Coordinates Of Points Research Articles

METHOD TRANSFORMATION OF COORDINATES FROM THE ARCHIVE SYSTEM (VARASH-42) TO THE CURRENT SYSTEM (LCS-56) USING QGIS

This article proposes a technique for transforming coordinates from an archival coordinate system into an active one using affine transformation using the finite element method in the QGIS geoinformation environment using a transformation field in the NTv2 format. The purpose of the work is to develop a method of transforming coordinates from the archival system into the one operating in Ukraine using the GRID model of the transformation field in the form of NTv2 format and QGIS software using the example of the Varash-42 coordinate system, derived from CS-42, and LCS-56, derived from UCS-2000. To implement the technique, a scheme for transforming point coordinates is defined. The technique of integrating the transformation field into the QGIS geoinformation environment was researched and implemented. The authors investigated the transformation of coordinates on the territory of the city of Varash, Rivne region, and determined the accuracy of the obtained results, which is within the limits of tolerance. According to the results of the study, it was established that the average squared error of a unit of weight is 0.024 m. Since the control coordinates were obtained with an accuracy within tolerance – up to 0.05 m; it was concluded that the coordinates obtained with the help of the NTv2 local transformation field for the territory of Varash are suitable for their further use. The developed technique makes it possible to transform coordinates from archival coordinate systems derived from UCS-2000 to use processed geospatial data in topography-geodetic, cartographic, land management, land surveying and other spheres of activity, as well as to ensure compliance with one of the requirements for compatibility and interoperability of geospatial data: a coordinate system in which coordinate descriptions of geospatial objects are provided.

Метод определения эффективности вариантов организации перевозок барже-буксирными составами

A study has been conducted on the method of evaluating options for organizing cargo transportation by barge-tow trains based on determining their effectiveness. Using the methods of the classical theory of transport processes, this problem has no quantitative solution, since it is not possible to take into account the regrouping of the composition during the passage of the route. To overcome this problem, additional mathematical tools have been developed for constructing integral time and velocity matrices, an objective function and graphs of the ratios of the total volume of transported cargo to the time it was en route. The consistent implementation of the proposed tools ensures the coherence of the calculation methods for determining the effectiveness of a flight with and without regrouping on the route, and also makes it possible to select the most appropriate option for organizing transportation. The cumulative result allows us to reflect the method of evaluation, comparison and selection of the most effective option for organizing a flight / group of flights, taking into account the ability to set individual parameters for the movement of the train and cargo. An example of approximation of the coordinate points of the route from the Nizhne-Svirsky shipping lock to Lake Ladoga is illustrated, as well as an example of discretization of an inland waterway section according to a three-level model. The parameters of equalization of the objective function of determining the efficiency of cargo transportation are considered. It is concluded that the optimal transportation option can be carried out on the basis of a combined approach, when several parameters are taken into account or sequentially set in the process of modeling the operation of ships. Graphs have been built that demonstrate the differences between the ways of organizing flights.

Online Signature Biometrics for Mobile Devices.

This paper addresses issues concerning biometric authentication based on handwritten signatures. Our research aimed to check whether a handwritten signature acquired with a mobile device can effectively verify a user's identity. We present a novel online signature verification method using coordinates of points and pressure values at each point collected with a mobile device. Convolutional neural networks are used for signature verification. In this paper, three neural network models are investigated, i.e., two self-made light SigNet and SigNetExt models and the VGG-16 model commonly used in image processing. The convolutional neural networks aim to determine whether the acquired signature sample matches the class declared by the signer. Thus, the scenario of closed set verification is performed. The effectiveness of our method was tested on signatures acquired with mobile phones. We used the subset of the multimodal database, MobiBits, that was captured using a custom-made application and consists of samples acquired from 53 people of diverse ages. The experimental results on accurate data demonstrate that developed architectures of deep neural networks can be successfully used for online handwritten signature verification. We achieved an equal error rate (EER) of 0.63% for random forgeries and 6.66% for skilled forgeries.

Research on AGV Global Positioning Algorithm Based on Reflector and Lidar

In order to improve the accuracy, stability, and robustness of AGV positioning with the use of the Cartographer algorithm, this paper proposes a global positioning algorithm strategy that integrates the reflector coordinate points as reference points for the trilateral positioning algorithm with the cartographer. Firstly, the shortcomings of existing cartographers in pure positioning were introduced. Then, two commonly used positioning algorithms were elaborated, and they were fused using reflective plates and cartographer algorithms. Static and dynamic experiments were conducted in real environments. The two experiments verified that the trilateral positioning algorithm has smaller errors, stronger stability, and better accuracy than the triangular positioning algorithm.

Measurement of the Angle between stems and leaves of rice based on key point detection

Stem-leaf angle is an important phenotypic parameter of rice, which is crucial for the growth and development of rice plants and scientific breeding. However, the traditional method is inefficient and subjective. In order to quickly and accurately calculate the stem-leaf pinch angle of rice, this paper proposes a key point-based stem-leaf pinch angle detection method. Experimentally, four periods of rice (Jointing stage, Booting stage, Heading stage and Mature stage) are selected as research objects, image data are collected, key points are extracted by YOLOv7-pose network model, and a lightweight convolution method GSConv is introduced, which is able to reduce the complexity of the model and improve the accuracy of the key point detection, the average accuracy of key point detection was improved from 93.7% to 98.7%, an improvement of 5%. Finally, the angular size of the pinch angle was determined based on the coordinates of the key points located by the model, and the R2 of the pinch angle calculation results to the actual manual measurements was the highest of 0.84, the errors for the four periods were 1.543°, 1.716°, 1.213°, and 0.998°. So the method ensures the accuracy of identification while the model size is reduced, and can effectively measure the angle of rice stem and leaf pinch, and the investigated method can better help farmers to understand the growth and development of plants and provide support for the selection of excellent crop traits.

Banana Bunch Weight Estimation and Stalk Central Point Localization in Banana Orchards Based on RGB-D Images

Precise detection and localization are prerequisites for intelligent harvesting, while fruit size and weight estimation are key to intelligent orchard management. In commercial banana orchards, it is necessary to manage the growth and weight of banana bunches so that they can be harvested in time and prepared for transportation according to their different maturity levels. In this study, in order to reduce management costs and labor dependence, and obtain non-destructive weight estimation, we propose a method for localizing and estimating banana bunches using RGB-D images. First, the color image is detected through the YOLO-Banana neural network to obtain two-dimensional information about the banana bunches and stalks. Then, the three-dimensional coordinates of the central point of the banana stalk are calculated according to the depth information, and the banana bunch size is obtained based on the depth information of the central point. Finally, the effective pixel ratio of the banana bunch is presented, and the banana bunch weight estimation model is statistically analyzed. Thus, the weight estimation of the banana bunch is obtained through the bunch size and the effective pixel ratio. The R2 value between the estimated weight and the actual measured value is 0.8947, the RMSE is 1.4102 kg, and the average localization error of the central point of the banana stalk is 22.875 mm. The results show that the proposed method can provide bunch size and weight estimation for the intelligent management of banana orchards, along with localization information for banana-harvesting robots.

Neural Network-Based Modeling of Diffusion-Induced Stress in a Hollow Cylindrical Nano-Electrode of Lithium-Ion Battery

Abstract Understanding the interaction between mechanical deformation and mass transport, such as diffusion-induced stress, is crucial in the development of advanced battery materials and electrochemical devices. Mathematical modeling and solving the coupling problems have played important roles in advancing the understanding of the interaction between mechanical deformation and mass transport. As the complexity of mathematical modeling continues to increase, numerical methods used to solve the related coupling problems are likely to encounter significant challenges. This work explores the feasibility of designing a neural network specifically for solving diffusion-induced stress in the electrode of lithium-ion battery via deep learning techniques. A loss function is constructed from the spatiotemporal coordinates of sampling points within the solution domain, the overall structure of the system of partial differential equations, boundary conditions, and initial conditions. The distributions of stress and lithium concentration in a hollow-cylindrical nanoelectrode are obtained. The high degree of conformity between the numerical results and those from finite element method is demonstrated.

Comparison of craniomaxillofacial morphology in children with unilateral cleft lip and palate treated with/without presurgical nasoalveolar molding - a retrospective study with a mean age of 5 years.

To three-dimensionally assess differences in craniomaxillofacial skeletal development in patients with operated unilateral cleft lip and palate (UCLP) treated with/without presurgical nasoalveolar molding (PNAM) with a mean age of 5 years. Cone-beam CT radiographs of 30 patients with UCLP who had undergone PNAM and 34 patients with UCLP who did not receive PNAM were analyzed. The data were stored in DICOM file format and were imported into the Dolphin Imaging program for 3D image reconstruction and landmark identification. 33 landmarks, 17 linear and three angular variables representing craniofacial morphology were analyzed and compared by using the Mann-Whitney U tests. The vast majority of linear variables and 3D coordinates of landmark points reflecting craniofacial skeletal symmetry were not significantly different between the two groups. In terms of craniofacial skeletal development, the PNAM group had a significantly smaller anterior nasal spine offset in the midsagittal plane and a greater maxillary length compared to the non-PNAM group. Evaluations performed in early childhood showed that treatment with/without PNAM in the neonatal period was not a major factor influencing craniomaxillofacial hard tissue development in patients with UCLP; moreover, PNAM treatment showed significant correction of skeletal deviation at the base of the nose. Follow-up in early childhood has shown that PNAM treatment administered during the neonatal stage does not impede maxillary development and has benefits in correcting nasal floor deviation. It is a viable option for improving nasal deformity in children with unilateral cleft lip and palate.

On the equilibrium points of the collinear restricted 4-body problem with non-spherical bodies

This study investigates a variation of the collinear restricted four-body problem, introducing complexity by incorporating the oblate or prolate shapes of the three primary bodies. Employing various numerical techniques, we analyze the dynamical properties of the equilibrium points within the system. In addition to identifying the coordinates of the libration points, we examine their linear stability and dynamic classifications. Our primary focus is on understanding the interplay between the system’s mass and shape parameters, revealing how they collectively influence equilibrium dynamics. Specifically, our results demonstrate that oblate-shaped peripheral bodies consistently produce six (6) equilibrium points, while prolate spheroids yield an even number – 6, 10, 14, or 18 – depending on the specific mass and shape parameters.

An Image-Based Interactive Training Method of an Upper Limb Rehabilitation Robot

Aimed at the problem of human–machine interaction between patients and robots in the process of using rehabilitation robots for rehabilitation training, this paper proposes a human–machine interactive control method based on an independently developed upper limb rehabilitation robot. In this method, the camera is used as a sensor, the human skeleton model is used to analyse the moving image, and the key points of the human body are extracted. Then, the three-dimensional coordinates of the key points of the human arm are extracted by depth estimation and spatial geometry, and then the real-time motion data are obtained, and the control instructions of the robot are generated from it to realise the real-time interactive control of the robot. This method can not only improve the adaptability of the system to individual patient differences, but also improve the robustness of the system, which is less affected by environmental changes. The experimental results show that this method can realise real-time control of the rehabilitation robot, and that the robot assists the patient to complete the action with high accuracy. The results show that this control method is effective and can be applied to the fields of robot control and robot-assisted rehabilitation training.

Accuracy of marine gravimetric measurements in terms of geodetic coordinates of land reference benchmark

The article presents how the values of (3D) coordinates of land reference points affect the results of gravimetric measurements made from the ship in sea areas. These measurements are the basis for 3D maritime inertial navigation, improving ships' operational safety. The campaign verifying the network absolute point coordinates used as a reference point for relative marine gravity measurements was described. The obtained values were compared with catalogue values. In verification of network points 3D position the satellite data Global Satellite Navigation System (GNSS) and ground supporting systems (GBAS) was used. In this example, the height difference of the land reference point was 0.32 m. As a consequence, the offset budget of the marine campaign was affected in the range of up to 0.35 mGal. The influence on gravity free-air anomaly was not constant over the entire area covered by the campaign.

Large Deflection Analysis of Functionally Graded Beam by Using Combining Method

In this study, the large deflection behavior of a circular cross-section beam is examined using the Combining Method (CM). The CM is a numerical solution method that uses block diagrams in the Matlab-Simulink program and weighting coefficients in the Differential Quadrature Method (DQM). The beam material considered is Functionally Graded Material (FGM). Boundary conditions of the beam are taken as clamped-free (C-F) and a singular load is assumed to be applied from the free end of the beam. Geometric nonlinear analysis is performed while calculating the large deflection equations of the beam and performing numerical analysis. The effects of increasing the force applied to the beam, changing the beam cross-section in the longitudinal direction, and changing the material index of the FGM on the extreme deflection behavior of the beam were examined. For comparison purposes, the results obtained from CM are compared with the results obtained from both SolidWorks-Simulation and Ansys-Workbench programs. As a result of the analysis, increasing the applied force causes the x and y coordinates of the end point of the beam to decrease. The change in geometry and material index greatly affects the large deflection occurring in the beam.

Impact of inter-lesion distance and first-pass isolation on outcomes of pulmonary venous isolation for paroxysmal atrial fibrillation.

Contiguity of ablation lesions is a critical determinant of success for paroxysmal atrial fibrillation (PAF) ablation. Evidence supports maintaining an inter-lesional distance (ILD) ≤ 6mm during pulmonary venous isolation (PVI). Meanwhile, first-pass isolation (FPI) on PVI outcome in follow-up was not deeply studied. The impact of ILD and FPI on PAF ablation outcomes was investigated. Consecutive PAF patients who underwent first-time antral PVI were recruited. Coordinates of ablation points were extracted from the electro-anatomical mapping system and analyzed using custom-developed software to determine the ILD. A gap is defined as ILD greater than 6mm. FPI was defined as the achievement of PVI by encircling the ipsilateral veins while simultaneously recording their electrical activity using a multipolar catheter. The primary endpoint was freedom from documented atrial arrhythmias including AF, atrial tachycardia (AT), or atrial flutter (AFL) lasting longer than 30s during follow-up. A total of 105 patients underwent first-time antral PVI. During 13.3 ± 0.6months of follow-up, atrial arrhythmias recurrence was noted in 22.9% of the patients. Atrial arrhythmia recurrence was significantly higher in patients with more gaps (> 2) (37.0% versus 11.9%, P < 0.01), and the number of gaps was an independent predictor of AF/AT/AFL recurrence. (Hazard ratio [HR] 1.20, 95% CI 1.03-1.40, P = 0.02). The group with FPI for at least one ipsilateral pair of PVs exhibited a decreased number of gaps (2.0 versus 7.0, P < 0.01) and demonstrated a significant correlation with a reduction of recurrence (HR 0.26, 95% CI 0.09-0.71, P = 0.01). Among 16 patients who underwent repeat ablation, the number of gaps during the index PVI was associated with PV reconnection (PVR) (P < 0.01). Gaps created during PVI are a modifiable determinant of AF/AT/AFL recurrence, and avoidance of gaps is crucial to improve clinical outcomes of PAF ablation. In addition, FPI exhibited a strong predictive capability for clinical success in patients with PAF.

Composite convolution: A flexible operator for deep learning on 3D point clouds

Deep neural networks require specific layers to process point clouds, as the scattered and irregular location of 3D points prevents the use of conventional convolutional filters. We introduce the composite layer, a flexible and general alternative to the existing convolutional operators that process 3D point clouds. We design our composite layer to extract and compress the spatial information from the 3D coordinates of points and then combine this with the feature vectors. Compared to mainstream point-convolutional layers such as ConvPoint and KPConv, our composite layer guarantees greater flexibility in network design and provides an additional form of regularization. To demonstrate the generality of our composite layers, we define both a convolutional composite layer and an aggregate version that combines spatial information and features in a nonlinear manner, and we use these layers to implement CompositeNets. Our experiments on synthetic and real-world datasets show that, in both classification, segmentation, and anomaly detection, our CompositeNets outperform ConvPoint, which uses the same sequential architecture, and achieve similar results as KPConv, which has a deeper, residual architecture. Moreover, our CompositeNets achieve state-of-the-art performance in anomaly detection on point clouds. Our code is publicly available at https://github.com/sirolf-otrebla/CompositeNet.

Morphogenesis of free-form surface structures based on geometrically nonlinear isogeometric analysis

Free-form surface structures have taken the forefront in space structure research owing to their free and flexible expressiveness and aesthetic visual effects. Yet, their irregular shapes and large span of the initial structure often lead to the problem of large displacement, necessitating the incorporation of geometric nonlinearity in the analysis. In this paper, we employ structural optimization design principles to investigate the morphogenesis of free-form surface structures while considering their geometric nonlinearity. Particularly, we explore both single-objective and double-objective shape optimization of free-form surface structures by employing structural strain energy and the first natural frequency as optimization indexes and the vertical coordinates of control points as optimization variables. The effectiveness of the proposed method is finally verified by several examples.

Usage of a Conventional Device with LiDAR Implementation for Mesh Model Creation

The trend of using conventional devices like mobile phones, tablets, and the other devices is gaining traction in improving customer service practices. This coincides with the growing popularity of building information modeling (BIM), which has led to increased exploration of various 3D object capture methods. Additionally, the technological boom has resulted in a surge of applications working with different 3D model formats including mesh models, point cloud, and TIN models. Among these, the usage of mesh models is experiencing particularly rapid growth. The main objective advantages of mesh models are their efficiency, scalability, flexibility, sense of detail, user-friendliness, and compatibility. The idea of this paper is to use a conventional device, specifically an iPad Pro equipped with light detection and ranging (LiDAR) technology, for creating mesh models. The different data capture methods employed by various applications will be compared to evaluate the final models´ precision. The accuracy of the 3D models generated by each application will be assessed by comparing the spatial coordinates of identical points distributed irregularly across the entire surface of the chosen object. Various available currently most-used applications were utilized in the process of data collection. In general, 3D representations of the object/area, etc., may be visualized, analyzed, and further processed in more formats such as TIN models, point cloud, or mesh models. Mesh models provide a visualization of the object mirroring the solid design of the real object, thus approximating reality in the closest way. This fact, along with automatized postprocessing after data acquisition, the ability to capture and visualize both convex and concave objects, and the possibility to use this type of 3D visualization for 3D printing, contribute to the decision to test and analyze mesh models. Consequently, the mesh models were created via the automatic post-processing, i.e., without external intervention. This fact leads to the problems of random coordinate systems being automatically pre-defined by every application. This research must deal with the resulting obstacles in order to provide a valid and credible comparative analysis. Various criteria may be applied to the mesh models’ comparisons, including objective qualitative and quantitative parameters and also the subjective ones. The idea of this research is not to analyze the data acquisition process in detail, but instead to assess the possibilities of the applications for the basic users.

Point Cloud Attacks in Graph Spectral Domain: When 3D Geometry Meets Graph Signal Processing.

With the increasing attention in various 3D safety-critical applications, point cloud learning models have been shown to be vulnerable to adversarial attacks. Although existing 3D attack methods achieve high success rates, they delve into the data space with point-wise perturbation, which may neglect the geometric characteristics. Instead, we propose point cloud attacks from a new perspective-the graph spectral domain attack, aiming to perturb graph transform coefficients in the spectral domain that correspond to varying certain geometric structures. Specifically, leveraging on graph signal processing, we first adaptively transform the coordinates of points onto the spectral domain via graph Fourier transform (GFT) for compact representation. Then, we analyze the influence of different spectral bands on the geometric structure, based on which we propose to perturb the GFT coefficients via a learnable graph spectral filter. Considering the low-frequency components mainly contribute to the rough shape of the 3D object, we further introduce a low-frequency constraint to limit perturbations within imperceptible high-frequency components. Finally, the adversarial point cloud is generated by transforming the perturbed spectral representation back to the data domain via the inverse GFT. Experimental results demonstrate the effectiveness of the proposed attack in terms of both the imperceptibility and attack success rates.

Treatment duration by morphology and location of impacted maxillary canines: A cone-beam computed tomography investigation

This study aimed to identify whether patients with impacted maxillary canines take longer to treat than orthodontic patients without an impacted canine. We also sought to identify factors that are predictive of increased treatment duration in patients with impacted maxillary canines and treated by surgical exposure. A retrospective investigation of 37 patients with an impacted maxillary canine, treated by surgical exposure and fixed appliance therapy, was undertaken. In addition, an age- and sex-matched control group of 39 patients (without impacted canines) was also collected. Patient age, sex, and total treatment duration were recorded. For patients with an impacted canine, patient records and pretreatment cone-beam computed tomography datasets were assessed. Point coordinates identifying relevant landmarks were recorded, and a geometric method was used to calculate variables describing canine location, orientation, and apical morphology. Controlling for age and sex, linear regression identified a statistically significant increase in treatment duration of 46.7 and 41.5 weeks for palatal and labial/midalveolar impacted canines, respectively, vs controls (P<0.002). Age and sex of patients with impacted canines collectively affected treatment duration (P= 0.04), with females of increased age being treated faster than younger males. Rotation of the impacted canine crown had a highly significant effect on treatment duration, with every degree of rotation increasing treatment duration by 0.32 weeks (P<0.001). There was a significant degree of multicollinearity between the other radiographic variables. Collectively, radiographic variables describing canine displacement significantly prolonged treatment duration (P<0.001) and explained 29.8% of the variability in total treatment time. The apical morphology of impacted maxillary canines was significantly associated with increased treatment duration (P= 0.01) and explained 11.3% of the overall treatment variability (P= 0.01). Increased total treatment duration of surgically exposed impacted maxillary canines is associated with increasing mesiopalatal canine crown rotation, worsening displacement, and hooked apical morphology.

Study on the motion characteristics of bedload sediment particles under different sediment transport intensities

AbstractBedload studies at the particle scale may help grasp the essence of the problem. Existing studies suffer from short filming durations, limited data volume, and a narrow range of sediment transport intensity variations. This paper employs the high‐speed photography technology and conducts experimental studies on bedload particle motion under 8 different sediment transport intensities. Using the latest image processing technology, over 6 million sediment particle coordinate points and nearly 400,000 particle motion trajectory curves were automatically obtained and used to compare the motion characteristics of bedload particles under different sediment transport intensities. The results show that under low sediment transport intensity, both the number of moving particles and particle motion velocity contribute to the bedload sediment transport rate, while under high‐intensity conditions, the transport rate mainly depends on the number of moving particles. The probability density distribution of sediment transport rate is concentrated and varies within a small range under low‐intensity conditions, exhibiting a tailing phenomenon. In contrast, under high‐intensity conditions, the range of sediment transport rate values increases, and the probability density curve tends to be symmetric, more closely approximating a normal distribution. Additionally, the paper compares the longitudinal and transverse motion velocities of particles and the coefficient of variation of the bedload sediment transport rate.

Establish an agricultural drought index that is independent of historical element probabilities

AbstractCurrently, there are three main shortcomings in meteorological drought indices: first, they rely on historical climate probability functions; second, the timescale used in calculations has a certain degree of subjectivity; third, the same index value may correspond to vastly different levels of actual drought in different climate types of regions. The purpose of this article is to establish a meteorological drought index that does not rely on historical meteorological element probability functions. Through theoretical derivation, four drought‐level maintenance lines are established on the cumulative precipitation‐cumulative water surface evaporation coordinate plane, and the coordinate quadrant is divided into five drought‐level areas. Through forward daily rolling accumulation, the maximum distance point is selected from the dynamically changing coordinate points to determine the corresponding cumulative precipitation and cumulative evaporation. The meteorological drought index is established by the distance from the selected coordinate point to each drought‐level maintenance line. Using daily precipitation and evaporation data from meteorological observation stations, the index is calculated based on the established meteorological drought index model, and compared with actual drought evolution and drought disaster records. The results show that the index can capture the development of drought well, and its changes are very consistent with drought disaster records. The index is of great significance for drought monitoring or assessment, and can provide guidance for water resource allocation, crop layout, and urban planning. Furthermore, it can also provide a way of thinking that does not rely on historical element probabilities for future drought research.