Accurate Shape Research Articles

Implementasi Algoritma YOLO Dalam Pengklasifikasian Objek Transportasi pada Lalu Lintas Kota Medan

This research allows an automated system for detecting classified means of transportation in Medan City traffic using the YOLOv8 algorithm. The YOLOv8 algorithm is used to detect transportation objects with accuracy that is many times better than other object detection algorithms and with good accuracy after training with various data sets. The use of this algorithm provides an effective solution for handling congestion in the form of increasing the number of vehicles and less orderly traffic users in the city of Medan. The placement of each transportation object in the image to be tested by the system has an influence on the shape accuracy of the object detection results by the algorithm.

Evaluating OSM Building Footprint Data Quality in Québec Province, Canada from 2018 to 2023: A Comparative Study

OpenStreetMap (OSM) is among the most prominent Volunteered Geographic Information (VGI) initiatives, aiming to create a freely accessible world map. Despite its success, the data quality of OSM remains variable. This study begins by identifying the quality metrics proposed by earlier research to assess the quality of OSM building footprints. It then evaluates the quality of OSM building data from 2018 and 2023 for five cities within Québec, Canada. The analysis reveals a significant quality improvement over time. In 2018, the completeness of OSM building footprints in the examined cities averaged around 5%, while by 2023, it had increased to approximately 35%. However, this improvement was not evenly distributed. For example, Shawinigan saw its completeness surge from 2% to 99%. The study also finds that OSM contributors were more likely to digitize larger buildings before smaller ones. Positional accuracy saw enhancement, with the average error shrinking from 3.7 m in 2018 to 2.3 m in 2023. The average distance measure suggests a modest increase in shape accuracy over the same period. Overall, while the quality of OSM building footprints has indeed improved, this study shows that the extent of the improvement varied significantly across different cities. Shawinigan experienced a substantial increase in data quality compared to its counterparts.

Fabrication of the curved Fresnel lens array on the spherical surface by 6-axis diamond ruling

The curved Fresnel lens array on the spherical surface owns exceptional optical performance and meets the growing demand for smart home and security alarm systems. However, the intricate three-dimensional microstructure of such optical component is typically considered impossible to be directly fabricated by diamond machining. In this paper, a novel 6-axis diamond ruling method is proposed to fabricate the complex optics utilizing a commercial 6-axis ultra-precision machine tool. The kinematic principle and tool path generation algorithm of this method are presented. A varying-angle sampling strategy is employed in the proposed algorithm to reduce the acceleration and following error in the rotation of the A-axis. Novel trial cutting processes are introduced to figure out the tool setting errors induced by visual inspection, which need to be compensated in the tool path. Based on the proposed tool path generation algorithm and cutting processes, this method enables the efficient processing of precise curved Fresnel lenses. There is no interference between the diamond tool and the curved microstructure in the 6-axis synchronized motions. Finally, the feasibility and superiority of this method are experimentally verified by analyzing the surface roughness and shape accuracy of the machined component. It can indeed generate high-quality curved Fresnel lenses on the spherical surface by the proposed 6-axis diamond ruling method.

Simulation and experimental research on the abrasive trajectories of plane lapping based on rotary swing drive

In the pursuit of achieving exceptional surface shape accuracy for MPCVD (Microwave Plasma Chemical Vapor Deposition) polycrystalline diamond wafers during the free abrasive lapping process, plane lapping based on rotary swing drive was employed in this study. The crux of this study lay in the development of a comprehensive kinematic model, scrutinizing the motion behavior of abrasive particles, and probing the influence of parameters on the uniformity of abrasive trajectories. The results show that the eccentricity, arc chord length and speed ratio affect the probability of track coincidence rate, and then affect the distribution uniformity. And then the verification experiments solidifying the reliability of our kinematic model and affirming the veracity of simulation results. The best surface shape accuracy ( PV) of the MPCVD polycrystalline diamond wafer was 2.3 μm under optimal parameters, representing a substantial advancement compared to the original lapping method, which only yielded a PV value of 8.4 μm. This study provides a promising method for high surface shape accuracy of MPCVD polycrystalline diamond wafers with large sizes.

Instance Segmentation Model for Accurate Linear Object Shape Prediction

Instance Segmentation Model for Accurate Linear Object Shape Prediction

Design and frequency control study of small-sized magnetorheological finishing device applied in optical manufacturing

With the continuous development of various advanced optical systems, there is an increasing demand for optical components with small apertures (generally ranging from a few millimeters to tens of millimeters in diameter), steep slopes, or even specific relief structures on their surfaces (such as continuous phase elements). These optical components all require high surface quality and shape accuracy. However, existing magnetorheological finishing (MRF) devices have larger dimensions, and the obtained removal function size is relatively larger than the size of small-diameter optical components, making it difficult to achieve high surface shape accuracy after processing. To achieve high-precision machining of small-aperture optical components and obtain higher frequency control capabilities, this study first designed and optimized a small-size MRF device with a 13 mm polishing wheel. Based on theoretical and finite element simulation analyses, the magnetic pole structure of the small-size MRF device was designed. The orthogonal experimental method was used to optimize the key parameters of the magnetic pole according to the magnetic field design requirements, and the device was constructed. Its performance and stability were experimentally analyzed, and the results showed that the peak magnetic field intensity in the polishing area of the device was about 230mT, which met the polishing requirements, and both its long-term and short-term processing stabilities met the design requirements. In addition, different sizes of removal functions were analyzed for frequency control ability, and theoretical and spectral analyses of the removal function indicated that the small-size removal function had better low-frequency error correction ability, while for mid-frequency band and mid-frequency ripple error, the opposite was true. The experimental results showed that when the optical component was shaped by 20 %, the low-frequency convergence capability of the 100 mm polishing device was only 18.72 %, much lower than that of the 13 mm polishing device, which was 52.51 %.Moreover, the mid-frequency ripple spectrum amplitude for the 13 mm polishing device was more than 15 times higher than that for the 100 mm polishing device when removing 50 nm material, and the mid-frequency root mean square (RMS) increased significantly, deteriorating the surface mid-frequency error of the optical component. Therefore, when performing magnetorheological polishing on an optical component surface, a process of using large-size MRF devices for roughing combined with small-size MRF devices for finishing can ensure machining efficiency while controlling low-frequency and mid-frequency errors well. This study provides theoretical support for the magnetic pole design of MRF devices and broadens the frequency spectrum correction ability and application range of MRF processes, which has great application value.

Learning Canonical Embeddings for Unsupervised Shape Correspondence With Locally Linear Transformations.

We present a new approach to unsupervised shape correspondence learning between pairs of point clouds. We make the first attempt to adapt the classical locally linear embedding algorithm (LLE)-originally designed for nonlinear dimensionality reduction-for shape correspondence. The key idea is to find dense correspondences between shapes by first obtaining high-dimensional neighborhood-preserving embeddings of low-dimensional point clouds and subsequently aligning the source and target embeddings using locally linear transformations. We demonstrate that learning the embedding using a new LLE-inspired point cloud reconstruction objective results in accurate shape correspondences. More specifically, the approach comprises an end-to-end learnable framework of extracting high-dimensional neighborhood-preserving embeddings, estimating locally linear transformations in the embedding space, and reconstructing shapes via divergence measure-based alignment of probability density functions built over reconstructed and target shapes. Our approach enforces embeddings of shapes in correspondence to lie in the same universal/canonical embedding space, which eventually helps regularize the learning process and leads to a simple nearest neighbors approach between shape embeddings for finding reliable correspondences. Comprehensive experiments show that the new method makes noticeable improvements over state-of-the-art approaches on standard shape correspondence benchmark datasets covering both human and nonhuman shapes.

Attention combined pyramid vision transformer for polyp segmentation

Colorectal cancer (CRC) has become one of the most frequent cancers in the world. To prevent CRC, proper polyp localization in endoscopy images plays a vital role for detecting and removing colorectal polyps. Most polyp segmentation methods use convolutional neural networks (CNN) as their backbone, and have achieved promising results to effectively assist clinicians in their diagnosis. However, those CNN-based approaches have limitations in modeling accurate location and shape of polyps, due to the intrinsic locality property of convolutional operations. To address these limitations, this study proposes a novel network, namely Att-PVT, that combines CNN and Pyramid Vision Transformer (PVT) together for poly segmentation. The main challenge lies in maintaining long-range semantic information without sacrificing low-level features. Att-PVT applies multidimensional information extraction (MIE) to generate refined feature maps extracted from PVT for better feature representation. Cascaded context integration (CCI) is designed to adaptively aggregating the three highest layers of refined polyp features for learning semantic and location information. To accurately segment colorectal polyps, Att-PVT introduces multilevel feature fusion (MFF) module that explores the boundary information in the shallower layer based on the global map. The proposed workflow has undergone comparative experiments on three public datasets, namely Kvasir, ColonDB, and ETIS. The results show that the proposed approach achieves impressive mDice scores of 0.926, 0.817, and 0.794 for polyp segmentation tasks on these datasets, surpassing other state-of-the-art methods. This indicates the superior generalization and scalability of the proposed approach.

Impact dynamic response of large aperture space deployable antenna supporting structures based on a dual-scale model

This study investigates the joint damage patterns and changes in shape accuracy of large aperture space deployable antenna supporting structures subject to hypervelocity impacts from micro space debris. Based on the dual-scale method, a joint scale model is constructed for a hexagonal prismatic space deployable truss antenna supporting structure with an aperture of six meters and 37 modules. ANSYS/AUTODYN is used for the impact damage analysis, with an equivalent model of impact force integrating the structure's actual damage characteristics in the structure scale model. The dynamic response and deformation performance of the antenna supporting structure under impact velocities from 2.5 to 15.0 km/s, with spherical space debris of 2.5 mm and 5.0 mm diameters, impacting modular central points in both positive and negative directions, are analyzed. The results show that the primary damage to the joint scale model after impact includes cratering, perforation, punch failure, and joint failure. The debris diameter significantly influences joint damage and deformation of the bolt hole diameter. Additionally, the debris cloud post-impact significantly affects the vertical bar's inner wall, spalling the wall and reducing the rod's strength. As the impact point moves towards the structure's centroid, the antenna's overall response increases. With higher impact velocities, the antenna supporting structure's overall deformation first increases, then decreases. At an impact velocity of 12.5 km/s, the impact area of the structure gradually reduces post-impact. Our proposed joint damage forms and three-case damage classification (no effect, repairable, and joint failure) may serve as a valuable reference for designing structural protection and impact identification for space deployable antennas.

A psychometric evaluation of the NIH Toolbox fluid cognition tests adapted for Swahili and Dholuo languages in Kenyan children and adolescents.

Our objective was to evaluate the psychometric properties of the culturally adapted NIH Toolbox African Languages® when used in Swahili and Dholuo-speaking children in western Kenya. Swahili-speaking participants were recruited from Eldoret and Dholuo-speaking participants from Ajigo; all were <14 years of age and enrolled in primary school. Participants completed a demographics questionnaire and five fluid cognition tests of the NIH Toolbox® African Languages program, including Flanker, Dimensional Change Card Sort (DCCS), Picture Sequence Memory, Pattern Comparison, and List Sorting tests. Statistical analyses examined aspects of reliability, including internal consistency (in both languages) and test-retest reliability (in Dholuo only). Participants included 479 children (n = 239, Swahili-speaking; n = 240, Dholuo-speaking). Generally, the tests had acceptable psychometric properties for research use within Swahili- and Dholuo-speaking populations (mean age = 10.5; SD = 2.3). Issues related to shape identification and accuracy over speed limited the utility of DCCS for many participants, with approximately 25% of children unable to match based on shape. These cultural differences affected outcomes of reliability testing among the Dholuo-speaking cohort, where accuracy improved across all five tests, including speed. There is preliminary evidence that the NIH Toolbox ® African Languages potentially offers a valid assessment of development and performance using tests of fluid cognition in Swahili and Dholuo among research settings. With piloting underway across other diverse settings, future research should gather additional evidence on the clinical utility and acceptability of these tests, specifically through the establishment of norming data among Kenyan regions and evaluating these psychometric properties.

Dimensional Deviations of Horizontal Thin Wall of Titanium Alloy Ti6Al4V Determined by Optical and Contact Methods

Thin-walled structures are used in many industries. The need to use such elements is dictated by the desire to reduce the weight of the finished product, as well as to reduce its cost. The most common method of machining such elements is the use of milling, which makes it possible to make a product of almost any shape. However, several undesirable phenomena occur during the milling of thin-walled structures. The main phenomenon is a deformation of the thin wall resulting from its reduced stiffness. Therefore, it is necessary to control the dimensional and shape accuracy of finished products, which is carried out using various measuring instruments. The development of newer measuring methods such as optical methods is being observed. One of the newer measuring machines is the 3D optical scanner. In the present experiment, thin-walled samples in horizontal orientation of Ti6Al4V titanium alloy were machined under controlled cutting conditions. During machining, the cutting speed and feed rate were assumed constant, while the input factors were the tool and cutting strategy. This paper presents graphs of deviations in the determined cross-section planes of thin-walled structures using a 3D optical scanner and a coordinate measuring machine. A correlation was made between the results obtained from the measurement by the optical method and those determined by the contact method. A maximum discrepancy of about 8% was observed between the methods used.

Adaptive Tikhonov regularization and dynamic control points for accurate shape parameter control of plasmas

Precise control of plasma shape parameters, such as elongation and triangularity is duly needed to achieve high-performance tokamak plasmas, for which we propose adaptive search schemes of (1) optimum regularization parameter for the Tikhonov regularization, and (2) control points to specify the key shape parameters such as elongation and triangularity. Many control points that exceed the number of actuator coils become an ill-conditioned problem, which is successfully resolved by Tikhonov regularization with adaptively optimized free parameters. Furthermore, we develop dynamically changed control points by using the Cauchy Condition Surface scheme, where elongation and triangularity become direct control values. By virtue of both the adaptive Tikhonov regularization scheme and the dynamic control point, we achieved accurate shape control with elongation up to 1.93 and triangularity up to 0.65 in JT-60SA, where the allowable speed for the change of the elongation is 0.1 s−1. We also verified the resilience of our developed our logics to the noises. The sequence of the result will contribute to enhance equilibrium controllability in upcoming JT-60SA experiments and provide the robust shape parameter control scheme for ITER and DEMO.

Features of processes of high-speed milling with a complex profile tool in the processing of aluminum alloys and composite materials

Complex computational and experimental studies substantiate rational modes of milling of complex contour equiaxed surfaces with high accuracy of shape, dimensions and roughness parameters. Bars made of nanostructured carbide composite (produced by extrusion of WC-Co-Al2O3 bimodal powder mixtures) with increased strength, crack resistance and heat resistance were used as a workpiece material for the manufacture of new original tool designs. The combination of these properties is a necessary prerequisite for the effective operation of the developed designs of multi-blade cutters at high cutting speeds and under conditions of variable cyclic loads. A more complex kinematics of the joint rotational movement of the tool during milling dictates the need for new approaches when assigning rational cutting modes. To obtain reliable calculation formulas, numerical experiments were previously carried out, including simulation of the processing process using the VisualStudio integrated development environment, which supports WindowsForms technology. The ability to display graphical 3D objects was implemented using an additional software product in the form of the Open CASCADE geometric core. Numerical experiments using MathCAD software products and based on the analytical provisions proposed in the work made it possible to evaluate the influence of cutting conditions, geometric parameters of the cutting part of the tool (profile and number of teeth), kinematics of relative movement in the “tool – part” system on the shape of surfaces and contour parameters (roughness obtained during milling. A technique, algorithm and program for the automated calculation of cutting conditions has been developed, which has been verified during full-scale experiments and the manufacture of complex profile parts from aluminum alloys for drives of aerospace products (in the form of a RC profile and parts of a pinion transmission of guidance mechanisms). At the same time, on the basis of a 3D model of products, control programs for CNC machines were created using MasterCAM. The practical significance and technical and economic efficiency of the proposed design and technological solutions is to increase productivity and reduce the complexity of processing (in comparison with the basic options) through the use of new multi-edge carbide tools for high-speed milling (including when processing composite materials).

High-quality 3D shape recovery from scattering scenario via deep polarization neural networks

High-quality three-dimension(3D) shape recovery from scattering scenario is of great importance with various potential applications. However, in turbid water scenarios, the absorption and scattering by water and suspending particles have a great disturbance on the generation of image clarity, texture details, and pixel-wise polarized properties such as degree of polarization (DoP) and angle of polarization (AoP), which significantly affect the 3D reconstructed performance. In this study, we present a data-driven polarimetric method for 3D reconstruction of underwater objects in turbid scenes, leveraging deep learning image priors. An underwater descattering network is designed to fit the underwater transport function of target signal light and generate clear underwater images, which are utilized to enhance the texture and remove the backscattering light. Subsequently, accurate pixel-wise DoP and AoP of the object could be calculated using the clear image prior and underwater imaging model. Finally, utilizing the obtained clear image and polarimetric information, polarimetric 3D reconstruction of object in turbid underwater scenarios is achieved. Experimental results demonstrate that accurate 3D shape of objects in turbid water can be well-reconstructed. The proposed technique has great potential for advancing marine exploration research.

Methodology for shape prediction and conversion of a conventional aerofoil to an inflatable baffled aerofoil

AbstractInflatable wings for UAVs are useful where storage space is a severe constraint. Literature in the field of inflatable wings often assumes an inflated aerofoil shape for various analyses. However, the flexible inflatable aerofoil fabric might deform to another equilibrium shape upon inflation. Hence accurate shape prediction of the inflated aerofoil is vital. Further, no standardised nomenclature or a process to convert a smooth aerofoil into its corresponding inflatable aerofoil counterpart is available. This paper analytically predicts the equilibrium shape of any inflatable aerofoil and validates the analytical prediction using non-linear finite element methods. Further, a scheme for the generation of two types of inflatable aerofoils is presented. Parameters such as the number and position of compartments and aerofoil length ratio (ALR) are identified as necessary to define the aerofoil’s shape fully. A process to minimise the deviation of the inflatable aerofoil from its original smooth aerofoil using particle swarm optimisation (PSO) is discussed. Research presented in this paper can help in performing various analyses on the actual equilibrium shape of the aerofoil.

Investigation of 3D printing of children starch gummies with precise and special shape based on change of model parameters

The practicability of using corn starch and erythritol as initial printing inks for manufacture to children printed products (with high accuracy and special shape) with addition of gelan gum (GG) was investigated. Materials properties and model parameters were applied to improve the printability and printing accuracy of special shape. The results showed that compared with the control group, all materials with hydrophilic colloid additions showed higher hardness, viscosity, rigidity and self-supporting ability. The results had shown that materials with higher GG additions possessed higher obvious viscosity and hardness, while printing inks with 1.5% GG concentration displayed best printing performance. Hydrophilic colloid additions attenuated the syneresis of samples. 3D printed objects using Ink-D (printing ink with GG addition of 1.5%) shown high printing precision with great self-supporting performance and smooth surface texture. Printing experiments revealed that model parameters (such as height and wall thickness) could significantly influence the printing precision and success rate of model with special shape.

An improved algorithm for thermal compensation of synchrotron radiation optical mirrors based on Hessian matrix

The heaters-based thermal-compensated adaptive adjustment of a reflection mirror at Shanghai high repetition rate X-ray Free-Electron Laser and extreme light facility (SHINE) is presented here based on finite element analysis. The correction performance of different control algorithms [singular value decomposition and gradient descent (GD)] is analyzed and compared. This study has demonstrated that a significant control algorithm can further improve the surface shape accuracy of the mirror. After optimizing the mirror control algorithm, the calculated slope errors and height errors of the mirror are reduced to nearly less than 50 nrad rms and 0.5 nm rms, respectively. The optimization result indicates that the GD control algorithm based on the Hessian matrix exhibits superior performance and practicality compared to the control algorithm before optimization.

VTO Model Tester with MindAR Library

Augmented Reality is not a new technology, with more than 30 years of age, AR, which used to require large resources, can now even be run using a website application. The advantage of using a website is that the website application can be run on almost any device that supports a web browser. Web AR can also be used as a trial tool that can be used by customers to try on clothes or other products which is also known as VTO or Virtual Try On. The problem that arises from VTO Application is from the 3D designer side, which must make 3D Object and always readjust if the 3D is not suitable for VTO that requires accuracy of shape and size, that must be adjusted between 3D objects and human faces. The focus of this research is creating a website application that can connect to the internet so that 3D designers can easily access the VTO tester from any device to test 3D objects that have been created for Virtual Try On. The result of this research is that we can use local storage as a temporary storage medium and proof that local storage cannot also be used to store documents but also to store 3D objects. By immediately deleting temporary storage in local storage, the storage quota will not increase so that our local storage drives are not affected, the memory usage of only 10MB is also an advantage of this VTO Tester application, because it does not require a large memory to run the VTO Tester. In terms of memory usage, there is no memory leak that results when using VTO Tester application, this proves that the application developed can be used repeatedly without worrying about burdened computer performance.

The Research For Quickly Measuring The Diameter And Roundness Of Solder Balls Based On Machine Vision Technology

Abstract Solder balls used in electronic packaging should have high dimensional and shape accuracy requirements to ensure the connection quality of solder balls during soldering. However, the existing solder ball detection methods were hard to measure the diameter and roundness in an integrated and fast manner. Therefore, a new method and device for measuring the diameter and roundness of solder balls was proposed based on machine vision technology, including detection device and software design. The experimental device could detect the parameters of at least 40 solder balls at a time. The solder ball image was preprocessed in the software system to improve the quality of the solder ball image, and then the Harris operator successfully detected the concave point on the bonded solder ball image and realized the solder ball separation based on the shortest path matching criterion. Compared with the SEM measurement value, the diameter and roundness of solder balls measured by the detection system were smaller than 3%.

Correction to: Investigating the Accuracy of Specimen Shape for Point Load Index Test in Predicting the Uniaxial Compressive Strength for Rocks Using Regression Analysis and Machine Learning

Correction to: Investigating the Accuracy of Specimen Shape for Point Load Index Test in Predicting the Uniaxial Compressive Strength for Rocks Using Regression Analysis and Machine Learning