University of Extremadura

About: University of Extremadura is a education organization based out in Badajoz, Spain. It is known for research contribution in the topics: Population & Hyperspectral imaging. The organization has 7856 authors who have published 18299 publications receiving 396126 citations. The organization is also known as: Universidad de Extremadura.

Tip position control of a lightweight flexible manipulator using a fractional order controller

Abstract: A new method to control single-link lightweight flexible manipulators in the presence of payload changes is proposed. Undoubtedly, the control of this kind of structures is nowadays one of the most challenging and attractive research areas, being remarkable its application to the aerospace industry, among others. One of the interesting features of the design method presented here is that the overshoot of the controlled system is independent of the tip mass. This allows a constant safety zone to be delimited for any given placement task of the arm, independent of the load being carried, thereby making it easier to plan collision avoidance. Other considerations about noise and motor saturation issues are also presented. To satisfy this performance, the overall control scheme proposed consists of three nested control loops. Once the friction and other nonlinear effects have been compensated, the inner loop is designed to give a fast motor response. The middle loop simplifies the dynamics of the system and reduces its transfer function to a double integrator. A fractional derivative controller is used to shape the outer loop into the form of a fractional order integrator. The result is a constant phase system with, in the time domain, step responses exhibiting constant overshoot, independent of variations in the load, and robust, in a stability sense, to spillover effects. Experimental results are shown, when controlling the flexible manipulator with this fractional order derivator, that prove the good performance of the system.

Parallel and Distributed Dimensionality Reduction of Hyperspectral Data on Cloud Computing Architectures

Abstract: Cloud computing offers the possibility to store and process massive amounts of remotely sensed hyperspectral data in a distributed way. Dimensionality reduction is an important task in hyperspectral imaging, as hyperspectral data often contains redundancy that can be removed prior to analysis of the data in repositories. In this regard, the development of dimensionality reduction techniques in cloud computing environments can provide both efficient storage and preprocessing of the data. In this paper, we develop a parallel and distributed implementation of a widely used technique for hyperspectral dimensionality reduction: principal component analysis (PCA), based on cloud computing architectures. Our implementation utilizes Hadoop’s distributed file system (HDFS) to realize distributed storage, uses Apache Spark as the computing engine, and is developed based on the map-reduce parallel model, taking full advantage of the high throughput access and high performance distributed computing capabilities of cloud computing environments. We first optimized the traditional PCA algorithm to be well suited for parallel and distributed computing, and then we implemented it on a real cloud computing architecture. Our experimental results, conducted using several hyperspectral datasets, reveal very high performance for the proposed distributed parallel method.

Science in america latina: A comparison of bibliometric and scientific-technical indicators

Abstract: Latin-American scientific achievement is generally under-represented in databases for a number of reasons pointed out in our study. In this paper we analyze Latin-American scientific production in terms of input (resources) and output (publications). The indicators used were: Gross Domestic Product (GDP), economically active population (EAP), percentage of GNP destined to R+D, and total number of researchers dedicated to R+D. These indicators were subjected to bivariant analysis to determine the degree of correlation with the number of ISI publications.

Fate map of the chicken neural plate at stage 4.

Abstract: A detailed fate map was obtained for the early chick neural plate (stages 3d/4). Numerous overlapping plug grafts were performed upon New-cultured chick embryos, using fixable carboxyfluorescein diacetate succinimidyl ester to label donor chick tissue. The specimens were harvested 24 hours after grafting and reached in most cases stages 9-11 (early neural tube). The label was detected immunocytochemically in wholemounts, and cross-sections were later obtained. The positions of the graft-derived cells were classified first into sets of purely neural, purely non-neural and mixed grafts. Comparisons between these sets established the neural plate boundary at stages 3d/4. Further analysis categorized graft contributions to anteroposterior and dorsoventral subdivisions of the early neural tube, including data on the floor plate and the eye field. The rostral boundary of the neural plate was contained within the earliest expression domain of the Ganf gene, and the overall shape of the neural plate was contrasted and discussed with regard to the expression patterns of the genes Plato, Sox2, Otx2 and Dlx5 (and others reported in the literature) at stages 3d/4.