Face Boundary Research Articles

An Algorithm for Simplifying 3D Building Models with Consideration for Detailed Features and Topological Structure

To tackle problems such as the destruction of topological structures and the loss of detailed features in the simplification of 3D building models, we propose a 3D building model simplification algorithm that considers detailed features and topological structures. Based on the edge collapse algorithm, the method defines the region formed by the first-order neighboring triangles of the endpoints of the edge to be collapsed as the simplification unit. It incorporates the centroid displacement of the simplification unit, significance level, and approximate curvature of the edge as influencing factors for the collapse cost to control the edge collapse sequence and preserve model details. Additionally, considering the unique properties of 3D building models, boundary edge detection and face overlay are added as constraints to maintain the model’s topological structure. The experimental results show that the algorithm is superior to the classic QEM algorithm in terms of preserving the topological structure and detailed features of the model. Compared to the QEM algorithm and the other two comparison algorithms selected in this paper, the simplified model resulting from this algorithm exhibit a reduction in Hausdorff distance, mean error, and mean square error to varying degrees. Moreover, the advantages of this algorithm become more pronounced as the simplification rate increases. The research findings can be applied to the simplification of 3D building models.

A Penalized Empirical Likelihood Approach for Estimating Population Sizes under the Negative Binomial Regression Model

In capture–recapture experiments, the presence of overdispersion and heterogeneity necessitates the use of the negative binomial regression model for inferring population sizes. However, within this model, existing methods based on likelihood and ratio regression for estimating the dispersion parameter often face boundary and nonidentifiability issues. These problems can result in nonsensically large point estimates and unbounded upper limits of confidence intervals for the population size. We present a penalized empirical likelihood technique for solving these two problems by imposing a half-normal prior on the population size. Based on the proposed approach, a maximum penalized empirical likelihood estimator with asymptotic normality and a penalized empirical likelihood ratio statistic with asymptotic chi-square distribution are derived. To improve numerical performance, we present an effective expectation-maximization (EM) algorithm. In the M-step, optimization for the model parameters could be achieved by fitting a standard negative binomial regression model via the R basic function glm.nb(). This approach ensures the convergence and reliability of the numerical algorithm. Using simulations, we analyze several synthetic datasets to illustrate three advantages of our methods in finite-sample cases: complete mitigation of the boundary problem, more efficient maximum penalized empirical likelihood estimates, and more precise penalized empirical likelihood ratio interval estimates compared to the estimates obtained without penalty. These advantages are further demonstrated in a case study estimating the abundance of black bears (Ursus americanus) at the U.S. Army’s Fort Drum Military Installation in northern New York.

A fully coupled Pressure-Based method for compressible flows at all Mach numbers

When extending the fully coupled pressure-based method to resolve compressible flows, the effective treatment of the boundary conditions is crucial due to the inherent characteristics of compressible flows. Failure to properly account for this can result in numerical instability and divergence. In this article, a detailed treatment of boundary conditions for compressible flows has been formulated in terms of the boundary face’s contribution to the discretization equation of the boundary element. These boundary conditions involve subsonic inlet, supersonic inlet, subsonic outlet, and supersonic outlet boundary conditions. The analysis has been focused on test cases of flow through a bumped arc channel and a converging–diverging nozzle including quasi-incompressible, subsonic, transonic, supersonic and hypersonic speed regimes, where the Mach number ranges from 0.1 to 10. The results indicate the robust performance of the fully coupled method in resolving compressible flows. The computational results obtained from the fully coupled algorithm exhibit a high degree of consistency with available literature cases and analytical solutions, with a maximum error of less than 5%. Moreover, the findings also suggest that the coupled solver presents promising potential in handling hypersonic flows.

Numerical Simulation of Gas Flow Coupled with Burning Surface Regression Based on Immersed Boundary Method and Face Offsetting Method

Numerical Simulation of Gas Flow Coupled with Burning Surface Regression Based on Immersed Boundary Method and Face Offsetting Method

Multi-task network with inter-task consistency learning for face parsing and facial expression recognition at real-time speed

In recent years, face parsing and facial expression recognition have attracted increasing interest. Even though there are relevant results about face parsing and face representation, these approaches seek accuracy at the expense of speed. In this paper, we design a novel multi-task learning network for face parsing and facial expression recognition (MPENet). Specifically, MPENet consists of shared encoders and three downstream branches. In the edge perceiving branch, we use category edge and binary edge to extract face boundary information and improve localization of face boundaries. In the segmentation branch, we use graph learning to fuse edge and semantic information of the image, analyze the relations between different feature regions, and capture more contextual relationships. Finally, we design a consistent learning loss function, forcing different branches to learn the same predictions. We have carried out experiments on face datasets, and found that it shows high precision and fast inference speed. Specifically, MPENet achieves F1 scores of 85.9 on the CelebAMask-HQ dataset and 92.9 on the Lapa dataset, with an inference speed of 92.9 FPS. Moreover, MPENet precisely delineates the semantic boundaries of facial regions and, through consistent multi-task learning, effectively facilitates synergy among various tasks.

Structural damage localization based on deflection influence surfaces calculated by the three-dimensional boundary face method

A structural damage localization method based on deflection influence surfaces (DIS) calculated by the three-dimensional (3D) boundary element method (BEM) is proposed. By combining the 3D BEM with Structural Properties Intelligent Analysis Programs (SPIAP), the static equilibrium method (SEM) is performed on a square plate. Then, all the deflection values are automatically extracted by the SPIAP for the purpose of using the optimized bivariate polynomial function (BPF) to fit the DIS. The accuracy of the SPIAP-fitted DIS is proved by the optimized BPF program. Finally, a structural damage localization module is developed and verified through an experimental example. The numerical and experimental results indicate that compared to the analytical solution, the deflection calculation error of the square plate is no more than 1.8‰. Moreover, the damage localization accuracy of the simply supported beam under single-damage and double-damage cases has been improved by 28.6% and 16.7%, respectively.

An efficient unstructured quadrilateral-dominated surface mesh generation method for arbitrary geometry with tiny features or crack defects in DiBFM

An efficient unstructured quadrilateral-dominated surface mesh generation algorithm is presented to generate high-quality surface elements for arbitrary geometry with tiny features or crack defects. For complex entities with proximity features, a novel type of meshing template has been proposed to solve the problem of entity boundary fitting of the outside-in grid-based method. The algorithm also works for regions with proximity features, as well as for arbitrary geometry with one or multiple cracks. The procedure incorporates aspects of well-known meshing techniques, but includes some original and efficient processes. The refinement field is constructed according to mesh size, boundary curvature, surface curvature and other geometry features. In order to effectively generate the core mesh, a fast intersection algorithm between topological elements and the solid boundary is established, which improves the efficiency of intersection calculation. The geometry-based techniques are employed for boundary matching of the core mesh. The method has been successfully employed in conjunction with the dual interpolation boundary face method (DiBFM). Several realistic geometries with cracks or proximity features are applied to demonstrate the accuracy and validity of the proposed approach.

Advancing Attendance: A Facial Recognition System Empowered by Deep Learning Techniques

Many studies during the last decade tried to provide an automatic technique for facial recognition and identification challenge especially in security systems. In this study, we suggested two methods for student attendance problem based on image processing and machine learning algorithms. The first method uses Haar cascade classifier with the Local Binary Patterns Histograms (LBPH) model and the second method composed from Histograms of Oriented Gradient (HoG) followed by the Convolutional Neural Network (CNN) model. Both methods take a collection of random student images taken from low quality sources as input. A set of image processing filters are first applied on images to enhance the method of extracting the face boundary. Then, each model will be trained using random images from student dataset. The trained model is tested using testing set. The results showed that the method that employ CNN model with HoG provides high accuracy value of 98.44%. While, the accuracy of LBPH model with Haar Cascade classifier is 95.63%.

Analysis of inclined length effect of roof fracture and overlying strata catastrophe in steeply inclined longwall face: A case study

In order to determine the optimal inclined length of steeply inclined working face, the fracture field, strain field, displacement field and strata movement trend of steeply inclined working face were monitored through physical simulation test and digital speckle technique. At the same time, combined with theoretical analysis, the movement law of overlying strata and the catastrophe mechanism of working face caused by the length effect of working face are deeply studied. The research results show that with the increase of working face length, the length and growth rate of middle extremely unstable region are always largest, followed by lower and upper. The spreading failure characteristics of “roof-overlying strata-roof” appear along the inclined direction. When the working face length is less than 125 m, the larger vertical displacement and horizontal displacement are concentrated in the middle extremely unstable region. When the working face length is greater than 140 m, the larger vertical displacement is transferred to the lower stable region and the larger horizontal displacement is transferred to the upper unstable region. Based on this, it is obtained that the working face boundary length of roof and overlying strata catastrophe is 125 m and 140 m respectively. Furthermore, it is put forward that the optimal working face length is 95 m ∼ 125 m on the premise of effectively controlling the hanging space instability in the upper goaf and the flying gangue disaster in the working face. The application of digital speckle technique in large deformation measurement of large-scale physical models is realized.

Artificial and Deceitful Faces Detection Using Machine Learning

Security certification is becoming popular for many applications, such as significant financial transactions. PIN and password authentication is the most common method of authentication. Due to the finite length of the password, the security level is low and can be easily damaged. Adding a new dimension to the sensing mode-driven state-of-the-art multi-modal boundary face recognition system of the image-based solutions. It combines the active complex visual features extracted from the latest facial recognition model and uses a custom Convolution Neural Network issue facial authentications and extraction capabilities to ensure the safety of face recognition. The Echo function is dependent on the geometry and material of the face, not disguised by the pictures and videos, such as multi-modal design is easy to image-based face recognition system

A batch-filling method of VIE-MoM matrix for inhomogeneous dielectric target with full- and half-SWG function

A batch-filling method (BFM) for generating the volume-integral-equation-methods of moment (VIE-MoM) matrix for the scattering of inhomogeneous objects by using the full- and half-SWG basis function is proposed. The BFM is based on the summation of contributions of all integrals over tetrahedrons and boundary faces, and the contributions are arranged into a column vector that represents the interactions of the source basis function with all the test basis functions. The time of the BFM for filling VIE-MoM matrix can be reduced over 95% compared with the conventional basis-basis (CBB) matching filling scheme due to the vector filling scheme, which avoids the repeated traversal between the source tetrahedron and test tetrahedron to fill the impedance matrix elements. Details for the numerical process and the filling scheme of impedance matrix are elaborated. Numerical results show that the batch-filling method has high computational efficiency and accuracy for VIE-MoM.

G1 spline functions for point cloud fitting

In this work we present a new construction of basis functions that generate the space of geometrically smooth splines on an unstructured quadrilateral mesh. The basis is represented in terms of biquintic Bézier polynomials on each quadrilateral face. The gluing along the face boundaries is achieved using quadratic gluing data functions, leading to globally G1–smooth spaces. We analyze the latter space and provide a combinatorial formula for its dimension as well as an explicit basis construction. Moreover, we assess the use of this basis in point cloud fitting problems. To apply G1 least squares fitting, a quadrilateral structure as well as parameters in each quadrilateral is required. Even though the general problem of segmenting and parametrizing point clouds is beyond the focus of the present work, we describe a procedure that produces such a structure as well as patch-local parameters. Our experiments demonstrate the accuracy and smoothness of the obtained reconstructed models in several challenging instances.

A peridynamic model for electromechanical fracture and crack propagation in piezoelectric solids

This paper presents for the first time an approach to the problem of electromechanical fracture and crack propagation in piezoelectric solids with peridynamics. Fracture in piezoelectric ceramics is an important problem in engineering due to its complexity. The majority of the computational models available on the literature rely on sharp crack representations, which have difficulties dealing with complex crack patterns, or rely on diffusive crack models, such as the phase-field fracture model, that can predict complex patterns but does not represent cracks in a discrete way. On the other hand, peridynamics has been designed to solve this problems and is able to simulate discrete cracks as well as complex crack phenomena like fragmentation and branching. We present a novel approach to the implementation of different electric crack face boundary conditions in a peridynamic way, by a field selective bond breaking approach. Moreover, it is also presented the first electromechanical failure criterion for fracture in piezoelectric ceramics. We develop an energy based failure criterion due to its generality and wide range of applications. These approaches are presented in a way such that they are valid for any type of peridynamic formulation. The used numerical model is implemented using correspondence-based peridynamics with the linear piezoelectricity constitutive setting, using a meshfree discretization and solved quasi-statically with an implicit incremental-iterative scheme. Numerical examples are presented to demonstrate the capabilities of these new approaches and assess the performance of the model against experimental results. The model is capable of numerically predicting complicated fracture behaviour and crack propagation in an intrinsic/autonomous way, as demonstrated by the results.

Dynamic Response Analysis of Roadway Surrounding Rock Induced by Dynamic Load under the Action of Hard and Thick Rock Stratum

In the process of coal seam mining, there are often hard thick key layers in the overlying strata. Due to the high strength and good integrity of the hard thick key layer, after the hard thick key layer is broken, the overlying strata will collapse and lose stability in a large area, which is very easy to induce dynamic disasters such as rock burst, mine earthquake, coal wall caving, and roof slab caving. Aiming at the hard and thick key layer overlying the working face, the dynamic response of the mine under the strong mine earthquake induced by the breaking of the main key layer of high-level magmatic rock is numerically simulated and analyzed by using FLAC2D numerical simulation software, and the variation laws of the stress field, displacement field, and velocity field of the coal seam roadway under different boundary conditions and different focal heights are studied. The research shows that the roof of solid coal roadway is prone to vibration in a small range, and the displacement increases and decreases with the disturbance. The displacement of the floor and two sides of the solid coal roadway and the top floor and two sides of the roadway along the goaf continues to increase in the initial stage of the disturbance, and the displacement will remain stable with the continuation of the disturbance. The displacement of both sides and roof and floor of gob roadway can reach stability in the later stage of disturbance, and with the increase of the number of adjacent goaf, the longer it takes for the displacement of surrounding rock to reach stability. When the focal height is lower than 90 m, the variation of surrounding rock response increases sharply with the decrease of focal height. When a strong earthquake occurs in the low rock stratum, the impact damage of roadway surrounding rock is almost inevitable. The influence degree of strong earthquake on the stability of roadway surrounding rock is arranged as follows: gob-side roadway (mined out on one side) > solid coal roadway (mined out on both sides) > solid coal roadway (mined out on one side). The evolution process also shows that the working face boundary conditions have an important influence on the energy propagation of mine earthquake. With the increase of the number of adjacent goafs, the faster the energy attenuation rate of mine earthquake propagation is. The research results have important reference significance for the safe mining of working face under similar geological conditions.

Automatic surface mesh generation by a binary-tree method

In order to realize the automation of surface mesh generation for arbitrary complex models, this paper proposes a binary-tree method (BTM) which can generate discontinuous grids. Compared with continuous grids, the adjacency relationship between discontinuous grids generated by BTM is more flexible, so it is easier to discretize “dirty” geometry without geometry repair than continuous grids. The BTM can adaptively generate meshes by features based on the curvature of curves and surfaces, and thus it does not need to construct a sizing field. Anisotropic meshes can also be directly generated by selecting the direction of subdividing meshes. Moreover, according to the periodic characteristics of periodic surfaces, the topological structure of the initial mesh can be designed to achieve mesh generation on periodic surfaces. Successful numerical examples are used to illustrate the effectiveness and robustness of the presented methods for meshing various types of geometric surfaces and reveal the excellent performance of the BTM. In addition, the BTM has been employed by the dual interpolation boundary face method (DiBFM) to solve 3D problems.

Dual interpolation boundary face method for 3-D acoustic problems based on binary tree grids

A dual interpolation boundary face method (DiBFM) based on binary tree grids is presented to solve 3-D acoustic problems in this paper. The boundary element method (BEM) is widely used to solve acoustic problems for its advantage of only discretizing boundaries and satisfying Sommerfeld radiation condition. Combining boundary integral equations with computer graphics, the boundary face method (BFM) is the enrichment of the BEM and is able to avoid the geometric errors between CAD and CAE models. By adding virtual nodes on the vertices and edges of tradition discontinuous elements, the dual interpolation elements are introduced and have higher interpolation accuracy. What's more, since there is no need for grids continuity, the binary tree grids can be applied to the implementation of the DiBFM, and have the ability to make mesh generation more automatic and easier. The Burton-Miller formulation is employed to remove the non-uniqueness issue. Several numerical examples are given to demonstrate the practicability and superiority of the proposed method.

The role of student peers in HE student mental health and well-being

PurposeThere is evidence that students’ experiences in higher education can be adversely affected by mental health issues, whilst well-being can be bolstered through a sense of belonging. This study aims to draw from Student Minds research into student mental health to consider the importance of peers to constructing a sense of belonging.Design/methodology/approachThis paper draws from a thematic review of 12 focus groups – involving student services staff in six UK universities (69 participants) – conducted as part of the consultation and creation of the Student Minds University Mental Health Charter. The schedule considered student support, service structures and developments to enhance student well-being and manage mental health risks.FindingsA significant theme explored here is the positionality of student peers in terms of relatability, and the importance of orientation and belonging for student mental health and well-being. The findings also consider types of peer involvement (formal/informal) and the influence of structure, training and boundaries in interventions.Research limitations/implicationsFindings reveal the importance of feeling a sense of belonging in the university community to achieve well-being and good mental health. Peer support is an important contributor that supports transitions into university and creates a sense of belonging, which is important to all students, but more so to those less familiar with university, who lack role models and more easily feel isolated.Practical implicationsThe research has implications for higher education providers, which should inform the promotion of peer support within student services, based on the recognised contribution to well-being and mental health. This is important for student success and related opportunities.Social implicationsSuccess in higher education will open opportunities and create improved future prospects for individuals. This will not be realised for individuals who face boundaries and barriers to successful transition through university. The importance of belonging and role of peer support has implications for those who find themselves excluded in society.Originality/valueThis is a qualitative study which gives voice to individuals in universities across the UK. The theme of peer support within this context and linked with mental health and well-being is underexplored.

A multi-domain BEM based on the dual interpolation boundary face method for 3D potential problems

A multi-domain BEM based on the dual interpolation boundary face method for 3D potential problems

Predicting Rural Ecological Space Boundaries in the Urban Fringe Area Based on Bayesian Network: A Case Study in Nanjing, China

Urban fringe areas are locations that compete between urban development and ecological protection; their ecological spatial boundaries face the risk of erosion and degradation. Previous studies have so far focused on the core area inside the ecological space. However, research on the ecological boundary zone has so far been insufficient. The delineation of ECR is based on large-scale administrative units, while it is less precise at the level of small-scale rural areas. This study selected Paifang village in Nanjing City as the study area and built a Bayesian network model to predict the ecological space boundary for 2030. The study also identified the driving factors and their mechanisms affecting the changes in the rural ecological space in an urban fringe area and put forward targeted suggestions for its protection. The results suggested that: (1) The ecological space of Paifang village will expand in 2030. Specifically, agricultural land has the greatest potential for restoration of ecological space, followed by shrubland and grassland, and water bodies and their surrounding areas are potentially shrinking ecological space. (2) Artificial construction activities will disturb the ecological space, with the change in agricultural land being the main factor affecting the change in the ecological space boundary. (3) The Ecological Conservation Redline has a significant effect on the protection of the rural ecological space. The results of this study can provide a reference for rural planning and the formulation of protection policies in urban fringe areas.

List star edge coloring of generalized Halin graphs

A star k-edge coloring is a proper edge coloring such that there are no bichromatic paths or cycles of length four. The smallest integer k such that G admits a star k-edge coloring is the star chromatic index of G. Deng et al. [5], and Bezegová et al. [1] independently proved that the star chromatic index of a tree is at most ⌊3Δ2⌋, and the bound is sharp. Han et al. [8] strengthened the result to list version of star chromatic index, and proved that ⌊3Δ2⌋ is also the sharp upper bound for the list star chromatic index of trees. A generalized Halin graph is a plane graph that consists of a plane embedding of a tree T with Δ(T)≥3, and a cycle C connecting all the leaves of the tree such that C is the boundary of the exterior face. In this paper, we prove that if H≔T∪C is a generalized Halin graph with |C|≠5, then its list star chromatic index is at mostmax⁡{⌊θ(T)+Δ(T)2⌋,2⌊Δ(T)2⌋+7}, where θ(T)=maxxy∈E(T)⁡{dT(x)+dT(y)}. As a consequence, if H is a (generalized) Halin graph with maximum degree Δ≥13, then the list star chromatic index is at most ⌊3Δ2⌋. Moreover, the upper bound for the list star chromatic index is sharp.