A dirichlet process elaboration diagnostic for binomial goodness of fit

Useful model checking tools can be constructed by measuring the distance between a prior distribution that concentrates most of its mass around a model of interest, and the resulting posterior distribution. In this paper we use this approach to construct a diagnostic measure for detecting lack of fit in discrete data, with special focus on binomial data. We begin by constructing a suitable probability model “around” the model of interest, via a Dirichlet Process elaboration. We derive the resulting diagnostic and show that, approximately, it is the sum of two terms: the first is the logarithm of the Bayes factor and the second is proportional to the Pearson chi-square statistics. We give details of a simulation algorithm for computing the diagnostic and illustrate its use in an application to biomedical data.     

Comparative investigation of GPU-accelerated triangle-triangle intersection algorithms for collision detection

Efficient collision detection is critical in 3D geometric modeling. In this paper, we first implement three parallel triangle-triangle intersection algorithms on a GPU and then compare the computational efficiency of these three GPU-accelerated parallel triangle-triangle intersection algorithms in an application that detects collisions between triangulated models. The presented GPU-based parallel collision detection method for triangulated models has two stages: first, we propose a straightforward and efficient parallel approach to reduce the number of potentially intersecting triangle pairs based on AABBs, and second, we conduct intersection tests with the remaining triangle pairs in parallel based on three triangle-triangle intersection algorithms, i.e., the Möller’s algorithm, Devillers’ and Guigue’s algorithm, and Shen’s algorithm. To evaluate the performance of the presented GPU-based parallel collision detection method for triangulated models, we conduct four groups of benchmarks. The experimental results show the following: (1) the time required to detect collisions for the triangulated model consisting of approximately 1.5 billion triangle pairs is less than 0.5 s; (2) the GPU-based parallel collision detection method speedup over the corresponding serial version is 50x - 60x, and (3) Devillers’ and Guigue’s algorithm is comparatively and comprehensively the best of the three GPU-based parallel triangle-triangle intersection algorithms. The presented GPU-accelerated method is capable of efficiently detecting the potential collisions of triangulated models. Overall, the GPU-accelerated parallel Devillers’ and Guigue’s triangle-triangle intersection algorithm is recommended when performing practical collision detections between large triangulated models.

     

Lessons learned from longitudinal modeling of mobile-equipped visitors in a complex museum

Neural Computing and Applications - Cultural sites are evolving toward smart environments, including the notion of hyper-connected museums. In this context, stakeholders of cultural assets need...     

Efficiency,effectiveness, and impacts assessment in the rail transport sector: a state‐of‐the‐art critical analysis of current research

This paper aims at being a comprehensive reference for stakeholders, policy makers, and scholars interested in analyzing the problem of efficiency, effectiveness, and impacts of rail transport systems in a sound empirical way, paying specific attention to passenger transport services. The paper combines different analytical frameworks (engineering, economics, impacts), systematic review techniques, and advanced mappings. Framing economic efficiency studies into a transport planning perspective permits to move from efficiency to effectiveness issues. In addition, including impacts offers a critical discussion of the existing empirical studies, relating them to the main methodological approaches used. This analysis can be useful for those interested in developing new techniques for the evaluation of this sector. The critical analysis developed in this paper provides a catalog of inputs, outputs, external factors, possible impacts to account for, data, and approaches, which allows us to identify areas in which new methodological developments, new approaches, are needed to address the relevant societal challenges of the rail transport sector.     

The numerical solution of fractional differential equations using the Volterra integral equation method based on thin plate splines

Finding the approximate solution of differential equations, including non-integer order derivatives, is one of the most important problems in numerical fractional calculus. The main idea of the current paper is to obtain a numerical scheme for solving fractional differential equations of the second order. To handle the method, we first convert these types of differential equations to linear fractional Volterra integral equations of the second kind. Afterward, the solutions of the mentioned Volterra integral equations are estimated using the discrete collocation method together with thin plate splines as a type of free-shape parameter radial basis functions. Since the scheme does not need any background meshes, it can be recognized as a meshless method. The proposed approach has a simple and computationally attractive algorithm. Error analysis is also studied for the presented method. Finally, the reliability and efficiency of the new technique are tested over several fractional differential equations and obtained results confirm the theoretical error estimates.

     

Verifying data secure flow in AUTOSAR models

This paper presents an approach for enhancing the design phase of AUTOSAR models when security annotations are required. The approach is based on information flow analysis and abstract interpretation. The analysis evaluates the correctness of the model by assessing if the flow of data is secure with respect to causal data dependencies within the model. To find these dependencies an exhaustive search through the model would be required. Abstract interpretation is used as a trade-off between the precision and complexity of the analysis. The approach also provides annotated models without oversizing the set of annotations.     

Bias extension test for pantographic sheets: numerical simulations based on second gradient shear energies

We consider a bi-dimensional sheet consisting of two orthogonal families of inextensible fibres. Using the representation due to Rivlin and Pipkin for admissible placements, i.e. placements preserving the lengths of the inextensible fibres, we numerically simulate a standard bias extension test on the sheet, solving a non-linear constrained optimization problem. Several first and second gradient deformation energy models are considered, depending on the shear angle between the fibres and on its gradient, and the results obtained are compared. The proposed numerical simulations will be helpful in designing a systematic experimental campaign aimed at characterizing the internal energy for physical realizations of the ideal pantographic structure presented in this paper.     

SRAM-Based FPGA Systems for Safety-Critical Applications：A Survey on Design Standards and Proposed Methodologies

As the ASIC design cost becomes affordable only for very large-scale productions, the FPGA technology is currently becoming the leading technology for those applications that require a small-scale prod...     

Nonlinear Galerkin methods for a system of PDEs with Turing instabilities

We address and discuss the application of nonlinear Galerkin methods for the model reduction and numerical solution of partial differential equations (PDE) with Turing instabilities in comparison with standard (linear) Galerkin methods. The model considered is a system of PDEs modelling the pattern formation in vegetation dynamics. In particular, by constructing the approximate inertial manifold on the basis of the spectral decomposition of the solution, we implement the so-called Euler–Galerkin method and we compare its efficiency and accuracy versus the linear Galerkin methods. We compare the efficiency of the methods by (a) the accuracy of the computed bifurcation points, and, (b) by the computation of the Hausdorff distance between the limit sets obtained by the Galerkin methods and the ones obtained with a reference finite difference scheme. The efficiency with respect to the required CPU time is also accessed. For our illustrations we used three different ODE time integrators, from the Matlab ODE suite. Our results indicate that the performance of the Euler–Galerkin method is superior compared to the linear Galerkin method when either explicit or linearly implicit time integration scheme are adopted. For the particular problem considered, we found that the dimension of approximate inertial manifold is strongly affected by the lenght of the spatial domain. Indeeed, we show that the number of modes required to accurately describe the long time Turing pattern forming solutions increases as the domain increases.