Two-dimensional Coordinates Research Articles

Rapid and Blind Watermarking Approach of the 3D Objects Using QR Code Images for Securing Copyright.

Watermarking techniques in a wide range of digital media was utilized as a host cover to hide or embed a piece of information message in such a way that it is invisible to a human observer. This study aims to develop an enhanced rapid and blind method for producing a watermarked 3D object using QR code images with high imperceptibility and transparency. The proposed method is based on the spatial domain, and it starts with converting the 3D object triangles from the three-dimensional Cartesian coordinate system to the two-dimensional coordinates domain using the corresponding transformation matrix. Then, it applies a direct modification on the third vertex point of each triangle. Each triangle's coordinates in the 3D object can be used to embed one pixel from the QR code image. In the extraction process, the QR code pixels can be successfully extracted without the need for the original image. The imperceptibly and the transparency performances of the proposed watermarking algorithm were evaluated using Euclidean distance, Manhattan distance, cosine distance, and the correlation distance values. The proposed method was tested under various filtering attacks, such as rotation, scaling, and translation. The proposed watermarking method improved the robustness and visibility of extracting the QR code image. The results reveal that the proposed watermarking method yields watermarked 3D objects with excellent execution time, imperceptibility, and robustness to common filtering attacks.

The response of invertebrate communities to a moisture gradient in artificial soils of Ukrainian steppe arid zone

Animals were sampled within the experimental area using traps to investigate the spatial and temporal variation in abundance, species richness, and species composition of invertebrate communities. A total of 60 traps were operated simultaneously during each sampling period. Traps were emptied 26 times every 7-9 days each year. Plant water availability, precipitation, wind speed, air temperature (minimum, maximum, daily mean), air humidity, and atmospheric pressure were used as ecological predictors of invertebrate community status and structure. Two-dimensional geographic coordinates of sampling locations were used to create a set of orthogonal spatial variables based on eigenvectors. We used time series of sampling dates to produce a set of orthogonal eigenvector time variables. The moisture content in technosols was the most important factor determining the terrestrial invertebrate community's temporal dynamics under semi-arid climate and reclaimed ecosystem conditions. Each ecological group of terrestrial invertebrates is homogeneous in terms of moisture gradient (xerophilic, xerozoophilic, mesophilic) and has a specific set of patterns best explain the species response to water content in technosols. However, one should consider the fact that the species response to soil water content is influenced not only by soil water content but also by a complex of other environmental, temporal and spatial factors. That is why the effect of other factors on the species response must be extracted previously to find real estimations of the species optima and tolerance. This task can be solved using the constrained correspondence analysis (CCA) or constrained redundancy analysis (RDA) depending on the type of response to ecological factors prevailing in the community – monotone or unimodal. We found that in more dry conditions, the prevalent species responses are unimodal asymmetric, in moister – bimodal, and in moderate conditions, the distributions are symmetric unimodal. The asymmetric species response to soil moisture in different parts of the soil humidity range may be assumed as predominantly due to the abiotic factors in the gradient's aridest margin and due predominantly to the biotic factors in the most humid margin of the gradient.

Evaluation of the efficiency of differential addition of points of curves in the generalized Edwards form

A survey of the main properties of three classes of curves in the generalized Edwards form is given: complete, quadratic and twisted Edwards curves. The analysis of the Montgomery algorithm for differential addition of points for the Montgomery curve is carried out. An estimation of the record low cost of computing the scalar product kP of a point P is given, which is equal to 5M+4S+1U on one step of the iterative cycle (M is the cost of finite field multiplication, S is the cost of squaring, U is the cost of field multiplication by a known constant). A detailed derivation of the formulas for addition-subtraction and doubling points for the curve in the generalized Edwards form in projective coordinates of Farashahi-Hosseini is carried out. Moving from three-dimensional projective coordinates (X: Y: Z) to two-dimensional coordinates (W: Z) allows achieving the same minimum computational cost for the Edwards curves as for the Montgomery curve. Aspects of the choice of an Edwards-form curve acceptable for cryptography and its parameters optimization in the problem of differential addition of points are discussed. Twisted Edwards curves with the order of NE=4n (n is prime) at p≡5mod8 are recommended, minimizing the parameters a and d allows achieving the minimum cost estimation 5M+4S for one step of computing the point product. It is shown that the transition from the Weierstrass curves (the form used in modern cryptographic standards) to the Edwards curves makes it possible to obtain a potential gain in the speed of computing the scalar product of the point by a factor of 3.09.

Modeling ArUco Markers Images for Accuracy Analysis of Their 3D Pose Estimation

Fiducial markers are used in vision systems to determine the position of objects in space, reconstruct movement and create augmented reality. Despite the abundance of work on analysis of the accuracy of the estimation of the fiducial markers spatial position, this question remains open. In this paper, we propose the computer modeling of images with ArUco markers for this purpose. The paper presents a modeling algorithm, which was implemented in the form of software based on the OpenCV library. Algorithm is based on projection of three-dimensional points of the marker corners into two-dimensional points using the camera parameters and rendering the marker image in the new two-dimensional coordinates on the modeled image with the use of the perspective transformation obtained from these points. A number of dependencies were obtained by which it is possible to evaluate the error in determining the position depending on markers size. Including the probability of detecting a marker depending on its area on an image.

Thermocapillary motion of a solid cylinder near a liquid–gas interface

The motion of a solid, infinitely long cylinder perpendicular to a convective liquid–gas interface due to thermocapillarity is investigated via an analytical model. If the cylinder temperature differs from the bulk temperature, a temperature gradient exists along the liquid–gas interface. This results in surface tension gradients at the liquid–gas interface, causing fluid flow around the particle, which induces propulsion. For small particles and, thus, small Péclet and Reynolds numbers, the steady-state equations for temperature and flow fields are solved exactly using two-dimensional bipolar cylindrical coordinates. The velocity of the cylinder as a function of separation distance from the liquid–gas interface is determined for the case of a constant temperature or a constant heat flux on the surface of the cylinder. A larger temperature gradient at the liquid–gas interface in the latter system leads to a larger cylinder velocity and a higher propulsion efficiency. The thermocapillary effect results in larger force on a cylinder than forces arising from other self-propulsion mechanisms.

\u03b1-Probabilistic flexible aggregate nearest neighbor search in road networks using landmark multidimensional scaling

In spatial database and road network applications, the search for the nearest neighbor (NN) from a given query object q is the most fundamental and important problem. Aggregate nearest neighbor (ANN) search is an extension of the NN search with a set of query objects Q = { q_0, dots , q_{M-1} } and finds the object p^* that minimizes g { d(p^*, q_i), q_i in Q }, where g (max or sum) is an aggregate function and d() is a distance function between two objects. Flexible aggregate nearest neighbor (FANN) search is an extension of the ANN search with the introduction of a flexibility factor phi , (0 < phi le 1) and finds the object p^* and the set of query objects Q^*_phi that minimize g { d(p^*, q_i), q_i in Q^*_phi }, where Q^*_phi can be any subset of Q of size phi |Q|. This study proposes an efficient alpha -probabilistic FANN search algorithm in road networks. The state-of-the-art FANN search algorithm in road networks, which is known as IER-khbox {NN}, used the Euclidean distance based on the two-dimensional coordinates of objects when choosing an R-tree node that most potentially contains p^*. However, since the Euclidean distance is significantly different from the actual shortest-path distance between objects, IER-khbox {NN} looks up many unnecessary nodes, thereby incurring many calculations of ‘expensive’ shortest-path distances and eventually performance degradation. The proposed algorithm transforms road network objects into k-dimensional Euclidean space objects while preserving the distances between them as much as possible using landmark multidimensional scaling (LMDS). Since the Euclidean distance after LMDS transformation is very close to the shortest-path distance, the lookup of unnecessary R-tree nodes and the calculation of expensive shortest-path distances are reduced significantly, thereby greatly improving the search performance. As a result of performance comparison experiments conducted for various real road networks and parameters, the proposed algorithm always achieved higher performance than IER-khbox {NN}; the performance (execution time) of the proposed algorithm was improved by up to 10.87 times without loss of accuracy.

Performance of a Shore Fixed Oscillating Water Column Device for Different Bottom Slopes and Front Wall Drafts: A Study Based on Computational Fluid Dynamics and BIEM

Abstract Oscillating water column (OWC) wave energy converters are one of the most widely researched devices for ocean wave energy harvesting. This study investigates the hydrodynamic performance of a shore-fixed OWC device for different bottom slopes using two numerical approaches, namely, computational fluid dynamics (CFD) and boundary integral equation method (BIEM). In the BIEM method, the boundary value problem is solved in two-dimensional Cartesian coordinates using the linear water wave theory. The CFD model uses a numerical wave tank (NWT) built using the volume of fluid (VOF) method. Numerical computations are carried out for different sloped bottom geometries and front wall drafts to analyze the hydrodynamic efficiency. There is a general agreement between CFD and BIEM results in terms of resonating behavior of the device. It is observed that the front wall draft has a more significant effect, a lower draft leading to a wider frequency band for optimum conversion at high efficiency. While the BIEM-based analysis resulted in improved performance curve for few of the steeper slopes, the CFD study predicted a lower peak efficiency for the same slopes due to the consideration of real fluid characteristics. Detailed performance comparisons are presented using the time histories of free surface elevation, chamber pressure, and streamlines at different time instants within the OWC chamber.

Analytic and numerical solutions to the seismic wave equation in continuous media.

This paper presents two approaches to mathematical modelling of a synthetic seismic pulse, and a comparison between them. First, a new analytical model is developed in two-dimensional Cartesian coordinates. Combined with an initial condition of sufficient symmetry, this provides a valuable check for the validity of the numerical method that follows. A particular initial condition is found which allows for a new closed-form solution. A numerical scheme is then presented which combines a spectral (Fourier) representation for displacement components and wave-speed parameters, a fourth-order Runge-Kutta integration method, and an absorbing boundary layer. The resulting large system of differential equations is solved in parallel on suitable enhanced performance desktop hardware in a new software implementation. This provides an alternative approach to forward modelling of waves within isotropic media which is efficient, and tailored to rapid and flexible developments in modelling seismic structure, for example, shallow depth environmental applications. Visual comparisons of the analytic solution and the numerical scheme are presented.

Deep Learning-Based Positioning of Visually Impaired People in Indoor Environments.

Wayfinding and navigation can present substantial challenges to visually impaired (VI) people. Some of the significant aspects of these challenges arise from the difficulty of knowing the location of a moving person with enough accuracy. Positioning and localization in indoor environments require unique solutions. Furthermore, positioning is one of the critical aspects of any navigation system that can assist a VI person with their independent movement. The other essential features of a typical indoor navigation system include pathfinding, obstacle avoidance, and capabilities for user interaction. This work focuses on the positioning of a VI person with enough precision for their use in indoor navigation. We aim to achieve this by utilizing only the capabilities of a typical smartphone. More specifically, our proposed approach is based on the use of the accelerometer, gyroscope, and magnetometer of a smartphone. We consider the indoor environment to be divided into microcells, with the vertex of each microcell being assigned two-dimensional local coordinates. A regression-based analysis is used to train a multilayer perceptron neural network to map the inertial sensor measurements to the coordinates of the vertex of the microcell corresponding to the position of the smartphone. In order to test our proposed solution, we used IPIN2016, a publicly-available multivariate dataset that divides the indoor environment into cells tagged with the inertial sensor data of a smartphone, in order to generate the training and validating sets. Our experiments show that our proposed approach can achieve a remarkable prediction accuracy of more than 94%, with a 0.65 m positioning error.

Spatial and temporal changes in follicle distribution in the human ovarian cortex

Research questionHow does follicle distribution evolve in the human ovarian cortex between the ages of 20 and 35 years? DesignFragments of ovarian cortex from women undergoing unilateral oophorectomy for fertility preservation were obtained for quantitative histological assessment, including recording the two-dimensional coordinates of the follicles. Data were analysed using spatial statistical methods. ResultsA total of 53 ovarian cortex tissue samples, containing 1–803 follicles each, were obtained from 14 women aged 20–35 years. Primordial and transitory follicles lay in a clustered manner in the human ovarian cortex, with an average cluster radius of around 270 µm (95% confidence interval 154–377 µm; n = 49). Follicle density declined with age (P = 0.006, n = 13), and the distance from the nearest neighbouring follicle increased (P = 0.004, n = 13). Cluster radius decreased with age (P = 0.02, n = 13), but the degree of clustering tended to increase (P = 0.11, n = 13). In the majority of the samples, follicles at different stages lay in different clusters (P < 0.05, n = 13). ConclusionsThis study shows that primordial and transitory follicles lie in different clusters in the human ovarian cortex. Spatio-temporal computer simulation suggests that interfollicular signals may hinder follicle loss and may therefore drive clustered follicle distribution. In clinical practice, the woman's age should be taken into account when assessing follicle density, as follicle distribution is increasingly clustered with advancing age.

Finding key points in a hand image using heatmaps

This paper presents an approach to finding key points in the image of a hand using heat maps. For this, a convolutional model of a neural network and a training method on heatmaps were combined. An open bank of palm photos, supplemented by a set of own images and synthetic data, was used as a dataset. Direct and inverse transformations of two-dimensional coordinates on the plane into heat maps with a 2D Gaussian function centered at coordinate points were applied, data was prepared, the model was trained and tested. As a result of this approach, a neural network model able to recognise real world images was obtained.

Grid‐searching method in polar coordinate system for PD location in substations

This study presents a grid-searching method in polar coordinate system (GSMIPCS) for the partial discharge (PD) location, in which the grids were divided into sectors according to radial distance r, azimuthal angle θ and polar angle φ. After theoretically proving that the positioning angle error, based on time difference of arriving algorithm, is relatively small, this study gives the process of PD positioning in two-dimensional and three-dimensional polar coordinates. Thereafter, this study discusses the optimal setting of grid parameters. The simulation results show that the success rate of angle positioning (SROAP), i.e. a percentage of positioning number with positioning angle error <2° in the total positioning number, for θ angle using two-dimensional (2D) GMSIPCS is 95.87%. For 3D GMSIPCS, the SROAP for θ and φ are 86.18 and 92%, respectively; and the computational cost is lower to 216. Finallly, on-site experiments in the substation verify the effectiveness of the proposed method.

Comparison of maxillary basal arch forms using the root apex in adult women with different skeletal patterns: A pilot study

This study aimed to establish maxillary basal arch forms using the root apices and to determine the differences in the basal arch forms in adult women with different sagittal skeletal patterns. This retrospective study included 91 adult women, with either a Class I (n=24), Class II Division 1 (n=22), Class II Division 2 (n=23), or Class III (n=22) malocclusion, who underwent cone-beam computed tomography. Three-dimensional coordinates of the root apices were determined using the multiplanar reformation mode of OnDemand3D software (Cybermed Inc, Seoul, South Korea). Two-dimensional coordinates were converted from acquired 3-dimensional coordinates via projection on the palatal plane, and the Procrustes superimposition method was used to build the basal arch form. Finally, interroot width measurements were performed for basal arch form comparisons. There were significant differences among the 4 groups (P<0.05) with respect to the intercanine width. The intercanine width of Class II Division 1 group was significantly narrower than that of the other groups. The Class II Division 1 and Class II Division 2 groups tended to have tapered arch forms and squared arch forms, respectively. We established maxillary basal arch forms using the root apices. The Class II Division 1 group had a significantly narrower intercanine distance. The use of the root apex to depict the basal arch form seems reasonable.

Deep Reinforcement Learning-Based Content Placement and Trajectory Design in Urban Cache-Enabled UAV Networks

Cache-enabled unmanned aerial vehicles (UAVs) have been envisioned as a promising technology for many applications in future urban wireless communication. However, to utilize UAVs properly is challenging due to limited endurance and storage capacity as well as the continuous roam of the mobile users. To meet the diversity of urban communication services, it is essential to exploit UAVs’ potential of mobility and storage resource. Toward this end, we consider an urban cache-enabled communication network where the UAVs serve mobile users with energy and cache capacity constraints. We formulate an optimization problem to maximize the sum achievable throughput in this system. To solve this problem, we propose a deep reinforcement learning-based joint content placement and trajectory design algorithm (DRL-JCT), whose progress can be divided into two stages: offline content placement stage and online user tracking stage. First, we present a link-based scheme to maximize the cache hit rate of all users’ file requirements under cache capacity constraint. The NP-hard problem is solved by approximation and convex optimization. Then, we leverage the Double Deep Q-Network (DDQN) to track mobile users online with their instantaneous two-dimensional coordinate under energy constraint. Numerical results show that our algorithm converges well after a small number of iterations. Compared with several benchmark schemes, our algorithm adapts to the dynamic conditions and provides significant performance in terms of sum achievable throughput.

An adaptive model for the location of low-frequency sound sources in shallow sea environments

At present, mathematical models applicable to the localization of shallow sea low-frequency sound source targets are usually complicated, and some environmental parameters need to be set in advance. This poses a great challenge to the scope of the application of this technology. To solve this problem, we propose an adaptive sound source localization model (ASSL) based on data driving, which only needs to input the vector hydrophone signal to output the two-dimensional coordinates of the sound source in real time. First, the four-channel sound source signal received by the single vector hydrophone is fused into a single-channel sound intensity signal and dynamically divided into suitable lengths based on Shannon entropy; then, the built deep bidirectional long short-term memory (DBiLSTM) network is used for a priori training; finally, the results are cross-validated, and the location of the target sound source is output. Experimental results show that the model can quickly estimate the position of the low-frequency sound source in the shallow sea environment using only a 1 s signal collected by a single vector hydrophone. The error between the estimated position and the actual position is approximately 35 m. Even with large samples, the method also showed great potential for application.

Penerapan Estimasi Posisi dan Tracking Wajah Pada Sistem Presensi Mahasiswa

The current presence system can be done with a computerized system, one of which is the face biometric system. This study focuses on the application of position estimation and tracking based on clustering on people's faces to determine the position in three dimensions. Position estimation can be obtained by making a kernel that is ready to be used to predict three-dimensional coordinates of faces based on two-dimensional coordinates of two images. Position estimation can be done by utilizing the Machine Learning algorithm family. In this study, Least Absolute Shrinkage and Selection Operators (LASSO) is used to perform the position estimation. Meanwhile, clustering in this study uses the K-Means algorithm. Based on the test results, the kernel error obtained in estimating the face location is 9.23 cm. The tracking accuracy of an object based on clustering is 100%.

Thrust generation by pitching and heaving of an elastic plate at low Reynolds number

We computationally study thrust generation and propulsive characteristics of an elastic plate pitching and/or heaving in free stream laminar flow. The pitching is considered about the leading edge, and the Reynolds number based on the plate length and free stream velocity is 150. An in-house fluid–structure interaction (FSI) solver is employed to simulate the large-scale flow-induced deformation of the structure along with active pitching and heaving in two-dimensional coordinates. The FSI solver utilizes a partitioned approach to strongly couple a sharp-interface immersed boundary method based flow solver with an open-source finite-element structural dynamics solver. We elucidate the mechanism of the thrust generation in the rigid and elastic plate by comparing the time-variation of thrust and work done by the plate, together with the wake signatures in the downstream. The time variation of the thrust is explained using first-order scaling arguments. The computed thrust as a function of pitching frequency for the rigid pitching plate shows a similar trend as compared to the published data of rigid foils, while the elastic plate exhibits a strong influence of the flow-induced deformation of the plate. They both exhibit reverse von Kármán-like vortex shedding in the downstream. We quantify the differences in propulsive characteristics of these two plate types as a function of pitching frequency. We found that there lies an optimum pitching frequency for the elastic plate for efficient propulsion, while the rigid one outperforms the elastic plate at larger pitching frequency. This is due to the fact that the elastic plate locks in to a higher mode of vibration at a larger pitching frequency. Furthermore, the influence of mass ratio, flexural rigidity, pitching amplitude, and Reynolds number on the performance of the elastic plate is also investigated. Finally, we study the combined effect of pitching and heaving on the propulsive performance. The pitching frequency for the maximum efficiency is lesser for the combined heaving and pitching plate as compared to only heaving or only pitching. Our results provide fundamental insights into the propulsive characteristics of the elastic pitching and/or heaving plates, which could help design autonomous underwater vehicles.

Validation of Diffeomorphic Registration on Cine Cardiac MR via Direct Frame-to-Frame Comparison with HARP Tracking on Tagged MR.

Cardiac magnetic resonance (MR) tissue tagging offers an excellent solution for tracking deformation and is considered the reference standard for the quantification of strain. However, due to the requirements for a dedicated acquisition sequence and post-processing software, tagged MR acquisitions are performed much less frequently in routine clinical practice than the anatomical cine MR sequence. Using tagged MR as the reference standard, this study proposes an approach to evaluate a diffeomorphic image registration algorithm applied on cine MR images to compute the cardiac deformation. In contrast to previous evaluation methods that compared the final results, such as strain, computed from cine and tagged MR sequences, the proposed method performs a direct frame-to-frame comparison in the evaluation. To overcome the problem of misalignment between the tagged and cine MR images, the proposed approach performs transformations to and from the two-dimensional image pixel coordinates and three-dimensional space using the meta-information encoded in the MR images. Linear temporal interpolation is performed using the frame acquisition time since the last R-wave peak value of the electrocardiogram signal recorded in the meta-information. Several statistic measures are computed and reported for the registration error using the Euclidean distances between the corresponding set of points obtained using cine and tagged MR images.

Convexity of Self-Similar Transonic Shocks and Free Boundaries for the Euler Equations for Potential Flow

We are concerned with geometric properties of transonic shocks as free boundaries in two-dimensional self-similar coordinates for compressible fluid flows, which are not only important for the understanding of geometric structure and stability of fluid motions in continuum mechanics but also fundamental in the mathematical theory of multidimensional conservation laws. A transonic shock for the Euler equations for self-similar potential flow separates elliptic (subsonic) and hyperbolic (supersonic) phases of the self-similar solution of the corresponding nonlinear partial differential equation in a domain under consideration, in which the location of the transonic shock is apriori unknown. We first develop a general framework under which self-similar transonic shocks, as free boundaries, are proved to be uniformly convex, and then apply this framework to prove the uniform convexity of transonic shocks in the two longstanding fundamental shock problems -- the shock reflection-diffraction by wedges and the Prandtl-Meyer reflection for supersonic flows past solid ramps. To achieve this, our approach is to exploit underlying nonlocal properties of the solution and the free boundary for the potential flow equation.

Analysis of effects of Thermal Non-Equilibrium and Non-Darcy Flow on Natural Convection in a Square Porous Enclosure Provided with a Heated L Shape Plate

This work involves a study on the convective heat transfer over a two perpendicular plates embedded inside a square porous cavity using non-Darcian flow and Local Thermal Non-Equilibrium (LTNE) assumptions. The problem has been assumed to be steady and two-dimensional coordinates. For non-Darcy flow, the effects of inertia and boundary layer have been included. Finite volume method has been used to discretize and solve the governing equations. The results show that the total average Nusselt number (NuT) is a strong function of modified Rayleigh number (Ra*) and inertia parameter (Fs/Pr*). For a fixed Fs/Pr*, the fluid Nusselt number (Nuf) has been found higher than the solid Nusselt number (Nus). The results also demonstrated that the thermal conductivity ratio (Kr) has a significant impact on all average Nusselt numbers compared to the scaled heat transfer coefficient (H). However, H has a considerable influence on the intensity of LTNE region in comparison to Kr, especially for their lower values. The size and the power of LTNE region are increased with increasing in Ra* and decreasing in Fs/Pr*. For higher Kr and H, the medium inside cavity be close to the thermal equilibrium condition. The results show that the effect of Kr on all Nu is comprehensive, whereas the effect of H is limited to Nus and hence, the behaviour of NuT is similar to the behaviour of Nuf. As Kr is increased, NuT becomes very close to Nuf. Finally, the obtained results have been summarised by developing a correlation of NuT which can be used in engineering design.