Search Results (1,918)

Motor vehicle encroachment into non-motorized lanes is a common but hard-to-verify violation in urban intersections, especially when monitored from unmanned aerial vehicles (UAVs) or high-mounted overhead views. Existing rule-based solutions built on horizontal bounding boxes and center-point/line-crossing criteria are sensitive to perspective distortion, occlusion, and frame-to-frame jitter, resulting in unstable decisions and low evidential value. This paper presents a cascaded UAV-view system that closes the loop from perception to evidence output through detection–segmentation–recognition–decision. First, we adopt a two-stage detection cascade: a lightweight vehicle detector localizes vehicles using axis-aligned bounding boxes, and a dedicated YOLOv5n-based oriented bounding box (OBB) license plate detector, constructed via architecture grafting and weight transfer, is then applied within each vehicle region of interest (ROI) to localize rotated license plates under large pose variation and small-target conditions. Second, a U-Net lane region segmentation module provides pixel-level spatial constraints to define an enforceable lane occupancy region. Third, a perspective rectification step is integrated with the PP-OCRv4 optical character recognition (OCR) framework to improve license plate recognition reliability for tilted plates. Finally, an area ratio criterion and an N-frame temporal counter are used to suppress transient misdetections and stabilize alarms. On a representative 100-sample controlled encroachment benchmark, the proposed system improves detection accuracy from 67.0% to 92.0% and reduces the false positive rate from 32.35% to 5.88% compared with a baseline horizontal bounding box (HBB)-based rule. The system outputs both violation alarms and license plate evidence, supporting practical deployment for multi-view traffic governance. Full article

Cultured urine-derived cells (UDCs) have been proposed as a source of material for the RNA-based molecular diagnosis of genetic disorders. Previous studies have shown that UDCs can be clonally expanded, passaged, frozen, regrown and have some stem cell characteristics, but their anatomic origin and diagnostic utility remain insufficiently explored. In this study, we cultured UDCs from 40 individuals (aged 4 to 20 years; 21 females) and extracted RNA for sequencing. We compared UDC gene expression to that of marker genes of the kidney and urinary tract segments. UDC gene expression most closely matched marker genes of parietal epithelial cells that line the inner surface of Bowman’s capsule in the kidney glomerulus. UDCs expressed VCAM1 (CD106) and POUF51 (OCT4), consistent with a progenitor cell type. UDCs also expressed 54.4% of 3125 OMIM-listed disease-causing genes. This indicated that UDCs can be used to diagnose a similar number of genetic disorders as skin fibroblasts and a wider range of genetic disorders than can be analysed by RNA extracted from whole blood. In conclusion, UDCs are a non-invasive cell source for RNA sequencing that is suitable for investigating a broad range of conditions. Full article

Manufacturing is going through a significant shift propelled by Industry 4.0 and smart manufacturing infrastructures, requiring sophisticated production control techniques that can adaptively adjust to fluctuating operational situations. This paper presents a novel five-step hybrid simulation framework for adaptive real-time production speed control in smart manufacturing lines, integrating conceptual modelling, hybrid simulation, algorithm redefinition, design of experiments, optimisation, and real-system implementation. The framework transforms the speed management systems into online digital twins capable of optimising system performance and mitigating unforeseen fluctuations, faults, and congestion. A comprehensive case study from the beverage manufacturing sector demonstrates the framework’s effectiveness, utilising a universal simulation platform to model both continuous fluid flow and discrete event processes. The proposed stepwise, multi-threshold algorithm employs multiple distinct logical thresholds evaluated sequentially to optimise both upstream and downstream station speeds, with decision thresholds independently adjustable for each production line segment. The experimental results show significant improvements, including around an 18% increase in overall throughput and a 95.7% reduction in work-in-process inventory. A comprehensive resiliency analysis and statistical tests under various disruption scenarios further validated the approach, demonstrating its superiority. Beyond the studied case, the framework provides a transferable pathway for real-time adaptive control across a wide range of smart manufacturing environments, enabling enhancements to operational efficiency without requiring additional capital investment in new equipment or infrastructure. Full article

The A* algorithm is widely used in path planning for Automated Guided Vehicles (AGVs), but the path it generates is prone to collision with random obstacles. To address this issue, this paper proposes a hybrid path planning algorithm integrating the improved A* algorithm with Dynamic Window Approach (DWA). Firstly, a global key point extraction strategy is adopted, and Bresenham’s line algorithm is used to eliminate redundant path points and turning inflection points, optimizing the conciseness and continuity of the path while redefining the child nodes of the current position. Secondly, in complex environments, the inflection points of the global path are taken as the target points of DWA to segment the path, and local dynamic planning is combined to achieve real-time obstacle avoidance. Simulation results show that compared with the traditional A* algorithm, the improved algorithm reduces the planning time by 24.19%, decreases the number of inflection points by 40.00%, and shortens the path length by 1.49%. In environments with random obstacles, the path generated by the hybrid algorithm is smoother, which can effectively enhance the local obstacle avoidance capability and improve the safety of path planning. Furthermore, physical experiments on an AGV platform with a distributed master-slave control architecture (STM32 microcontroller and Jetson embedded processor) verify the algorithm’s hardware compatibility and real-time computing performance, validating its engineering applicability in practical industrial scenarios. Full article

Taking the Daliang Tunnel of the Lanzhou–Xinjiang High-speed Railway crossing a reverse strike-slip fault as the engineering background, seismic damage investigations of the Daliang Tunnel and other cross-fault tunnels under earthquake action were conducted. Using 1:50 meso-scale model tests, experimental analyses were carried out on the lining strain response, internal crack development and failure, and surrounding rock pressure variation during fault dislocation. The failure modes and mechanisms of tunnels crossing reverse strike-slip faults were thoroughly explored. Meanwhile, a three-dimensional numerical model of the Daliang Tunnel was established to investigate the influence of dislocation modes with structural zonation within the fault zone on the surrounding rock response. The results indicate that the damage and strain response of the tunnel lining are mainly distributed within the fracture zone, predominantly characterized by combined oblique shear and compression failure. Due to the displacement of the lining induced by strong surrounding rock movement, surrounding rock pressure exhibits considerable variation at the boundaries of the fracture zone, accompanied by certain void detachment phenomena. The overall deformation of the tunnel crossing the reverse strike-slip fault presents an “S”-shaped pattern, which is consistent with the numerical simulations. The compression and dislocation morphology of the sidewalls within the rupture surface is in good agreement with the point cloud plan view. The compressive deformation and strain of the surrounding rock are most significant within the rupture surface. Meanwhile, the soft-to-hard transition segments between the new fracture zone and the rupture surface, as well as between the rupture surface and the influence zone, exhibit a trend of first decreasing and then increasing. Full article

Insulators are essential components in high-voltage transmission lines and require regular inspection to ensure reliable power delivery. Traditional manual inspection methods are inefficient and labor intensive, highlighting the need for intelligent and automated solutions. In this study, we propose a missing insulator detection method that integrates Unmanned Aerial Vehicle (UAV) imaging with deep learning techniques. Firstly, an improved Faster Region-based Convolutional Neural Network (Faster R-CNN) is employed to detect and localize insulators in aerial images. Secondly, the localized insulators are segmented using an improved U-Net to reduce background interference. A bounding box regression approach is adopted to obtain the minimum enclosing rectangles, and the insulators are aligned vertically. Adaptive thresholding is then applied to extract binary images of the insulators. These binary images are further transformed into defect curves, from which missing insulators are identified based on curve distribution. To address the limited availability of labeled samples, a transfer learning-based strategy is adopted to improve model generalization. A dataset of glass insulators was collected using a DJI M300 UAV equipped with an H20T camera along a 330 kV overhead transmission line. On the collected UAV insulator dataset, the proposed method achieved an AP@0.5 of 99.85% and an average IoU of 88.56% for insulator string detection, while the improved U-Net achieved an mIoU of 89.73% for insulator string segmentation. Outdoor flight experiments further verified performance under varying backgrounds and illumination conditions in our UAV inspection scenarios. Full article

The mechanical method has become a new construction method for connected aisles in metro tunnels due to its advantages of fast construction speed, high safety, and minimal ground disturbance. During the tunneling process, the interaction mechanism between the composite segment and the shield cutterhead is complex. Taking Shenzhen Metro Line 8 No. 1 Connected Aisle as the research object, a 3D refined model of the shield cutterhead, composite segments and bolt system were built with Abaqus to investigate their dynamic response under cutting. The Drucker–Prager damage model and contact algorithm were introduced to describe the nonlinear behavior of the cutting process. The reliability of the numerical model was verified by concrete cutting tests and on-site Fiber Bragg Grating monitoring, and good agreements were observed. Results show cutterhead cutting first induces circumferential squeezing, then extends longitudinally with a notable time lag, and longitudinal dynamic response is much stronger than transverse. Affected by cutterhead thrust–rotation coupling, cuttable segments have larger displacement with maximum 0.07 mm, forming an asymmetric deformation zone. Ring joint opening follows “a distal attenuation of the opening amount” rule with maximum 0.018 mm, while bolt stress and displacement show “near-end concentration with gradient attenuation”, with longitudinal bolts being more responsive. Mechanical disturbance from small-shield cutting is minimal, with tunnel segment deformation, joint openings, and bolt stress all remaining well below code-specified allowable values. Numerical results show good agreement with field monitoring data of ring joint openings obtained using Fiber Bragg Grating (FBG) sensors, confirming the reliability of the simulation. The results can provide references for structural design and construction parameter optimization of composite segments in a connected aisle. Full article

Prefabricated lining is increasingly used in railway tunnels due to its advantages of environmental friendliness, high construction efficiency, and convenience. However, the existence of block joints weakens structural integrity, and the segmentation optimization of prefabricated lining remains a challenge especially for irregular lining. Based on the Yongfengcun tunnel in the Fuzhou Ganghou Railway Project, the nonlinear mechanical behaviors of joint stiffness were investigated under axial force, bending moment and shear force. A beam–spring model was established by considering the bending and shearing stiffness of block joints, and the mechanical behaviors were analyzed efficiently by Python 3.9 and ABAQUS 2025 for 572 segmentation schemes. Based on a Delphi questionnaire, three key indicators including horizontal convergence, bending moment amplitude and length variance were selected as independent optimization objectives. The stable Pareto frontier was obtained using the NSGA-II algorithm. Application in the Yongfengcun tunnel fully verified the effectiveness of the method. Full article

To address the difficulty of accurately localizing automotive chassis bolts during the assembly process—caused by non-uniform illumination, limited camera installation space, and occlusions from the vehicle body structure—a fiducial-marker-based localization method is proposed. In this method, a concentric ring-shaped fiducial marker is affixed to the bottom of the assembly wrench, and its region of interest (ROI) is extracted using an HSV color space segmentation algorithm. To overcome interference from uneven lighting and insufficient brightness in industrial environments, an improved Retinex-based image enhancement algorithm is introduced, which significantly improves the robustness and accuracy of ROI extraction. The extracted ROI image is subjected to ellipse fitting, and the fitting process is optimized by incorporating the Leitz criterion. Experimental results show that the optimized ellipse fitting algorithm achieves higher accuracy and significantly enhances the reliability of fitting. Since perspective projection of spatial circles leads to displacement of the circle center, the actual projected center of the fiducial marker in the image is calculated by estimating the normal vector of the circular plane using vanishing lines and the ellipse parameter matrix. This enables spatial localization of the bolt end. The proposed method is validated by comparing the localization results with the theoretical coordinates of the bolt holes. Experimental results demonstrate that the method offers high localization accuracy and strong robustness, meeting the practical precision requirements for automatic bolt assembly in industrial applications. Full article

Plane segmentation of real-world 3D point clouds captured by LiDAR or depth sensors remains challenging due to data sparsity, noise, and complex geometric configurations such as stepwise and intersecting non-coplanar structures. To address these issues inherent in sensor-acquired data, this paper proposes a geometry-aware plane segmentation method that leverages supervoxel boundary adjacency, normal coherence, and projection-line fitting constraints. Supervoxels were generated using the toward better boundary preserved supervoxel segmentation (TBBS) algorithm, and their natural adjacency relationships were constructed based on boundary points. Subsequently, the supervoxels were initially clustered according to their normal information. Finally, the projected point clouds of adjacent supervoxel were fitted with straight lines, and the fitting errors were calculated to optimize the clustering results. Experimental results demonstrate that this method performs excellently in handling stepwise non-coplanar structures, effectively segmenting planar regions with significant geometric features. It shows particular advantages in cases involving stepwise non-coplanar and intersecting planes. On benchmark datasets, the method achieves precision and recall rates of (97.7%, 94.4%, 91.2%, 80.4%, 92.3%) and (98.9%, 95.7%, 93.7%, 84.8%, 96.0%), respectively, highlighting its effectiveness and robustness for practical 3D sensing applications. Full article

Two-wheeled self-balancing robots (TWSBRs) are difficult to control because they are nonlinear, unstable, and underactuated, particularly when balance, velocity regulation, and line tracking must be achieved simultaneously. This paper proposes a hybrid parallel control architecture for a line-following TWSBR operating on straight segments, ${90}^{\circ }$ curves, and a ${15}^{\circ }$ slope. Balance stabilization is handled by a classical PD loop, while traslational velocity is regulated by an adaptive fuzzy PI controller, and line following is performed with an adaptive fuzzy PD controller. The fuzzy modules adjust the effective gains based on tracking errors, thereby improving robustness to disturbances, sensor noise, and changes in operating conditions. The complete strategy is implemented on a low-cost PIC18F4550 microcontroller. Experiments show that the fuzzy line-following controller reduces the orientation tracking error compared with a conventional controller. At $0.10{\displaystyle \frac{\mathrm{m}}{\mathrm{s}}}$, RMSE decreases from $0.042\mathrm{rad}$ to $0.038\mathrm{rad}$, and at $0.175{\displaystyle \frac{\mathrm{m}}{\mathrm{s}}}$, it decreases from $0.083\mathrm{rad}$ to $0.066\mathrm{rad}$. The fuzzy approach also improves IAE ($1.317{\displaystyle \frac{\mathrm{rad}}{\mathrm{s}}}$ to $1.185{\displaystyle \frac{\mathrm{rad}}{\mathrm{s}}}$) and ISE ($0.242{\displaystyle \frac{{\mathrm{rad}}^2}{\mathrm{s}}}$ to $0.153{\displaystyle \frac{{\mathrm{rad}}^2}{\mathrm{s}}}$) at $0.175{\displaystyle \frac{\mathrm{m}}{\mathrm{s}}}$, while maintaining similar maximum error ($0.299\mathrm{rad}$ to $0.261\mathrm{rad}$). Overall, the proposed hybrid scheme achieves better adaptability without retuning. These results support real-time deployment on resource-limited platforms. Full article

Background: Floating barbed threads are commonly used for minimally invasive midface lifting and rely on mobile subcutaneous tissue for support, which may limit stability. Fixation is primarily achieved by barb engagement within the subcutaneous fat and fibrous septa of the retinacula cutis. Objectives: To describe an anatomically guided modification of the APTOS Excellence Visage Soft (PLLA/PCL) thread technique, positioning the terminal segment posterior to the zygomatic retaining ligament line with the aim to enhancing mechanical stability. This technical report presents the anatomical rationale, procedural steps, and illustrative clinical cases demonstrating feasibility. Methods: The modified technique uses a single-entry point at the superior zygomatic margin, with five threads per hemiface. After linear insertion, the cannula is rotated laterally and inferiorly to position the terminal barbs posterior to the zygomatic retaining ligament line, thereby transferring tensile load toward a more fixed anatomical structure. Representative cases were documented and are presented. Results: Illustrative cases showed immediate midface elevation with improved malar projection and softening of the nasolabial and mentolabial folds. Standardized 3D imaging and vector analysis demonstrated a superolateral pattern of soft tissue displacement along the intended vectors, consistent with the proposed fixed-anchorage concept. The procedure was well tolerated, with only mild and transient local effects observed. One illustrative case included photographic follow-up at 12 months, in which preservation of midface contour and malar projection was visually appreciable. Conclusions: Redirecting the terminal thread segment posterior to the zygomatic retaining ligament line is a feasible modification that may contribute to improved vector stability by engaging a fixed fascial structure. Observations—including one case with 12-month follow-up—support the anatomical plausibility of the approach, although controlled studies with objective endpoints are necessary to confirm long-term efficacy and reproducibility. Full article

Voids behind the lining that develop during long-term operation can seriously compromise the seismic safety performance of metro shield tunnels. To investigate the influence of such void defects on large-diameter shield tunnels, this study systematically analyzed the causes and distribution patterns of voids. A three-dimensional discontinuous finite element model was developed to simulate the interaction among lining segments, connecting bolts, and surrounding rock. The seismic responses, including circumferential stress, interface slip, interface opening, and bolt tensile stress, were analyzed considering coupled factors such as the void circumferential angle, radial depth, distribution location, and geological conditions. Single-factor and multi-factor sensitivity analyses were conducted to evaluate the significance of the above coupled factors on the overall seismic response. The results show that lining circumferential stress, displacement, interface opening, and bolt stress increase with void enlargement, a shift in void location from the crown to the haunch, and deterioration of geological conditions. A void located at the right haunch leads to a peak circumferential stress of 3.27 MPa, causing local segment damage. Sensitivity analysis reveals that void location is the most influential factor affecting the seismic response, while geological conditions exhibit lower sensitivity. A predictive model for the peak circumferential stress around the void was established using multiple linear regression, incorporating void position, circumferential angle, and radial depth. Within the parameter range considered in this study, this model provides a theoretical basis and practical reference for rapid seismic risk assessment and safety management of shield tunnels with void defects. Full article

The paper proposes a completely new geometric interpretation of intuitionistic fuzzy sets for confidence-aware decision making. Instead of directly using ordered pairs of membership and non-membership degrees, we reinterpret the intuitionistic fuzzy triangle as a structured coordinate framework that simultaneously represents the evaluation outcomes and the evaluators’ expertise in the following manner: experts’ confidence levels are modelled with line segments parallel to the hypotenuse, while evaluation scores are represented by line segments radiating from the origin of the coordinate system toward the hypotenuse. Their intersections form a finite lattice of points whose total number depends on the chosen confidence and assessment scales. The proposed construction preserves the semantic foundations of intuitionistic fuzziness: points closer to the origin reflect higher uncertainty in the evaluator’s confidence, while points onto the hypotenuse represent determinate judgments (with varying degrees of positivity or negativity) based on the complete evaluator’s confidence. The geometric distances between intersections provide a formal explanation of varying discriminative power: assessments from highly confident reviewers are more distinguishable than those from less confident ones. In addition, a colour-based visualization further supports the intuitive interpretation of confidence-weighted evaluations. The proposed framework offers an alternative yet fully consistent way to model expertise-dependent decision processes within the intuitionistic fuzzy setting, bridging geometric insight and practical evaluation scenarios via a structured system of parallels and meridians. Full article

The reliable operation of transmission lines is essential for grid stability. Growing electricity demand pushes existing lines to full capacity, while new construction is constrained by resources and the environment. Dynamic capacity increase technology addresses this by boosting transmission capacity without physical upgrades, with the identification of weak points along the line being central to its application. This study integrates correlation analysis and the Analytic Hierarchy Process to develop an evaluation method for transmission line segments, with a supporting software implementation also developed. A system of characteristic quantities was first established using operation and maintenance guidelines combined with correlation analysis. The Analytic Hierarchy Process was applied to score features and derive weights after consistency validation. Preprocessed line data were then weighted to calculate segment weakness levels, and fuzzy comprehensive evaluation was used for both qualitative and quantitative condition analysis. The model was validated through a case study, and its software implementation streamlines and enhances the assessment process. Full article