Offline GA-Based optimization for heterogeneous modular multi-configurable chained microrobots

This paper presents a GA-based optimization procedure for bioinspired heterogeneous modular multiconfigurable chained microrobots. When constructing heterogeneous chained modular robots that are composed of several different drive modules, one must select the type and position of the modules that form the chain. One must also develop new locomotion gaits that combine the different drive modules. These are two new features of heterogeneous modular robots that they do not share with homogeneous modular robots. This paper presents an offline control system that allows the development of new configuration schemes and locomotion gaits for these heterogeneous modular multiconfigurable chained microrobots. The offline control system is based on a simulator that is specifically designed for chained modular robots and allows them to develop and learn new locomotion patterns.

A waypoint-based mission planner for a farmland coverage with an aerial robot - a precision farming tool

Remote sensing (RS) with aerial robots is becoming more usual in every day time in Precision Agriculture (PA) practices, do to their advantages over conventional methods. Usually, available commercial platforms providing off-the-shelf waypoint navigation are adopted to perform visual surveys over crop fields, with the purpose to acquire specific image samples. The way in which a waypoint list is computed and dispatched to the aerial robot when mapping non empty agricultural workspaces has not been yet discussed. In this paper we propose an offline mission planner approach that computes an efficient coverage path subject to some constraints by decomposing the environment approximately into cells. Therefore, the aim of this work is contributing with a feasible waypoints-based tool to support PA practices

Solving identity delegation problem in the e-government environment

At present, many countries allow citizens or entities to interact with the government outside the telematic environment through a legal representative who is granted powers of representation. However, if the interaction takes place through the Internet, only primitive mechanisms of representation are available, and these are mainly based on non-dynamic offline processes that do not enable quick and easy identity delegation. This paper proposes a system of dynamic delegation of identity between two generic entities that can solve the problem of delegated access to the telematic services provided by public authorities. The solution herein is based on the generation of a delegation token created from a proxy certificate that allows the delegating entity to delegate identity to another on the basis of a subset of its attributes as delegator, while also establishing in the delegation token itself restrictions on the services accessible to the delegated entity and the validity period of delegation. Further, the paper presents the mechanisms needed to either revoke a delegation token or to check whether a delegation token has been revoked. Implications for theory and practice and suggestions for future research are discussed.

Non-failure analysis for logic programs

We provide a method whereby, given mode and (upper approximation) type information, we can detect procedures and goals that can be guaranteed to not fail (i.e., to produce at least one solution or not termínate). The technique is based on an intuitively very simple notion, that of a (set of) tests "covering" the type of a set of variables. We show that the problem of determining a covering is undecidable in general, and give decidability and complexity results for the Herbrand and linear arithmetic constraint systems. We give sound algorithms for determining covering that are precise and efiicient in practice. Based on this information, we show how to identify goals and procedures that can be guaranteed to not fail at runtime. Applications of such non-failure information include programming error detection, program transiormations and parallel execution optimization, avoiding speculative parallelism and estimating lower bounds on the computational costs of goals, which can be used for granularity control. Finally, we report on an implementation of our method and show that better results are obtained than with previously proposed approaches.

Calibration proposal for new antenna array architectures and technologies for space communications

In large antenna arrays with a large number of antenna elements, the required number of measurements for the characterization of the antenna array is very demanding in cost and time. This letter presents a new offline calibration process for active antenna arrays that reduces the number of measurements by subarray-level characterization. This letter embraces measurements, characterization, and calibration as a global procedure assessing about the most adequate calibration technique and computing of compensation matrices. The procedure has been fully validated with measurements of a 45-element triangular panel array designed for Low Earth Orbit (LEO) satellite tracking that compensates the degradation due to gain and phase imbalances and mutual coupling.

Gesture recognition using mobile phone's inertial sensors

The availability of inertial sensors embedded in mobile devices has enabled a new type of interaction based on the movements or “gestures” made by the users when holding the device. In this paper we propose a gesture recognition system for mobile devices based on accelerometer and gyroscope measurements. The system is capable of recognizing a set of predefined gestures in a user-independent way, without the need of a training phase. Furthermore, it was designed to be executed in real-time in resource-constrained devices, and therefore has a low computational complexity. The performance of the system is evaluated offline using a dataset of gestures, and also online, through some user tests with the system running in a smart phone.

Accurate pedestrian indoor navigation by tightly coupling foot-mounted IMU and RFID measurements

We present a new method to accurately locate persons indoors by fusing inertial navigation system (INS) techniques with active RFID technology. A foot-mounted inertial measuring units (IMUs)-based position estimation method, is aided by the received signal strengths (RSSs) obtained from several active RFID tags placed at known locations in a building. In contrast to other authors that integrate IMUs and RSS with a loose Kalman filter (KF)-based coupling (by using the residuals of inertial- and RSS-calculated positions), we present a tight KF-based INS/RFID integration, using the residuals between the INS-predicted reader-to-tag ranges and the ranges derived from a generic RSS path-loss model. Our approach also includes other drift reduction methods such as zero velocity updates (ZUPTs) at foot stance detections, zero angular-rate updates (ZARUs) when the user is motionless, and heading corrections using magnetometers. A complementary extended Kalman filter (EKF), throughout its 15-element error state vector, compensates the position, velocity and attitude errors of the INS solution, as well as IMU biases. This methodology is valid for any kind of motion (forward, lateral or backward walk, at different speeds), and does not require an offline calibration for the user gait. The integrated INS+RFID methodology eliminates the typical drift of IMU-alone solutions (approximately 1% of the total traveled distance), resulting in typical positioning errors along the walking path (no matter its length) of approximately 1.5 m.

Codificador de voz MIDI

El presente proyecto tiene el objetivo de facilitar la composición de canciones mediante la creación de las distintas pistas MIDI que la forman. Se implementan dos controladores. El primero, con objeto de transcribir la parte melódica, convierte la voz cantada o tarareada a eventos MIDI. Para ello, y tras el estudio de las distintas técnicas del cálculo del tono (pitch), se implementará una técnica con ciertas variaciones basada en la autocorrelación. También se profundiza en el segmentado de eventos, en particular, una técnica basada en el análisis de la derivada de la envolvente. El segundo, dedicado a la base rítmica de la canción, permite la creación de la percusión mediante el golpe rítmico de objetos que disponga el usuario, que serán asignados a los distintos elementos de percusión elegidos. Los resultados de la grabación de estos impactos serán señales de corta duración, no lineales y no armónicas, dificultando su discriminación. La herramienta elegida para la clasificación de los distintos patrones serán las redes neuronales artificiales (RNA). Se realizara un estudio de la metodología de diseño de redes neuronales especifico para este tipo de señales, evaluando la importancia de las variables de diseño como son el número de capas ocultas y neuronas en cada una de ellas, algoritmo de entrenamiento y funciones de activación. El estudio concluirá con la implementación de dos redes de diferente naturaleza. Una red de Elman, cuyas propiedades de memoria permiten la clasificación de patrones temporales, procesará las cualidades temporales analizando el ataque de su forma de onda. Una red de propagación hacia adelante feed-forward, que necesitará de robustas características espectrales y temporales para su clasificación. Se proponen 26 descriptores como los derivados de los momentos del espectro: centroide, curtosis y simetría, los coeficientes cepstrales de la escala de Mel (MFCCs), y algunos temporales como son la tasa de cruces por cero y el centroide de la envolvente temporal. Las capacidades de discriminación inter e intra clase de estas características serán evaluadas mediante un algoritmo de selección, habiéndose elegido RELIEF, un método basado en el algoritmo de los k vecinos mas próximos (KNN). Ambos controladores tendrán función de trabajar en tiempo real y offline, permitiendo tanto la composición de canciones, como su utilización como un instrumento más junto con mas músicos. ABSTRACT. The aim of this project is to make song composition easier by creating each MIDI track that builds it. Two controllers are implemented. In order to transcribe the melody, the first controler converts singing voice or humming into MIDI files. To do this a technique based on autocorrelation is implemented after having studied different pitch detection methods. Event segmentation has also been dealt with, to be more precise a technique based on the analysis of the signal's envelope and it's derivative have been used. The second one, can be used to make the song's rhythm . It allows the user, to create percussive patterns by hitting different objects of his environment. These recordings results in short duration, non-linear and non-harmonic signals. Which makes the classification process more complicated in the traditional way. The tools to used are the artificial neural networks (ANN). We will study the neural network design to deal with this kind of signals. The goal is to get a design methodology, paying attention to the variables involved, as the number of hidden layers and neurons in each, transfer functions and training algorithm. The study will end implementing two neural networks with different nature. Elman network, which has memory properties, is capable to recognize sequences of data and analyse the impact's waveform, precisely, the attack portion. A feed-forward network, needs strong spectral and temporal features extracted from the hit. Some descriptors are proposed as the derivates from the spectrum moment as centroid, kurtosis and skewness, the Mel-frequency cepstral coefficients, and some temporal features as the zero crossing rate (zcr) and the temporal envelope's centroid. Intra and inter class discrimination abilities of those descriptors will be weighted using the selection algorithm RELIEF, a Knn (K-nearest neighbor) based algorithm. Both MIDI controllers can be used to compose, or play with other musicians as it works on real-time and offline.

Simulación de componentes no estacionarias de viento en orografías complejas

Realistic operation of helicopter flight simulators in complex topographies (such as urban environments) requires appropriate prediction of the incoming wind, and this prediction should be made in real time. Unfortunately, the wind topology around complex topographies shows time-dependent, fully nonlinear, turbulent patterns (i.e., wakes) whose simulation cannot be made using computationally inexpensive tools based on corrected potential approximations. Instead, the full Navier-Stokes plus some kind of turbulent modeling is necessary, which is quite computationally expensive. The complete unsteady flow depends on two parameters, namely the velocity and orientation of the free stream flow. The aim of this MSc thesis is to develop a methodology for the real time simulation of these complex flows. For simplicity, the flow around a single building (20 mx20 m cross section and 100 m height) is considered, with free stream velocity in the range 5-25 m/s. Because of the square cross section, the problem shows two reflection symmetries, which allows for restricting the orientations to the range 0° < a. < 45°. The methodology includes an offline preprocess and the online operation. The preprocess consists in three steps: An appropriate, unstructured mesh is selected in which the flow is sim¬ulated using OpenFOAM, and this is done for 33 combinations of 3 free stream intensities and 11 orientations. For each of these, the simulation proceeds for a sufficiently large time as to eliminate transients. This step is quite computationally expensive. Each flow field is post-processed using a combination of proper orthogonal decomposition, fast Fourier transform, and a convenient optimization tool, which identifies the relevant frequencies (namely, both the basic frequencies and their harmonics) and modes in the computational mesh. This combination includes several new ingredients to filter errors out and identify the relevant spatio-temporal patterns. Note that, in principle, the basic frequencies depend on both the intensity and the orientation of the free stream flow. The outcome of this step is a set of modes (vectors containing the three velocity components at all mesh points) for the various Fourier components, intensities, and orientations, which can be organized as a third order tensor. This step is fairly computationally inexpensive. The above mentioned tensor is treated using a combination of truncated high order singular value, decomposition and appropriate one-dimensional interpolation (as in Lorente, Velazquez, Vega, J. Aircraft, 45 (2008) 1779-1788). The outcome is a tensor representation of both the relevant fre¬quencies and the associated Fourier modes for a given pair of values of the free stream flow intensity and orientation. This step is fairly compu¬tationally inexpensive. The online, operation requires just reconstructing the time-dependent flow field from its Fourier representation, which is extremely computationally inex¬pensive. The whole method is quite robust.

Novel Negotiation protocol to support CDM process in a layered ATM System

In the SESAR Step 2 concept of operations a RBT is available and seen by all making it possible to conceive a different operating method than the current ATM system based on Collaborative Decisions Making processes. Currently there is a need to describe in more detail the mechanisms by which actors (ATC, Network Management, Flight Crew, airports and Airline Operation Centre) will negotiate revisions to the RBT. This paper introduces a negotiation model, which uses constraint based programing applied to a mediator to facilitate negotiation process in a SWIM enabled environment. Three processes for modelling the negotiation process are explained as well a preliminary reasoning agent algorithm modelled with constraint satisfaction problem is presented. Computational capability of the model is evaluated in the conclusion.

Noise-agnostic adaptive image filtering without training references on an evolvable hardware platform

One of the main concerns of evolvable and adaptive systems is the need of a training mechanism, which is normally done by using a training reference and a test input. The fitness function to be optimized during the evolution (training) phase is obtained by comparing the output of the candidate systems against the reference. The adaptivity that this type of systems may provide by re-evolving during operation is especially important for applications with runtime variable conditions. However, fully automated self-adaptivity poses additional problems. For instance, in some cases, it is not possible to have such reference, because the changes in the environment conditions are unknown, so it becomes difficult to autonomously identify which problem requires to be solved, and hence, what conditions should be representative for an adequate re-evolution. In this paper, a solution to solve this dependency is presented and analyzed. The system consists of an image filter application mapped on an evolvable hardware platform, able to evolve using two consecutive frames from a camera as both test and reference images. The system is entirely mapped in an FPGA, and native dynamic and partial reconfiguration is used for evolution. It is also shown that using such images, both of them being noisy, as input and reference images in the evolution phase of the system is equivalent or even better than evolving the filter with offline images. The combination of both techniques results in the completely autonomous, noise type/level agnostic filtering system without reference image requirement described along the paper.

Automatic design of Ant Colony Optimization for permutation problems

In this study, we present a framework based on ant colony optimization (ACO) for tackling combinatorial problems. ACO algorithms have been applied to many diferent problems, focusing on algorithmic variants that obtain high-quality solutions. Usually, the implementations are re-done for various problem even if they maintain the same details of the ACO algorithm. However, our goal is to generate a sustainable framework for applications on permutation problems. We concentrate on understanding the behavior of pheromone trails and specific methods that can be combined. Eventually, we will propose an automatic offline configuration tool to build an efective algorithm. ---RESUMEN---En este trabajo vamos a presentar un framework basado en la familia de algoritmos ant colony optimization (ACO), los cuales están dise~nados para enfrentarse a problemas combinacionales. Los algoritmos ACO han sido aplicados a diversos problemas, centrándose los investigadores en diversas variantes que obtienen buenas soluciones. Normalmente, las implementaciones se tienen que rehacer, inclusos si se mantienen los mismos detalles para los algoritmos ACO. Sin embargo, nuestro objetivo es generar un framework sostenible para aplicaciones sobre problemas de permutaciones. Nos centraremos en comprender el comportamiento de la sendas de feromonas y ciertos métodos con los que pueden ser combinados. Finalmente, propondremos una herramienta para la configuraron automática offline para construir algoritmos eficientes.

Análisis y modelización de la dinámica emergente durante el proceso de difusión de información en las redes sociales de internet

Durante la actividad diaria, la sociedad actual interactúa constantemente por medio de dispositivos electrónicos y servicios de telecomunicaciones, tales como el teléfono, correo electrónico, transacciones bancarias o redes sociales de Internet. Sin saberlo, masivamente dejamos rastros de nuestra actividad en las bases de datos de empresas proveedoras de servicios. Estas nuevas fuentes de datos tienen las dimensiones necesarias para que se puedan observar patrones de comportamiento humano a grandes escalas. Como resultado, ha surgido una reciente explosión sin precedentes de estudios de sistemas sociales, dirigidos por el análisis de datos y procesos computacionales. En esta tesis desarrollamos métodos computacionales y matemáticos para analizar sistemas sociales por medio del estudio combinado de datos derivados de la actividad humana y la teoría de redes complejas. Nuestro objetivo es caracterizar y entender los sistemas emergentes de interacciones sociales en los nuevos espacios tecnológicos, tales como la red social Twitter y la telefonía móvil. Analizamos los sistemas por medio de la construcción de redes complejas y series temporales, estudiando su estructura, funcionamiento y evolución en el tiempo. También, investigamos la naturaleza de los patrones observados por medio de los mecanismos que rigen las interacciones entre individuos, así como medimos el impacto de eventos críticos en el comportamiento del sistema. Para ello, hemos propuesto modelos que explican las estructuras globales y la dinámica emergente con que fluye la información en el sistema. Para los estudios de la red social Twitter, hemos basado nuestros análisis en conversaciones puntuales, tales como protestas políticas, grandes acontecimientos o procesos electorales. A partir de los mensajes de las conversaciones, identificamos a los usuarios que participan y construimos redes de interacciones entre los mismos. Específicamente, construimos una red para representar quién recibe los mensajes de quién y otra red para representar quién propaga los mensajes de quién. En general, hemos encontrado que estas estructuras tienen propiedades complejas, tales como crecimiento explosivo y distribuciones de grado libres de escala. En base a la topología de estas redes, hemos indentificado tres tipos de usuarios que determinan el flujo de información según su actividad e influencia. Para medir la influencia de los usuarios en las conversaciones, hemos introducido una nueva medida llamada eficiencia de usuario. La eficiencia se define como el número de retransmisiones obtenidas por mensaje enviado, y mide los efectos que tienen los esfuerzos individuales sobre la reacción colectiva. Hemos observado que la distribución de esta propiedad es ubicua en varias conversaciones de Twitter, sin importar sus dimensiones ni contextos. Con lo cual, sugerimos que existe universalidad en la relación entre esfuerzos individuales y reacciones colectivas en Twitter. Para explicar los factores que determinan la emergencia de la distribución de eficiencia, hemos desarrollado un modelo computacional que simula la propagación de mensajes en la red social de Twitter, basado en el mecanismo de cascadas independientes. Este modelo nos permite medir el efecto que tienen sobre la distribución de eficiencia, tanto la topología de la red social subyacente, como la forma en que los usuarios envían mensajes. Los resultados indican que la emergencia de un grupo selecto de usuarios altamente eficientes depende de la heterogeneidad de la red subyacente y no del comportamiento individual. Por otro lado, hemos desarrollado técnicas para inferir el grado de polarización política en redes sociales. Proponemos una metodología para estimar opiniones en redes sociales y medir el grado de polarización en las opiniones obtenidas. Hemos diseñado un modelo donde estudiamos el efecto que tiene la opinión de un pequeño grupo de usuarios influyentes, llamado élite, sobre las opiniones de la mayoría de usuarios. El modelo da como resultado una distribución de opiniones sobre la cual medimos el grado de polarización. Aplicamos nuestra metodología para medir la polarización en redes de difusión de mensajes, durante una conversación en Twitter de una sociedad políticamente polarizada. Los resultados obtenidos presentan una alta correspondencia con los datos offline. Con este estudio, hemos demostrado que la metodología propuesta es capaz de determinar diferentes grados de polarización dependiendo de la estructura de la red. Finalmente, hemos estudiado el comportamiento humano a partir de datos de telefonía móvil. Por una parte, hemos caracterizado el impacto que tienen desastres naturales, como innundaciones, sobre el comportamiento colectivo. Encontramos que los patrones de comunicación se alteran de forma abrupta en las áreas afectadas por la catástofre. Con lo cual, demostramos que se podría medir el impacto en la región casi en tiempo real y sin necesidad de desplegar esfuerzos en el terreno. Por otra parte, hemos estudiado los patrones de actividad y movilidad humana para caracterizar las interacciones entre regiones de un país en desarrollo. Encontramos que las redes de llamadas y trayectorias humanas tienen estructuras de comunidades asociadas a regiones y centros urbanos. En resumen, hemos mostrado que es posible entender procesos sociales complejos por medio del análisis de datos de actividad humana y la teoría de redes complejas. A lo largo de la tesis, hemos comprobado que fenómenos sociales como la influencia, polarización política o reacción a eventos críticos quedan reflejados en los patrones estructurales y dinámicos que presentan la redes construidas a partir de datos de conversaciones en redes sociales de Internet o telefonía móvil. ABSTRACT During daily routines, we are constantly interacting with electronic devices and telecommunication services. Unconsciously, we are massively leaving traces of our activity in the service providers’ databases. These new data sources have the dimensions required to enable the observation of human behavioral patterns at large scales. As a result, there has been an unprecedented explosion of data-driven social research. In this thesis, we develop computational and mathematical methods to analyze social systems by means of the combined study of human activity data and the theory of complex networks. Our goal is to characterize and understand the emergent systems from human interactions on the new technological spaces, such as the online social network Twitter and mobile phones. We analyze systems by means of the construction of complex networks and temporal series, studying their structure, functioning and temporal evolution. We also investigate on the nature of the observed patterns, by means of the mechanisms that rule the interactions among individuals, as well as on the impact of critical events on the system’s behavior. For this purpose, we have proposed models that explain the global structures and the emergent dynamics of information flow in the system. In the studies of the online social network Twitter, we have based our analysis on specific conversations, such as political protests, important announcements and electoral processes. From the messages related to the conversations, we identify the participant users and build networks of interactions with them. We specifically build one network to represent whoreceives- whose-messages and another to represent who-propagates-whose-messages. In general, we have found that these structures have complex properties, such as explosive growth and scale-free degree distributions. Based on the topological properties of these networks, we have identified three types of user behavior that determine the information flow dynamics due to their influence. In order to measure the users’ influence on the conversations, we have introduced a new measure called user efficiency. It is defined as the number of retransmissions obtained by message posted, and it measures the effects of the individual activity on the collective reacixtions. We have observed that the probability distribution of this property is ubiquitous across several Twitter conversation, regardlessly of their dimension or social context. Therefore, we suggest that there is a universal behavior in the relationship between individual efforts and collective reactions on Twitter. In order to explain the different factors that determine the user efficiency distribution, we have developed a computational model to simulate the diffusion of messages on Twitter, based on the mechanism of independent cascades. This model, allows us to measure the impact on the emergent efficiency distribution of the underlying network topology, as well as the way that users post messages. The results indicate that the emergence of an exclusive group of highly efficient users depends upon the heterogeneity of the underlying network instead of the individual behavior. Moreover, we have also developed techniques to infer the degree of polarization in social networks. We propose a methodology to estimate opinions in social networks and to measure the degree of polarization in the obtained opinions. We have designed a model to study the effects of the opinions of a small group of influential users, called elite, on the opinions of the majority of users. The model results in an opinions distribution to which we measure the degree of polarization. We apply our methodology to measure the polarization on graphs from the messages diffusion process, during a conversation on Twitter from a polarized society. The results are in very good agreement with offline and contextual data. With this study, we have shown that our methodology is capable of detecting several degrees of polarization depending on the structure of the networks. Finally, we have also inferred the human behavior from mobile phones’ data. On the one hand, we have characterized the impact of natural disasters, like flooding, on the collective behavior. We found that the communication patterns are abruptly altered in the areas affected by the catastrophe. Therefore, we demonstrate that we could measure the impact of the disaster on the region, almost in real-time and without needing to deploy further efforts. On the other hand, we have studied human activity and mobility patterns in order to characterize regional interactions on a developing country. We found that the calls and trajectories networks present community structure associated to regional and urban areas. In summary, we have shown that it is possible to understand complex social processes by means of analyzing human activity data and the theory of complex networks. Along the thesis, we have demonstrated that social phenomena, like influence, polarization and reaction to critical events, are reflected in the structural and dynamical patterns of the networks constructed from data regarding conversations on online social networks and mobile phones.

Desarrollo de un sistema automático de medida para el control del consumo en sistemas empotrados

El Grupo de Diseño Electrónico y Microelectrónico de la Universidad Politécnica de Madrid -GDEM- se dedica, entre otras cosas, al estudio y mejora del consumo en sistemas empotrados. Es en este lugar y sobre este tema donde el proyecto a exponer ha tomado forma y desarrollo. Según un artículo de la revista online Revista de Electrónica Embebida, un sistema empotrado o embebido es aquel “sistema controlado por un microprocesador y que gracias a la programación que incorpora o que se le debe incorporar, realiza una función específica para la que ha sido diseñado, integrando en su interior la mayoría de los elementos necesarios para realizar dicho función”. El porqué de estudiar sobre este tema responde a que, cada vez, hay mayor presencia de sistemas empotrados en nuestra vida cotidiana. Esto es debido a que se está tendiendo a dotar de “inteligencia” a todo lo que puedan hacer nuestra vida un poco más fácil. Nos podemos encontrar dichos sistemas en fábricas, oficinas de atención a los ciudadanos, sistemas de seguridad de hogar, relojes, móviles, lavadoras, hornos, aspiradores y un largo etcétera en cualquier aparato que nos podamos imaginar. A pesar de sus grandes ventajas, aún hay grandes inconvenientes. El mayor problema que supone a día de hoy es la autonomía del mismo sistema, ya que hablamos de aparatos que muchas veces están alimentados por baterías -para ayudar a su portabilidad–. Por esto, se está intentando dotar a dichos sistemas de una capacidad de ahorro de energía y toma de decisiones que podrían ayudar a duplicar la autonomía de dicha batería. Un ejemplo claro son los Smartphones de hoy en día, unos aparatos casi indispensables que pueden tener una autonomía de un día. Esto es poco práctico para el usuario en caso de viajes, trabajo u otras situaciones en las que se le dé mucho uso y no pueda tener acceso a una red eléctrica. Es por esto que surge la necesidad de investigar, sin necesidad de mejorar el hardware del sistema, una manera de mejorar esta situación. Este proyecto trabajará en esa línea creando un sistema automático de medida el cual generará las corrientes que servirán como entrada para verificar el sistema de adquisición que junto con la tarjeta Beagle Board permitirá la toma de decisiones en relación con el consumo de energía. Para realizar este sistema, nos ayudaremos de diferentes herramientas que podremos encontrar en el laboratorio del GDEM, como la fuente de alimentación Agilent y la Beagle Board –como principales herramientas de trabajo- . El objetivo principal será la simulación de unas señales que, después de pasar un proceso de conversión y tratado, harán la función de representación del consumo de cada una de las partes que pueden formar un sistema empotrado genérico. Por lo tanto, podemos decir que el sistema hará la funcionalidad de un banco de pruebas que ayudará a simular dicho consumo para que el microprocesador del sistema pueda llegar a tomar alguna decisión. ABSTRACT. The Electronic and Microelectronic Design Group of Universidad Politécnica de Madrid -GDEM- is in charge, between other issues, of improving the embedded system’s consumption. It is in this place and about this subject where the exposed project has taken shape and development. According to an article from de online magazine Revista de Electronica Embebida, an embedded system is “the one controlled by a microprocessor and, thanks to the programing that it includes, it carries out a specific function what it has been designed for, being integrated in it the most necessary elements for realizing the already said function”. The because of studying this subject, answers that each time there is more presence of the embedded system in our daily life. This is due to the tendency of providing “intelligence” to all what can make our lives easier. We can find this kind of systems in factories, offices, security systems, watchers, mobile phones, washing machines, ovens, hoovers and, definitely, in all kind of machines what we can think of. Despite its large vantages, there are still some inconveniences. Nowadays, the most important problem is the autonomy of the system itself when machines that have to be supplied by batteries –making easier the portability-. Therefore, this project is going after a save capacity of energy for the system as well as being able to take decisions in order to duplicate batteries’ autonomy. Smartphones are a clear example. They are a very successful product but the autonomy is just one day. This is not practical for users, at all, if they have to travel, to work or to do any activity that involves a huge use of the phone without a socket nearby. That is why the need of investigating a way to improve this situation. This project is working on this line, creating an automatic system that will generate the currents for verifying the acquisition system that, with the beagle board, will help taking decisions regarding the energy’s consumption. To carry out this system, we need different tools that we can find in the laboratory of the group previously mentioned, like power supply Agilent and the Beagle Board – as main working tools –. The main goal is the simulation of some signals that, after a conversion process, will represent de consumption of each of the parts in the embedded generic system. Therefore, the system will be a testing ground that simulate the consumption, once sent to the processor, to be processed and so the microprocessor system might take some decision.

Fashion in Actions on Social Media – Spanish SME Fashion Brands Case Studies

Fashion is one of the most vibrant sectors in Europe and important contributors to the European Union (EU) economy. In particular, Small and Medium Enterprises (SMEs) play a major part in European fashion industry (EU 2012). Just like fashion, where people¿s style has inherently meant to be shared as it is foremost a representation of one¿s self-image, social media allow the reflection of ones' personality and emotions. Although fashion practitioners have embraced social media in their marketing activities, it is still relatively few known at an academic level about the specificities of fashion industry when approaching social media marketing (SMM) strategies. This study sets out to explore fashion companies' SMM strategy and its activities. From an exploratory approach, we present case studies of two Spanish SME fashion companies, anonymously named hereafter as Company A and Company B, to deepen our understanding on how fashion brands implement their SMM strategy. Company A offers high-end fashion products while Company B produces medium fashion products. We analyzed the case studies using qualitative (interviews to companies' executives) and a mix of qualitative and quantitative (content analysis of companies' social media platform) methods. Public posts data of both companies' Facebook brand pages were used to perform the content analysis. Our findings through case studies of the two companies reveal that branding-oriented strategic objectives are the main drivers of their SMM implementations. There are significant differences between both companies. The main strategic action employed by Company A is engaging customers to participate into brand's offline social gathering events by inviting them through social media platform, while Company B focuses its effort on posting product promotion related contents and engaging influencers such as fashion bloggers. Our results are expected to serve as a basis of further investigations on how SMM strategy and strategic actions implemented by fashion brands may influence marketing outcomes.