Fit Sphere Research Articles

The impact of cooling rate on the structure and properties of VGF-InP single crystals

InP is a III-V compound semiconductor with a zinc-blende crystal structure, widely used in optical communications, high-frequency millimeter-wave devices, optoelectronic integrated circuits, and solar cells. During the growth of VGF-InP single crystals, defects such as twinning, dislocations, and polycrystals are prone to occur. Experimental research on the cooling rate, an important control condition during the growth process, was conducted. By analyzing a large amount of discrete cooling data from the premium InP production and using spherical fitting algorithms for numerical analysis, the optimal cooling curve was obtained. Forward and reverse experimental verification results show that by adjusting the cooling rate at each growth stage, the recurrence of twinning and dislocations was successfully improved. Increasing the cooling rate during the shouldering process helps suppress intrinsic twinning but tends to increase dislocation density during the equal diameter stage process, leading to dislocation proliferation. Therefore, while increasing the cooling rate during shouldering, it is necessary to appropriately reduce the cooling rate during the equal diameter stage process to effectively suppress dislocation proliferation. By precisely controlling the temperature gradient and cooling rate inside the furnace, the thermal field conditions during the crystal growth process can be optimized, significantly improving the quality of InP single crystals.

Field-grown tomato yield estimation using point cloud segmentation with 3D shaping and RGB pictures from a field robot and digital single lens reflex cameras

The aim of this study was to estimate field-grown tomato yield (weight) and quantity of tomatoes using a self-developed robot and digital single lens reflex (DSLR) camera pictures. The authors suggest a new approach to predicting tomato yield that is based on images taken in the field, 3D scanning, and shape. Field pictures were used for tomato segmentation to determine the ripeness of the crop. A convolution neural network (CNN) model using TensorFlow library was devised for the segmentation of tomato berries along with a small robot, which had a 59.3 % F1 score. To enhance the accurate tomato crop model and to estimate the yield later, point cloud imaging was applied using a Ciclops 3D scanner. The best fitting sphere model was generated using the 3D model. The most optimal model was the 3D model, which gave the best representation and provided the weight of the tomatoes with a relative error of 21.90 % and a standard deviation of 17.9665 %. The results indicate a consistent object-based classification of the tomato crop above the plant/row level with an accuracy of 55.33 %, which is better than in-row sampling (images taken by the robot). By comparing the measured and estimated yield, the average difference for DSLR camera images was more favorable at 3.42 kg.

Automatic 3D pelvimetry framework in CT images and its validation

In the field of spinal pathology, sagittal balance of the spine is usually judged by the spatial structure and morphology of pelvis, which can be represented by pelvic parameters. Pelvic parameters, including pelvic incidence, pelvic tilt and sacral slope, are therefore essential for the diagnosis and treatment of spinal disorders, however, it is a time-consuming and laborious procedure to measure these parameters by traditional methods. In this paper, an automatic measurement framework for pelvic CT images was proposed to calculate three-dimensional (3D) pelvic parameters with the support of deep learning technology. Pelvic images were first preprocessed, and 3D reconstruction was then performed to obtain 3D pelvic model by the Visualization Toolkit. DRINet was trained to segment the femoral head region in the pelvic images, and 3D sphere fitting was performed to locate the femoral heads. In addition, VGG16 was adopted to recognize images containing superior sacral endplate, and the plane growth algorithm was used to fit the plane so that the midpoint and normal vector of the superior sacral endplate could be obtained. Finally, 3D pelvic parameters were automatically calculated, and compared with manual measurements for 15 patients. The proposed framework automatically generated 3D pelvic models, and calculated two-dimensional (2D) and 3D pelvic parameters from continuous CT images. Experiments demonstrated that the framework can greatly speed up the calculation of pelvic parameters, and these parameters are accurate when compared with the manual measurements. In conclusion, the proposed framework demonstrates good performance on automatic pelvimetry measurement by incorporating deep learning technology, and can well replace the traditional methods for pelvic parameter measurement.

Obtaining Continental‐Scale, High‐Resolution 2‐D Ionospheric Flows and Application to Meso‐Scale Flow Science

AbstractAn approach for creating continental‐scale, multi‐scale plasma convection maps in the nightside high‐latitude ionosphere using the spherical elementary current systems technique has been developed and evaluated. The capability to reconstruct meso‐scale flow channels improved dramatically, and the velocity errors were reduced by ∼30% compared to the spherical harmonic fitting method. Uncertainties of velocity vectors estimated by varying the model setup was also low. Convection maps for a substorm event revealed multiple flow channels in the polar cap, dominating the convection in the quiet time and early growth phase. The meso‐scale flows extended toward the nightside auroral oval and had continuous flow channels over >20° of latitude, and the flow channels dynamically merged and bifurcated. The substorm onset occurred along one of the flow channels, and the azimuthal extent of the enhanced flows coincided with the initial width of the auroral breakup. During the expansion phase, the meso‐scale flows repetitively crossed the oval poleward boundary, and some of them contributed to subauroral polarization streams enhancements. Increased flows extended duskward, along with the westward traveling surge. Then, flows near midnight weakened and evolved to the Harang flow shear. The meso‐scale flow channels had significant (∼10%–40% on average) contributions to the total plasma transport. The meso‐scale flows were highly variable on ∼10 min time scales and their individual maximum contributions reached upto 73%. These results demonstrate the capability of specifying realistic convection patterns, quantifying the contribution of meso‐scale transport, and evaluating the relationship between meso‐scale flows and localized auroral forms.

Morphometry of the proximal humerus and the relationship to global offset

BackgroundPrevious research has consistently identified the medial and posterior offset of the native humeral head in relation to the intramedullary canal. These anatomic parameters and others such as humeral head and intramedullary diameter provide valuable insight for prosthesis development. However, it is critical to understand the relationship of morphometry to the native center of rotation. Our objective was to use 3-dimensional analysis to demonstrate the native morphometry of the proximal humerus and those relationships to global offset. MethodsFourteen cadaveric humeri were manually measured then digitally analyzed following 3-dimensional scanning. Pearson’s r was used to determine the relationship between variables. ResultsThe mean digital humeral head diameter (Hdd) was 46.5 (± 4.67) mm and the mean manual humeral head diameter was 46.8 (± 4.42) mm. The mean global offset (GO) was 6.36 (± 2.21) mm, and the mean best fit sphere diameter was 46.5 (± 4.63) mm. Pearson’s r = 0.58 (95% confidence interval 0.07-0.84, P = .021) for GO and Hdd which indicates a moderate correlation. Pearson’s r = 0.96 (95% confidence interval 0.89-0.99, P < .001) for Hdd and manual humeral head diameter which indicates a strong correlation. DiscussionNative GO demonstrated a moderately positive correlation to humeral head diameter. The manual measurement of head diameter was strongly correlated to the 3-dimensional software value which reinforces the importance of intraoperative measurement. These data contribute to further understanding of shoulder morphometry which is integral to prosthesis design which impacts postoperative function and complications.

Measurement method of spherical radius size of differential planetary gear tooth surface based on 3D vision

Abstract In order to accurately measure the spherical radius dimensions of planetary gear tooth surfaces, we propose a non-contact measurement method based on 3D vision technology. Firstly, the point cloud data of the planetary gear captured by the laser 3D profiler is preprocessed, and the tooth surface point cloud is extracted. Next, based on the structural characteristics of the planetary gear tooth surface, a uniform slicing and sampling algorithm is used to extract circular contour points where the tooth surface point cloud intersects with the slicing planes. These points are then projected onto a two-dimensional plane, where an improved RANSAC algorithm is used to precisely fit each circular cross-section. Contour points associated with significant fitting errors are removed based on a set tolerance value. Finally, an improved differential evolution algorithm is used to perform a three-dimensional spherical fitting on the contour points that meet the tolerance criteria, achieving accurate measurement of the spherical radius of the planetary gear tooth surfaces. Experimental results demonstrate that the repeatability error of the proposed method is ±0.02 mm, with a maximum absolute error of 0.026 mm and an average measurement time of 4.76 s. The method exhibits high robustness and measurement accuracy, meeting practical engineering measurement requirements.

Determination of rotation center and diameter of femoral heads using off-the-shelf augmented reality hardware for navigation

In total hip arthroplasty (THA), determining the center of rotation (COR) and diameter of the hip joint (acetabulum and femoral head) is essential to restore patient biomechanics. This study investigates on-the-fly determination of hip COR and size, using off-the-shelf augmented reality (AR) hardware. An AR head-mounted device (HMD) was configured with inside-out infrared tracking enabling the determination of surface coordinates using a handheld stylus. Two investigators examined 10 prosthetic femoral heads and cups, and 10 human femurs. The HMD calculated the diameter and COR through sphere fitting. Results were compared to data obtained from either verified prosthetic geometry or post-hoc CT analysis. Repeated single-observer measurements showed a mean diameter error of 0.63 mm ± 0.48 mm for the prosthetic heads and 0.54 mm ± 0.39 mm for the cups. Inter-observer comparison yielded mean diameter errors of 0.28 mm ± 0.71 mm and 1.82 mm ± 1.42 mm for the heads and cups, respectively. Cadaver testing found a mean COR error of 3.09 mm ± 1.18 mm and a diameter error of 1.10 mm ± 0.90 mm. Intra- and inter-observer reliability averaged below 2 mm. AR-based surface mapping using HMD proved accurate and reliable in determining the diameter of THA components with promise in identifying COR and diameter of osteoarthritic femoral heads.

Three-dimensional measurement based on equal spacing binary fringe coding

Abstract Binary fringe projection technology can effectively avoid the measurement error caused by nonlinearity in structured light three-dimensional measurement system. In this paper, a binary fringe projection coding based on equal spacing is proposed firstly, the image sequence projected by binary fringes with equal spacing is corresponding to the sinusoidal intensity values in the same period one by one, and then the sinusoidal fringes are generated by weighted superposition. The experimental results show that, compared with the traditional four-step and 12-step phase shifting methods, the mean square error of the synthesized sinusoidal pattern is reduced by 36.74% and 18.24% respectively, and the mean square error of the distance between the obtained spherical point cloud of the standard sphere and the center of the fitting standard sphere is reduced by 89.36% and 77.27% respectively.

Simultaneous Localization and Mapping System for Agricultural Yield Estimation Based on Improved VINS-RGBD: A Case Study of a Strawberry Field

Crop yield estimation plays a crucial role in agricultural production planning and risk management. Utilizing simultaneous localization and mapping (SLAM) technology for the three-dimensional reconstruction of crops allows for an intuitive understanding of their growth status and facilitates yield estimation. Therefore, this paper proposes a VINS-RGBD system incorporating a semantic segmentation module to enrich the information representation of a 3D reconstruction map. Additionally, image matching using L_SuperPoint feature points is employed to achieve higher localization accuracy and obtain better map quality. Moreover, Voxblox is proposed for storing and representing the maps, which facilitates the storage of large-scale maps. Furthermore, yield estimation is conducted using conditional filtering and RANSAC spherical fitting. The results show that the proposed system achieves an average relative error of 10.87% in yield estimation. The semantic segmentation accuracy of the system reaches 73.2% mIoU, and it can save an average of 96.91% memory for point cloud map storage. Localization accuracy tests on public datasets demonstrate that, compared to Shi–Tomasi corner points, using L_SuperPoint feature points reduces the average ATE by 1.933 and the average RPE by 0.042. Through field experiments and evaluations in a strawberry field, the proposed system demonstrates reliability in yield estimation, providing guidance and support for agricultural production planning and risk management.

Keratoconus Progression Determined at the First Visit: A Deep Learning Approach With Fusion of Imaging and Numerical Clinical Data.

Multiple clinical visits are necessary to determine progression of keratoconus before offering corneal cross-linking. The purpose of this study was to develop a neural network that can potentially predict progression during the initial visit using tomography images and other clinical risk factors. The neural network's development depended on data from 570 keratoconus eyes. During the initial visit, numerical risk factors and posterior elevation maps from Scheimpflug imaging were collected. Increase of steepest keratometry of 1 diopter during follow-up was used as the progression criterion. The data were partitioned into training, validation, and test sets. The first two were used for training, and the latter for performance statistics. The impact of individual risk factors and images was assessed using ablation studies and class activation maps. The most accurate prediction of progression during the initial visit was obtained by using a combination of MobileNet and a multilayer perceptron with an accuracy of 0.83. Using numerical risk factors alone resulted in an accuracy of 0.82. The use of only images had an accuracy of 0.77. The most influential risk factors in the ablation study were age and posterior elevation. The greatest activation in the class activation maps was seen at the highest posterior elevation where there was significant deviation from the best fit sphere. The neural network has exhibited good performance in predicting potential future progression during the initial visit. The developed neural network could be of clinical significance for keratoconus patients by identifying individuals at risk of progression.

Tomato pose estimation using the association of tomato body and sepal

In facility horticulture smart farms, harvesting robotic systems to automate harvesting tasks are challenging due to the complex environment, irregular growth and fruits pose. To harvest a fruits, the vision information required by a harvesting robot is accurate position and pose. Especially, fruit pose information is essential for planning paths to avoid damaging stems, leaves, branches, and obstacles, preventing damage to the fruit and harvesting robots, and planning efficient harvest sequences. This paper presents a method that uses information from tomato sepals to estimate the orientation of tomatoes, which are a commonly grown crop in horticulture. First, we train a YOLOv8 model to detect and segment bodies and sepals of tomatoes. For robust training of the model, the training data is constructed using effective data augmentation, which synthesizes segmented foreground objects and inserting them into the background. Then, for finding association between the body and sepal of a tomato, we apply IoU score based matching and the Hungarian algorithm. Consequently, we obtain point clouds for both parts using RGB-D data. Finally, we compute the center point of each object by using spherical fitting and the statistics of the point cloud, respectively. Then, we estimate the pose of the tomato as a vector between two center points of the body and sepal. To accurately and practically evaluate the proposed method, we generated ground truth data using calibration patterns in tomato greenhouse. As the experimental results show, The segmentation results show that AP50,sepal is 94.7, AP50,tomato is 96.3, and mAP is 61.5. The result of the pose estimation for the pose validation dataset is a mean error angle of 6.79 ± 3.18 and angle errors of less than 10 degrees account for 87.2%. The total algorithm proposed in this paper requires about 0.038s for each tomato greenhouse image. As a result, our proposed pose estimation can be practically utilized in robot systems for tomato harvesting.

Algorithm and software for field distortion correction in a commercial SD-OCT for corneal curvature assessment.

Accurate assessment of corneal curvatures using frequency domain optical coherence tomography (OCT) with galvanometer scanners remains challenging due to the well-known scan field distortion. This paper presents an algorithm and software for correcting the distortion using only two simple measurements in which a readily available standard sphere is positioned in different depths in front of the OCT scanner. This offers a highly accessible and easily reproducible method for the field distortion correction (FDC). The correction was validated by measuring different spherical phantoms and conducting corneal curvature measurements of ex vivo porcine corneas using a commercial spectral-domain OCT system and a clinically approved swept-source OCT as a reference instrument. Thus, the error in radius measurements of spherical phantoms was reduced by >90% and astigmatism by >80% using FDC. In explanted porcine eyes, the error in astigmatism measurements with the Telesto was reduced by 75% for power and 70% for angle. The best fitting sphere radius was determined up to a deviation of 0.4% from the Anterion. This paper describes a correction algorithm for OCT immanent distortion that is applicable to any scanning OCT setup and enables precise corneal curvature measurements. The MATLAB software for the FDC is publicly available on GitHub.

3D compression-twist lattice metamaterials for surface reconfigurability of future architecture

Metamaterials refer to a class of materials with special properties, whose characteristics mainly come from the microstructures designed artificially. Among them, those metamaterials with tunable shape and mechanical properties under external stimuli provide a new inspiration for the design of the multifunctional structures. This work deals with the three-dimensional (3D) compression-twist lattice metamaterials, studies the surface reconfigurability under external forces, and reveals the torsion-bending coupling (TBC) effect of the special metamaterials. To explain the main characteristics of the TBC effect, the deformation mechanism of the metamaterials is analyzed. Combining the finite element method (FEM) and the spherical fitting algorithm, the relationship between the bending angle and the load of the metamaterials after deformation is analyzed and verified by experiments. Finally, a metamaterial module that could be freely transformed between planar and spherical surfaces is envisaged. A faster and greener solution is proposed for the construction of curved surfaces of engineering structures in the future, which promotes the subsequent applications of metamaterials to engineering practice.

A new height contouring method for severity prediction in cam-type hip joints: 20 subject-specific cases

Cam-type femoroacetabular impingement syndrome (FAIS) is characterised by a non-spherical continuation of the femoral head into the femoral head-neck junction and is associated with damage to the acetabular cartilage. Diagnostic methods based on cam shape are progressing from 2D radiographic measurements to 3D CT measures, providing greater insight. There is currently no consensus on how to describe the 3D cam lesion shape and subject-specific impingement mechanisms are difficult to determine.A novel 3D ‘contour’ method was used to describe the proximal femur of 20 cam-type hips. Five contours, analogous to height contours on a terrain map, were used to describe the femoral head-neck junction, capturing the progressive height of the cam lesion. From that description, the cam apex (a subject's largest alpha angle), cam extent (spread around the femoral head), cam location (position around the femoral head) and average acetabular coverage, were recorded. A previously developed hip impingement model was used to apply 126 activity-based motions to each subject-specific hip shape and predict impingement occurrence and depth of incursion past the acetabular rim. Correlations between shape measures and impingement occurrence were investigated.The two contours representing the lowest heights (close to the head best fit sphere and 1 mm greater than that) generated cam alpha angle and cam extent measurements which contained the typical clinical measures (Alpha: close to best fit 47°-98°, at 1 mm 45°–77°; Extent: close to best fit 0°–129°, at 1 mm 0°–100°). The remaining contours described the progressive height of the cam lesion up to 4 mm greater than the head radius. Impingement was predicted predominantly from the first 1 mm height of the cam, with only two subjects impinging at a cam height greater than 2 mm. Therefore, it is possible that adequate resection of the first 1 mm of cam height is the most critical in reducing a subject's impingement severity.Impingement occurrence was positively correlated with the cam apex (ρ = 0.84 close to best fit, ρ = 0.70 at 1 mm height), the cam extent (ρ = 0.68 close to best fit, ρ = 0.80 at 1 mm height) and the acetabular coverage (ρ = 0.50, at 1 mm height). However, in line with other work on cam impingement, correlations between any single shape measure and the risk of impingement were not strong enough to be used with confidence as predictive tools. This supports the further development of modelling tools which sufficiently capture the complex shape and can generate an impingement risk metric which accounts for joint motion.

Changes in posterior corneal elevation after small incision lenticule extraction for different myopic diopters.

To study the changes and effect factors of posterior corneal surface after small incision lenticule extraction (SMILE) with different myopic diopters. Ninety eyes of 90 patients who underwent SMILE were included in this retrospective study. Patients were allocated into three groups based on the preoperative spherical equivalent (SE): low myopia (SE≥-3.00 D), moderate myopia (-3.00 D>SE>-6.00 D) and high myopia (SE≤-6.00 D). Posterior corneal surfaces were measured by a Scheimpflug camera preoperatively and different postoperative times (1wk, 1, 3, 6mo, and 1y). Posterior mean elevation (PME) at 25 predetermined points of 3 concentric circles (2-, 4-, and 6-mm diameter) above the best fit sphere was analyzed. All surgeries were completed uneventfully and no ectasia was found through the observation. The difference of myopia group was significant at the 2-mm ring at 1 and 3mo postoperatively (1mo: P=0.017; 3mo: P=0.018). The effect of time on ΔPME was statistically significant (2-mm ring: P=0.001; 4-mm ring: P<0.001; 6-mm ring: P<0.001). The effect of different corneal locations on ΔPME was significant except 1wk postoperatively (1mo: P=0.000; 3mo: P=0.000; 6mo: P=0.001; 1y: P=0.001). Posterior corneal stability was linearly correlated with SE, central corneal thickness, ablation depth, residual bed thickness, percent ablation depth and percent stromal bed thickness. The posterior corneal surface changes dynamically after SMILE. No protrusion is observed on the posterior corneal surface in patients with different degrees of myopia within one year after surgery. SMILE has good stability, accuracy, safety and predictability.

An errors-unidentified hand-eye calibration method via robot relocalization and iterative combinatorial refinement

The accuracy of hand-eye calibration is easily affected by robot kinematic error, measurement error, random error, etc., and can be to a certain extent enhanced by the complicated error identification. To address this problem, we propose a novel errors-unidentified hand-eye calibration method. A relocalization-based hand-eye calibration is implemented to overcome the challenge from robot kinematics at first owing to the high robot relocalization accuracy. The tool center point (TCP) coordinates are then obtained based on an iterative reweighted least squares (IRLS) spherical fitting algorithm. An iterative combinatorial refinement algorithm is finally presented to search the solutions in the form of permutation and combination when solving the rigid transformation matrix. Experiments on criterion sphere and blade demonstrate that by converting the hand-eye matrix solving problem into a point set matching problem, the accuracy of the proposed method is enhanced by 60% on average compared with three state-of-the-art hand-eye calibration methods.

Three-Dimensional Magnetic Resonance Imaging Fast Field Echo Resembling a Computed Tomography Using Restricted Echo-Spacing Sequence Is Equivalent to 3-Dimensional Computed Tomography in Quantifying Bone Loss and Measuring Shoulder Morphology in Patients With Shoulder Dislocation

PurposeTo evaluate the equivalence of 3D-MRI (Fast field echo Resembling A CT Using Restricted Echo-spacing,FRACTURE) and 3D-CT in quantifying bone loss in patients with shoulder dislocation and measuring morphological parameters of the shoulder. MethodsFrom July 2022 to June 2023,patients with anterior shoulder dislocation who were over 18 years of age and underwent both MRI and CT within 1 week were included in the study.The MRI protocol included an additional FRACTURE sequence.3D reconstructions of MRI(FRACTURE) and CT were completed by two independent observers using Mimics 21.0 software through simple threshold-based segmentation.For bone defect cases, two independent observers evaluated glenoid defect, percentage of glenoid defect,glenoid track(GT), Hill-Sachs Interval (HSI), and "on-track/off-track".For all cases,glenoid width, glenoid height,humeral head fitting sphere radius,Critical Shoulder Angle(CSA),glenoid version,vault depth, and post-processing time were assessed.Paired t-test was utilized to assess the difference between 3D-CT and 3D-MRI (FRACTURE).Bland-Altman plot was constructed to evaluate the consistency between 3D-CT and 3D-MRI (FRACTURE). Inter- and intra-observer agreement was evaluated by Interclass Correlation Coefficient (ICC). Paired chi-square test and Cohen’s kappa statistic were used for binary variable("on-track/off-track"). ResultsA total of 56 patients(16 bipolar bone defect, 5 only Hill-Sachs lesion,35 without bone defect) were eventually enrolled in the study.The measurements of 21 bone defect cases showed no statistical difference between 3D-CT and 3D-MRI.Glenoid defect,3D-CT(4.05±1.44mm) vs 3D-MRI(4.16±1.39mm,P=0.208);Percentage of glenoid defect,3D-CT(16.21±5.95%) vs 3D-MRI(16.61±5.66%, P=0.199);Glenoid Track,3D-CT (18.02±2.97mm) vs 3D-MRI(18.08±2.98mm, P=0.659);Hill-Sachs Interval,3D-CT (14.29±1.93mm) vs 3D-MRI(14.35±2.07mm, P=0.668).No significant difference was found between 3D-CT and 3D-MRI in the diagnosis of "on-track/off-track"(P=1.000), and the diagnostic agreement was perfect (Kappa=1.00,P=0.000). There was no statistical difference between two examination methods in the measurements of all 56 cases,except that the post-processing time of 3D-MRI was obviously longer than that of 3D-CT.Glenoid height,3D-CT(34.56±1.98mm) vs 3D-MRI (34.67±2.01mm, P=0.139).Glenoid width,3D-CT(25.32±1.48mm) vs 3D-MRI(25.45±1.47mm, P=0.113).Humeral head fitting sphere radius,3D-CT(22.91±1.70mm) vs 3D-MRI(23.00±1.76mm, P=0.211).Critical Shoulder Angle,3D-CT(33.49°±2.55°) vs 3D-MRI (33.57°±2.51°, P=0.328). Glenoid version, 3D-CT(-3.25°±2.57°) vs 3D-MRI (-3.18°±2.57°, P=0.322).Vault depth,3D-CT(37.43±1.68mm) vs 3D-MRI(37.58±1.75mm, P=0.164).Post-processing time,3D-CT(89.66±10.20s) vs 3D-MRI (360.93±26.76s, P=0.000).For all assessments, the Bland-Altman plots demonstrated excellent consistency between two examination methods,and the ICCs revealed excellent inter-observer and intra-observer agreement. Conclusions3D-MRI (FRACTURE) is equivalent to 3D-CT in quantifying bone loss in patients with shoulder dislocation and measuring shoulder morphological parameters.

Mapping soil property variability in oil palm (Elaeis guineensis jacq.) plantationsof Krishna basin of Andhra Pradesh through geospatial technologies

Sixty seven soil samples were collected from oil palm growing regions of NTR District of Andhra Pradesh and were analysed for different soil properties. The data was subjected to descriptive analysis to find out the variability and then to geostatistical analysis to design best fit models having minimal error for developing prediction maps. Highest variation was observed in exch. Mg and the lowest in pH. The mean values of soil pH, EC (dS/m), OC (g/kg), Olsen-P (mg/kg), NH4OAc-K (mg/kg), Exch. Ca (mg/kg), Exch. Mg (mg/kg), CaCl2-S (mg/kg) and HWB (mg/kg) were 7.32 ± 0.08, 0.25 ± 0.02, 0.87 ± 0.03, 101.47 ± 6.95, 566.14 ± 42.97, 4.72 ± 0.24, 2.46 ± 0.27, 60.86 ± 2.6 and 5.98 ± 0.25 respectively in the surface layer (0-20 cm) of the soil. Geostatistical analysis revealed wider spatial variability in surface soil properties and they had circular, spherical, stable and exponential best fit semi variogram models for evaluating dependency. The wide spatial variability of soil properties warrants site specific nutrient management for higher oil palm production. Nutrient distribution maps could be developed through kriging interpolation to interpolate the nutrient levels in unsampled areas.

EXPLORING THE LIMITS OF TERRESTRIAL LASER SCANNERS ON AEROSPACE MATERIALS

Abstract. Terrestrial laser scanners are powerful measurement devices commonly used for 3D modelling tasks generating large volumes of data with fast acquisition as a first priority. However, these scanners can alternatively be used to produce near real-time, engineering quality spatial data concerning the changing state of manufactured components. This paper provides a comprehensive analysis of two terrestrial laser scanners capturing aerospace materials and components, and their associated quality measures. In order to explore the limitations of the tested TLS instruments, a mechanical jig was designed incorporating both a rotation and translation stage. This study involved three elements of a point cloud processing workflow: data capture, registration and feature extraction. Sphere-based 7DoF registration is applied using two different commercially available software packages with varying levels of user control. To analyse the quality of the registration, control points extracted from captured point clouds were compared to nominal values measured using a laser tracker. The quality of the registration was consistent, with differences kept between 0.4 mm and 0.6 mm. To evaluate the quality of the captured point clouds, two different tests were conducted. This included planar fit tests on an aluminium drilling template, and sphere fitting tests on white 1.5” spherical targets in magnetic nests. One half of the aluminium drilling template was coated with matte spray to reduce erroneous laser reflections. Finally, the registered point clouds were input to a developed algorithm which automatically extracted drilling holes from the drilling template. Previous scanning work performed on aerospace materials showed evidence of optical rattling caused by high intensity reflections from the interior holes in a drilling template. Further exploration showed that the amount of optical rattle varies systematically with incidence angle. This work demonstrates a systematic offset in the location of extracted hole centres in the drilling template. This offset is dependent on laser incidence angle, and can therefore be accounted for when locating manufacturing components from a known scanning position.

Does Corneal Topography Using 3-Dimensional Optical Coherence Tomography Suggest Different Subtypes of Terrien Marginal Degeneration?

The aim of this study was to analyze corneal topography relative to astigmatism, higher order aberrations, and corneal curvatures in Terrien marginal degeneration using 3-dimensional anterior-segment optical coherence tomography. Twenty-nine eyes of 15 Finnish patients from a tertiary referral center had topographic axial power maps classified into 4 patterns by visual grading: crab claw (CC), mixed (M), arcuate (A), and normal. Regular astigmatism, keratometry, higher order aberrations, maximal corneal thinning, apex thickness, and curvature changes relative to best fit sphere toward maximal peripheral thinning were compared. Four, 9, and 12 eyes were classified as CC, M, and A, respectively; 1 as normal with clinical disease; and 3 as normal with unilateral disease. Median follow-up was 2.3 (range, 0-7.2) years. Three eyes changed pattern. Patients with the CC pattern were the youngest when diagnosed, progressed more rapidly, exhibited cavities in superior quadrants with anterior bulging, and had greater higher order posterior aberrations. Patients with the M pattern were older, progressed slower, and showed superonasal asymmetric corneal steepening extending centrally, often with asymmetric bow tie. Patients with pattern A showed little progression and were the oldest when diagnosed, with maximal corneal thinning equally in all quadrants. According to the Wang classification, the median stage was 4, 2, and 2 in CC, M, and A patterns, respectively, whereas it was always 2 by the Süveges classification. Terrien marginal degeneration is characterized by distinct corneal topographic patterns that differ in tomographic features, suggesting existence of subtypes in addition to different stages of disease. Patients representing CC and M patterns might benefit from more frequent monitoring.