Mesures urgents quant a medi ambient

El darrer 5 de maig s'ha publicat el Reial decret llei 17/2012, de mesures urgents quant a Medi ambient. Aquest RD llei comporta la modificació d'algunes de les principals lleis pel que fa a medi ambient del nostre àmbit normatiu. La promulgació d'aquest ha obviat, com ja ens estan acostumant els diversos governs del PP, el coneixement previ dels seus esborranys i projectes i per tant la seua corresponent anàlisi i debat amb els interlocutors socials, econòmics i mediambientals, com així ho han posat de manifest organitzacions sindicals, ecologistes, agràries i de consumidors, integrants del Consell Assessor de Medi ambient

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-

Relaciones entre las aportaciones a la zona regable del río Jucar y la conductividad de la Albufera de Valencia.

Las aportaciones a la zona regable del río Júcar condicionan la conductividad de la Albufera porque recibe las aguas sobrantes de riego. Se ha observado una relación inversa entre ambas variables. La demanda de agua para otras zonas pretende satisfacerse a partir del trasvase de los sobrantes de riego basándose en una mejora de la eficiencia del regadío. Estas actuaciones deben realizarse sólo cuando se aseguren previamente las aportaciones necesarias para mantener la calidad del lago. The water inflows to the irrigation area of the Júcar river determine the conductivity of the Albufera because it receives the surplus irrigation water. It has been observed an inverse relationship between both variables. The water demands for otherregions is sought by transferring the surplus irrigation water based on an improvement of the irrigation efficiency. These actions must be carried out only after having ensured a sufficient quantity of water inflow to maintain the quality of the lak

El seguimiento de los embalses en la demarcación hidrográfica del Ebro. El estado de los embalses aragoneses.

De los 30 embalses aragoneses, en 2013 se han muestreado, 22. En la tabla 7 se recogen los resultados obtenidos en dichos embalses, ordenados por masa de agua. La representación gráfica de la tabla 7 se puede observar en la figura 6. Del análisis de los datos se aprecia, referente al estado trófico, que de los 22 embalses muestreados la mayor parte son «ultraoligotróficos» y «oligotróficos» (un 59%), es decir, presentan una buena calidad del agua. Para el potencial ecológico se observa también que la mayoría (un68%) presenta un potencial ecológico «máximo» o «bueno», cumpliendo por tanto con la Directiva

Outdoor exit detection using combined techniques to increase GPS efficiency

The recent boom of GPS (Global Positioning System) as a universal method of location has meant that most people in developed countries have already used this technology sometime in their lives. However, this system suffers from an ever-increasing problem: energy expenditure. GPS receivers have been integrated into increasingly smaller devices such as the latest generation of mobiles, thereby making batterysaving a priority in the use of this technology. This article lays out a series of ideas which, through the use of auxiliary technologies, are able to maximize energy saving. By means of outdoor exit detection, it will be possible to automatically disconnect the GPS while the user stays indoors and later reconnect it on leaving the building.Ministerio de Ciencia e Innovación ARTEMISA TIN2009-14378-C02-0

Discrete classification technique applied to TV advertisements liking recognition system based on low‑cost EEG headsets

Background: In this paper a new approach is applied to the area of marketing research. The aim of this paper is to recognize how brain activity responds during the visualization of short video advertisements using discrete classification techniques. By means of low cost electroencephalography devices (EEG), the activation level of some brain regions have been studied while the ads are shown to users. We may wonder about how useful is the use of neuroscience knowledge in marketing, or what could provide neuroscience to marketing sector, or why this approach can improve the accuracy and the final user acceptance compared to other works. Methods: By using discrete techniques over EEG frequency bands of a generated dataset, C4.5, ANN and the new recognition system based on Ameva, a discretization algorithm, is applied to obtain the score given by subjects to each TV ad. Results: The proposed technique allows to reach more than 75 % of accuracy, which is an excellent result taking into account the typology of EEG sensors used in this work. Furthermore, the time consumption of the algorithm proposed is reduced up to 30 % compared to other techniques presented in this paper. Conclusions: This bring about a battery lifetime improvement on the devices where the algorithm is running, extending the experience in the ubiquitous context where the new approach has been tested.Ministerio de Economía y Competitividad HERMES TIN2013-46801-C4-1-rJunta de Andalucia Simon TIC-805

Interaction control in children using NFC tags

Children younger than 3 years old are very special humans, their psychomotor and social development is very fast and parents and relatives would like to know every new detail (when, who, where, what, how and why) in real time. These news are difficult to remember and some kind of diary is needed. Here we propose a “prosthetic memory” based on Digital Object Memories applied to Web of Things using hidden NFC tags in children’s clothes, mobile applications for smartphones and a cen tral server to store the ontologized information

Prosthetic Memory: Object Memories and Security for Children

Children younger than 3 years old are very special humans, their psychomotor and social development is very fast and parents and relatives would like to know every new detail (when, who, where, what, how and why) in real time. These news are difficult to remember and some kind of diary is needed. Here we propose a “prosthetic memory” based on Digital Object Memories applied to Web of Things using hidden NFC tags in children’s clothes, mobile applications for smartphones and a central server to store the ontologized information

Single-Board-Computer Clusters for Cloudlet Computing in Internet of Things

The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-RMinisterio de Economía y Competitividad RTI2018-098062-A-I00European Union’s Horizon 2020 No. 754489Science Foundation Ireland grant 13/RC/209