Los edificios de paneles más altos de España

RESUMEN Este artículo describe el proceso constructivo de un conjunto de 484 viviendas realizadas con paneles prefabricados portantes de hormigón. Dicho conjunto edi¿catorio, de 20 plantas de altura, se compone de diversos bloques que integran además, locales comerciales, o¿cinas, trasteros, 4 plantas de garaje e instalaciones comunes. El principal interés de este edi¿cio consiste en haber alcanzado veinte plantas sobre rasante y 4 más de sótano con el sistema constructivo de paneles prefabricados de hormigón INDAGSA; el cual dispone de un Documento de Idoneidad Técnica emitido por el IETcc, con el número DIT 452. Las obras de INDAGSA son conocidas por ser precisas, ordenadas y limpias; debido a estas características, se pudieron establecer visitas no sólo para doctorandos de la ETSAM, sino para estudiantes de la Cátedra de sistemas industrializados y prefabricados. A través de la descripción del sistema constructivo, podremos mostrar una perspectiva global de las posibilidades de los sistemas de paneles prefabricados de hormigón y las capacidades evolutivas de éstos

Dos estrategias de búsqueda anytime basadas en programación lineal entera para resolver el problema de selección de requisitos

El problema de selección de requisitos (o Next Release Problem, NRP) consiste en seleccionar el subconjunto de requisitos que se va a desarrollar en la siguiente versión de una aplicación software. Esta selección se debe hacer de tal forma que maximice la satisfacción de las partes interesadas a la vez que se minimiza el esfuerzo empleado en el desarrollo y se cumplen un conjunto de restricciones. Trabajos recientes han abordado la formulación bi-objetivo de este problema usando técnicas exactas basadas en resolutores SAT y resolutores de programación lineal entera. Ambos se enfrentan a dificultades cuando las instancias tienen un gran tamaño, sin embargo la programación lineal entera (ILP) parece ser más efectiva que los resolutores SAT. En la práctica, no es necesario calcular todas las soluciones del frente de Pareto (que pueden llegar a ser muchas) y basta con obtener un buen número de soluciones eficientes bien distribuidas en el espacio objetivo. Las estrategias de búsqueda basadas en ILP que se han utilizado en el pasado para encontrar un frente bien distribuido en cualquier instante de tiempo solo buscan soluciones soportadas. En este trabajo proponemos dos estrategias basadas en ILP que son capaces de encontrar el frente completo con suficiente tiempo y que, además, tienen la propiedad de aportar un conjunto de soluciones bien distribuido en el frente objetivo en cualquier momento de la búsqueda.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Ministerio de Economía y Competitividad mediante la red TIN2015-71841-REDT y el proyecto TIN2014-57341-R

OBOE: an Explainable Text Classification Framework

Explainable Artificial Intelligence (XAI) has recently gained visibility as one of the main topics of Artificial Intelligence research due to, among others, the need to provide a meaningful justification of the reasons behind the decision of black-box algorithms. Current approaches are based on model agnostic or ad-hoc solutions and, although there are frameworks that define workflows to generate meaningful explanations, a text classification framework that provides such explanations considering the different ingredients involved in the classification process (data, model, explanations, and users) is still missing. With the intention of covering this research gap, in this paper we present a text classification framework called OBOE (explanatiOns Based On concEpts), in which such ingredients play an active role to open the black-box. OBOE defines different components whose implementation can be customized and, thus, explanations are adapted to specific contexts. We also provide a tailored implementation to show the customization capability of OBOE. Additionally, we performed (a) a validation of the implemented framework to evaluate the performance using different corpora and (b) a user-based evaluation of the explanations provided by OBOE. The latter evaluation shows that the explanations generated in natural language express the reason for the classification results in a way that is comprehensible to non-technical users

Separation of the optical and mass features of particle components in different aerosol mixtures by using POLIPHON retrievals in synergy with continuous polarized Micro-Pulse Lidar (P-MPL) measurements

The application of the POLIPHON (POlarization-LIdar PHOtometer Networking) method is presented for the first time in synergy with continuous 24/7 polarized Micro-Pulse Lidar (P-MPL) measurements to derive the vertical separation of two or three particle components in different aerosol mixtures, and the retrieval of their particular optical properties. The procedure of extinction-to-mass conversion, together with an analysis of the mass extinction efficiency (MEE) parameter, is described, and the relative mass contribution of each aerosol component is also derived in a further step. The general POLIPHON algorithm is based on the specific particle linear depolarization ratio given for different types of aerosols and can be run in either 1-step (POL-1) or 2 steps (POL-2) versions with dependence on either the 2- or 3-component separation. In order to illustrate this procedure, aerosol mixing cases observed over Barcelona (NE Spain) are selected: a dust event on 5 July 2016, smoke plumes detected on 23 May 2016 and a pollination episode observed on 23 March 2016. In particular, the 3-component separation is just applied for the dust case: a combined POL-1 with POL-2 procedure (POL-1/2) is used, and additionally the fine-dust contribution to the total fine mode (fine dust plus non-dust aerosols) is estimated. The high dust impact before 12:00UTC yields a mean mass loading of 0.6±0.1gm-2 due to the prevalence of Saharan coarse-dust particles. After that time, the mean mass loading is reduced by two-thirds, showing a rather weak dust incidence. In the smoke case, the arrival of fine biomass-burning particles is detected at altitudes as high as 7km. The smoke particles, probably mixed with less depolarizing non-smoke aerosols, are observed in air masses, having their origin from either North American fires or the Arctic area, as reported by HYSPLIT back-trajectory analysis. The particle linear depolarization ratio for smoke shows values in the 0.10–0.15 range and even higher at given times, and the daily mean smoke mass loading is 0.017±0.008gm-2, around 3% of that found for the dust event. Pollen particles are detected up to 1.5km in height from 10:00UTC during an intense pollination event with a particle linear depolarization ratio ranging between 0.10 and 0.15. The maximal mass loading of Platanus pollen particles is 0.011±0.003gm-2, representing around 2% of the dust loading during the higher dust incidence. Regarding the MEE derived for each aerosol component, their values are in agreement with others referenced in the literature for the specific aerosol types examined in this work: 0.5±0.1 and 1.7±0.2m2g-1 are found for coarse and fine dust particles, 4.5±1.4m2g-1 is derived for smoke and 2.4±0.5m2g-1 for non-smoke aerosols with Arctic origin, and a MEE of 2.4±0.8m2g-1 is obtained for pollen particles, though it can reach higher or lower values depending on predominantly smaller or larger pollen grain sizes. Results reveal the high potential of the P-MPL system, a simple polarization-sensitive elastic backscatter lidar working in a 24/7 operation mode, to retrieve the relative optical and mass contributions of each aerosol component throughout the day, reflecting the daily variability of their properties. In fact, this procedure can be simply implemented in other P-MPLs that also operate within the worldwide Micro-Pulse Lidar Network (MPLNET), thus extending the aerosol discrimination at a global scale. Moreover, the method has the advantage of also being relatively easily applicable to space-borne lidars with an equivalent configuration such as the ongoing Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) on board NASA CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) and the forthcoming Atmospheric Lidar (ATLID) on board the ESA EarthCARE mission.Peer ReviewedPostprint (published version