No abstract

In this paper, we focus on the parameter estimation of dynamic state-space models using privacy-protected data. We consider an scenario with two parties: on one side, the data owner, which provides privacy-protected observations to, on the other side, an algorithm owner, that processes them to learn the system's state vector. We combine additive homomorphic encryption and Secure Multiparty Computation protocols to develop secure functions (multiplication, division, matrix inversion) that keep all the intermediate values encrypted in order to effectively preserve the data privacy. As an application, we consider a tracking problem, in which a Extended Kalman Filter estimates the position, velocity and acceleration of a moving target in a collaborative environment where encrypted distance measurements are used.

No abstract

A systematic approach to obtain mixed order curlconforming basis functions for a triangular prism is presented; focus is made on the second-order case. Space of functions for the prism is given. Basis functions are obtained as dual basis with respect to properly discretized Nédélec degrees of freedom functionals acting on elements of the space. Thus, the linear independence of the basis functions is assured while the belonging of the basis to the a-priori given space of functions is guaranteed. Different strategies for the finite element assembly of the basis are discussed. Numerical results showing the verification procedure of the correctness of the implemented basis functions are given. Numerical results about sensibility with respect to quality of the elements of the mesh of the condition number of the basis obtained are also shown. Comparison with other representative sets of basis functions for prisms are included.

No abstract

Finite element method (FEM) has been used for years for radiation problems in the field of electromagnetism. To tackle problems of this kind, mesh truncation techniques are required, which may lead to the use of high computational resources. In fact, electrically large radiation problems can only be tackled using massively parallel computational resources. Different types of multi-core machines are commonly employed in diverse fields of science for accelerating a number of applications. However, properly managing their computational resources becomes a very challenging task. On the one hand, we present a hybrid message passing interface + OpenMP-based acceleration of a mesh truncation technique included in a FEM code for electromagnetism in a high-performance computing cluster equipped with 140 compute nodes. Results show that we obtain about 85% of the theoretical maximum speedup of the machine. On the other hand, a graphics processing unit has been used to accelerate one of the parts that presents high fine-grain parallelism.

No abstract

No abstract