Search Results (944)

This paper addresses the issues of target unreachability and local optima in traditional artificial potential field (APF) methods for UAV swarm path planning by proposing an improved collaborative obstacle avoidance algorithm. By introducing a virtual target position function to reconstruct the repulsive field model, the repulsive force exponentially decays as the UAV approaches the target, effectively resolving the problem where excessive obstacle repulsion prevents UAVs from reaching the goal. Additionally, we design a dynamic virtual target point generation mechanism based on mechanical state detection to automatically create temporary target points when UAVs are trapped in local optima, thereby breaking force equilibrium. For multi-UAV collaboration, intra-formation UAVs are treated as dynamic obstacles, and a 3D repulsive field model is established to avoid local optima in planar scenarios. Combined with a leader–follower control strategy, a hybrid potential field position controller is designed to enable rapid formation reconfiguration post-obstacle avoidance. Simulation results demonstrate that the proposed improved APF method ensures safe obstacle avoidance and formation maintenance for UAV swarms in complex environments, significantly enhancing path planning reliability and effectiveness. Full article

The rapid growth of new energy vehicles necessitates accurate battery state of health (SOH) assessment to ensure safety and reliability. However, real-world SOH estimation is challenging because users rarely perform full charge–discharge cycles, leaving only fragmented charging segments that obscure true battery capacity. To address this, we propose a data-driven method that reconstructs a virtual full-charge cycle. By clustering charging segments based on temperature and current, the approach creatively splices multiple incomplete curves from similar mileages and conditions into a complete charging profile. This enables robust full-capacity estimation on a large-scale real-world vehicle dataset, achieving estimation errors below 2% when compared with offline validation tests. The method offers a practical and scalable solution for SOH monitoring and fleet management using field data. Full article

The craniofacial skeleton is a complex three-dimensional structure, and major reconstructive cases remain challenging. We describe a synergistic approach combining intra-operative navigation, three-dimensionally (3D) printed skull models, and mixed reality (MR) to improve predictability in surgical outcomes. A patient with previously repaired bilateral cleft lip and palate, significant midfacial retrusion, and a large maxillary alveolar gap underwent segmental Le Fort I osteotomy and advancement. Preoperative virtual planning was performed, and reference templates were uploaded onto MR glasses. Intra-operatively, the MR glasses projected the templates as holograms onto the patient’s skull, guiding osteotomy line marking and validating bony segment movement, which was confirmed with conventional navigation. The 3D-printed skull model facilitated dissection and removal of intervening bony spicules. Preoperative planning proceeded seamlessly across software platforms. Osteotomy lines marked with MR showed good concordance with conventional navigation, and final segment positioning was accurately validated. Postoperative outcomes were satisfactory, with re-established occlusion and closure of the maxillary alveolar gap. The combined use of conventional navigation, 3D-printed models, and MR is feasible and allows safe integration of MR into complex craniofacial reconstruction while further validation of the technology is ongoing. Full article

Coastal monitoring requires a synthesis of accuracy, temporal and context flexibility. Unmanned aerial vehicles (UAVs) equipped with LiDAR (light detection and ranging) sensors are a valuable option, made more widespread by the commercialization of consumer-grade systems, although they often limit user control over data processing. This work quantifies the impact of the base station type (temporary, permanent, or virtual) and its distance from the survey site on UAV-LiDAR direct georeferencing accuracy. The comparison is carried out, in a specific coastal study site, on both the estimated trajectories and the final outputs, using novel QGIS tools (PT2DEM, DEM2DEM, T2T). While temporary base stations are affected by uncertainties of the base coordinates, virtual reference stations are affected by a wider range of errors, compromising the relative model reconstruction. In contrast, permanent stations may avoid base-coordinate uncertainties, but if their distance from the site exceeds the suggested limit (15 km), their use leads to a loss of accuracy in both the relative reconstruction of the model and the absolute georeferencing. Although the use of vertical constraints has proven to be a valuable tool for reducing the vertical bias induced by a suboptimal base station, their distribution may not be adequate for minimizing residual random deviations, and their deployment may be challenging in environmental contexts lacking stable and accessible areas. Full article

Virtual planning and patient-specific surgical guides have become standard practice to achieve accurate mandibular reconstruction with fibula free flaps. Although these technologies have greatly improved surgical precision, slight deviations may still occur. To further minimize these inaccuracies, we focused on the drilling process and developed a novel drill-fitting hole guide (DFG) system. This in vitro study compared the DFG with two conventional guide designs—a drill-wide hole guide (DWG) and a trocar-fitting hole guide (TFG)—using 3D-printed resin models. Twenty oral and maxillofacial surgeons performed guided drilling with all three guide types, and drilling accuracy and subsequent plate positioning were evaluated using a fully digitized workflow in 3-matic software. Deviations in drill entry points and trajectories were quantified, along with plate overlap ratios (Dice coefficients) and plate angular discrepancies. The DFG achieved the highest accuracy, showing the smallest drilling point deviation (0.17 ± 0.08 mm) and angular deviation (2.41 ± 1.24°), the greatest plate overlap (0.90 ± 0.04), and the lowest plate angular misalignment (0.87 ± 0.59°). Although all guide types yielded clinically acceptable results, the DFG demonstrated significantly higher accuracy. These findings suggest that the drill-guide interface is a key factor in surgical precision that has received limited attention. Full article

The PHEND (Past Has Ears at Notre-Dame) collaborative research project is being carried out by a team of multidisciplinary researchers interested in the acoustic history of Notre-Dame Cathedral in Paris. The project involved the creation of seven digital models representing the interior of the monument between 1182 and 2018. To support one of the virtual reconstructions, that of 1868, a technical report was drawn up based on the written and iconographic archives of the restorations carried out between 1845 and 1870 by the architects Eugène Viollet-le-Duc (1814–1879) and Jean-Baptiste-Antoine Lassus (1807–1857). The archives come mainly from the “Fonds Viollet-le-Duc”, from the work diary of the “Médiathèque du patrimoine et de la photographie” (MPP), and from the archives of the Notre-Dame chapter. In order to select the most relevant data for the digital reconstruction, the research addresses specific questions regarding the cathedral’s materiality, such as structural modifications, restorations, and the choice of materials and furnishings. To understand how the interior of the cathedral was transformed in the 19th century, a detailed inventory of its condition was compiled at two points in time: at the beginning of the restoration in 1848 and following its completion in 1868. In parallel with this work, to provide a graphic representation of the changes that had occurred in each area, comparative illustrations were produced showing the situation before and after restoration. The modifications were then detailed by area: general restoration (vaults, openings, paving), and redevelopment of the choir and the main body of the building (chapels, transept, nave). This research revealed the building’s profound structural changes and the fact that the renovations spared no space. These included mainly modifications to the high windows, a complete redesign of the decorative layout of the choir and chapels, the restoration of all the vaults and paving at different levels, and a complete restoration of the organ. Full article

Background/Objectives: Aortic valve calcification is commonly evaluated using 3.0 mm true non-contrast (TNC) computed tomography (CT) images. This study evaluates the reproducibility of virtual non-contrast (VNC) reconstructions at different slice intervals using photon-counting detector CT (PCD-CT). Methods: In this retrospective study, we included 279 consecutive patients, who underwent PCD-CT for evaluation of native aortic valve between February 2023 and December 2023 with both TNC and VNC images at 3.0 and 1.5 mm slice intervals. Aortic valve calcium score (AVCS) and aortic valve calcium volume (AVCV) were compared between the two methods using paired t-tests. Agreement for continuous variables was assessed using inter-class coefficients (ICCs). Cohen’s Kappa (κ) was calculated to evaluate the agreement between different modalities in diagnosing severe AV calcification. Results: Compared to the standard, TNC images at 1.5 mm intervals showed higher AVCS (mean difference: −290 ± 418, p < 0.001), with high reproducibility between techniques (CS: ICC 0.969, [IQR 0.962, 0.975]). Compared with reference, VNC showed no significant differences in AVCS at either slice intervals, with excellent reproducibility (3.0 mm, ICC 0.970 [0.963, 0.976]; 1.5 mm, ICC 0.971 [0.964, 0.977]). Compared to TNC 3.0 mm, strong concordance was observed using other reconstruction techniques in assessing severe AV calcification (κ = 0.81 [95% CI: 0.74–0.88], 0.83 [95% CI: 0.76–0.90], and 0.83 [95% CI: 0.76–0.90] for TNC at 1.5 mm, VNC at 3.0 mm, and 1.5 mm, respectively), with low misclassification rates. Conclusions: Our study highlights high reproducibility in the evaluation of AVCS by VNC reconstruction at 3.0 and 1.5 mm intervals compared with reference offering a reliable alternative with an excellent diagnostic accuracy. Full article

Three-dimensional (3D) printing enables accurate implant pre-shaping in orbital reconstruction but is costly and time-consuming. Naked-eye stereoscopic displays (NEDs) enable virtual implant modeling without fabrication. This study aimed to compare the reproducibility and accuracy of NED-based virtual reality (VR) pre-shaping with conventional 3D-printed models. Two surgeons pre-shaped implants for 11 unilateral orbital floor fractures using both 3D-printed and NED-based VR models with identical computed tomography data. The depth, area, and axis dimensions were measured, and reproducibility and agreement were assessed using intraclass correlation coefficients (ICCs), Bland–Altman analysis, and shape similarity metrics—Hausdorff distance (HD) and root mean square error (RMSE). Intra-rater ICCs were ≥0.80 for all parameters except depth in the VR model. The HD and RMSE reveal no significant differences between 3D (2.64 ± 0.85 mm; 1.02 ± 0.42 mm) and VR (3.14 ± 1.18 mm; 1.24 ± 0.53 mm). Inter-rater ICCs were ≥0.80 for the area and axes in both modalities, while depth remained low. Between modalities, no significant differences were found; HD and RMSE were 2.95 ± 0.94 mm and 1.28 ± 0.49 mm. The NED-based VR pre-shaping achieved reproducibility and dimensional agreement comparable to 3D printing, suggesting a feasible cost- and time-efficient alternative for orbital reconstruction. These preliminary findings suggest that NED-based preshaping may be feasible; however, larger studies are required to confirm whether VR can achieve performance comparable to 3D-printed models. Full article

Background. Accurate anatomical assessment is essential for pre-procedural planning in structural heart disease. Advanced 3D imaging could offer improved visualization for more accurate reconstruction. We assessed the performance of a novel immersive 3D virtual reality (VEA) for the pre-procedural planning of transcatheter aortic valve implantation (TAVI) candidates. Methods. Measurement of cardiac-gated contrast-enhanced computed tomography (CT) scans was performed with the novel VEA and established tools: 3Mensio and Horos. Results. 50 consecutive patients were included. Annular and LVOT measurements obtained with VEA were strongly correlated with those derived from standard CT analysis. The intraclass correlation coefficient (ICC) confirmed excellent consistency for annular measurements (ICC = 0.93), while the concordance correlation coefficient indicated very good overall agreement (CCC = 0.83, 95% CI 0.73–0.90). Similarly, LVOT measurements obtained with VEA showed strong correlation with CT values, with good consistency (ICC = 0.90) and good overall agreement (CCC = 0.77, 95% CI 0.64–0.86). VEA-based planning improved prosthesis size selection accuracy, achieving higher concordance with implanted valves and a significant net reclassification gain over conventional CT. Conclusions. Given the increasing use of advanced 3D cardiac imaging technologies, understanding their diagnostic accuracy to guide pre-procedural planning of TAVI is paramount. In our study, VEA provided reliable assessment of aortic root anatomy for TAVI planning. This novel 3D software provides accurate, patient-specific reconstructions of the aortic root and surrounding structures that may optimize valve sizing, improve procedural safety and enhance procedural outcomes. This provides a rationale for future studies to assess the procedural benefit derived from a three-dimensional assessment of the aortic valve geometry. Full article

Background: The management of complex hepato-pancreato-biliary (HPB) pathologies demands exceptional surgical precision. Traditional two-dimensional imaging has limitations in depicting intricate anatomical relationships, potentially complicating preoperative planning. This review explores the synergistic application of three-dimensional (3D) reconstruction and artificial intelligence (AI) to support surgical decision-making in complex HPB cases. Methods: This narrative review synthesized the existing literature on the applications, benefits, limitations, and implementation challenges of 3D reconstruction and AI technologies in HPB surgery. Results: The literature suggests that 3D reconstruction provides patient-specific, interactive models that significantly improve surgeons’ understanding of tumor resectability and vascular anatomy, contributing to reduced operative time and blood loss. Building upon this, AI algorithms can automate image segmentation for 3D modeling, enhance diagnostic accuracy, and offer predictive analytics for postoperative complications, such as liver failure. By analyzing large datasets, AI can identify subtle risk factors to guide clinical decision-making. Conclusions: The convergence of 3D visualization and AI-driven analytics is contributing to an emerging paradigm shift in HPB surgery. This combination may foster a more personalized, precise, and data-informed surgical approach, particularly in anatomically complex or high-risk cases. However, current evidence is heterogeneous and largely observational, underscoring the need for prospective multicenter validation before routine implementation. Full article

Digital twins are emerging as a pivotal technology for the performance optimization, predictive maintenance, and real-time monitoring of wind turbines. However, the accuracy of these virtual representations critically depends on the availability of the power coefficient ($C_p$) curve, a key descriptor of a turbine’s aerodynamic efficiency. This information is often proprietary and not disclosed by manufacturers, posing a significant barrier to the development of high-fidelity digital twins. This study addresses this critical gap by proposing a novel framework for estimating $C_p$ curves using operational Supervisory Control and Data Acquisition (SCADA) data. The proposed methodology utilizes a parameterized mathematical formulation to model the $C_p$ curve and employs the Adam optimizer to robustly tune the model’s parameters against real-world operational data. The framework was evaluated through a two-pronged process. First, the model’s accuracy was assessed using synthetic SCADA data from a high-fidelity simulator under ideal conditions, demonstrating excellent agreement with an $R^2$ exceeding 0.99 and a normalized Mean Absolute Percentage Error (nMAPE) ranging from 4.38% to 6.03%. Second, its practical performance was evaluated using real SCADA data from a commercial wind turbine, where it maintained high accuracy with an $R^2$ ranging from 0.89 to 0.98 and an nMAPE of 3.27% to 5.97%. The findings demonstrate that the proposed methodology can effectively reconstruct a turbine’s aerodynamic characteristics without proprietary manufacturer data. This research offers a viable pathway for operators and researchers to create accurate, turbine-specific digital twins, thereby enabling enhanced performance monitoring, advanced control optimization, and predictive maintenance for more efficient and reliable wind energy production. Full article

Background/Objectives: Pediatric orbital tumors are rare and complex, requiring multidisciplinary care at specialized centers. Contemporary treatment paradigms emphasize centralized care delivery through experienced multidisciplinary teams to optimize patient outcomes. Recent advances in surgical planning technologies and intraoperative navigation systems have substantially enhanced surgical safety through improvement in tumor resection and reconstruction and reduction in complications, including recurrence of the lesion. Computed-aided surgical technologies enable precise virtual planning, minimally invasive approaches and more precise reconstruction methods when necessary by mean of patient-specific cutting guides, premolded orbital plates or individual patient solutions (IPS) prosthesis. Three-dimensional biomodelling visualizes tumor architecture and aids localization while preserving neurovascular structures, and real-time neuronavigation improves safety and efficacy. Methods: We conducted a retrospective analysis of 98 pediatric patients with orbital tumors treated between 2014 and 2025 at a tertiary center to evaluate the use of computed-assisted surgical technologies and the indications for treatment. Inclusion criteria comprised all cases where computer-assisted techniques were employed. Patients were classified into two groups: Group 1—intraconal or extensive periorbital lesions with eye-sparing intent treated via craniofacial approaches; Group 2—periorbital tumors with orbital wall involvement, to analyze the use of the different technologies. Data collected included tumor age, type, location, technology used, adjunctive treatments, and postoperative outcomes. Results: Twelve patients underwent computer-assisted surgery. Technologies employed over the last six years included intraoperative navigation, 3D planning with/without tumor segmentation, orbital-wall reconstruction by mirroring, IPS or titanium mesh bending, and preoperative biomodelling. Patients were grouped by tumor location and treatment goals: Group 1—intraorbital lesions (primarily intraconal or 270–360° involvement), including one case of orbital encephalocele treated transcranially; Group 2—periorbital tumors with orbital-wall destruction, treated mainly via midfacial approaches. Intraoperative navigation was used in 10/12 cases (8/11 with tumor segmentation); in 3 cases with ill-defined margins, navigation localized residual tumor. Virtual surgery predominated in Group 2 (4 patients) and one in Group 1, combined with cutting guides for margins and Individual Prosthetic Solutions (IPS) prosthesis fitting (two patients: titanium and PEEK). In two cases, virtual plans were performed, STL models printed, and premolded titanium meshes used. No complications related to tumor persistence or orbital disturbance were observed. Conclusions: Advanced surgical technologies substantially enhance safety, efficiency, and outcomes in pediatric orbital tumors. Technology-assisted approaches represent a paradigm shift in this complex field. Additional studies are needed to establish evidence-based protocols for systematic integration of technology in pediatric orbital tumor management. Full article

Three-dimensional (3D) building models are essential for urban planning, spatial analysis, and virtual simulations. However, most reconstruction methods based on Airborne LiDAR Scanning (ALS) rely primarily on rooftop information, often resulting in distorted footprints and the omission of façade semantics such as windows and doors. To address these limitations, this study proposes an automatic 3D building reconstruction method driven by façade geometry. The proposed method introduces three key contributions: (1) a façade-guided footprint generation strategy that eliminates geometric distortions associated with roof projection methods; (2) robust detection and reconstruction of façade openings, enabling reliable identification of windows and doors even under sparse ALS conditions; and (3) an integrated volumetric modeling pipeline that produces watertight models with embedded façade details, ensuring both structural accuracy and semantic completeness. Experimental results show that the proposed method achieves geometric deviations at the decimeter level and feature recognition accuracy exceeding 97%. On average, the reconstruction time of a single building is 91 s, demonstrating reliable reconstruction accuracy and satisfactory computational performance. These findings highlight the potential of the method as a robust and scalable solution for large-scale ALS-based urban modeling, offering substantial improvements in both structural precision and semantic richness compared with conventional roof-based approaches. Full article

Aiming at the dynamic characteristics and stability of smart distribution network stations under the combined effect of the uncertainty of new energy output and the control logic of power electronics, an adaptive dimensionally increasing linear dynamic modeling method based on Koopman theory is proposed. Firstly, a regional nonlinear model of an intelligent transformer integrating photovoltaic, wind power, battery, hydrogen fuel cell, and synchronous generator is constructed. The control logic of the virtual synchronous generator is then integrated to characterize the dynamic response of the power electronic interface. Secondly, by constructing a set of nonlinear observation functions, including high-order polynomials, exponents, and periodic functions, the dimensional upgrade mapping of the system state is carried out. The dynamic mode decomposition algorithm is adopted to adaptively extract the dominant dynamic modes in the dimensional upgrade space, achieving global linear approximation of complex nonlinear dynamical systems. Finally, the simulation example results show that the average RMAE error of the Koopman method proposed in this paper in voltage spatiotemporal reconstruction is 0.1419, and the maximum RMSE error is 0.1915, significantly improving the accuracy and stability of dynamic modeling. Full article

The integration of the Scalable Service-Oriented Middleware over IP (SOME/IP) within Automotive Ethernet enables efficient, service-oriented communication in vehicles. This study presents a video stream transmission library using SOME/IP to transfer pre-recorded video data between virtual Electronic Control Units (ECUs). Implemented with vsomeip, OpenCV, and Protocol Buffers, the system handles video serialization, Ethernet transmission, and reconstruction at the receiver side. Experimental evaluation with front and rear dashboard cameras (2560 × 1440 and 1920 × 1080 px) demonstrated that video resolution and file size directly affect processing duration. Optimized 1920 × 1080 videos achieved total processing times of about 400 ms, confirming the feasibility of near-real-time video transmission. A GUI application was also developed to simulate event-based communication by sending object detection updates after video transfer. The proposed framework provides a scalable and modular architecture that can be adapted to real ECU systems, establishing a foundation for future real-time video communication in automotive networks. Full article