Política pública en el desarrollo de la juventud rural

La política pública es fundamental para cumplir con el propósito de atender los problemas colectivos a través de la negociación colectiva. En el medio rural se expresa en toda su amplitud, como agenda de formulación, de ejecución y de evaluación ajena a los actores municipales. De esta forma, este artículo tiene como objetivo comprobar los procesos, condiciones y efectos que genera en la población que las recibe, las acepta y se adapta a ellas. Desde el enfoque territorial, se encontró que la política pública y algunos programas dirigidos a los jóvenes, se centran en la juventud urbana; mientras que los jóvenes rurales desconocen las políticas públicas y los programas que son creados o aplicados a ellos. Las instancias de gobierno municipal, registran una falta de atención a los jóvenes, por la escases de estructura administrativa y de recursos económicos, que profundizan la ausencia de coordinación y comunicación entre los tres niveles de gobierno y la sociedad civil; causando que la duplicidad de programas con recursos limitados e insuficientes se sumen a los demás factores que limitan la atención de los jóvenes de la Sierra Norte de Puebla.

A study of a soft computing based method for 3D scenario reconstruction

Several recent works deal with 3D data in mobile robotic problems, e.g., mapping. Data comes from any kind of sensor (time of flight, Kinect or 3D lasers) that provide a huge amount of unorganized 3D data. In this paper we detail an efficient approach to build complete 3D models using a soft computing method, the Growing Neural Gas (GNG). As neural models deal easily with noise, imprecision, uncertainty or partial data, GNG provides better results than other approaches. The GNG obtained is then applied to a sequence. We present a comprehensive study on GNG parameters to ensure the best result at the lowest time cost. From this GNG structure, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm. Final results of 3D mapping are also shown.

GPGPU implementation of growing neural gas: application to 3D scene reconstruction

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6× compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.

Sentiment classification for early detection of health alerts in the chemical textile domain

In the chemical textile domain experts have to analyse chemical components and substances that might be harmful for their usage in clothing and textiles. Part of this analysis is performed searching opinions and reports people have expressed concerning these products in the Social Web. However, this type of information on the Internet is not as frequent for this domain as for others, so its detection and classification is difficult and time-consuming. Consequently, problems associated to the use of chemical substances in textiles may not be detected early enough, and could lead to health problems, such as allergies or burns. In this paper, we propose a framework able to detect, retrieve, and classify subjective sentences related to the chemical textile domain, that could be integrated into a wider health surveillance system. We also describe the creation of several datasets with opinions from this domain, the experiments performed using machine learning techniques and different lexical resources such as WordNet, and the evaluation focusing on the sentiment classification, and complaint detection (i.e., negativity). Despite the challenges involved in this domain, our approach obtains promising results with an F-score of 65% for polarity classification and 82% for complaint detection.

An overview of the Applications of Natural Language to Information Systems

This introduction provides an overview of the state-of-the-art technology in Applications of Natural Language to Information Systems. Specifically, we analyze the need for such technologies to successfully address the new challenges of modern information systems, in which the exploitation of the Web as a main data source on business systems becomes a key requirement. It will also discuss the reasons why Human Language Technologies themselves have shifted their focus onto new areas of interest very directly linked to the development of technology for the treatment and understanding of Web 2.0. These new technologies are expected to be future interfaces for the new information systems to come. Moreover, we will review current topics of interest to this research community, and will present the selection of manuscripts that have been chosen by the program committee of the NLDB 2011 conference as representative cornerstone research works, especially highlighting their contribution to the advancement of such technologies.

Albaceteplural: perspectiva de género y gestión de la participación en un plan de ordenación municipal

La incorporación de la perspectiva de género al planeamiento es una obligación de las administraciones públicas españolas, nacionales, autonómicas y locales. El ayuntamiento de Albacete y la Junta de Comunidades de Castilla La Mancha, en cumplimiento de estos preceptos y en ocasión de la revisión del Plan General de Ordenación Urbana, encargan a la autora del presente artículo la dirección de los equipos de trabajo para la gestión de la participación ciudadana, que se sitúa en la base misma de la consecución de los objetivos propuestos. El trabajo presentado se centra en la experiencia metodológica de la participación in situ, en la investigación que la sustentó y en las innovaciones que aporta. Se exponen los mecanismos e instrumentos habilitados para la participación que, habida cuenta de la casi total ausencia de referencias en España, constituyen una primera aproximación de posibles buenas prácticas a aplicar en otros proyectos similares.

Enantioselective Michael addition of isobutyraldehyde to nitroalkenes organocatalyzed by chiral primary amine-guanidines

Primary amine-guanidines derived from trans-cyclohexane-1,2-diamines are used as organocatalysts for the enantioselective conjugate addition of isobutyraldehyde to arylated and heteroarylated nitroalkenes. The reaction was performed in the presence of imidazole as the additive in aqueous DMF as the solvent at 0 °C. The corresponding Michael adducts bearing a new stereocenter were obtained in high yields and with enantioselectivities of up to 80%. Theoretical calculations are used to justify the observed sense of the stereoinduction.

Reduction of emerging micropollutants, organic matter, nutrients and salinity from real wastewater by combined MBR–NF/RO treatment

To study the possibility of producing better water quality from municipal wastewater, a membrane bioreactor (MBR) pilot plant with flat sheet (FS) and hollow fiber (HF) membranes coupled with another pilot plant equipped with nanofiltration (NF)/reverse osmosis (RO) membranes were operated to treat municipal wastewater from the wastewater treatment plant (WWTP) Rincón de León, Alicante (Spain). This study was focused on improving the quality of the permeate obtained from the MBR process when complemented by NF or RO stages with respect to salinity, organic matter and nutrients. Furthermore, the removal efficiencies of 10 EMPs were evaluated, comparing the reductions achieved between the wastewater treatment by MBR (adsorption to sludge and biodegradation) and the later treatment using NF or RO (mainly size exclusion). The results showed that the high quality of water was obtained which is appropriate for reuse with salinity removal efficiencies higher than 97%, 96% for total organic carbon (TOC), 91% for nitrates View the MathML sourceNO3- and 99% for total phosphorous (TP). High removal efficiencies were obtained for the majority of the analyzed EMP compounds.