David Álvarez

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— This paper presents a novel robotic learning technique based on Fast Marching Square (F M 2). This method, which we have called FM Learning, is based on incorporating previous experience to the path planning system of the robot by taking into account paths taught to the robot via kinesthetic teaching, this is, guiding manually the robot through the(More)
Group A Streptococcus (GAS) causes human diseases ranging in severity from uncomplicated pharyngitis to life-threatening necrotizing fasciitis and shows high rates of macrolide resistance in several countries. Our goal is to identify antimicrobial resistance in Spanish GAS isolates collected between 1994 and 2006 and to determine the molecular epidemiology(More)
ADHD and Writing learning disabilities: comorbidity in basis of attention and working memory. The aim of this study was to compare the differences between children with ADHD both with and without writing LD (WLD) and those with WLD, in the measurements of different constructs related to ADHD (selective and sustained attention, working memory and cognitive(More)
Sampling-based path planning algorithms are well-known because they are able to find a path in a very short period of time, even in high-dimensional spaces. However, they are non-smooth, random paths far away from the optimum. In this paper we introduce a novel improving technique based on the Fast Marching Method which improves in a deterministic,(More)
The Fast Marching Method is a very popular algorithm to compute times-of-arrival maps (distances map measured in time units). Since their proposal in 1995, it has been applied to many different applications such as robotics, medical computer vision, fluid simulation, etc. Many alternatives have been proposed with two main objectives: to reduce its(More)
In organisms such as fish, where body size is considered an important state variable for the study of their population dynamics, size-specific growth and survival rates can be influenced by local variation in both biotic and abiotic factors, but few studies have evaluated the complex relationships between environmental variability and size-dependent(More)