An Eulerian approach for constructing a map between surfaces with different topologies

3D objects of the same kind often have different topologies, and finding correspondence between them is important for operations such as morphing, attribute transfer, and shape matching. This paper presents a novel method to find the surface correspondence between topologically different surfaces. The method is characterized by deforming the source polygonal mesh to match the target mesh by using the intermediate implicit surfaces, and by performing a topological surgery at the appropriate locations on the mesh. In particular, we propose a mathematically well‐defined way to detect the topology change of surface by finding the non‐degenerate saddle points of the velocity fields that tracks implicit surfaces. We show the effectiveness and possible applications of the proposed method through several experiments.     

From transport to diffusion through a space asymptotic approach

The spatially asymptotic theory is a useful approach to the neutron transport model for nuclear reactor physics applications. For steady-state problems the transport equation is taken in an infinite medium and it is treated by the Fourier transform. A formal solution is thus obtained for any assumption on the order of anisotropy, leading to the _BN$B_N$ formulation. In the case of isotropic emissions the Green function of the problem can be given an explicit expression by the inverse Fourier transformation, leading to the solution that can also be obtained by Case method.     

An evolving approach to unsupervised and Real-Time fault detection in industrial processes

Fault detection in industrial processes is a field of application that has gaining considerable attention in the past few years, resulting in a large variety of techniques and methodologies designed to solve that problem. However, many of the approaches presented in literature require relevant amounts of prior knowledge about the process, such as mathematical models, data distribution and pre-defined parameters. In this paper, we propose the application of TEDA – Typicality and Eccentricity Data Analytics – , a fully autonomous algorithm, to the problem of fault detection in industrial processes. In order to perform fault detection, TEDA analyzes the density of each read data sample, which is calculated based on the distance between that sample and all the others read so far. TEDA is an online algorithm that learns autonomously and does not require any previous knowledge about the process nor any user-defined parameters. Moreover, it requires minimum computational effort, enabling its use for real-time applications. The efficiency of the proposed approach is demonstrated with two different real world industrial plant data streams that provide “normal” and “faulty” data. The results shown in this paper are very encouraging when compared with traditional fault detection approaches.     

An approach to optimization in transport logistics

A new approach to some optimization problems arising in the transport logistics was proposed. Consideration was given to the fundamental problems of the today logistics such as the problem of optimal arrangement and that of identification and segmentation of the logistic zones. They are solved using the “wave” method which relies on the analogy between the determination of the global extremum of the integral functional and propagation of light in an optically inhomogeneous medium. A numerical algorithm was developed, and the results of calculations presented.     

An efficient system using implicit feedback and lifelong learning approach to improve recommendation

The Journal of Supercomputing - This paper presents a new technique for contextual item-to-item Collaborative Filtering-based Recommender System, an improved version popularised by...     

An architectural approach to the correct and automatic assembly of evolving component-based systems

Software components are specified, designed and implemented with the intention to be reused, and they are assembled in various contexts in order to produce a multitude of software systems. However, in the practice of software development, this ideal scenario is often unrealistic. This is mainly due to the lack of an automatic and efficient support to predict properties of the assembly code by only assuming a limited knowledge of the properties of single components. Moreover, to make effective the component-based vision, the assembly code should evolve when things change, i.e., the properties guaranteed by the assembly, before a change occurs, must hold also after the change. Glue code synthesis approaches technically permit one to construct an assembly of components that guarantees specific properties but, practically, they may suffer from the state-space explosion phenomenon.In this paper, we propose a Software Architecture (SA) based approach in which the usage of the system SA and of SA verification techniques allows the system assembler to design architectural components whose interaction is verified with respect to the specified properties. By exploiting this validation, the system assembler can perform code synthesis by only focusing on each single architectural component, hence refining it as an assembly of actual components which respect the architectural component observable behaviour. In this way code synthesis is performed locally on each architectural component, instead of globally on the whole system interactions, hence reducing the state-space explosion phenomenon.The approach can be equally well applied to efficiently manage the whole reconfiguration of the system when one or more components need to be updated, still maintaining the required properties. The specified and verified system SA is used as starting point for the derivation of glue adaptors that are required to apply changes in the composed system. The approach is firstly illustrated over an explanatory example and is then applied and validated over a real-world industrial case study.     

An Eulerian–Lagrangian approach for simulating explosions of energetic devices

An approach for the simulation of explosions of “energetic devices” is described. In this context, an energetic device is a metal container filled with a high explosive (HE). Examples include bombs, mines, rocket motors or containers used in storage and transport of HE material. Explosions may occur due to detonation or deflagration of the HE material, with initiation resulting from either mechanical or thermal input. This approach is applicable to a wide range of fluid–structure interaction scenarios, the application to energetic devices is chosen because it demonstrates the full capability of this methodology.Simulations of this type are characterized by a number of interesting and challenging behaviors. These include the transformation of the solid HE into highly pressurized gaseous products that initially occupy regions which formerly contained only solid material. This rapid pressurization of the container leads to large deformations at high strain rates and eventual case rupture. Once the container breaks apart, the highly pressurized product gas that escapes the failing container generates shock waves that propagate through the initially quiescent surrounding fluid.The approach, which uses a finite-volume, multi-material compressible CFD formulation, within which solid materials are represented using a particle method known as the Material Point Method, is described, including certain of the sub-grid models required to close the governing equations. Results are first presented for “rate stick” and “cylinder test” scenarios, each of which involves detonating unconfined and confined HE material, respectively. Experimental data are available for these configurations and as such they serve as validation tests. Finally, results from an unvalidated “fast cookoff” simulation in which the HE is initiated by thermal input, which causes deflagration, are shown.     

An enhanced opinion retrieval approach via implicit feature identification

Journal of Intelligent Information Systems - Recently, there has been an enormous increase in the number of reviews of popular products. Therefore, opinion analysis has become a tedious task for...     

Shape and tone depiction for implicit surfaces

We present techniques for rendering implicit surfaces in different pen-and-ink styles. The implicit models are rendered using point-based primitives to depict shape and tone using silhouettes with hidden-line attenuation, drawing directions, and stippling. We present sample renderings obtained for a variety of models. Furthermore, we describe simple and novel methods to control point placement and rendering style. Our approach is implemented using HRBF Implicits, a simple and compact representation, that has three fundamental qualities: a small number of point-normal samples as input for surface reconstruction, good projection of points near the surface, and smoothness of the gradient field. These qualities of HRBF Implicits are used to generate a robust distribution of points to position the drawing primitives.     

An image segmentation approach on improved implicit surface model in straddle strategy

Multimedia Tools and Applications - At present, some experts and scholars do not explicitly mention the static model in the analysis of the straddle strategy, which leads to the research results...     

An Eulerian approach for large displacements of thin shells including geometrical non-linearities

This paper is devoted to the problem of large displacement of shells, the only non-linearity being geometrical. The geometry of the mid-surface of the shell is determined thanks to the knowledge of nodes and normal vectors, and is continuously updated. Stresses are also carried from one configuration to another, which enables us to linearize the equilibrium equations. It is then possible to build an Eulerian formulation. Moreover, some control strategies are proposed, in order to find limit points and unstable solutions. Finally, we check in some classical examples, the accuracy of this technique.     

Interactive modeling of implicit surfaces using a direct visualization approach with signed distance functions

Modeling appealing virtual scenes is an elaborate and time-consuming task, requiring not only training and experience, but also powerful modeling tools providing the desired functionality to the user. In this paper, we describe a modeling approach using signed distance functions as an underlying representation for objects, handling both conventional and complex surface manipulations. Scenes defined by signed distance functions can be stored compactly and rendered directly in real-time using sphere tracing. Hence, we are capable of providing an interactive application with immediate visual feedback for the artist, which is a crucial factor for the modeling process. Moreover, dealing with underlying mathematical operations is not necessary on the user level. We show that fundamental aspects of traditional modeling can be directly transferred to this novel kind of environment, resulting in an intuitive application behavior, and describe modeling operations which naturally benefit from implicit representations. We show modeling examples where signed distance functions are superior to explicit representations, but discuss the limitations of this approach as well.     

Orthogonal distance fitting of implicit curves and surfaces

Dimensional model fitting finds its applications in various fields of science and engineering and is a relevant subject in computer/machine vision and coordinate metrology. In this paper, we present two new fitting algorithms, distance-based and coordinate-based algorithm, for implicit surfaces and plane curves, which minimize the square sum of the orthogonal error distances between the model feature and the given data points. Each of the two algorithms has its own advantages and is to be purposefully applied to a specific fitting task, considering the implementation and memory space cost, and possibilities of observation weighting. By the new algorithms, the model feature parameters are grouped and simultaneously estimated in terms of form, position, and rotation parameters. The form parameters determine the shape of the model feature and the position/rotation parameters describe the rigid body motion of the model feature. The proposed algorithms are applicable to any kind of implicit surface and plane curve. In this paper, we also describe algorithm implementation and show various examples of orthogonal distance fit     

Fitting curves and surfaces with constrained implicit polynomials

A problem which often arises while fitting implicit polynomials to 2D and 3D data sets is the following: although the data set is simple, the fit exhibits undesired phenomena, such as loops, holes, extraneous components, etc. Previous work tackled these problems by optimizing heuristic cost functions, which penalize some of these topological problems in the fit. The paper suggests a different approach-to design parameterized families of polynomials whose zero-sets are guaranteed to satisfy certain topological properties. Namely, we construct families of polynomials with star-shaped zero-sets, as well as polynomials whose zero-sets are guaranteed not to intersect an ellipse circumscribing the data or to be entirely contained in such an ellipse. This is more rigorous than using heuristics which may fail and result in pathological zero-sets. The ability to parameterize these families depends heavily on the ability to parameterize positive polynomials. To achieve this, we use some powerful results from real algebraic geometry     

基于Potts模型的隐式曲面上的图像分割方法

针对隐式曲面上多相图像分割的问题,基于曲面的隐式表达、隐式曲面上的内蕴梯度等概念,将用于平面图像分割的Potts模型推广.首先对于隐式封闭曲面和隐式开放曲面,分别给出Potts模型的推广形式.然后对于传统梯度降方法计算效率低的问题,为曲面上的Potts模型设计了Split Bregman算法和对偶方法,并在对偶方法的基础上提出了一种改进的快速算法.多个数值实验结果表明,所提出的曲面上的Potts模型能有效地分割闭/开曲面上的分段常值图像,并且新的改进对偶方法在计算效率方面优于其他两种方法.     

Reply to comments on 'A computational evolutionary approach to evolving game strategy and Cooperation'

This is a reply to the comment by H.-C. Wu and C.-T. Sun on the paper "A Computational Evolutionary Approach to Evolving Game Strategies and Cooperation." Key design problems, limitations and potential applications are discussed.     

A computational evolutionary approach to evolving game strategy and cooperation

This paper describes an approach to the co-evolution of competing virtual creatures. Pairs of individuals enter one-on-one contests in which they contend to establish contact with a common resource. The individuals are subjected to competitive fitness functions. In each tournament one type of organism implements a game rule based on a set of basic cognitive capabilities. The second type of contestant genetically determines its game strategy. Interesting strategy patterns are identified when this evolutionary process is simulated on populations of competing individuals. These experiments show how cooperation emerges in order to improve both individual and collective game performances.