A Support Vector Machine (SVM) is an effective method for pedestrian detection
applications; however, performance of an SVM is closely related to the samples that are …

We address the development of innovative algorithms designed to solve the strong-
constraint Four Dimensional Variational Data Assimilation (4DVar DA) problems in large …

We introduce a decomposition of the Tikhonov Regularization (TR) functional which split this
operator into several TR functionals, suitably modified in order to enforce the matching of …

Modern graphics processing units (GPUs) have been at the leading edge of increasing
parallelism over the last 10 years. This fact has encouraged the use of GPUs in a broader …

We present a numerical algorithm for solving large scale Tikhonov Regularization problems.
The approach we consider introduces a splitting of the regularization functional which uses …

We present an innovative approach for solving Four Dimensional Variational Data
Assimilation (4D-VAR DA) problems. The approach we consider starts from a decomposition …

Matrix multiplication (MM) is a computationally-intensive operation in many algorithms used
in scientific computations. Not only one of the kernels in numerical linear algebra, the …

In this work, a parallel adaptive algorithm for the computation of a multidimensional integral
on heterogeneous GPU and multicore based systems is described. Two different strategies …

Heap-based priority queues are very common dynamical data structures used in several
fields, ranging from operating systems to scientific applications. However, the rise of new …

Multiresolution streamline placement is useful for interactive visualization of flow fields. In
this paper, a new method is proposed to build placements of streamlines in different …