Environmental engagement of costumer in the tourism industry

This article contributes to a better understanding of tourists’ environmental concerns, assuming that distance from the place of residence is relevant. The analysis is conducted for EU-27 countries, combining micro-data, correspond to the Flash Eurobarometer 281 drawn from the European Commission and macro-data from different international sources. Since the environmental attitudes may vary across different cultures and societies, the individuals should be nested into countries. Therefore, it is inappropriate to analyze data using traditional regression analysis. Mixed model specifically may take into account such hierarchical data structure considering simultaneously individual and contextual variables. A general finding from the estimates indicated that significant variance exists within and among nations in the level of environmental support. This finding is congruent with the necessity of simultaneously assessing the effect of individual and country levels variables on environmental support across the European countries. Additionally, this paper demonstrates that people who are actively involved in protecting the environment at home do not maintain this type of behavior when they go on vacation, which may have negative environmental consequences on destinations, albeit involuntarily. The environmental concerns of tourists when travelling domestically were around 15% higher than those travelling abroad. Additionally, the random slope variance regarding destination choice parameter is statistically significant, which allows us to explore the underpinning behind the heterogeneous pattern across countries. Our results can be of great importance to minimize the negative environmental impacts when traveling, and represents an interesting starting point to reduce the environmentally unsustainable behaviors in the tourist field

From perception to action and vice versa: a new architecture showing how perception and action can modulate each other simultaneously

Presentado en: 6th European Conference on Mobile Robots (ECMR) Sep 25-27, 2013 Barcelona, SpainArtificial vision systems can not process all the information that they receive from the world in real time because it is highly expensive and inefficient in terms of computational cost. However, inspired by biological perception systems, it is possible to develop an artificial attention model able to select only the relevant part of the scene, as human vision does. From the Automated Planning point of view, a relevant area can be seen as an area where the objects involved in the execution of a plan are located. Thus, the planning system should guide the attention model to track relevant objects. But, at the same time, the perceived objects may constrain or provide new information that could suggest the modification of a current plan. Therefore, a plan that is being executed should be adapted or recomputed taking into account actual information perceived from the world. In this work, we introduce an architecture that creates a symbiosis between the planning and the attention modules of a robotic system, linking visual features with high level behaviours. The architecture is based on the interaction of an oversubscription planner, that produces plans constrained by the information perceived from the vision system, and an object-based attention system, able to focus on the relevant objects of the plan being executed.Spanish MINECO projects TIN2008-06196, TIN2012-38079-C03-03 and TIN2012-38079-C03-02. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

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

Collective unambiguous positioning with high-order BOC signals

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The unambiguous estimation of high-order BOC signals in harsh propagation conditions is still an open problem in the literature. This paper proposes to overcome the limitations observed in state-of-the-art unambiguous estimation techniques based on the application of existing direct positioning techniques and the exploitation of the spatial diversity introduced by arrays of antennas. In particular, the ambiguity problem is solved as a multiple-input multiple-output (MIMO) estimation problem in the position domain.Peer ReviewedPostprint (author's final draft

La percepción española de la ONU (1945 - 1962)

Sin resume

Técnicas avanzadas de geolocalización en redes UMTS

Las redes de comunicaciones móviles han evolucionado a un ritmo exponencial a lo largo de los últimos años. Este crecimiento ha acentuado la necesidad de disponer de herramientas que ayuden a la detección de problemas (troubleshooting), a la optimización y a la monitorización de estas redes. En este contexto es donde entran en juego los mapas geolocalizados, ya que ofrecen una manera sencilla, eficaz y visual de llevar a cabo estas tareas, además de proporcionar una alternativa de bajo coste a los drive tests. De este modo, y a partir de las trazas de las llamadas de los usuarios (call traces), surge la posibilidad de emplear diversas técnicas de geolocalización para estimar la posición de los eventos reportados por el dispositivo móvil. Naturalmente, las dos cuestiones más críticas para este enfoque son las precisión punto a punto y la calidad visual de los mapas. En esta tesis se analizan y desarrollan varios algoritmos avanzados de geolocalización para redes UMTS, aunque gran parte de los mismos pueden ser fácilmente extrapolados a redes LTE. Estos algoritmos se implementan dentro de herramientas autónomas para ser, posteriormente, evaluados y verificados mediante datos reales provenientes de redes móviles actualmente en servicio. La utilización de datos reales es un aspecto clave, puesto que proporciona una alta fiabilidad y robustez a los resultados y conclusiones extraídos. En primer lugar, se desarrolla una herramienta híbrida de geolocalización que combina diversos algoritmos y fuentes de información con el objetivo de establecer un compromiso entre mapas geolocalizados poblados y realistas, y una buena precisión punto a punto. Se definen un conjunto de procesos secuenciales que van introduciendo y combinando medidas de nivel de señal, medidas temporales, parámetros del Nodo B servidor y de los Nodos B vecinos, predicciones de señal, e incluso datos geográficos del terreno y el entorno. El resultado final es la posibilidad de generar mapas, por ejemplo de señal o de mejor celda servidora, que ofrecen gran cohesión y coherencia visual, además de una mejora de precisión gracias a la combinación de diferentes estrategias. En segundo instancia, se presenta una herramienta basada en la multilateración hiperbólica u OTDOA (Observed Time Difference of Arrival) para estimar, conjuntamente, tanto la posición de los usuarios como la diferencia de sincronización entre los Nodos B. Para ello, y a partir de los eventos Measurement Report que reportan el parámetro TM, esta técnica resuelve un problema de estimación de mínimos cuadrados no lineal a través de un método numérico iterativo. En particular, se analizan y comparan los métodos de Gauss-Newton, Levenberg-Marquardt y un nuevo Levenberg-Marquardt modificado surgido de este trabajo. Asimismo, se plantea una geometría espacial de cuatro sites, la configuración en estrella, que evita la aparición de mínimos locales. Como resultado, las modificaciones propuestas incrementan la precisión implícita en OTDOA, proporcionan rápida convergencia y alta robustez, y reducen el coste monetario general del método al no requerir de sistemas externos, tales como los LMUs, que recuperen previamente la sincronización. Finalmente, se detalla una técnica de compresión para ajustar de manera inteligente las posiciones estimadas de cualquier usuario dadas por diferentes estrategias de geolocalización, por ejemplo basadas en OTDOA, ángulo de llegada (AOA) o retardo de propagación (PD). La idea se centra en subir un nivel de abstracción, pasando de los eventos como entes independientes a los eventos que conforman una llamada, distinguiendo también si éstas son estáticas o dinámicas. En concreto, el método propuesto desplaza las posiciones hacia un ancla virtual calculada previamente según las áreas de confianza al 95% de cada evento geolocalizado. A su vez, estas regiones de confianza son computadas con simuladores en función de diversos parámetros de la red móvil y del propio evento. De este modo, se logra una notable mejora de precisión y mitigar los efectos adversos de distintas fuente de error, como puede ser el multitrayecto

Microcontroller-Based Sinusoidal Voltage Generation for Electrical Bio-Impedance Spectroscopy Applications

A sinusoidal voltage wave generator is proposed based on the use of micro- processor digital signals with programmable duty-cycles, with application to real-time Electrical Cell-substrate Impedance Spectroscopy (ECIS) assays in cell cultures. The working principle relies on the time convolution of the programmed microcontroller (μC) digital signals. The expected frequency is easily tuned on the bio-impedance spectroscopy range [100 Hz, 1 MHz] thanks to the μC clock frequency selection. This system has been simulated and tested on the 8 bits μC Arduino™ Uno with ATmega328 version. Results obtained prove that only three digital signals are required to fit the general specification in ECIS experiments, below 1% THD accuracy, and show the appropriateness of the system for the real-time monitoring of this type of biological experiments.Spanish founded Project: TEC 2013- 46242-C3-1-P: Integrated Microsystem for Cell Culture AssaysFEDE