Search Results (776)

Detecting trees accurately from terrestrial laser scanning (TLS) point clouds is crucial for processing terrestrial LiDAR data in individual tree analyses. Due to the heterogeneity of savanna ecosystems, our understanding of how various segmentation methods perform on savanna trees remains limited. Therefore, we compared two segmentation algorithms based on the ecological theory of resource distribution, which enables the prediction of the branching geometry of plants. This approach suggests that the shortest path along the vegetation from a point on the tree to the ground remains within the same tree. The algorithms were tested on a 15.2 ha plot scanned at 0.025° resolution during the dry season, using a Riegl VZ1000 Terrestrial Laser Scanner (TLS) in October 2019 at the Skukuza Flux Tower in Kruger National Park, South Africa. Individual tree segmentation was performed on the cloud using the comparative shortest-path (CSP) algorithm, implemented in LiDAR 360 (v 5.4), and the shortest path-based tree isolation method (SPBTIM), implemented in MATLAB (R2022a). The accuracy of each segmentation method was validated using 125 trees that were segmented and manually edited. Results were evaluated using recall (r), precision (p), and the F-score (F). Both algorithms detected (recall) 90% of the trees. The SPBTIM achieved a precision of 91%, slightly higher than the CSP’s 90%. Overall, both methods demonstrated an F-score of 0.90, indicating equal segmentation accuracy. Our findings suggest that both techniques can reliably segment savanna trees, with no significant difference between them in practical application. These results provide valuable insights into the suitability of each method for savanna ecosystems, which is essential for ecological monitoring and efficient TLS data processing workflows. Full article

Simultaneous Localization and Mapping (SLAM) is crucial for the safe navigation of autonomous systems. Its accuracy is not based solely on the robustness of the algorithm employed or the metrological performances of the sensor, but rather on a combination of both factors. In this work, we present a comprehensive comparison framework for evaluating LiDAR-SLAM systems, focusing on key performance indicators including absolute trajectory error, uncertainty, number of tracked features, and computational time. Our case study compares two LiDAR-inertial SLAM configurations: one based on a motorized optomechanical scanner (the Ouster OS1) with a 360° field of view and the other based on MEMS scanners (the Livox Horizon) with a limited field of view and a non-repetitive scanning pattern. The sensors were mounted on a UGV for the experiments, where data were collected by driving the UGV along a predefined path at different speeds and angles. Despite substantial differences in field of view, detection range, and noise, both systems demonstrated comparable trajectory estimation performance, with average absolute trajectory errors of 0.25 m for the Livox-based system and 0.24 m for the Ouster-based system. These findings underscore the importance of sensor–algorithm co-design and demonstrate that even cost-effective, lower-field-of-view solutions can deliver competitive SLAM performance in real-world conditions. Full article

Inspired by the self-organizing optimization mechanisms in nature, the leaf venation of the royal water lily exhibits a hierarchically branched fractal network that combines excellent mechanical performance with lightweight characteristics. In this study, a structural bionic approach was adopted to systematically investigate the venation architecture through macroscopic morphological observation, experimental testing, 3D scanning-based reverse reconstruction, and finite element simulation. The influence of key fractal geometric parameters under vertical loading on the mechanical behavior and energy absorption capacity was analyzed. The results demonstrate that the leaf venation of the royal water lily exhibits a core-to-margin gradient fractal pattern, with vein thickness linearly decreasing along the radial direction. At each hierarchical bifurcation, the vein width is reduced to 65–75% of the preceding level, while the bifurcation angle progressively increases with branching order. During leaf development, the fractal dimension initially decreases and then increases, indicating a coordinated functional adaptation between the stiff central trunk and the compliant peripheral branches. The veins primarily follow curved trajectories and form a multidirectional interwoven network, effectively extending the energy dissipation path. Finite element simulations reveal that the fractal venation structure of the royal water lily exhibits pronounced nonlinear stiffness behavior. A smaller bifurcation angle and higher fractal branching level contribute to enhanced specific energy absorption and average load-bearing capacity. Moreover, a moderate branching length ratio enables a favorable balance between yield stiffness, ultimate strength, and energy dissipation. These findings highlight the synergistic optimization between energy absorption characteristics and fractal geometry, offering both theoretical insights and bioinspired strategies for the design of impact-resistant structures. Full article

To solve the issue of environmental noise pollution and promote the resource recycling of waste pomelo peel, X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM) are used to systematically characterize the microstructure and chemical composition of waste pomelo peel. It was found that waste pomelo peel has a porous network structure, which is conducive to the improvement of sound absorption performance. Waste pomelo peel/polycaprolactone (PCL) sound-absorbing composites are prepared by the hot-pressing molding process, and the single-factor analysis method is adopted to explore the effects of seven factors (waste pomelo peel mass fraction, composite density, composite thickness, hot-pressing time, hot-pressing pressure, hot-pressing temperature, and thickness of rear air layer) on the sound absorption performance. Through process optimization, under the optimal conditions, the average sound absorption coefficient (SAC) of the composites reaches 0.54, the noise reduction coefficient (NRC) reaches 0.57, and the maximum SAC reaches 0.99, with the sound absorption performance reaching Grade III. This study not only provides a new idea for the preparation of porous sound-absorbing composites but also opens a new path for the high-value utilization of waste pomelo peel resources. Full article

This paper presents a fully electronic, CMOS-compatible ultrasonic sensing system integrated into a 3D beamforming architecture for advanced automotive applications. The proposed system eliminates mechanical scanning by implementing a dual-path beamforming structure comprising programmable transmit (TX) and receive (RX) paths. The TX beamformer introduces per-element time delays derived from steering angles to control the direction of ultrasonic wave propagation, while the RX beamformer aligns echo signals for spatial focusing. Electrostatic actuation governs the CMOS-compatible ultrasonic transmission mechanism, whereas dynamic modulation under acoustic pressure forms the reception mechanism. The system architecture supports full horizontal and vertical angular coverage, leveraging delay-and-sum processing to achieve electronically steerable beams. The system enables low-power, compact, and high-resolution sensing modules by integrating signal generation, beam control, and delay logic within a CMOS framework. Theoretical modeling demonstrates its capability to support fine spatial resolution and fast response, making it suitable for integration into autonomous vehicle platforms and driver-assistance systems. Full article

Picosecond laser drilling offers high precision and quality, and compared to femtosecond lasers, it also balances processing efficiency, making it widely used across various fields. However, existing drilling processes still face issues such as roundness and taper. Therefore, further research into the processing characteristics of picosecond laser technology is needed to improve processing quality. This paper uses ANSYS software to conduct numerical simulations of picosecond laser ring-cutting drilling, analyzing the temperature field of microholes under ring-cutting scanning paths as parameters change. Experimental studies were conducted using AISI 310S heat-resistant stainless steel as the base material. This material exhibits excellent high-temperature oxidation resistance and strength retention, making it suitable for laser thermal processing. Using a single-factor method, the study investigated the influence of equidistant concentric circular paths and inner-dense-outer-sparse concentric circular paths on microhole morphology characteristics. The results show that the laser energy distribution is different under different paths. The entrance aperture of the equidistant concentric circle path is larger than that of the inner dense and outer sparse concentric circle path, while the exit aperture is smaller than the latter. Moreover, the roundness is also better than that of the inner dense and outer sparse concentric circle path. The taper of the inner dense and outer sparse concentric circle path is better than that of the equidistant concentric circle path. This study can provide a reference for the optimization of different processing paths in the future. Full article

Understanding human perceptual strategies in high-stakes environments, such as crime scene investigations, is essential for developing cognitive models that reflect expert decision-making. This study presents an immersive experimental framework that utilizes virtual reality (VR) and eye-tracking technologies to capture and analyze visual attention during simulated forensic tasks. A360° panoramic crime scene, constructed using the Nikon KeyMission 360 camera, was integrated into a VR system with HTC Vive and Tobii Pro eye-tracking components. A total of 46 undergraduate students aged 19 to 24–23, from the National University of Singapore in Singapore and 23 from the Central Police University in Taiwan—participated in the study, generating over 2.6 million gaze samples (IRB No. 23-095-B). The collected eye-tracking data were analyzed using statistical summarization, temporal alignment techniques (Earth Mover’s Distance and Needleman-Wunsch algorithms), and machine learning models, including K-means clustering, random forest regression, and support vector machines (SVMs). Clustering achieved a classification accuracy of 78.26%, revealing distinct visual behavior patterns across participant groups. Proficiency prediction models reached optimal performance with a random forest regression ($R^2$ = 0.7034), highlighting scan-path variability and fixation regularity as key predictive features. These findings demonstrate that eye-tracking metrics—particularly sequence-alignment-based features—can effectively capture differences linked to both experiential training and cultural context. Beyond its immediate forensic relevance, the study contributes a structured methodology for encoding visual attention strategies into analyzable formats, offering valuable insights for cognitive modeling, training systems, and human-centered design in future perceptual intelligence applications. Furthermore, our work advances the development of autonomous vehicles by modeling how humans visually interpret complex and potentially hazardous environments. By examining expert and novice gaze patterns during simulated forensic investigations, we provide insights that can inform the design of autonomous systems required to make rapid, safety-critical decisions in similarly unstructured settings. The extraction of human-like visual attention strategies not only enhances scene understanding, anomaly detection, and risk assessment in autonomous driving scenarios, but also supports accelerated learning of response patterns for rare, dangerous, or otherwise exceptional conditions—enabling autonomous driving systems to better anticipate and manage unexpected real-world challenges. Full article

Traditional unmanned aerial vehicle (UAV) path planning methods for image-based 3D reconstruction often rely solely on geometric information from initial models, resulting in redundant data acquisition in non-architectural areas. This paper proposes a UAV path planning method via semantic segmentation of 3D reality mesh models to enhance efficiency and accuracy in complex scenarios. The scene is segmented into buildings, vegetation, ground, and water bodies. Lightweight polygonal surfaces are extracted for buildings, while planar segments in non-building regions are fitted and projected into simplified polygonal patches. These photography targets are further decomposed into point, line, and surface primitives. A multi-resolution image acquisition strategy is adopted, featuring high-resolution coverage for buildings and rapid scanning for non-building areas. To ensure flight safety, a Digital Surface Model (DSM)-based shell model is utilized for obstacle avoidance, and sky-view-based Real-Time Kinematic (RTK) signal evaluation is applied to guide viewpoint optimization. Finally, a complete weighted graph is constructed, and ant colony optimization is employed to generate a low-energy-cost flight path. Experimental results demonstrate that, compared with traditional oblique photogrammetry, the proposed method achieves higher reconstruction quality. Compared with the commercial software Metashape, it reduces the number of images by 30.5% and energy consumption by 37.7%, while significantly improving reconstruction results in both architectural and non-architectural areas. Full article

Tests during methane hydrate (MH) production in Japan have shown that excessive water production is a primary challenge in MH development. It can lead to sand production, inhibit effective reservoir depressurization, and hinder gas production. This study investigated the ability of a reactive grout, produced by the in situ reaction of CO₂ with sodium silicate (SS), to inhibit water generation from unconsolidated sand layers by forming a water-blocking gel barrier. The performance of this grout was evaluated through laboratory experiments using silica sand as a porous medium. Under controlled conditions, diluted SS and CO₂ were sequentially injected. The injection and gelation processes were monitored in real time using CT scanning, and SEM was employed to analyze the microstructure of the reaction products. The results indicated that SS exhibited piston-like flow, with elevated concentrations increasing viscosity and promoting more uniform injection. CO₂ injection resulted in successful in situ gel formation. A homogeneous gel distribution decreased permeability by ~98% when the SS concentration was 25 wt%. However, at 50 wt%, rapid localized gelation caused preferential flow paths and reduced sealing efficiency. These findings highlight the potential of CO₂ reactive grouting for water management in MH exploitation and the importance of optimizing injection parameters. Full article

Fracture toughness anisotropy is a key concern in IN718 components produced by Laser Powder Bed Fusion (LPBF), due to their strong crystallographic texture and characteristic lamellar microstructure. In this study, the effect of grain orientation on fracture toughness was evaluated by testing two LPBF IN718 builds with the same laser scanning strategy (R0), but with two different orientations: vertical (R0-0) and 45° inclined (R0-45) relative to the build direction. The mechanical response was assessed through compact tension (CT) tests following ASTM E399 and ASTM E1820 standards. Results show that the R0-45 specimens exhibited a fracture toughness nearly 2.5 times higher than R0-0 specimens. Detailed microstructural analysis, supported by EBSD and SEM, reveals that the higher toughness in the R0-45 orientation is linked to a combination of smaller effective grain size along the crack path, higher levels of geometrically necessary dislocations (GND), and increased kernel average misorientation (KAM), which collectively enhance plastic accommodation and crack-tip shielding. These findings support and reinforce the established understanding of the relationship between microstructure and anisotropic fracture behavior in LPBF IN718, facilitating its practical application in the design and orientation of additively manufactured components. Full article

Notoginsenoside Rb1 (Rb1), a bioactive saponin from Panax notoginseng, exerts cardio-cerebrovascular protective, anti-inflammatory, antioxidant, and glucose homeostasis-regulating effects. However, its oral bioavailability is limited by gastric degradation and poor intestinal permeability. This study presents a food-grade bigel system for encapsulating Rb1 to enhance its stability and controlled-release performance. Oleogels were structured using monoglycerides (8%, w/w) in soybean oil. Rb1-loaded binary hydrogels (gellan gum/xanthan gum, 12:1 w/w) were emulsified in 10% Tween-80 (w/w). Bigels were formulated at varying hydrogel-to-oleogel ratios, and a ratio of 4:6 was identified as optimal. Stress-sweep rheological analysis revealed a dense gel structure with a peak storage modulus (G′) of 290.64 Pa—the highest among all tested ratios—indicating superior structural integrity. Confocal microscopy confirmed homogeneous encapsulation of Rb1 within the continuous hydrogel phase, effectively preventing payload leakage. Differential scanning calorimetry (DSC) analysis detected a distinct endothermic transition at 55 °C (ΔH = 6.25 J/g), signifying energy absorption that enables thermal buffering during food processing. The system achieved an encapsulation efficiency of 99.91% and retains both water and oil retention. Effective acid protection and colon-targeted delivery were observed in the digestion test. Effective acid protection and colon-targeted delivery were observed in the digestion test. Less than 5% of Rb1 was released in the gastric phase, and over 90% sustained intestinal release occurred at 4 h. The optimized bigel effectively protected Rb1 from gastric degradation and enabled sustained intestinal release. Its food-grade composition, thermal stability, and tunable rheology offer significant potential for use in functional foods and nutraceuticals. Full article

In scenarios such as field exploration, disaster relief, and agricultural automation, LIDAR-based reconstructed terrain models can largely contribute to robot activities such as passable area identification and path planning optimization. However, unstructured terrain environments are typically absent and poorly characterized by artificially labeled features, which makes it difficult to find reliable feature correspondences in the point cloud between two consecutive LiDAR scans. Meanwhile, the persistence of noise accompanying unstructured terrain environments also causes certain difficulties in finding reliable feature correspondences between two consecutively scanned point clouds, which in turn leads to lower matching accuracy and larger offsets between neighboring frames. Therefore, this paper proposes an unstructured terrain construction algorithm combined with graph optimization theory based on LOAM algorithm further introducing the robots motion information provided by IMU. Experimental results show that the method proposed in this paper can achieve accurate and effective reconstruction in unstructured terrain environments. Full article

Development of forming methods for surface-coated metals is a current concern due to their economic and environmental advantages. For a successful forming operation, it is necessary that both components, the substrate and the coating, are able to withstand stress without damage until the final shape and dimensions are reached. This goal can be achieved through good knowledge of the elastic and plastic properties of the substrate and the coating, the compatibility between them, the appropriate surface treatment, and the rigorous control of technological forming parameters. Our study was carried out with flat specimens of pre-painted Al 99.0 sheet that were electromagnetically formed by bulging. Forming behavior was investigated as depending on the initial thickness of the substrate, on the aluminum sheet pretreatment, as well as on the plastic deformation path of the metal–paint structure. To verify the damage to the paint layer, tests with increasing strains were performed, and the interface between the metal and the coating layer was investigated by scanning electron microscopy. The obtained results indicate that electromagnetic forming of pre-painted sheets can be a feasible method for specific applications if the forming degree of the substrate is tightly correlated with the type of desired coating and with the pretreatment method used for the metal surface. Full article

To develop high-performance electrode materials for supercapacitors, in this paper, a heterostructured composite material of cerium sulfide and zinc sulfide quantum dots (CeS₂/ZnS QD) was successfully prepared by hydrothermal method. Characterization through scanning electron microscopy (SEM), X-ray diffraction (XRD), and transmission electron microscopy (TEM) showed that ZnS QD nanoparticles were uniformly composited with CeS₂, effectively increasing the active sites surface area and shortening the ion diffusion path. Electrochemical tests show that the specific capacitance of this composite material reaches 2054 F/g at a current density of 1 A/g (specific capacity of about 256 mAh/g), significantly outperforming the specific capacitance of pure CeS₂ 787 F/g at 1 A/g (specific capacity 98 mAh/g). The asymmetric supercapacitor (ASC) assembled with CeS₂/ZnS QD and activated carbon (AC) retained 84% capacitance after 10,000 charge–discharge cycles. Benefited from the synergistic effect between CeS₂ and ZnS QDs, the significantly improved electrochemical performance of the composite material suggests a promising strategy for designing rare-earth and QD-based advanced energy storage materials. Full article

To address the technical bottlenecks of low path planning efficiency and insufficient point cloud coverage in the automated 3D scanning of complex structural components, this study proposes an offline method for the generation and optimization of scanning paths based on CAD models. Discrete sampling of the model’s surface is achieved through the construction of an oriented bounding box (OBB) and a linear object–triangular mesh intersection algorithm, thereby obtaining a discrete point set of the model. Incorporating a standard vector analysis of the discrete points and the kinematic constraints of the scanning system, a scanner pose parameter calculation model is established. An improved nearest neighbor search algorithm is employed to generate a globally optimized scanning path, and an adaptive B-spline interpolation algorithm is applied to path smoothing. A joint MATLAB (R2023b)—RobotStudio (6.08) simulation platform is developed to facilitate the entire process, from model pre-processing and path planning to path verification. The experimental results demonstrate that compared with the traditional manual teaching methods, the proposed approach achieves a 25.4% improvement in scanning efficiency and an 18.6% increase in point cloud coverage when measuring typical complex structural components. This study offers an intelligent solution for the efficient and accurate measurement of large-scale complex parts and holds significant potential for broad engineering applications. Full article