Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods

This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Convolutional layers and Spatial Transformer Networks. Such trials are built to measure the impact of diverse factors with the end goal of designing a Convolutional Neural Network that can improve the state-of-the-art of traffic sign classification task. First, different adaptive and non-adaptive stochastic gradient descent optimisation algorithms such as SGD, SGD-Nesterov, RMSprop and Adam are evaluated. Subsequently, multiple combinations of Spatial Transformer Networks placed at distinct positions within the main neural network are analysed. The recognition rate of the proposed Convolutional Neural Network reports an accuracy of 99.71% in the German Traffic Sign Recognition Benchmark, outperforming previous state-of-the-art methods and also being more efficient in terms of memory requirements.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-RMinisterio de Economía y Competitividad TIN2013-46801-C4-1-

Detecting Social Interactions in Working Environments Through Sensing Technologies

The knowledge about social ties among humans is important to optimize several aspects concerning networking in mobile social networks. Generally, ties among people are detected on the base of proximity of people. We discuss here how ties concerning colleagues in an office can be detected by leveraging on a number of sociological markers like co-activity, proximity, speech activity and similarity of locations visited. We present the results from two data gathering campaigns located in Italy and Spain.Ministerio de Economía y Competitividad TIN2013-46801-C4-1-RJunta de Andalucía TIC-805

City-Friendly Smart Network Technologies and Infrastructures: The Spanish Experience

Efficient, resilient, and sustainable electricity delivery is a key cornerstone in increasingly large and complex urban environments, where citizens expect to keep or rise their living standards. In this context, cost-effective and ubiquitous digital technologies are driving the transformation of existing electrical infrastructures into truly smart systems capable of better providing the services a low-carbon society is demanding. The goal of this paper is twofold: 1) to review the dramatically evolving landscape of power systems, from the old framework based on centralized generation and control, aimed at serving inelastic customers through alternating current (ac) transmission networks and one-way distribution feeders, to a new paradigm centered mainly around two main axes: renewable generation, both centralized and distributed, and active customers (prosumers), interacting with each other through hybrid ac/dc smart grids; 2) to illustrate, through featured success stories, how several smart grid concepts and technologies have been put into practice in Spain over the last few years to optimize the performance of urban electrical assets

Effect of feeding lactating ewes with <i>Moringa oleifera</i> leaf extract on milk yield, milk composition and preweaning performance of ewe/lamb pair

The objective this study was to evaluate the effect of different doses of Moringa oleifera leaf extract (MOE) on milk production and milk composition in ewes and on preweaning performance of their lambs. Twenty-four lactating ewes were housed individually with their lambs and assigned to four groups in a completely randomized design. The treatments included a basal diet without MOE (MOE0) or a basal diet supplemented with either 20 mL MOE per ewe per day (MOE20), 40 mL MOE per ewe per day (MOE40) or 60 mL MOE per ewe per day (MOE60). Over 45 days, milk production was recorded weekly and individual milk samples were collected for chemical analysis. Milk yield, fat-corrected milk and daily yields were similar among the four treatments. The supply of MOE did not affect ewe weaning efficiency and average daily gain or litter weaning weight of the lambs. Overall, the results from this study showed that dietary supplementation of hydroalcoholic extracts of Moringa oleifera leaves at doses of 20, 40 or 60 mL/ewes/d in lactating ewes does not have negative effects on milk yield, milk composition or lamb performance

Plataforma para gestión de información de ciudadanos de una SmartCity

JARCA 2015: Actas de las XVII Jornadas de ARCA: Sistemas Cualitativos y sus Aplicaciones en Diagnosis, Robótica, Inteligencia Ambiental y Ciudades Inteligentes = Proceedings of the XVII ARCA Days: Qualitative Systems and its Applications in Diagnose Robotics, Ambient Intelligence and Smart Cities, Vinaros (Valencia), 23 al 27 de Junio de 2015El aumento de la población en áreas urbanas y el ritmo de vida cada vez más sedentario es una preocupación creciente. Por otra parte, los avances tecnológicos en sensores y redes de comunicaciones permiten obtener mucha información, que antes no era posible conocer, prácticamente en tiempo real. Este trabajo en progreso utiliza estos avances, para recopilar datos de los habitantes de una zona urbana en una plataforma web en que en un futuro, los profesionales puedan obtener datos anónimos, analizarlos y suministrar patrones de salud en base a los mismos, dotando al sistema de la capacidad de crear planes de acción comunes y personalizados a los perfiles de los ciudadanos, con el fin de mejorar su calidad de vida.Este trabajo ha sido parcialmente financiado por el proyecto del Ministerio de Economía y Competitividad HERMES (TIN2013-46801-C4-1-r) y los proyectos de excelencia de la Junta de Andalucía Simon (P11-TIC-8052) y Context-Learning (P11-TIC-7124)

Aquacultural Homoeopathy: A Focus on Marine Species

Homoeopathy is an alternative medical system proposed by Samuel Hahnemann in the eighteenth century. It uses highly diluted and agitated substances that derived from plants, minerals or animals, which have shown to be effective in human medicine, agronomy, veterinary, and as a novelty, in marine aquaculture. Aquacultural homoeopathy has developed rapidly in recent years, partially motivated by the misuse of powerful drugs (hormones, antibiotics, disinfectants) that when solving a problem generate undesirable side effects. In the last 10 years, scientific articles have been published on its application in freshwater fish native to Brazil, obtaining beneficial effects on growth, survival, hepatosomatic index, development of muscle fibres and lipid content in muscle. At Centro de Investigaciones Biológicas del Noroeste (CIBNOR, Mexico: www.cibnor.mx), we have studied the effects of homoeopathy to improve the culture of economically important marine species of molluscs, fish and shrimp. In this chapter, we show a selection of different research with preliminary or advanced results, related to the use of homoeopathy and its impact on zootechnic, biochemical, genomic and transcriptomic parameters in marine molluscs, fish and crustaceans. The results obtained suggest that homoeopathy is an eco-friendly alternative applicable in aquaculture industry to improve various productive and health aspects

Measurement-While-Drilling Based Estimation of Dynamic Penetrometer Values Using Decision Trees and Random Forests

Machine learning is a branch of artificial intelligence (AI) that consists of the application of various algorithms to obtain information from large data sets. These algorithms are especially useful to solve nonlinear problems that appear frequently in some engineering fields. Geotechnical engineering presents situations with complex relationships of multiple variables, making it an ideal field for the application of machine learning techniques. Thus, these techniques have already been applied with a certain degree of success to determine such things as soil parameters, admissible load, settlement, or slope stability. Moreover, dynamic penetrometers are a very common type of test in geotechnical studies, and, in many cases, they are used to design the foundation solution. In addition, its continuous nature allows us to know the variations of the terrain profile. The objective of this study was to correlate the drilling parameters of deep foundation machinery (Measurement-While-Drilling, MWD) with the number of blows of the dynamic penetrometer test. Therefore, the drilling logs could be equated with said tests, providing information that can be easily interpreted by a geotechnical engineer and that would allow the validation of the design hypotheses. Decision trees and random forest algorithms have been used for this purpose. The ability of these algorithms to replicate the complex relationships between drilling parameters and terrain characteristics has allowed obtaining a reliable reproduction of the penetrometric profile of the traversed soil

Incorporación de la metodología BIM en el Máster de Ingeniería de Caminos

University syllabus of architecture and building degrees have already included the use of BIM. Nevertheless, the implementation of BIM in most of the Civil Engineering syllabus is still pending. In the case of the Master degree in Civil Engineering, new considerations are needed to prepare future engineers for the use of BIM in infrastructure and civil engineering projects in their career. In the case of Spain, the use of BIM will be introduced in civil engineering projects for the public administration in 2019. However, in the the Master Degree in Ingeniería de Caminos, Canales y Puertos there is not a clear path to be followed in order to implement BIM in the university syllabus. With the aim of satisfying this demand, the Civil Engineering School (Escuela de Caminos, Canales y Puertos) of Universidad Politécnica de Madrid has decided to create a new specific subject to be included in the third semester of the Master degree. This contribution shows the approach and the strategies used in order to implement this methodology as the results obtained. ----------RESUMEN---------- En el ámbito de la formación universitaria ya han aparecido una serie de iniciativas dirigidas a incorporar la metodología BIM en los estudios de Arquitectura y Edificación. Sin embargo, sigue estando pendiente su introducción en el campo de la Ingeniería de Caminos, apostando por un nuevo enfoque que combine la formación tradicional y los recursos tecnológicos aportados por la metodología BIM y que prepare a los egresados para el mundo profesional en el ámbito de las infraestructuras. En España se están dando los primeros pasos y a partir de 2019 la metodología BIM será obligatoria para la licitación y construcción de infraestructuras la Administración Pública. Sin embargo, en los planes de estudios de Ingeniería de Caminos solo existen implementaciones aisladas que no disponen de una estrategia global en el desarrollo formativo del alumno. Para atender esta necesidad, la Escuela de Caminos, Canales y Puertos (ETSICCP) de la Universidad Politécnica de Madrid ha creado una asignatura específica para incluirla en el Máster Universitario en Ingeniería de Caminos, Canales y Puertos (Máster de carácter habilitante) que responde a las necesidades actuales y sirve de guía para implementar la tecnología BIM de manera transversal al resto de niveles universitarios. Esta aportación muestra el enfoque y las estrategias utilizadas para implementar esta metodología así como los resultados obtenidos en su primer año de implantación

Measurement-While-Drilling Based Estimation of Dynamic Penetrometer Values Using Decision Trees and Random Forests

Machine learning is a branch of artificial intelligence (AI) that consists of the application of various algorithms to obtain information from large data sets. These algorithms are especially useful to solve nonlinear problems that appear frequently in some engineering fields. Geotechnical engineering presents situations with complex relationships of multiple variables, making it an ideal field for the application of machine learning techniques. Thus, these techniques have already been applied with a certain degree of success to determine such things as soil parameters, admissible load, settlement, or slope stability. Moreover, dynamic penetrometers are a very common type of test in geotechnical studies, and, in many cases, they are used to design the foundation solution. In addition, its continuous nature allows us to know the variations of the terrain profile. The objective of this study was to correlate the drilling parameters of deep foundation machinery (Measurement-While-Drilling, MWD) with the number of blows of the dynamic penetrometer test. Therefore, the drilling logs could be equated with said tests, providing information that can be easily interpreted by a geotechnical engineer and that would allow the validation of the design hypotheses. Decision trees and random forest algorithms have been used for this purpose. The ability of these algorithms to replicate the complex relationships between drilling parameters and terrain characteristics has allowed obtaining a reliable reproduction of the penetrometric profile of the traversed soil