Circle Fitting Research Articles

Forest Stem Extraction and Modeling (FoSEM): A LiDAR-Based Framework for Accurate Tree Stem Extraction and Modeling in Radiata Pine Plantations

Accurate characterization of tree stems is critical for assessing commercial forest health, estimating merchantable timber volume, and informing sustainable value management strategies. Conventional ground-based manual measurements, although precise, are labor-intensive and impractical at large scales, while remote sensing approaches using satellite or UAV imagery often lack the spatial resolution needed to capture individual tree attributes in complex forest environments. To address these challenges, this study provides a significant contribution by introducing a large-scale dataset encompassing 40 plots in Western Australia (WA) with varying tree densities, derived from Hovermap LiDAR acquisitions and destructive sampling. The dataset includes parameters such as plot and tree identifiers, DBH, tree height, stem length, section lengths, and detailed diameter measurements (e.g., DiaMin, DiaMax, DiaMean) across various heights, enabling precise ground-truth calibration and validation. Based on this dataset, we present the Forest Stem Extraction and Modeling (FoSEM) framework, a LiDAR-driven methodology that efficiently and reliably models individual tree stems from dense 3D point clouds. FoSEM integrates ground segmentation, height normalization, and K-means clustering at a predefined elevation to isolate stem cores. It then applies circle fitting to capture cross-sectional geometry and employs MLESAC-based cylinder fitting for robust stem delineation. Experimental evaluations conducted across various radiata pine plots of varying complexity demonstrate that FoSEM consistently achieves high accuracy, with a DBH RMSE of 1.19 cm (rRMSE = 4.67%) and a height RMSE of 1.00 m (rRMSE = 4.24%). These results surpass those of existing methods and highlight FoSEM’s adaptability to heterogeneous stand conditions. By providing both a robust method and an extensive dataset, this work advances the state of the art in LiDAR-based forest inventory, enabling more efficient and accurate tree-level assessments in support of sustainable forest management.

Improved Cylinder-Based Tree Trunk Detection in LiDAR Point Clouds for Forestry Applications

The application of LiDAR technology in extracting individual trees and stand parameters plays a crucial role in forest surveys. Accurate identification of individual tree trunks is a critical foundation for subsequent parameter extraction. For LiDAR-acquired forest point cloud data, existing two-dimensional (2D) plane-based algorithms for tree trunk detection often suffer from spatial information loss, resulting in reduced accuracy, particularly for tilted trees. While cylinder fitting algorithms provide a three-dimensional (3D) solution for trunk detection, their performance in complex forest environments remains limited due to sensitivity to parameters like distance thresholds. To address these challenges, this study proposes an improved individual tree trunk detection algorithm, Random Sample Consensus Cylinder Fitting (RANSAC-CyF), specifically optimized for detecting cylindrical tree trunks. Validated in three forest plots with varying complexities in Tianhe District, Guangzhou, the algorithm demonstrated significant advantages in the inlier rate, detection success rate, and robustness for tilted trees. The study showed the following results: (1) The average difference between the inlier rates of tree trunks and non-tree points for the three sample plots using RANSAC-CyF were 0.59, 0.63, and 0.52, respectively, which were significantly higher than those using the Least Squares Circle Fitting (LSCF) algorithm and the Random Sample Consensus Circle Fitting (RANSAC-CF) algorithm (p < 0.05). (2) RANSAC-CyF required only 2 and 8 clusters to achieve a 100% detection success rate in Plot 1 and Plot 2, while the other algorithms needed 26 and 40 clusters. (3) The effective distance threshold range of RANSAC-CyF was more than twice that of the comparison algorithms, maintaining stable inlier rates above 0.9 across all tilt angles. (4) The RANSAC-CyF algorithm still achieved good detection performance in the challenging Plot 3. Together, the other two algorithms failed to detect. The findings highlight the RANSAC-CyF algorithm’s superior accuracy, robustness, and adaptability in complex forest environments, significantly improving the efficiency and precision of individual tree trunk detection for forestry surveys and ecological research.

Inline-Acquired Product Point Clouds for Non-Destructive Testing: A Case Study of a Steel Part Manufacturer

Modern vision-based inspection systems are inherently limited by their two-dimensional nature, particularly when inspecting complex product geometries. These systems are often unable to capture critical depth information, leading to challenges in accurately measuring features such as holes, edges, and surfaces with irregular curvature. To address these shortcomings, this study introduces an approach that leverages computer-aided design-oriented three-dimensional point clouds, captured via a laser line triangulation sensor mounted onto a motorized linear guide. This setup facilitates precise surface scanning, extracting complex geometrical features, which are subsequently processed through an AI-based analytical component. Dimensional properties, such as radii and inter-feature distances, are computed using a combination of K-nearest neighbors and least-squares circle fitting algorithms. This approach is validated in the context of steel part manufacturing, where traditional 2D vision-based systems often struggle due to the material’s reflectivity and complex geometries. This system achieves an average accuracy of 95.78% across three different product types, demonstrating robustness and adaptability to varying geometrical configurations. An uncertainty analysis confirms that the measurement deviations remain within acceptable limits, supporting the system’s potential for improving quality control in industrial environments. Thus, the proposed approach may offer a reliable, non-destructive inline testing solution, with the potential to enhance manufacturing efficiency.

The Coraco-Gleno-Scapular line: A simple tool for assessing glenoid bone defects.

The treatment decisions for shoulder instability often necessitate surgical intervention, with glenoid bone loss being a key factor. Currently, various techniques exist to identify glenoid bone loss, each with its own advantages and disadvantages. This study introduces the Coraco-Gleno-Scapular (CGS) line as a tool for assessing critical glenoid bone defects. The objective is to define the CGS line and evaluate its utility in guiding clinical decisions regarding bone loss, proposing that defects extending posterior to this line indicate critical bone involvement requiring surgical intervention. The study analyzed 50 normal right shoulders from individuals aged 18-40 years. Using 3D en face views of the glenoid, the CGS line was defined from the anteroinferior base of the coracoid process, crossing the anterior glenoid, to the anteroinferior pole of the scapula. The best-fit circle area method and the glenoid index linear method were used to calculate the percentage of the bone area located anterior to the CGS line. The best fit circle area method revealed a mean glenoid surface area anterior to the CGS line of 22.19%, while the glenoid index linear method indicated a mean area of 27.2% anterior to the CGS line. Of the 50 shoulders, 14 had a glenoid surface area <20% anterior to the CGS line using the best-fit circle method, with no cases below 17.5%, while 36 individuals had a glenoid surface area >20%. The Coraco-Gleno-Scapular line is a reliable and simple tool for assessing glenoid bone loss, providing valuable guidance in managing shoulder instability. Its ease of use makes it a promising candidate for standard application in clinical practice. Prospective observational study, Level III.

Event-Based Measurement of Aeroelastic Structure in High-Speed Flow

In high-speed aerodynamics research, point sensors are ideal for embedding in test models but lack spatial resolution, whereas high-speed cameras offer spatiotemporally resolved measurement but involve significant footprint, cost, and data size. To address these tradeoffs, this study explores the application of nascent event-based cameras for high-speed tests. Event-based cameras support continuous, data-sparse kilohertz-equivalent imaging at 720p resolution, on form factors as small as 36 mm and 40 grams in mass, combining the benefits of point sensors and high-speed cameras. However, these attributes come from asynchronous pixels that necessitate unique operating and postprocessing approaches. Here, the authors adapted event-based cameras for two-/three-dimensional photogrammetric tracking of aeroelastic structures, demonstrating an event-based workflow and two tracking algorithms (mean-shift filtering and circle fit). Bench-top validations achieved three-dimensional precision of 0.35 mm/s on 20 mm/s motion across a 259 mm field of view, while two-dimensional measurements of an aeroelastic titanium panel in Mach 0.76 transonic flow successfully identified millimeter-scale vibrations at 43.7, 120, and 270 Hz, validated against a laser displacement and high-speed camera. The transonic test’s raw data were 145.8 MB on the event-based camera, compared to 88.5 GB on the high-speed camera. The presented results demonstrated the viability of event-based techniques in high-speed aerodynamic testing, while highlighting challenges such as polarity switching and pixel latency.

A Circle Center Location Algorithm Based on Sample Density and Adaptive Thresholding

How to acquire the exact center of a circular sample is an essential task in object recognition. Present algorithms suffer from the high time consumption and low precision. To tackle these issues, we propose a novel circle center location algorithm based on sample density and adaptive thresholding. After obtaining circular contours through image pre-processing, these contours were segmented using a grid method to obtain the required coordinates. Based on the principle of three points forming a circle, a data set containing a large number of samples with circle center coordinates was constructed. It was highly probable that these circle center samples would fall within the near neighborhood of the actual circle center coordinates. Subsequently, an adaptive bandwidth fast Gaussian kernel was introduced to address the issue of sample point weighting. The mean shift clustering algorithm was employed to compute the optimal solution for the density of candidate circle center sample data. The final optimal center location was obtained by an iteration algorithm. Experimental results demonstrate that in the presence of interference, the average positioning error of this circle center localization algorithm is 0.051 pixels. Its localization accuracy is 64.1% higher than the Hough transform and 86.4% higher than the circle fitting algorithm.

Automated recognition and rebar dimensional assessment of prefabricated bridge components from low-cost 3D laser scanner

Dimension quality inspections for rebar spacing and length of prefabricated bridge components are critical for subsequent efficient assembly on-site. Currently, the traditional manual inspection method is time-consuming, labor-intensive, and error-prone. The existing commercial 3D LiDAR-based methods are difficult in making balances between inspection cost, efficiency, and accuracy. Thus, the automated recognition and segmentation method of 3D point clouds acquired by a self-developed low-cost LiDAR is proposed to evaluate the rebar spacing and length of bridge prefabricated components. Due to the high-cost commercial 3D laser scanner, a spinning 2D LiDAR-based low-cost 3D laser scanner device and geometric calibration model were developed to acquire the 3D spatial point cloud. Then, two-stage automated point cloud segmentation framework is proposed with coarse extraction of the point cloud in the interest region and fine recognition of point cloud using machine learning methods, including plane segmentation and circle fitting employing random sample consensus (RANSAC) algorithm, and rebars segmentation utilizing Gaussian mixture model (GMM) and density-based spatial clustering of applications with noise (DBSCAN) algorithm. The proposed system was evaluated in two prefabricated concrete columns and shows the potential for improving the quality inspection efficiency and accuracy.

Investigation of axis-fitting-based measurement and identification techniques for kinematic parameters in multi-joint industrial robots

To improve the positioning accuracy of industrial robots and meet the requirements of industrial applications, this study begins with the structural design of multi-jointed industrial robots and proposes a kinematic calibration method based on axis fitting. The proposed method introduces an axis fitting technique based on circle fitting. Utilizing the results of the axis fitting, a method for establishing link coordinate systems by referencing the Modified Denavit-Hartenberg (MD-H) model is presented. Subsequently, a kinematic parameter identification method is proposed. This study primarily investigates the impact of joint rotation angles on the accuracy of axis fitting. The study reveals that when the rotation angle is greater than or equal to 20°, the circularity of the circle fitting is less than 0.008 mm, and the planarity is less than 0.01 mm, indicating that the proposed fitting algorithm meets the required precision for small angle rotations. Finally, the positioning accuracy of the target robot is verified according to ISO 9283:1998. After calibration, the positioning accuracy at point P1 improves from 1.64 mm to 0.46 mm, an enhancement of 71.95 %, which is the most significant improvement. At point P2, the positioning accuracy improves from 1.75 mm to 0.69 mm, an enhancement of 60.5 %, which is the least improvement. The advantage of this method lies in its ability to identify kinematic parameters that align with the actual structure of the robot using a simple measurement method, thereby improving the robot's positioning accuracy.

A morphological indicator for aortic dissection: fitting circle of the thoracic aorta

BackgroundThis study aims to identify a morphological indicator of aortic dissection (AD) based on the geometrical characteristics of the thoracic aorta.MethodsWe evaluated computed tomographic angiograms of 63 samples with AD (22 with type A AD, 41 with type B AD) and 71 healthy samples. Via centerline extraction and spatial transformation, the spatial entanglement of the aorta was minimized, and the expanded 2D aortic morphology was obtained. The 2D morphology of the thoracic aorta was fit to a circle. The applicability of the fitting circle method for identifying aortic dissection was verified by multivariable logistic regression analysis.ResultsVia the 3D coordinate transformation algorithm, the optimal aortic view was obtained. On this view, the geometrical characteristics of the thoracic aortas of the healthy controls were similar to a portion of a circle (sum of residuals: 3502.45 ± 2566.71, variance: 86.23 ± 56.60), while that of AD samples had poorer similarity to the circle (sum of residuals: 5404.78 ± 3891.69, variance: 129.90 ± 90.09). This difference was significant (p < 0.001). A logistic regression model showed that increased deformation of the thoracic aorta was a significant indicator of aortic dissection (odds ratio: 1.35, p = 0.034).ConclusionsThe morphology of the healthy thoracic aorta could be fit to a circle, while that of the dissected aorta had poorer similarity to the circle. The statistics of the circle are an effective indicator of aortic deformation in AD.Trial registrationThis study is registered in the Chinese Clinical Trial Registry (ChiCTR2000029219).

A robust circle fitting method for component fiducialization

The fiducialization for the round component is an indispensable step in the alignment. The traditional geometric and algebraic fitting algorithms are prone to be contaminated by outliers and the accuracy of existing robust algorithms can be further improved. In this study, we present a robust weighted Hyper method that combines the strengths of both the M-estimator and the Hyper method. Through Black-Rangarajan duality, outliers are assigned minimal or even zero weights, effectively enhancing robustness. We tested the proposed algorithm with several benchmarking algorithms using Monte Carlo data. In the presence of outliers, our method demonstrates the lowest root mean squared errors (RMSE). Specifically, when fitting points observed by the laser tracker in Dalian Advanced Light Source (DALS), our method outperforms existing algorithms in terms of repeat accuracy, yielding standard errors (STD) of 11.7 μm and 14.31 μm for the center and radius respectively. The robust weighted Hyper algorithm enhances fiducialization precision without requiring additional instruments and provides valuable guidance in the alignment.

Coronoid height index: a reliable and reproducible technique for quantifying coronoid bone loss in elbow instability

Coronoid fracture size is one important factor in decision-making on surgical vs. nonsurgical management. There is currently no reliable, standardized technique to measure coronoid fracture size or bone loss. Hence, decision-making remains arbitrary, and recommendations made in the literature are unreliable. The aim of the study was to develop and assess a simple, reliable computed tomography (CT)-based technique that allows measurement of apical and anteromedial facet (AMF) coronoid height and bone loss. To achieve this, we sought to understand normal coronoid height across a large patient cohort, and whether the new technique was sensitive at detecting bone loss in patients with a fracture. 163 CT scans were manually formatted in the plane of the proximal ulna. A best fit circle was drawn in the greater sigmoid notch on the sagittal section. The coronoid coverage height (CCH) was defined as the distance (in mm) measured at 90° from the greater sigmoid notch floor to a line between the olecranon and coronoid tips (or fracture base in fractured coronoids), bisecting the center of the circle. The coronoid height index (CHI) was calculated as a % by dividing the CCH by the diameter of the circle. The measurements were performed at the coronoid apex and the center of the AMF in 108 intact coronoids to understand normative values and 55 fractured coronoids to assess the sensitivity of the technique at detecting bone loss. Measurements were independently performed by two investigators, and interobserver reliability was assessed with weighted Cohen's kappa (ĸ) and intraclass correlation coefficient. For intact coronoids, the mean CCH was 11.4±1.4 mm at the apex and 11.6±1.3 mm at the AMF. The mean CHI was 56.7±4.9% at the apex and 41.1±3.6% at the AMF. For fractured coronoids, the mean CCH and CHI were significantly lower (P<.001) at both the apical (9.7±1.4 mm, 45.8%±6.5%) and AMF (9.8±1.6 mm, 33.9%±6.5%) positions, confirming that the technique was capable of detecting coronoid bone loss. While the CCH (a metric measurement) was significantly higher in men than in women (P<.001), the CHI (a proportion) demonstrated no significant difference at both the apex (P=.06) and AMF (P=.91). Interobserver reliability was good to excellent across all parameters. CHI is a reliable CT-based technique to assess coronoid height and bone loss that is independent of patient size and can be used for clinical and research purposes.

Analysis of Variation in Sagittal Curvature of the Femoral Condyles.

In designing femoral components, which restore native (i.e., healthy) knee kinematics, the flexion-extension (F-E) axis of the tibiofemoral joint should match that of the native knee. Because the F-E axis is governed by the curvature of the femoral condyles in the sagittal plane, the primary objective was to determine the variation in radii of curvature. Eleven high accuracy three-dimensional (3D) femur models were generated from ultrahigh resolution CT scans. The sagittal profile of each condyle was created. The radii of curvature at 15 deg increments of arc length were determined based on segment circles best-fit to ±15 deg of arc at each increment. Results were standardized to the radius of the best-fit overall circle to 15 deg-105 deg for the femoral condyle having a radius closest to the mean radius. Medial and lateral femoral condyles exhibited multiradius of curvature sagittal profiles where the radius decreased at 30 deg flexion by 10 mm and at 15 deg flexion by 8 mm, respectively. On either side of the decrease, radii of segment circles were relatively constant. Beyond the transition angles where the radii decreased, the anterior-posterior (A-P) positions of the centers of curvature varied 4.8 mm and 2.3 mm for the medial and lateral condyles, respectively. A two-radius of curvature profile approximates the radii of curvature of both native femoral condyles, but the transition angles differ with the transition angle of the medial femoral condyle occurring about 15 deg later in flexion. Owing to variation in A-P positions of centers of curvature, the F-E axis is not strictly fixed in the femur.

Role of CT Scan in Preoperative Evaluation of Bone Loss in Anterior Shoulder Instability Using the On Track and Off Track Concept

Abstract Purpose The purpose of this study was to assess the role of CT scan in preoperative evaluation of glenoid and humeral head bone loss in cases of recurrent anterior shoulder joint dislocation using on track and off track concept and whether it can be used to predict engagement during arthroscopy. Patients and Methods In the period from June 2019 to October 2022, this study was conducted in Ain Shams University hospitals including 40 cases with recurrent anterior shoulder dislocation. CT scan with 3D reconstruction was done to calculate the width of the glenoid track using the best fit circle method as well as the Hill Sachs interval. We used the on-track off-track method to predict engagement and these results were compared with the findings related to engagement seen during arthroscopy Results Using the on-track /off-track technique on CT images, 22 of the 25 engaging (off-track) lesions was predicted correctly (sensitivity, 88%).While 13 of the 15 cases that did not engage (on-track) was correctly predicted (specificity, 86.7%). Overall, the accuracy of the on-track off-track method was 87.5% with a positive predictive value (PPV) of 91.7% and negative predictive value (NPV) of 81.3%. The on-track /off-track method was found to be a significant predictor of engagement as there is no statistically significant difference (p = 0.18) between this method and arthroscopic findings. Conclusion Our study showed that using the on-track off-track method by CT scan can accurately assess the glenoid and humeral head bone losses seen in patients with anterior shoulder instability for predicting the presence of engagement, or off-track, lesions. This technique can be used for preoperative evaluation to help in deciding the type of surgical procedure performed on patients with anterior shoulder instability.

Poster 361: Changes in Anterior Tibial Translation Are Not Associated with Degradation in Weightbearing Cartilage of the Knee Following Anterior Cruciate Ligament Reconstruction

Objectives: Anterior cruciate ligament (ACL) injury is a frequent knee injury that commonly results in post-traumatic osteoarthritis (PTOA). ACL injury has been shown to increase the risk of osteoarthritis (OA) over eightfold within 11 years following injury. While the development of OA is well documented, the mechanism by which this accelerated cartilage degradation occurs is not well understood. The ACL is crucial in providing anterior-posterior and rotational stability of the tibia relative to the femur. Our previous work has demonstrated that ACLR does not restore pathologic anterior tibial translation (ATT) in the lateral or medial tibiofemoral compartment to levels present in uninjured knee. Increased static ATT, specifically the lateral tibial plateau on static magnetic resonance imaging (MRI) in ACL-deficient knees is associated with rotary instability. However’ how ATT relates to clinical outcomes, specifically the development of PTOA, has not been well studied. The objective of this study was two-fold. (1) Compare T2 relaxation times of cartilage in injured knees [a measure of water content and collagen organization of articular cartilage that indicates early cartilage breakdown] 6 months after ACL reconstruction (ACLR); (2) investigate whether greater ATT associates with longer (worse) T2 relaxation times in the lateral and medial compartment. We hypothesized that T2 relaxation times would increase (worsen) from before to 6-months post-operatively, and would be positively correlated with greater amounts of ATT. Methods: Twenty-nine participants between the ages of 15 and 35 were enrolled within one month of ACL injury but prior to ACLR. Individuals older than 35 were excluded due to possible baseline cartilage degeneration. Other exclusion criteria included previous injury or surgery to either knee, acute chondral lesions, concomitate Grade III tear to other ligaments of the knee, or open growth plates requiring altered ACLR technique. Bilateral knee quantitative MRI data were acquired on a 3-Tesla Phillips Ingenia MRI scanner T2 relaxation maps were generated by using multi-echo MRI data at each signal to fit the signal equation using Levenberg-Marquardt nonlinear least squares algorithm ( Si = the signal at echo time TEi, and S0 = signal at TE = 0) within Interactive Data Language (Harris Geospatial Solutions Inc.). Cartilage segmentation was manually segmented using ITK-SNAP software (Figure 1) The medial and lateral tibial (MTC, LTC) and femoral (MFC, LFC) condyles were divided into three weightbearing regions of interest (ROI) related to the meniscal horns in the sagittal plane (figure 1). Accuracy of segmentation and ROI boundaries were confirmed by a bord-certified, fellowship-Trained musculoskeletal radiologist. ATT was measured on MRI using the validated method described by Iwaki et al. A midsagittal point was identified halfway between the posterior cruciate ligament (PCL) insertion and the lateral edge of the LTC was identified on sagittal MRI. At the midsagittal point, a vertical line was drawn off the posterior cortex of the tibia, perpendicular to the plateau. A best-fit circle was then drawn over the posterior LFC and a second line perpendicular to the LTC was drawn off the posterior margin of the best fit circle. The distance between the two vertical lines was used to calculate ATT. Paired t tests were used to determine if T2 relaxation times differed in the injured limb from before to 6 months after ACLR. Pearson correlations were used to determine the relationship in each weightbearing ROI between 1) change in ATT and percent change in T2 relaxation times from before to 6 months after ACLR, and 2) between-limb difference in ATT before ACLR and percent change in T2 relaxation time. Results: Demographic data including age, sex, race, and pre-injury cutting and pivoting sport participation are presented in Table 1. Twenty-six (89.7%) individuals participated in level one activities (i.e. basketball, soccer) prior to injury. T2 relaxation times increased (worsened) in all weightbearing ROIs from before to 6 months after ACLR except the posterior weightbearing region in the LFC (p=0.296) and the central weightbearing region in the LTC (0.470). Neither the postoperative change in ATT nor the difference in ATT between injured and uninjured limbs before ACLR were significantly correlated with increase in T2 relaxation times (Table 3). Conclusions: The results of this study support our hypothesis that T2 relaxation times would be significantly longer, representing cartilage degradation, after ACLR, even at an early time point of 6 months post-operatively. However, greater ATT in ACL-injured knees remaining at 6 months after ACLR as well as relative to the uninjured limb before ACLR was not correlated with changes in T2 relaxation times in the weightbearing cartilage of the femur and tibia. Future work is needed to identify possible dynamic changes in cartilage loading related to early OA development following ACL injury and reconstruction.

Enhanced Spectroscopic Insight into Acceptor-Modified Barium Strontium Titanate Thin Films Deposited via the Sol-Gel Method.

In the present paper, composite thin films of barium strontium titanate (BaxSr1-xTiO3) with an acceptor modifier (magnesium oxide-MgO) were deposited on metal substrates (stainless steel type) using the sol-gel method. The composite thin films feature BaxSr1-xTiO3 ferroelectric solid solution as the matrix and MgO linear dielectric as the reinforcement, with MgO concentrations ranging from 1 to 5 mol%. Following thermal treatment at 650 °C, the films were analyzed for their impedance response. Experimental impedance spectra were modeled using the Kohlrausch-Williams-Watts function, revealing stretching parameters (β) in the range of approximately 0.78 to 0.89 and 0.56 to 0.90 for impedance and electric modulus formalisms, respectively. Notably, films modified with 3 mol% MgO exhibited the least stretched relaxation function. Employing the electric equivalent circuit method for data analysis, the "circle fit" analysis demonstrated an increase in capacitance from 2.97 × 10-12 F to 5.78 × 10-10 F with the incorporation of 3 mol% MgO into BST-based thin films. Further analysis based on Voigt, Maxwell, and ladder circuits revealed trends in resistance and capacitance components with varying MgO contents, suggesting non-Debye-type relaxation phenomena across all tested samples.

An edge-based interface tracking (EBIT) method for multiphase-flow simulation with surface tension

We present a novel Front-Tracking method, the Edge-Based Interface Tracking (EBIT) method for multiphase flow simulations. In the EBIT method, the markers are located on the grid edges and the interface can be reconstructed without storing the connectivity of the markers. This feature makes the process of marker addition or removal easier than in the traditional Front-Tracking method. The EBIT method also allows almost automatic parallelization due to the lack of explicit connectivity.In a previous journal article we have presented the kinematic part of the EBIT method, that includes the algorithms for piecewise linear reconstruction and advection of the interface. Here, we complete the presentation of the EBIT method and combine the kinematic algorithm with a Navier–Stokes solver. A circle fit is now implemented to improve the accuracy of mass conservation in the reconstruction phase. Furthermore, to identify the reference phase and to distinguish ambiguous topological configurations, we introduce a new feature: the Color Vertex. For the coupling with the Navier–Stokes equations, we first calculate volume fractions from the position of the markers and the Color Vertex, then viscosity and density fields from the computed volume fractions and finally surface tension stresses with the Height-Function method. In addition, an automatic topology change algorithm is implemented into the EBIT method, making it possible the simulation of more complex flows. The two-dimensional version of the EBIT method has been implemented in the free Basilisk platform, and validated with seven standard test cases: stagnation flow, translation with uniform velocity, single vortex, Zalesak's disk, capillary wave, Rayleigh-Taylor instability and rising bubble. The results are compared with those obtained with the Volume-of-Fluid (VOF) method already implemented in Basilisk.

Noise Analysis for Unbiased Tree Diameter Estimation from Personal Laser Scanning Data

Personal laser scanning devices employing Simultaneous Localization and Mapping (SLAM) technology have rightfully gained traction in various applications, including forest mensuration and inventories. This study focuses the inherent stochastic noise in SLAM data. An analysis of noise distribution is performed in GeoSLAM ZEB Horizon for point clouds of trees of two species, Norway spruce and European beech, to mitigate bias in diameter estimates. The method involved evaluating residuals of individual 3D points concerning the real tree surface model based on TLS data. The results show that the noise is not symmetrical regarding the real surface, showing significant negative difference, and moreover, the difference from zero mean significantly differs between species, with an average of −0.40 cm for spruce and −0.44 cm for beech. Furthermore, the residuals show significant dependence on the return distance between the scanner and the target and the incidence angle. An experimental comparison of RANSAC circle fitting outcomes under various configurations showed unbiased diameter estimates with extending the inlier tolerance to 5 cm with 2.5 cm asymmetry. By showing the nonvalidity of the assumption of zero mean in diameter estimation methods, the results contribute to fill a gap in the methodology of data processing with the widely utilized instrument.

Circle fit optimization for resonator quality factor measurements: Point redistribution for maximal accuracy

The control of material loss mechanisms is playing an increasingly important role for improving coherence times of superconducting quantum devices. Such material losses can be characterized through the measurement of planar superconducting resonators, which reflect losses through the resonance's quality factor Ql. The resonance quality factor consists of both internal (material) losses as well as coupling losses when resonance photons escape back into the measurement circuit. The combined losses are then described as Ql−1=Re{Qc−1}+Qi−1, where Qc and Qi reflect the coupling and internal quality factors of the resonator, respectively. To separate the relative contributions of Qi and Qc to Ql, diameter-correcting circle fits use algebraic or geometric means to fit the resonance signal on the complex plane. However, such circle fits can produce varied results, so to address this issue, we use a combination of simulation and experiment to determine the reliability of a fitting algorithm across a wide range of quality factor values from Qi≪Qc to Qc≪Qi. In addition, we develop a measurement protocol that can not only reduce fitting errors by factors ≳2 but also mitigates the influence of the measurement background on the fit results. This technique can be generalized for other resonance systems beyond superconducting resonators. Published by the American Physical Society 2024

Tree Diameter at Breast Height Extraction Based on Mobile Laser Scanning Point Cloud

The traditional measurement method (e.g., field survey) of tree diameter circumference often has high labor costs and is time-consuming. Mobile laser scanning (MLS) is a powerful tool for measuring forest diameter at breast height (DBH). However, the accuracy of point cloud registration seriously affects the results of DBH measurements. To address this issue, this paper proposes a new method for extracting tree DBH parameters; it achieves the purpose of efficient and accurate extraction of tree DBH by point cloud filtering, single-tree instance segmentation, and least squares circle fitting. Firstly, the point cloud data of the plantation forest samples were obtained by a self-constructed unmanned vehicle-mounted mobile laser scanning system, and the ground point cloud was removed using cloth simulation filtering (CSF). Secondly, fast Euclidean clustering (FEC) was employed to segment the single-tree instances, and the point cloud slices at breast height were extracted based on the point sets of single-tree instances, which were then fitted in two dimensions using the horizontally projected point cloud slices. Finally, a circle fitting algorithm based on intensity weighted least squares (IWLS) was proposed to solve the optimal circle model based on 2D point cloud slices, to minimize the impact of misaligned point clouds on DBH measures. The results showed that the mean absolute error (MAE) of the IWLS method was 2.41 cm, the root mean square error (RMSE) was 2.81 cm, and the relative accuracy was 89.77%. Compared with the random sample consensus (RANSAC) algorithm and ordinary least squares (OLS), the MAE was reduced by 36.45% and 9.14%, the RMSE was reduced by 40.90% and 12.26%, and the relative accuracy was improved by 8.99% and 1.63%, respectively. The R2 value of the fitted curve of the IWLS method was the closest to 1, with the highest goodness of fit and a significant linear correlation with the true value. The proposed intensity weighted least squares circle-fitting DBH extraction method can effectively improve the DBH extraction accuracy of mobile laser scanning point cloud data and reduce the influence of poorly aligned point clouds on DBH fitting.

A Methodological Approach for Motor Selection in Dental Impression Material Dispensers Using Experimental and Image Analysis Techniques.

This study presents a methodology to prevent the overdesign of electric dispensers for dental impression materials by analyzing the necessary load and determining the appropriate pressurization speed and drive motor capacity. We derived an equation to calculate the required torque and rotational speed of the motor based on the extrusion load and the speed of the impression material. A specialized load measurement system was developed to measure the load necessary to extrude the impression material. Through experiments and image processing, we measured the radius of curvature of the trajectory of the impression material and correlated it with the pressurization speed. Techniques such as position coordinate plotting, curve fitting, and circle fitting were employed to determine the pressurization speed that aligns with the manufacturer's recommended curvature radius. These findings led to a substantial decrease in the necessary motor torque and rotational speed compared with the current standards. This research provides a systematic approach to sizing drive motors using extrusion load and pressurization speed, aiming to reduce overdesign, power consumption, and the weight and size of the motor and battery, thereby contributing to the development of more efficient and compact dental impression material dispensers.