisotropic obstruction geometry through discrete angular sampling, the proposed method achieves sub-centimeter positioning accuracy and robust ambiguity resolution in challenging mining environments without additional hardware or empirical threshold tuning, offering a cost-effective solution for large-scale, real-time deformation monitoring systems. Full article

Precision alignment and target contact are critical tasks for mobile manipulators in industrial inspection and flexible manufacturing. However, achieving high accuracy after navigation remains challenging due to accumulated errors from mobile base localization, perception noise, and calibration uncertainty. This paper proposes a vision-guided precision alignment framework for mobile manipulators using a single front-facing RGB-D camera. The method integrates YOLO-based target detection, AR marker-assisted plane depth estimation, and depth-based 3D localization within a coarse-to-fine alignment strategy. After navigation, the manipulator first moves to a predefined pre-alignment pose, followed by visual localization and iterative refinement to compensate for residual errors before executing precise target contact. The proposed system is implemented and evaluated in a Gazebo-based simulation environment using a mobile manipulator platform model. In a static touch panel experiment with 50 trials, the system achieves a success rate of 98%, with positioning errors maintained within a millimeter-level range. Simulation results demonstrate that the proposed method provides stable alignment performance in the simulation environment without relying on external sensing devices such as force sensors or multi-camera systems. The proposed approach shows promising potential for precision contact tasks in mobile manipulation. Full article

Train track occupancy detection is essential for railway operation safety and dispatching, yet GNSS-based positioning and track matching can degrade or fail in turnouts and station yards due to multipath, interference, and dense track layouts. This paper presents an IMU-only method to discriminate track-switching events during turnout passage by exploiting the transient change in heading angular velocity. The Z-axis gyroscope measurement (approximately aligned with the track-plane normal) is used as a heading-rate proxy, and a lightweight indicator is constructed from the difference between a short-window moving average and the full-run mean. The full-run mean further serves as an in situ approximation of the gyroscope zero bias, alleviating the need for pre-calibration and improving robustness to systematic drift. A fixed discrimination threshold is determined from stationary gyroscope noise statistics, and the minimum effective operating speed is derived by combining gyro noise characteristics with the kinematic relationship among train speed, turnout curvature radius, and heading rate. Field experiments conducted from January to April 2025 on three railway sections covering 27 turnouts (300 turnout-passage events) show that, using a constant threshold $T_0=0.002\mathrm{rad}/\mathrm{s}$, the proposed method achieves 100% track-switching discrimination accuracy within 5–40 km/h, without requiring track maps, GNSS, or prior databases. Full article

Background/Objectives: Cone beam computed tomography (CBCT) is vital in endodontics but suffers from beam-hardening artifacts caused by metallic restorations, which can obscure diagnostic details. This study evaluated a novel patient positioning protocol—a controlled head tilt—designed to mitigate these artifacts by moving contralateral metallic structures outside the primary X-ray path in small field of view (FoV) CBCTs. Methods: Using a skull phantom with metallic restorations CBCT scans were acquired in three positions: standard alignment, a 12° tilt toward the region of interest (ROI), and a 12° tilt to the opposite side. Fifty experienced dentists, blinded to the protocol, subjectively compared image quality and artifact severity between the tilted and reference images. Results: The tilt away from the ROI was rated as providing better image quality significantly more often than the tilt towards the side of the ROI (442 of 585 non-tied comparisons; p < 0.001). A complementary rater-clustered GEE analysis adjusted for slide confirmed higher odds of “better” ratings under head tilt away from the ROI for image quality (OR = 4.16, 95% CI 3.12–5.56) and artefacts (OR = 2.87, 95% CI 1.93–4.26). An individual head tilt significantly improves subjective small-FoV CBCT image quality, most evidently in the longitudinal plane, by reducing artifact interference from contralateral metals, and should be considered a practical strategy for clinical use, and may serve as a practical chairside strategy, pending clinical validation. Full article

Background: Sport climbing, encompassing lead, bouldering, and speed disciplines, has transformed from a niche activity to a widely popular trend, notably after its Olympic debut at the Tokyo Games 2021. This recognition spurred an increase in publications. Despite the emerging scientific interest, terminology in climbing textbooks often relies on experiential rather than scientific understanding, leading to inconsistencies. This paper aims to standardize terminology by applying sports science frameworks, including biomechanics, training science, and sports medicine. Methods: The study reinterprets general sports science concepts for climbing-specific applications, proposing a structure of climbing skill that covers physical fitness components, biomechanical principles and techniques (body positioning), and specific components (hand and foot positioning). This integrated approach seeks to establish a coherent nomenclature, facilitating research, training, prevention, and rehabilitation within the climbing discipline. Results: Five primary climbing principles are proposed: optimal wall contact, maintained stability, center of mass shift, movement initiation from the legs and optimal climbing speed. Two technique categories—frontal and rotational—are defined in consideration of the spatial position of the pelvic frontal plane in relation to the wall surface. Each climbing technique can be described by applying the three-phase model of acyclic movements. Principles and techniques both aim to maximize efficiency in moving and resting on the climbing wall. Conclusions: A unified understanding of climbing principles and techniques is vital for progressing research, training programs, prevention strategies, and rehabilitation efforts in sport climbing. Adopting a comprehensive sports science framework promises enhanced clarity and efficacy in climbing practices, benefiting both theoretical analyses and practical applications. Full article