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Development of microwave components is an inherently multi-objective task. This is especially pertinent to the design closure stage, i.e., final adjustment of geometry and/or material parameters carried out to improve the electrical performance of the system. The design goals are often conflicting so that the improvement of one normally leads to a degradation of others. Compact microwave passives constitute a representative case: reduction of the circuit footprint area is detrimental to electrical figures of merit (e.g., the operating bandwidth). Identification of the best available trade-off designs requires multi-objective optimization (MO). This is a computationally expensive task, especially when executed at the level of full-wave electromagnetic (EM) simulation. The computational complexity issue can be mitigated through the employment of surrogate modeling methods, yet their application is limited by a typically high nonlinearity of system responses, and the curse of dimensionality. In this paper, a novel technique for fast MO of compact microwave components is proposed, which allows for sequential rendition of the trade-off designs using triangulation of the already available Pareto front as well as rapid refinement algorithms. Our methodology is purely deterministic; in particular, it does not rely on population-based nature-inspired procedures. The three major benefits are low computational cost, possibility of handling explicit design constraints, and a capability of producing a visually uniform representation of the Pareto front. The algorithm is demonstrated using a compact branch-line coupler and a three-section impedance matching transformer. In both cases, considerable savings are obtained over the benchmark, here, the state-of-the-art surrogate-assisted MO technique.

Safety in coastal areas such as beaches, ports, pontoons, etc., is a current problem with a difficult solution and on which many organizations are putting efforts in terms of technological innovation. In this work the design of a possible solution based on magnetic sensors is presented. First, a study has been made of the type of sensors that best suit the application based on parameters such as sensitivity, the allowed bandwidth of excitation, price or physical construction. Then the system of excitation of the sensors and signal measurement is presented. To justify the design, a series of simulations of magnetic field variations have been carried out in the presence of large objects of conductive material, in the vicinity of the measuring points. With these data a mathematical model has been established that allows the identification of the dimensions and position of the object through triangulation and knowing only the data of the magnetic field. It was found that although this method seems quite effective, it has a significant error, so another method based on neural networks was developed also using data from the simulations. This method seems to yield much better and more reliable results.

We propose a fast solution method for banded linear systems that transforms the original system into an equivalent one with an almost block triangular coefficient matrix, and then constructs a preconditioner based on this formulation. We analyze the algorithmic complexity of the new method and the eigenvalue distribution of the resulting preconditioned matrix. Numerical examples involving block tridiagonal, block Hessenberg and block pentadiagonal systems are illustrated to demonstrate the computational performance and the efficiency of the new matrix solver.

Folding a thin sheet material such as paper along curves creates a developable surface composed of ruled surface patches. When using such surfaces in design, designers often repeat a process of folding along curves drawn on a sheet and checking the folded shape. Although several methods for constructing such shapes on a computer have been proposed, it is still difficult to check the folded shapes instantly from the crease patterns. In this paper, we propose a simple method that approximately realizes a simulation of curved folds with a triangular mesh from its crease pattern. The proposed method first approximates curves in a crease pattern with polylines and then generates a triangular mesh. In order to construct the discretized developable surface, the edges in the mesh are rearranged so that they align with the estimated rulings. The proposed method is characterized by its simplicity and is implemented on an existing origami simulator that runs in a web browser.

A well-known problem with distance-based formation control is the existence of multiple equilibrium points not associated with the desired formation. This problem can be potentially mitigated by introducing an additional controlled variable. In this article, we generalize the distance + angle-based scheme for 2-D formations of single-integrator agents by using directed graphs and triangulation of the n-agent formation. We show that under certain conditions on the control gains and desired formation shape, our controller ensures the asymptotic stability of the correct formation for almost all initial agent positions.

Multi-view depth map reconstruction is a popular approach to generate 3D information with good flexibility and scalability. However, texture-weak regions and repeated textures challenge these methods in urban scenes. To address this need, this paper proposes an image-triangle based multi-view 3D reconstruction (IMGTR) method. Starting from constructing a density-adaptive image triangulation for each image, the main procedure is to determine the corresponding object plane for each image triangle under an objective function consisting of the image similarity measure, the smoothness constraint and the continuity constraint on the edges between adjacent triangles. Qualitative and quantitative experiments show that the proposed method can reconstruct complex urban structures more accurate and achieve higher fidelity in planar urban structures than some recently released multi-view stereo algorithms. Specifically, for the Vaihingen dataset IMGTR achieves an average improvement of 4.27% compared to PMVD, 50.94% to SURE and 54.76% to COLMAP in position accuracy.

We present an algorithm that enumerates all the minimal triangulations of a graph in incremental polynomial time. Consequently, we get an algorithm for enumerating all the proper tree decompositions, in incremental polynomial time, where “proper” means that the tree decomposition cannot be improved by removing or splitting a bag. The algorithm can incorporate any method for (ordinary, single result) triangulation or tree decomposition, and can serve as an anytime algorithm to improve such a method. We describe an extensive experimental study of an implementation on real data from different fields. Our experiments show that the algorithm improves upon central quality measures over the underlying tree decompositions, and is able to produce a large number of high-quality decompositions.

This study aims to determine the mathematical concepts applied to Javanese gamelan musical instruments. The type of research used in this research is qualitative research with an ethnographic approach, namely describing Javanese gamelan musical instruments as a medium for learning Mathematics. Data obtained through interviews, observation, and documentation. The instrument in this study consisted of the main instrument, namely the researcher himself and auxiliary instruments in the form of interview guidelines, observation sheets, and documentation tools. The data validity technique used is method triangulation and source triangulation. The results of this study indicate that there are mathematical concepts that are applied to Javanese gamelan musical instruments such as one-dimensional geometry, namely the concept of lines, parallel lines and right angles, two-dimensional geometry, namely square, rectangle, circle, trapezoid, and triangle. three in the form of a tube, a sphere, and a truncated cone. With the existence of mathematical concepts in Javanese gamelan musical instruments, it is very possible for mathematics learning media to be designed using Javanese gamelan ethnomathematics so that mathematics contributes to the preservation of the nation's culture.

We present Supervision by Registration and Triangulation (SRT), an unsupervised approach that utilizes unlabeled multi-view video to improve the accuracy and precision of landmark detectors. Being able to utilize unlabeled data enables our detectors to learn from massive amounts of unlabeled data freely available and not be limited by the quality and quantity of manual human annotations. To utilize unlabeled data, there are two key observations: (1) the detections of the same landmark in adjacent frames should be coherent with registration, i.e., optical flow. (2) the detections of the same landmark in multiple synchronized and geometrically calibrated views should correspond to a single 3D point, i.e., multi-view consistency. Registration and multi-view consistency are sources of supervision that do not require manual labeling, thus it can be leveraged to augment existing training data during detector training. End-to-end training is made possible by differentiable registration and 3D triangulation modules. Experiments with 11 datasets and a newly proposed metric to measure precision demonstrate accuracy and precision improvements in landmark detection on both images and video. Code is available at https://github.com/D-X-Y/landmark-detection., Comment: Accepted to IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2020

A graph is locally-connected if the neighborhood of each vertex induces a connected graph. It is well known that a triangulation on a closed surface is locally-connected, and some results for triangulations were generalized to those for connected locally-connected graphs. In this paper, we extend two characterization theorems of triangulations for a complete coloring and a facial complete coloring, which are vertex colorings with constraints on the appearance of color tuples, to those of connected locally-connected graphs. Moreover, we also investigate the relation between the corresponding invariants and the number of independent elements.

Triangulation is a fundamental module in vision based navigation system, which reconstructs the observed 3D point using cameras with known intrinsic and poses. In this article, we adopt the minimization of the angular residual as the criterion of triangulation and a novel structure of multiple-view triangulation is proposed. A multiple-view triangulation problem is divided into several two-view triangulation problems and a linear algorithm is derived to find the explicit closed form solutions of these two-view triangulation problems. Then, the Cramer–Rao lower bound (CRLB) is employed to calculate their covariances, according to which these solutions are fused to obtain the final result of the multiple-view triangulation. Our proposed algorithm is proved to be efficient based on the theoretical analysis, as it is linear and non-iterative. The simulations on both synthetic and real data show that the proposed algorithm can achieve competitive accuracy within less processing time, comparing with the most state-of-art algorithms.

This article places Claire Jean Kim’s racial triangulation theory in the context of Kim’s other writings from the late 1990s and early 2000s. I analyze Kim’s theory not as an analytical framework o...

In this work, we venture to show how careful use of a program for quantum chemical calculations (such as VASP) may enrich teaching in solid-state chemistry and how principles of thermodynamics contribute to a validation of phase diagrams and reaction pathways using the quasiternary system Li2O–Al2O3–SiO2 as an example. We show how to calculate formation and reaction energies, we discuss the stability of compounds with respect to their decomposition by introducing the convex hull principle, and we compare the relative stability of polymorphs as well. In a final sum-up, we treat the problem of triangulation in ternary phase diagrams. We show how such a practical course can refer to earlier preparatory courses on thermodynamics, crystallography, and quantum chemistry, and how the results of different tasks distributed among several groups of students can merge to an overall picture and help to solve many problems in understanding solid-state chemistry.

We consider a parametric family of quadratically constrained quadratic programs (QCQP) and their associated semidefinite programming (SDP) relaxations. Given a nominal value of the parameter at which the SDP relaxation is exact, we study conditions (and quantitative bounds) under which the relaxation will continue to be exact as the parameter moves in a neighborhood around the nominal value. Our framework captures a wide array of statistical estimation problems including tensor principal component analysis, rotation synchronization, orthogonal Procrustes, camera triangulation and resectioning, essential matrix estimation, system identification, and approximate GCD. Our results can also be used to analyze the stability of SOS relaxations of general polynomial optimization problems., 23 pages, 3 figures

The possibility of evaluating the energy spectra of precipitating electrons which form rayed auroral structures has been substantiated. The data of triangulation observations by equipment recording radiation in a wide range of wavelengths (380–580 nm) have been used. A technique for calculating the height profiles of deposition energy from the height profiles of the volume emission rate recorded by the receiving equipment. The energy spectra of precipitating electron fluxes responsible for the formation of rayed structures in auroras have been reconstructed. It is shown that the energy spectra of the precipitating electron flux can be approximated by the sum of two electron fluxes having a power-law energy spectrum and a Maxwellian energy distribution. It has been suggested that radiant structures in auroras are formed due to the discharge of electrons into the ionosphere, which have a power-law energy distribution.

Objectives This paper demonstrates how to investigate the external validity of a study sample by triangulating survey and registry data, using data from the Norwegian Offender Mental Health and Addiction (NorMA) Study as a case. Methods We use survey data from the NorMA study ( n = 1495), including the NorMA cohort ( n = 733), and data from the Norwegian Prison Registry on all people imprisoned on 1 September 2013 ( n = 3386). Triangulation was performed by (1) comparing the NorMA cohort to those lost to follow-up ( n = 762), using survey data from the NorMA study. Secondly, we compared the NorMA cohort to the one-day population, using data from the Norwegian Prison Registry. We also stratified the one-day sample by possession of a Norwegian personal identification number (PIN). Results We found differences in birthplace, imprisonment and drug use between the NorMA cohort, lost to follow-up and the one-day population. Twenty-three percent of the one-day population did not have a Norwegian PIN. The NorMA cohort was more similar to those with a Norwegian PIN in the one-day population. Our triangulation demonstrates that 56–62% of the Norwegian prison population had an indication of drug use before imprisonment. Conclusions The NorMA cohort was overall representative of the one-day prison population holding a Norwegian PIN and less representative of prisoners without a Norwegian PIN. Using this method provides tangible inputs on the strengths and limitations of a study sample and can be a feasible method to investigate the external validity of survey data.

GPS measurements have proved extremely useful in quantifying strain accumulation rate and assessing seismic hazard in a region. Continuous GPS measurements provide estimates of secular motion used to understand the earthquake and other geodynamic processes. GNSS stations extending from the South of India to the Higher Himalayan region have been used to quantify the strain build-up rate in Central India and the Himalayan region to assess the seismic hazard potential in this realm. Velocity solution has been determined after the application of Markov noise estimated from GPS time series data. The recorded GPS data are processed along with the closest International GNSS stations data for estimation of daily basis precise positioning. The baseline method has been used for the estimation of the linear strain rate between the two stations. Whereas the principal strain axes, maximum shear strain, rotation rate, and crustal shortening rate has been calculated through the site velocity using an independent approach; least-square inversion approach-based triangulation method. The strain rate analysis estimated by the triangulation approach exhibits a mean value of extension rate of 26.08 nano-strain/yr towards N131°, the compression rate of –25.38 nano-strain/yr towards N41°, maximum shear strain rate of 51.47 nano-strain/yr, dilation of –37.57 nano-strain/yr and rotation rate of 0.7°/Ma towards anti-clockwise. The computed strain rate from the Baseline method and the Triangulation method reports an extensive compression rate that gradually increases from the Indo-Gangetic Plain in South to Higher Himalaya in North. The slip deficit rate between India and Eurasia Plate in Kumaun Garhwal Himalaya has been computed as 18±1.5 mm/yr based on elastic dislocation theory. Thus, in this study, present-day surface deformation rate and interseismic strain accumulation rate in the Himalayan region and the Central Indian region have been estimated for seismic hazard analysis using continuous GPS measurements.

The purpose of this research to describe how the social competence in professional of educators at SDN 1 Sinarmulya, Banyumas District, Pringsewu Regency. The type of research used is qualitative research. The informants used in this study were teachers of grades IV, V, and VI of SDN 1 Sinarmulya, Banyumas District, Pringsewu Regency. Data collection techniques used by researchers are observation and interviews. The technique of cheking the validity of the data is using source triangulation. The results of the study found that teacher at SDN 1 Sinarmulya have good social competence, especially in the indicators of communicating effectively, which are the indicators most mastered by teachers. Teachers at SD N 1 Sinarmulya have good social competence in acting and acting objectively, teachers at SD N 1 Sinarmulya have good social competence in adapting to the environment, teachers at SD N 1 Sinarmulya have good social competence in empathy and courtesy in communicating.

Stocks are one of the aspects that affect the economy in the world. In the stock market, the price of a stock changes every time. Investors who are able to predict the increase in stock prices will tend to get profit, but investors who are unable to predict the increase in stock prices will tend to experience losses. This study aims to find statistical models and use them to predict the probability of an increase in the price of a stock in the stock market. The method used in this study is a literature study regarding stochastic models and selected suitable stochastic models. This study finds stochastic models and uses them to predict the probability of an increase in stock prices. The novelty in this research lies in the stochastic model triangulation. The increase in stock prices is predicted using two stochastic models, namely: Bernoulli and autoregressive. The decision on stock prediction is determined by the results of the triangulation of the two methods. The proposed method in this study has the advantage that decision making is based on more than one stochastic model. The results of this study can be applied to the financial sector, especially in the stock market.

The scalar triangulation and ranging (STAR) method is a magnetic detection method based on magnetic gradient tensor invariants, which has a wide application prospect. Due to the asphericity parameter, there are distance error and direction error in the STAR method. There have been studies to compensate the direction error, but the distance error has not been compensated. This article proposes a new STAR method (NSM) that uses an iterative method to compensate both the direction error and the distance error. Considering the convenience and feasibility of the operation, previous researchers analyzed the detection accuracy of the magnetic detection method by the detection error of the magnetic target on a latitude trajectory (latitude line in the spherical coordinate system of magnetic detection). But different latitude trajectories will lead to different analysis results. In order to analyze the influence of motion trajectory on the detection error, the omnidirectional magnetic detection model (OMDM) is established. The omnidirectional error expectation is used to more accurately measure the detection accuracy of the magnetic detection method. Based on the OMDM, the warp trajectory (warp line in the spherical coordinate system of magnetic detection) that accurately measures the detection accuracy is found. Simulation results show that NSM reduces the localization error of the STAR method, Lv-STAR method, and Wang-STAR method by 87.5%, 58.8%, and 12.5%, respectively. Both simulation and experimental results show that when comparing and analyzing the detection accuracy of the magnetic detection method, the results obtained by a latitude trajectory are one-sided, but a warp trajectory is both operable and accurate.

This paper attempts to investigate the capacity of restorative justice (RJ) to reduce incarceration in China. It utilizes a “top-down” approach to explore how macro transitions in Chinese politics ...

Improve Early Childhood Education, teachers must have high creativity in delivering material using methods that make children motivated to learn. One of them is the collage method which aims to improve fine motor skills in early childhood. This study uses qualitative and descriptive methods with data collection techniques by triangulation, observation, interviews, and documentation. The collage method applied at Cahaya Ananda Kindergarten uses various media such as paper, seeds, cotton.

The present article proposes a geometry-based fuzzy relational technique for capturing gradual change in human emotion over time available from relevant face image sequences. As associated features, we make use of fuzzy membership arising out of five triangle signatures such as - (i) Fuzzy Isosceles Triangle Signature (FIS), (ii) Fuzzy Right Triangle Signature (FRS), (iii) Fuzzy Right Isosceles Triangle Signature (FIRS), (iv) Fuzzy Equilateral Triangle Signature (FES), and (v) Other Fuzzy Triangles Signature (OFS) to achieve the task of appropriate classification of facial transition from neutrality to one among the six expressions viz. anger (AN), disgust (DI), fear (FE), happiness (HA), sadness (SA) and surprise (SU). The effectiveness of the Multilayer Perceptron (MLP) classifier is tested and validated through 10 fold cross-validation method on three benchmark image sequence datasets namely Extended Cohn-Kanade (CK+), M&M Initiative (MMI), and Multimedia Understanding Group (MUG). Experimental outcomes are found to have achieved accuracy to the tune of 98.47%, 93.56%, and 99.25% on CK+, MMI, and MUG respectively vindicating the effectiveness by exhibiting the superiority of our proposed technique in comparison to other state-of-the-art methods in this regard.

This paper describes a numerical method for surface parameterization, yielding maps that are locally injective and discretely conformal in an exact sense. Unlike previous methods for discrete conformal parameterization, the method is guaranteed to work for any manifold triangle mesh, with no restrictions on triangulatiothat each task can be formulated as a convex problem where the triangulation is allowed to change---we complete the picture by introducing the machinery needed to actually construct a discrete conformal map. In particular, we introduce a new scheme for tracking correspondence between triangulations based on normal coordinates , and a new interpolation procedure based on layout in the light cone. Stress tests involving difficult cone configurations and near-degenerate triangulations indicate that the method is extremely robust in practice, and provides high-quality interpolation even on meshes with poor elements.

Purpose The purpose of this paper is to introduce a methodology aimed to detect debonding induced by low impacts energies in typical aeronautical structures. The methodology is based on high frequency sensors/actuators system simulation and the application of elliptical triangulation (ET) and probability ellipse (PE) methods as damage detector. Numerical and experimental results on small-scale stiffened panels made of carbon fiber-reinforced plastic material are discussed. Design/methodology/approach The damage detection methodology is based on high frequency sensors/actuators piezoceramics system enabling the ET and the PE methods. The approach is based on ultrasonic guided waves propagation measurement and simulation within the structure and perturbations induced by debonding or impact damage that affect the signal characteristics. Findings The work is focused on debonding detection via test and simulations and calculation of damage indexes (DIs). The ET and PE methodologies have demonstrated the link between the DIs and debonding enabling the identification of position and growth of the damage. Originality/value The debonding between two structural elements caused in manufacturing or in-service is very difficult to detect, especially when the components are in low accessibility areas. This criticality, together with the uncertainty of long-term adhesive performance and the inability to continuously assess the debonding condition, induces the aircrafts’ manufacturers to pursuit ultraconservative design approach, with in turn an increment in final weight of these parts. The aim of this research’s activity is to demonstrate the effectiveness of the proposed methodology and the robustness of the structural health monitoring system to detect debonding in a typical aeronautical structural joint.

We present a guaranteed quality mesh generation algorithm for the curvilinear triangulation of planar domains with piecewise polynomial boundary. The resulting mesh consists of higher-order triangular elements which are not only regular (i.e., with injective geometric map) but respect strict bounds on quality measures like scaled Jacobian and MIPS distortion. This also implies that the curved triangles' inner angles are bounded from above and below. These are key quality criteria, for instance, in the field of finite element analysis. The domain boundary is reproduced exactly, without geometric approximation error. The central idea is to transform the curvilinear meshing problem into a linear meshing problem via a carefully constructed transformation of bounded distortion, enabling us to leverage key results on guaranteed-quality straight-edge triangulation. The transformation is based on a simple yet general construction and observations about convergence properties of curves under subdivision. Our algorithm can handle arbitrary polynomial order, arbitrarily sharp corners, feature and interface curves, and can be executed using rational arithmetic for strict reliability.

In this work, we use some results concerning the connection between blossoms and splines, especially those related to the smoothness conditions to develop an algorithm for constructing on an arbitrary triangulation a C 2 spline approximant with minimal degree. Numerical tests are presented to illustrate the theoretical results.

Objective: In this paper, we present a novel, low-profile, scleral-coil based, distance ranging system which is suitable for smart, accommodating contact lenses. Methods: We measure the induced emf between a set of four thin semi-circular coils patterned on flexible Kapton substrates that conform to the eyes’ sclera. This induced emf is a function of eye gaze angles. The system then determines the distance from the eyes to the desired object via the triangulation of these eye gaze angles Results : Experiments on eyeball simulated tissue gels indicate an accurate prediction of object distance in the 0.1-15 D range with a 0.15 D RMS error and object direction in the −15 to 15-degree arc with 0.4-degree RMS error, respectively. The energy required was determined to be as low as 20 μJ per range reading. Conclusion: Experimental data shows that our proposed new method of eye-tracking and distance ranging system can accurately predict eye-gaze angles and object-distance, whilst using only 20 μJ per range reading. Significance: The high-accuracy, low-profile and reduced energy requirements of the proposed eye-tracking technique, make it suitable for applications in the vast field of adaptive optics such as smart contact lenses and other low-power vision corrective applications.

Background/purpose: With the rise of digitalization in dentistry, intraoral scanners and digital impressions have recently been adopted by many clinicians. The aim of this study was to investigate surface topography of prepared teeth and the accuracy of digital impressions. Materials and methods: Twenty mandibular typodonts, containing left first premolar and left first molar abutment teeth manufactured by using CAD/CAM, were used in this study. An intraoral scanner was used to scan each typodont, and each STL file generated was exported in high resolution (Group H), moderate resolution (Group M), and low resolution (Group L). All 60 files were inspected in a 3-D mesh processing software. For each file, the number of triangulation points in the meshwork were obtained for both abutment teeth. Results: The measurements obtained from the 3-D mesh processing software revealed that the mean number of triangulation points on the 3-D surface of the abutment teeth (20 premolars + 20 M) were 790,625 ± 98,890 dots in Group H, 592,283 ± 74,881 dots in Group M, and 198,067 ± 19,328 dots in Group L. Significant differences were found between Group H and M (p

Aiming at the phenomenon that the traditional measurement methods cannot complete large-scale measurement in a short time, and the image quality obtained by remote sensing in cloudy and rainy areas is difficult to meet the demand, this paper puts forward the idea of using UAV tilt photography to build three-dimensional modeling of urban real scene. The UAV tilt photography technology is used to collect the image data of about 200 km2 in Wuzhishan City. By laying a small number of ground image control points, the aerial triangulation is used to establish the connection, and the three-dimensional modeling of the collected data is carried out. Through the field verification to verify the attribute information of ground objects, the accuracy is verified by using CORS system field coordinate collection. The results show that the ground property and mathematical accuracy of UAV tilt photography model meet the requirements, and can be effectively used in real 3D modeling.

A new predictor-corrector type incremental algorithm is proposed for the exact construction of weighted straight skeletons of 2D general planar polygons of arbitrary complexity based on the notion of deforming polygon. In the proposed algorithm, the raw input provided by the polygon itself is enough to resolve edge collapse and edge split events. Neither the construction of a kinetic triangulation nor the computation of a motorcycle graph is required. Due to its incremental nature, there is always a room in the algorithm for the interactive construction of the straight skeleton. The proposed algorithm is of predictor-corrector type. In the algorithm, the edge collapse and edge split events are tackled by a completely different novel original approach which is first of its kind. In the predictor step, the position of the vertices is advanced in time by direct integration assuming no event. Then predicted positions are corrected by using linear interpolation if there are edge collapse or edge split events within the same increment. In the algorithm edge collapse and edge split events are detected by, respectively, edge swap and edge penetration. The proposed algorithm has been used to construct roof topology starting from a floor plan of various complexity ranging from simple convex to highly nonconvex with holes. In order to construct, improve and test the building blocks of the underlying algorithm, a graphical user interface, Straight Skeleton Development Kit, has also been developed in parallel by the author using C++ programming language.

The problem of electromagnetic wave diffraction by a flat convex screen of arbitrary shape is considered. The numerical solution for the problem is obtained by the method of moments using the parallel programming technology CUDA. As basic and testing functions RWG functions are used. To construct the corresponding RWG elements on CUDA, a simple and fast algorithm of triangulation for a convex screen with an arbitrary boundary is developed. Numerical results are presented for the problem of diffraction by a rectangular screen, as well as by screen octagonal shape. The results obtained for the rectangle are in good correspondence with the results published in previous works. A comparative analysis of the running time of sequential and parallel algorithms is presented. The analysis shows that the method of moments implementation by GPU significantly improves the performance of the algorithm for solving the problem of electromagnetic wave diffraction by the flat metal screens.

Mesh models generated by multi view stereo (MVS) algorithms often fail to represent in an adequate manner the sharp, natural edge details of the scene. The harsh depth discontinuities of edge regions are eventually a challenging task for dense reconstruction, while vertex displacement during mesh refinement frequently leads to smoothed edges that do not coincide with the fine details of the scene. Meanwhile, 3D edges have been used for scene representation, particularly man-made built environments, which are dominated by regular planar and linear structures. Indeed, 3D edge detection and matching are commonly exploited either to constrain camera pose estimation, or to generate an abstract representation of the most salient parts of the scene, and even to support mesh reconstruction. In this work, we attempt to jointly use 3D edge extraction and MVS mesh generation to promote edge detail preservation in the final result. Salient 3D edges of the scene are reconstructed with state-of-the-art algorithms and integrated in the dense point cloud to be further used in order to support the mesh triangulation step. Experimental results on benchmark dataset sequences using metric and appearance-based measures are performed in order to evaluate our hypothesis.

Examining the general impact of Controlled Language (CL) rules in the context of Machine Translation (MT) has been an area of research for many years. The present study focuses on the following question: how do CL rules impact MT output individually? By analysing a German corpus-based test suite of technical texts that have been translated into English by different MT systems, this study endeavours to answer this question at different levels: the general impact of CL rules (rule- and system-independent), their impact at rule level (system-independent) as well as at rule and system level. The results of five MT systems are analysed and contrasted: a rule-based system, a statistical system, two differently constructed hybrid systems, and a neural system. For this, a mixed-methods triangulation approach that includes error annotation, human evaluation, and automatic evaluation was applied. The data was analysed both qualitatively and quantitatively in terms of CL influence on the following parameters: number and type of MT errors, style and content quality, and scores of two automatic evaluation metrics. In line with many studies, the results show a general positive impact of the applied CL rules on the MT output. However, at rule level, only four rules proved to have positive effects on the aforementioned parameters; three rules had negative effects on the parameters; and two rules did not show any significant impact. At rule and system level, the rules affected the MT systems differently, as expected. Rules that had a positive impact on earlier MT approaches did not show the same impact on the neural MT approach. Furthermore, neural MT delivered distinctly better results than earlier MT approaches, namely the highest error-free, style and content quality rates both before and after applying the rules, which indicates that neural MT offers a promising solution that no longer requires CL rules for improving the MT output.

A posteriori error estimates are constructed for the three-field variational formulation of the Biot problem involving the displacements, the total pressure and the fluid pressure. The discretization under focus is the H 1 ( Ω ) -conforming Taylor–Hood finite element combination, consisting of polynomial degrees k + 1 for the displacements and the fluid pressure and k for the total pressure. An a posteriori error estimator is derived on the basis of H ( div ) -conforming reconstructions of the stress and flux approximations. The symmetry of the reconstructed stress is allowed to be satisfied only weakly. The reconstructions can be performed locally on a set of vertex patches and lead to a guaranteed upper bound for the error with a constant that depends only on local constants associated with the patches and thus on the shape regularity of the triangulation. Particular emphasis is given to nearly incompressible materials and the error estimates hold uniformly in the incompressible limit. Numerical results on the L-shaped domain confirm the theory and the suitable use of the error estimator in adaptive strategies.

To address the problem of feature points missing and surface holes after 3D reconstruction. A method of filling holes after extracting feature points of point cloud data is proposed. In this paper, the method of extracting feature points by multi-discriminant parameters is used to simplify the point cloud. The original shape features are retained while the data are simplified. Then, the initial triangulation of the point cloud is carried out. The resulting triangular mesh is least squared to get a relatively normal mesh, and finally the curvature of the surface is adjusted and optimized. The experimental results show that the simplification rate corresponding to improving the efficiency and retaining the original features is different for the point cloud data of different magnitude. The simplification rate of tens of thousands point cloud data is 70-80%, and that of hundreds of thousands of point cloud data is 40%. It also shows that the combination of feature point extraction and hole repair not only improves the efficiency of the repair process, but also retains the original features of the data.

Chinese were first imported to the Mississippi Delta1 as the solution to the shortage of Black laborers and the maintenance of the plantation system after the Civil War. As foreigners and people of...

Traditional approaches require a velocity model to compute travel times for estimating the location of earthquakes. Moreover, the velocity model typically assumed is layered in nature, ignoring the perturbations around the background velocity model. In this study, we propose a novel method that does not require any assumption on a velocity model. Also, triangulation estimates of location require three-station recordings. Even if the single station is used, three components of recordings are needed. In this work, we propose a machine learning method, based on support vector machines (SVM), that can predict earthquake location and magnitude with just one component (vertical) of a single station. Machine learning methods are typically used for either regression or classification. Literature shows that the SVM algorithm is promising for the classification of an arbitrary signal. This research demonstrates that, by using complementary input features from a seismic recording, a comparable performance can be obtained, with a substantial reduction in detection time. Furthermore, only the vertical component of a single recording station data is used to train the network. The SVM algorithm is applied on synthetic seismograms from 400 earthquakes of different focal mechanisms and magnitudes. This falls under supervised machine learning, as we give the input features and use them for training the model. Overfitting is avoided by tenfold cross-validation, i.e., the algorithm is repeated ten times, each time giving a different 10% as a testing portion. The classifier's performance is quite good, on the synthetic noise-free data, in predicting the magnitude, elevation angle, and hypocentral distance, but not the azimuthal angle. The trained model in the present work can be readily used where noise levels are quite low without sophisticated ray-tracing or Green's function computation. The performance of the algorithm is checked by adding additive noise to the data. The novelty of this work is that knowledge of the velocity model is not required, and the estimation of magnitude and the origin of the earthquake are done using the single-station/single-component earthquake records.

The purpose of this study is to find and explain the language of traders in the interaction of buying andselling in the Kawasan Makam Gus Dur Tebuireng Jombang (KMGD) market. The research method used is adescriptive qualitative approach. The data collection techniques used were: 1. Technique survey, 2. Recordingtechnique, 3. Listening technique and 4. Note technique. The data analysis technique uses the followingtechniques: 1. Data collection, 2. Data reduction, 3. Data presentation, 4. Conclusing drawing / verification. In thisstudy, the validity of the data used data triangulation: 1. Technique triangulation, 2. Time triangulation. Theresults of the research that can be formulated that the language expressions used by merchants are Javanese,Indonesian and Madurese.

The current study examined the applicability of the spillover effect and the compensatory hypothesis in a sample of 80 Israeli Arab mothers living in polygamous families. It was posited that the marital dissatisfaction reflected in mothers’ romantic jealousy and their desire for revenge against their husbands would be transformed into feelings of rejection toward their own eldest sons and would involve the parental practice of triangulation. The results indicated that mothers’ desire for revenge mediated the association between romantic jealousy and mother–child rejection. Furthermore, mothers’ desire for revenge also mediated the association between romantic jealousy and mother-child triangulation. These findings point to the complexity of mother-child relationships in polygamous families.

This study proposes a framework implementing triangular estimation for better modeling and forecasting time series. In order to improve the performance of estimation, we employ two sources of triangulation to generate a time series, which is statistically indistinguishable with the latent time series hidden in a system. Thanks to Bayesian hierarchical estimation, which is akin to deep learning but more sophisticate and longer history, the framework has been validated by a large amount of records in vegetable auctions. The hierarchical Bayesian estimation and Monte Carlo Markov Chain particle filters used in hidden Markov model are appreciated during the massive bootstrapping of data. Our results demonstrate excellent estimation performance in discovering hidden states.

Social network analysis has become a popular methodology in human geography. This article develops three propositions – connectivity, contextuality, and reflexivity – for relational analysis to overcome the dualism between universalist network science on the one hand and idiosyncratic network stories on the other. Building on a detailed meta-analysis of over 300 network studies published between 1990 and 2018, we offer a sympathetic critique of the actual use of network methods in human geography. To unleash further potential of network research, we propose several research strategies for more inclusive relational analysis, including informed pre-specification, triangulation, and communicative validation.

In this letter, an efficient closed-form solution for the state initialization in visual-inertial odometry (VIO) and simultaneous localization and mapping (SLAM) is presented. Unlike the state-of-the-art, we do not derive linear equations from triangulating pairs of point observations. Instead, we build on a direct triangulation of the unknown $3D$ point paired with each of its observations. We show and validate the high impact of such a simple difference. The resulting linear system has a simpler structure and the solution through analytic elimination only requires solving a $6\times 6$ linear system (or $9 \times 9$ when accelerometer bias is included). In addition, all the observations of every scene point are jointly related, thereby leading to a less biased and more accurate solution. The proposed formulation attains up to 50 percent decreased velocity and point reconstruction error compared to the standard closed-form solver, while it is $4\times$ faster for a 7-frame set. Apart from the inherent efficiency, fewer iterations are needed by any further non-linear refinement thanks to better parameter initialization. In this context, we also present a non-linear optimizer that optionally refines the initial parameters. The superior performance of the proposed solver is established by quantitative comparisons with the state-of-the-art solver.

The unified control points (UCPs), the multi-dimensional geodetic reference points installed in the low elevated area, has been established in Korea for the combination of the horizontal and the vertical geodetic control. While the 1st-phase UCPs network was completed in 2011 with a spatial density of about 10km, its densification has been underway as the 2nd-phase project. The UCPs supersedes the legacy geodetic points, such as triangulation points and benchmarks (BMs) once the 2nd-phase implementation. Although the horizontal network of the UPCs can be readily realised by GNSS technology, a technical challenge of the vertical component remains to be settled due to characteristics of the geodetic levelling technique. To this end, a pilot study was conducted to design a new version of the UCPs-based levelling network and to demonstrate its effectiveness with a comparison of the legacy. In this paper, a concept of the UCPs-based levelling network is briefly addressed with some prominent examples, and details of a pilot network and its measurements is given with the network adjustment procedure. Finally, results of the adjustments are provided with an emphasis on the influence of the newly designed network in terms of accuracy, reliability and estimated heights.