Security control brought back to the user

The activity of the Ph.D. student Juri Luca De Coi involved the research field of policy languages and can be divided in three parts. The first part of the Ph.D. work investigated the state of the art in policy languages, ending up with: (i) identifying the requirements up-to-date policy languages have to fulfill; (ii) defining a policy language able to fulfill such requirements (namely, the Protune policy language); and (iii) implementing an infrastructure able to enforce policies expressed in the Protune policy language. The second part of the Ph.D. work focused on simplifying the activity of defining policies and ended up with: (i) identifying a subset of the controlled natural language ACE to express Protune policies; (ii) implementing a mapping between ACE policies and Protune policies; and (iii) adapting the ACE Editor to guide users step by step when defining ACE policies. The third part of the Ph.D. work tested the feasibility of the chosen approach by applying it to meaningful real-world problems, among which: (i) development of a security layer on top of RDF stores; and (ii) efficient policy-aware access to metadata stores. The research activity has been performed in tight collaboration with the Leibniz Universität Hannover and further European partners within the projects REWERSE, TENCompetence and OKKAM.

Query rewriting in information retrieval: automatic context extraction from local user documents to improve query results

The central objective of research in Information Retrieval (IR) is to discover new techniques to retrieve relevant information in order to satisfy an Information Need. The Information Need is satisfied when relevant information can be provided to the user. In IR, relevance is a fundamental concept which has changed over time, from popular to personal, i.e., what was considered relevant before was information for the whole population, but what is considered relevant now is specific information for each user. Hence, there is a need to connect the behavior of the system to the condition of a particular person and his social context; thereby an interdisciplinary sector called Human-Centered Computing was born. For the modern search engine, the information extracted for the individual user is crucial. According to the Personalized Search (PS), two different techniques are necessary to personalize a search: contextualization (interconnected conditions that occur in an activity), and individualization (characteristics that distinguish an individual). This movement of focus to the individual's need undermines the rigid linearity of the classical model overtaken the ``berry picking'' model which explains that the terms change thanks to the informational feedback received from the search activity introducing the concept of evolution of search terms. The development of Information Foraging theory, which observed the correlations between animal foraging and human information foraging, also contributed to this transformation through attempts to optimize the cost-benefit ratio. This thesis arose from the need to satisfy human individuality when searching for information, and it develops a synergistic collaboration between the frontiers of technological innovation and the recent advances in IR. The search method developed exploits what is relevant for the user by changing radically the way in which an Information Need is expressed, because now it is expressed through the generation of the query and its own context. As a matter of fact the method was born under the pretense to improve the quality of search by rewriting the query based on the contexts automatically generated from a local knowledge base. Furthermore, the idea of optimizing each IR system has led to develop it as a middleware of interaction between the user and the IR system. Thereby the system has just two possible actions: rewriting the query, and reordering the result. Equivalent actions to the approach was described from the PS that generally exploits information derived from analysis of user behavior, while the proposed approach exploits knowledge provided by the user. The thesis went further to generate a novel method for an assessment procedure, according to the "Cranfield paradigm", in order to evaluate this type of IR systems. The results achieved are interesting considering both the effectiveness achieved and the innovative approach undertaken together with the several applications inspired using a local knowledge base.

Seafloor hydrothermal activity in sediment core MV0502-15JC

A large diameter piston core containing 8.35 m of metalliferous sediment has been recovered from a small abyssal valley in the remote Southwest Pacific Basin (31°42.194'S, 143°30.331'W; 5082 m water depth), providing unique insight into hydrothermal activity and eolian sedimentation there since the early Oligocene. A combination of fish-teeth Sr-isotope stratigraphy and INAA geochemical data reveals an exponentially decreasing hydrothermal flux 31 Ma to the present. Although hydrothermal sedimentation related to seafloor spreading explains this trend, a complex history of late Eocene/early Oligocene ridge jumps, propagating rifts and plate tectonic reorganization of South Pacific seafloor could have also played a role. A possible hiatus in deposition, as recorded by changes in core composition just below 2 m depth, is beyond the resolution of the fish teeth Sr isotope dating method employed here; however, the timing of this interval may be coincident with extinction of the Pacific-Farallon Ridge at ~20 Ma. A low flux eolian component accumulating at this site shows an increase relative to the hydrothermal component above 2 m depth, consistent with dust-generating continental sources far to the west (Australia/New Zealand). This is the first long-term paleoceanographic record obtained from within the South Pacific "bare zone" (Rea et al., 2006), an anomalous region where Pacific seafloor has largely escaped sediment accumulation since the Late Cretaceous.

Effects of ocean acidification on the photosynthetic performance, carbonic anhydrase activity and growth of the giant kelp Macrocystis pyrifera

Under ocean acidification (OA), the 200 % increase in CO2(aq) and the reduction of pH by 0.3-0.4 units are predicted to affect the carbon physiology and growth of macroalgae. Here we examined how the physiology of the giant kelp Macrocystis pyrifera is affected by elevated pCO2/low pH. Growth and photosynthetic rates, external and internal carbonic anhydrase (CA) activity, HCO3 (-) versus CO2 use were determined over a 7-day incubation at ambient pCO2 400 µatm/pH 8.00 and a future OA treatment of pCO2 1200 µatm/pH 7.59. Neither the photosynthetic nor growth rates were changed by elevated CO2 supply in the OA treatment. These results were explained by the greater use of HCO3 (-) compared to CO2 as an inorganic carbon (Ci) source to support photosynthesis. Macrocystis is a mixed HCO3 (-) and CO2 user that exhibits two effective mechanisms for HCO3 (-) utilization; as predicted for species that possess carbon-concentrating mechanisms (CCMs), photosynthesis was not substantially affected by elevated pCO2. The internal CA activity was also unaffected by OA, and it remained high and active throughout the experiment; this suggests that HCO3 (-) uptake via an anion exchange protein was not affected by OA. Our results suggest that photosynthetic Ci uptake and growth of Macrocystis will not be affected by elevated pCO2/low pH predicted for the future, but the combined effects with other environmental factors like temperature and nutrient availability could change the physiological response of Macrocystis to OA. Therefore, further studies will be important to elucidate how this species might respond to the global environmental change predicted for the ocean.

Enhancing Activity Recognition by Fusing Inertial and Biometric Information

Activity recognition is an active research field nowadays, as it enables the development of highly adaptive applications, e.g. in the field of personal health. In this paper, a light high-level fusion algorithm to detect the activity that an individual is performing is presented. The algorithm relies on data gathered from accelerometers placed on different parts of the body, and on biometric sensors. Inertial sensors allow detecting activity by analyzing signal features such as amplitude or peaks. In addition, there is a relationship between the activity intensity and biometric response, which can be considered together with acceleration data to improve the accuracy of activity detection. The proposed algorithm is designed to work with minimum computational cost, being ready to run in a mobile device as part of a context-aware application. In order to enable different user scenarios, the algorithm offers best-effort activity estimation: its quality of estimation depends on the position and number of the available inertial sensors, and also on the presence of biometric information.

A Method for Developing Ontologies from User-Generated Classication Systems

Abstract Web 2.0 applications enabled users to classify information resources using their own vocabularies. The bottom-up nature of these user-generated classification systems have turned them into interesting knowledge sources, since they provide a rich terminology generated by potentially large user communities. Previous research has shown that it is possible to elicit some emergent semantics from the aggregation of individual classifications in these systems. However the generation of ontologies from them is still an open research problem. In this thesis we address the problem of how to tap into user-generated classification systems for building domain ontologies. Our objective is to design a method to develop domain ontologies from user-generated classifications systems. To do so, we rely on ontologies in the Web of Data to formalize the semantics of the knowledge collected from the classification system. Current ontology development methodologies have recognized the importance of reusing knowledge from existing resources. Thus, our work is framed within the NeOn methodology scenario for building ontologies by reusing and reengineering non-ontological resources. The main contributions of this work are: An integrated method to develop ontologies from user-generated classification systems. With this method we extract a domain terminology from the classification system and then we formalize the semantics of this terminology by reusing ontologies in the Web of Data. Identification and adaptation of existing techniques for implementing the activities in the method so that they can fulfill the requirements of each activity. A novel study about emerging semantics in user-generated lists. Resumen La web 2.0 permitió a los usuarios clasificar recursos de información usando su propio vocabulario. Estos sistemas de clasificación generados por usuarios son recursos interesantes para la extracción de conocimiento debido principalmente a que proveen una extensa terminología generada por grandes comunidades de usuarios. Se ha demostrado en investigaciones previas que es posible obtener una semántica emergente de estos sistemas. Sin embargo la generación de ontologías a partir de ellos es todavía un problema de investigación abierto. Esta tesis trata el problema de cómo aprovechar los sistemas de clasificación generados por usuarios en la construcción de ontologías de dominio. Así el objetivo de la tesis es diseñar un método para desarrollar ontologías de dominio a partir de sistemas de clasificación generados por usuarios. El método propuesto reutiliza conceptualizaciones existentes en ontologías publicadas en la Web de Datos para formalizar la semántica del conocimiento que se extrae del sistema de clasificación. Por tanto, este trabajo está enmarcado dentro del escenario para desarrollar ontologías mediante la reutilización y reingeniería de recursos no ontológicos que se ha definido en la Metodología NeOn. Las principales contribuciones de este trabajo son: Un método integrado para desarrollar una ontología de dominio a partir de sistemas de clasificación generados por usuarios. En este método se extrae una terminología de dominio del sistema de clasificación y posteriormente se formaliza su semántica reutilizando ontologías en la Web de Datos. La identificación y adaptación de un conjunto de técnicas para implementar las actividades propuestas en el método de tal manera que puedan cumplir automáticamente los requerimientos de cada actividad. Un novedoso estudio acerca de la semántica emergente en las listas generadas por usuarios en la Web.

Localization and activity detection Based on the fusion of environment And inertial sensors = Localización y detección de actividad Basadas en integración de sensores y dispositivos inerciales

Los sensores inerciales (acelerómetros y giróscopos) se han ido introduciendo poco a poco en dispositivos que usamos en nuestra vida diaria gracias a su minituarización. Hoy en día todos los smartphones contienen como mínimo un acelerómetro y un magnetómetro, siendo complementados en losmás modernos por giróscopos y barómetros. Esto, unido a la proliferación de los smartphones ha hecho viable el diseño de sistemas basados en las medidas de sensores que el usuario lleva colocados en alguna parte del cuerpo (que en un futuro estarán contenidos en tejidos inteligentes) o los integrados en su móvil. El papel de estos sensores se ha convertido en fundamental para el desarrollo de aplicaciones contextuales y de inteligencia ambiental. Algunos ejemplos son el control de los ejercicios de rehabilitación o la oferta de información referente al sitio turístico que se está visitando. El trabajo de esta tesis contribuye a explorar las posibilidades que ofrecen los sensores inerciales para el apoyo a la detección de actividad y la mejora de la precisión de servicios de localización para peatones. En lo referente al reconocimiento de la actividad que desarrolla un usuario, se ha explorado el uso de los sensores integrados en los dispositivos móviles de última generación (luz y proximidad, acelerómetro, giróscopo y magnetómetro). Las actividades objetivo son conocidas como ‘atómicas’ (andar a distintas velocidades, estar de pie, correr, estar sentado), esto es, actividades que constituyen unidades de actividades más complejas como pueden ser lavar los platos o ir al trabajo. De este modo, se usan algoritmos de clasificación sencillos que puedan ser integrados en un móvil como el Naïve Bayes, Tablas y Árboles de Decisión. Además, se pretende igualmente detectar la posición en la que el usuario lleva el móvil, no sólo con el objetivo de utilizar esa información para elegir un clasificador entrenado sólo con datos recogidos en la posición correspondiente (estrategia que mejora los resultados de estimación de la actividad), sino también para la generación de un evento que puede producir la ejecución de una acción. Finalmente, el trabajo incluye un análisis de las prestaciones de la clasificación variando el tipo de parámetros y el número de sensores usados y teniendo en cuenta no sólo la precisión de la clasificación sino también la carga computacional. Por otra parte, se ha propuesto un algoritmo basado en la cuenta de pasos utilizando informaiii ción proveniente de un acelerómetro colocado en el pie del usuario. El objetivo final es detectar la actividad que el usuario está haciendo junto con la estimación aproximada de la distancia recorrida. El algoritmo de cuenta pasos se basa en la detección de máximos y mínimos usando ventanas temporales y umbrales sin requerir información específica del usuario. El ámbito de seguimiento de peatones en interiores es interesante por la falta de un estándar de localización en este tipo de entornos. Se ha diseñado un filtro extendido de Kalman centralizado y ligeramente acoplado para fusionar la información medida por un acelerómetro colocado en el pie del usuario con medidas de posición. Se han aplicado también diferentes técnicas de corrección de errores como las de velocidad cero que se basan en la detección de los instantes en los que el pie está apoyado en el suelo. Los resultados han sido obtenidos en entornos interiores usando las posiciones estimadas por un sistema de triangulación basado en la medida de la potencia recibida (RSS) y GPS en exteriores. Finalmente, se han implementado algunas aplicaciones que prueban la utilidad del trabajo desarrollado. En primer lugar se ha considerado una aplicación de monitorización de actividad que proporciona al usuario información sobre el nivel de actividad que realiza durante un período de tiempo. El objetivo final es favorecer el cambio de comportamientos sedentarios, consiguiendo hábitos saludables. Se han desarrollado dos versiones de esta aplicación. En el primer caso se ha integrado el algoritmo de cuenta pasos en una plataforma OSGi móvil adquiriendo los datos de un acelerómetro Bluetooth colocado en el pie. En el segundo caso se ha creado la misma aplicación utilizando las implementaciones de los clasificadores en un dispositivo Android. Por otro lado, se ha planteado el diseño de una aplicación para la creación automática de un diario de viaje a partir de la detección de eventos importantes. Esta aplicación toma como entrada la información procedente de la estimación de actividad y de localización además de información almacenada en bases de datos abiertas (fotos, información sobre sitios) e información sobre sensores reales y virtuales (agenda, cámara, etc.) del móvil. Abstract Inertial sensors (accelerometers and gyroscopes) have been gradually embedded in the devices that people use in their daily lives thanks to their miniaturization. Nowadays all smartphones have at least one embedded magnetometer and accelerometer, containing the most upto- date ones gyroscopes and barometers. This issue, together with the fact that the penetration of smartphones is growing steadily, has made possible the design of systems that rely on the information gathered by wearable sensors (in the future contained in smart textiles) or inertial sensors embedded in a smartphone. The role of these sensors has become key to the development of context-aware and ambient intelligent applications. Some examples are the performance of rehabilitation exercises, the provision of information related to the place that the user is visiting or the interaction with objects by gesture recognition. The work of this thesis contributes to explore to which extent this kind of sensors can be useful to support activity recognition and pedestrian tracking, which have been proven to be essential for these applications. Regarding the recognition of the activity that a user performs, the use of sensors embedded in a smartphone (proximity and light sensors, gyroscopes, magnetometers and accelerometers) has been explored. The activities that are detected belong to the group of the ones known as ‘atomic’ activities (e.g. walking at different paces, running, standing), that is, activities or movements that are part of more complex activities such as doing the dishes or commuting. Simple, wellknown classifiers that can run embedded in a smartphone have been tested, such as Naïve Bayes, Decision Tables and Trees. In addition to this, another aim is to estimate the on-body position in which the user is carrying the mobile phone. The objective is not only to choose a classifier that has been trained with the corresponding data in order to enhance the classification but also to start actions. Finally, the performance of the different classifiers is analysed, taking into consideration different features and number of sensors. The computational and memory load of the classifiers is also measured. On the other hand, an algorithm based on step counting has been proposed. The acceleration information is provided by an accelerometer placed on the foot. The aim is to detect the activity that the user is performing together with the estimation of the distance covered. The step counting strategy is based on detecting minima and its corresponding maxima. Although the counting strategy is not innovative (it includes time windows and amplitude thresholds to prevent under or overestimation) no user-specific information is required. The field of pedestrian tracking is crucial due to the lack of a localization standard for this kind of environments. A loosely-coupled centralized Extended Kalman Filter has been proposed to perform the fusion of inertial and position measurements. Zero velocity updates have been applied whenever the foot is detected to be placed on the ground. The results have been obtained in indoor environments using a triangulation algorithm based on RSS measurements and GPS outdoors. Finally, some applications have been designed to test the usefulness of the work. The first one is called the ‘Activity Monitor’ whose aim is to prevent sedentary behaviours and to modify habits to achieve desired objectives of activity level. Two different versions of the application have been implemented. The first one uses the activity estimation based on the step counting algorithm, which has been integrated in an OSGi mobile framework acquiring the data from a Bluetooth accelerometer placed on the foot of the individual. The second one uses activity classifiers embedded in an Android smartphone. On the other hand, the design of a ‘Travel Logbook’ has been planned. The input of this application is the information provided by the activity and localization modules, external databases (e.g. pictures, points of interest, weather) and mobile embedded and virtual sensors (agenda, camera, etc.). The aim is to detect important events in the journey and gather the information necessary to store it as a journal page.

User benefit assessment by a dynamic LUTI model for Madrid

Assessing users’ benefit in a transport policy implementation has been studied by many researchers using theoretical or empirical measures. However, few of them measure users’ benefit in a different way from the consumer surplus. Therefore, this paper aims to assess a new measure of user benefits by weighting consumer surplus in order to include equity assessment for different transport policies simulated in a dynamic middle-term LUTI model adapted to the case study of Madrid. Three different transport policies, including road pricing, parking charge and public transport improvement have been simulated through the Metropolitan Activity Relocation Simulator, MARS, the LUTI calibrated model for Madrid). A social welfare function (WF) is defined using a cost benefit analysis function that includes mainly costs and benefits of users and operators of the transport system. Particularly, the part of welfare function concerning the users, (i.e. consumer surplus), is modified by a compensating weight (CW) which represents the inverse of household income level. Based on the modified social welfare function, the effects on the measure of users benefits are estimated and compared with the old WF ́s results as well. The result of the analysis shows that road pricing leads a negative effect on the users benefits specially on the low income users. Actually, the road pricing and parking charge implementation results like a regressive policy especially at long term. Public transport improvement scenario brings more positive effects on low income user benefits. The integrated (road pricing and increasing public services) policy scenario is the one which receive the most user benefits. The results of this research could be a key issue to understanding the relationship between transport systems policies and user benefits distribution in a metropolitan context.

Mars: a personalised mobile activity recognition system

Mobile activity recognition focuses on inferring the current activities of a mobile user by leveraging the sensory data that is available on today’s smart phones. The state of the art in mobile activity recognition uses traditional classification learning techniques. Thus, the learning process typically involves: i) collection of labelled sensory data that is transferred and collated in a centralised repository; ii) model building where the classification model is trained and tested using the collected data; iii) a model deployment stage where the learnt model is deployed on-board a mobile device for identifying activities based on new sensory data. In this paper, we demonstrate the Mobile Activity Recognition System (MARS) where for the first time the model is built and continuously updated on-board the mobile device itself using data stream mining. The advantages of the on-board approach are that it allows model personalisation and increased privacy as the data is not sent to any external site. Furthermore, when the user or its activity profile changes MARS enables promptly adaptation. MARS has been implemented on the Android platform to demonstrate that it can achieve accurate mobile activity recognition. Moreover, we can show in practise that MARS quickly adapts to user profile changes while at the same time being scalable and efficient in terms of consumption of the device resources.

Efficiency of human activity on information spreading on Twitter

In this work we study Twitter data to understand influence dynamics in social networks. We define user efficiency on Twitter, as the ratio between the emergent spreading process and the activity employed by the user. We characterize this property by means of a quantitative analysis of the structural and dynamical patterns emergent from human interactions, and show it to be universal across several Twitter conversations.

Quality cost in bus operations based on activity-based costing

The study of service quality and its implication for transport contracts has several approaches in research and practical applications, where the main emphasis is the consideration of quality from the user's point of view, thus obtaining a customer satisfaction index as a measurement of the overall quality with no further implications for service providers. The main aim of this paper is to estimate the real economic impact of improving quality attributes for a bus operator. An application of the activity-based costing methodology is developed for a bus contract in Madrid, using quality data from surveys together with economic and performance information, and focusing on headway as a quality variable. Results show the consistency and practicality of this methodology, overcoming simplifications from traditional procedures. This method is a powerful tool in quality-based contracting as well as for effective investment in transport quality under poverty funding constraints

Anomalous Consistency in Mild Cognitive Impairment: A Complex Networks Approach

Increased variability in performance has been associated with the emergence of several neurological and psychiatric pathologies. However, whether and how consistency of neuronal activity may also be indicative of an underlying pathology is still poorly understood. Here we propose a novel method for evaluating consistency from non-invasive brain recordings. We evaluate the consistency of the cortical activity recorded with magnetoencephalography in a group of subjects diagnosed with Mild Cognitive Impairment (MCI), a condition sometimes prodromal of dementia, during the execution of a memory task. We use metrics coming from nonlinear dynamics to evaluate the consistency of cortical regions. A representation known as parenclitic networks is constructed, where atypical features are endowed with a network structure, the topological properties of which can be studied at various scales. Pathological conditions correspond to strongly heterogeneous networks, whereas typical or normative conditions are characterized by sparsely connected networks with homogeneous nodes. The analysis of this kind of networks allows identifying the extent to which consistency is affected in the MCI group and the focal points where MCI is especially severe. To the best of our knowledge, these results represent the first attempt at evaluating the consistency of brain functional activity using complex networks theory.

User experience with immersive and interactive media = Experiencia de usuario en entornos 3D inmersivos e interactivos

Estudios recientes promueven la integración de estímulos multisensoriales en activos multimedia con el fin de mejorar la experiencia de usuario mediante la estimulación de nuevos sentidos, más allá de la tradicional experiencia audiovisual. Del mismo modo, varios trabajos proponen la introducción de componentes de interacción capaces de complementar con nuevas características, funcionalidades y/o información la experiencia multimedia. Efectos sensoriales basados en el uso de nuevas técnicas de audio, olores, viento, vibraciones y control de la iluminación, han demostrado tener un impacto favorable en la sensación de Presencia, en el disfrute de la experiencia multimedia y en la calidad, relevancia y realismo de la misma percibidos por el usuario. Asimismo, los servicios basados en dos pantallas y la manipulación directa de (elementos en) la escena de video tienen el potencial de mejorar la comprensión, la concentración y la implicación proactiva del usuario en la experiencia multimedia. El deporte se encuentra entre los géneros con mayor potencial para integrar y explotar éstas soluciones tecnológicas. Trabajos previos han demostrado asimismo la viabilidad técnica de integrar éstas tecnologías con los estándares actualmente adoptados a lo largo de toda la cadena de transmisión de televisión. De este modo, los sistemas multimedia enriquecidos con efectos sensoriales, los servicios interactivos multiplataforma y un mayor control del usuario sobre la escena de vídeo emergen como nuevas formas de llevar la multimedia immersiva e interactiva al mercado de consumo de forma no disruptiva. Sin embargo, existen numerosas interrogantes relativas a los efectos sensoriales y/o soluciones interactivas más adecuadas para complementar un contenido audiovisual determinado o a la mejor manera de de integrar y combinar dichos componentes para mejorar la experiencia de usuario de un segmento de audiencia objetivo. Además, la evidencia científica sobre el impacto de factores humanos en la experiencia de usuario con estas nuevas formas de immersión e interacción en el contexto multimedia es aún insuficiente y en ocasiones, contradictoria. Así, el papel de éstos factores en el potencial de adopción de éstas tecnologías ha sido amplia-mente ignorado. La presente tesis analiza el impacto del audio binaural, efectos sensoriales (de iluminación y olfativos), interacción con objetos 3D integrados en la escena de vídeo e interacción con contenido adicional utilizando una segunda pantalla en la experiencia de usuario con contenidos de deporte. La posible influencia de dichos componentes en las variables dependientes se explora tanto a nivel global (efecto promedio) como en función de las características de los usuarios (efectos heterogéneos). Para ello, se ha llevado a cabo un experimento con usuarios orientado a explorar la influencia de éstos componentes immersivos e interactivos en dos grandes dimensiones de la experiencia multimedia: calidad y Presencia. La calidad de la experiencia multimedia se analiza en términos de las posibles variaciones asociadas a la calidad global y a la calidad del contenido, la imagen, el audio, los efectos sensoriales, la interacción con objetos 3D y la interacción con la segunda pantalla. El posible impacto en la Presencia considera dos de las dimensiones definidas por el cuestionario ITC-SOPI: Presencia Espacial (Spatial Presence) e Implicación (Engagement). Por último, los individuos son caracterizados teniendo en cuenta los siguientes atributos afectivos, cognitivos y conductuales: preferencias y hábitos en relación con el contenido, grado de conocimiento de las tecnologías integradas en el sistema, tendencia a involucrarse emocionalmente, tendencia a concentrarse en una actividad bloqueando estímulos externos y los cinco grandes rasgos de la personalidad: extroversión, amabilidad, responsabilidad, inestabilidad emocional y apertura a nuevas experiencias. A nivel global, nuestro estudio revela que los participantes prefieren el audio binaural frente al sistema estéreo y que los efectos sensoriales generan un aumento significativo del nivel de Presencia Espacial percibido por los usuarios. Además, las manipulaciones experimentales realizadas permitieron identificar una gran variedad de efectos heterogéneos. Un resultado interesante es que dichos efectos no se encuentran distribuidos de forma equitativa entre las medidas de calidad y Presencia. Nuestros datos revelan un impacto generalizado del audio binaural en la mayoría de las medidas de calidad y Presencia analizadas. En cambio, la influencia de los efectos sensoriales y de la interacción con la segunda pantalla se concentran en las medidas de Presencia y calidad, respectivamente. La magnitud de los efectos heterogéneos identificados está modulada por las siguientes características personales: preferencias en relación con el contenido, frecuencia con la que el usuario suele ver contenido similar, conocimiento de las tecnologías integradas en el demostrador, sexo, tendencia a involucrarse emocionalmente, tendencia a a concentrarse en una actividad bloqueando estímulos externos y niveles de amabilidad, responsabilidad y apertura a nuevas experiencias. Las características personales consideradas en nuestro experimento explicaron la mayor parte de la variación en las variables dependientes, confirmando así el importante (y frecuentemente ignorado) papel de las diferencias individuales en la experiencia multimedia. Entre las características de los usuarios con un impacto más generalizado se encuentran las preferencias en relación con el contenido, el grado de conocimiento de las tecnologías integradas en el sistema y la tendencia a involucrarse emocionalmente. En particular, los primeros dos factores parecen generar un conflicto de atención hacia el contenido versus las características/elementos técnicos del sistema, respectivamente. Asimismo, la experiencia multimedia de los fans del fútbol parece estar modulada por procesos emociona-les, mientras que para los no-fans predominan los procesos cognitivos, en particular aquellos directamente relacionados con la percepción de calidad. Abstract Recent studies encourage the integration of multi-sensorial stimuli into multimedia assets to enhance the user experience by stimulating other senses beyond sight and hearing. Similarly, the introduction of multi-modal interaction components complementing with new features, functionalities and/or information the multimedia experience is promoted. Sensory effects as odor, wind, vibration and light effects, as well as an enhanced audio quality, have been found to favour media enjoyment and to have a positive influence on the sense of Presence and on the perceived quality, relevance and reality of a multimedia experience. Two-screen services and a direct manipulation of (elements in) the video scene have the potential to enhance user comprehension, engagement and proactive involvement of/in the media experience. Sports is among the genres that could benefit the most from these solutions. Previous works have demonstrated the technical feasibility of implementing and deploying end-to-end solutions integrating these technologies into legacy systems. Thus, sensorially-enhanced media, two-screen services and an increased user control over the displayed scene emerge as means to deliver a new form of immersive and interactive media experiences to the mass market in a non-disruptive manner. However, many questions remain concerning issues as the specific interactive solutions or sensory effects that can better complement a given audiovisual content or the best way in which to integrate and combine them to enhance the user experience of a target audience segment. Furthermore, scientific evidence on the impact of human factors on the user experience with these new forms of immersive and interactive media is still insufficient and sometimes, contradictory. Thus, the role of these factors on the potential adoption of these technologies has been widely ignored. This thesis analyzes the impact of binaural audio, sensory (light and olfactory) effects, interaction with 3D objects integrated into the video scene and interaction with additional content using a second screen on the sports media experience. The potential influence of these components on the dependent variables is explored both at the overall level (average effect) and as a function of users’ characteristics (heterogeneous effects). To these aims, we conducted an experimental study exploring the influence of these immersive and interactive elements on the quality and Presence dimensions of the media experience. Along the quality dimension, we look for possible variations on the quality scores as-signed to the overall media experience and to the media components content, image, audio, sensory effects, interaction with 3D objects and interaction using the tablet device. The potential impact on Presence is analyzed by looking at two of the four dimensions defined by the ITC-SOPI questionnaire, namely Spatial Presence and Engagement. The users’ characteristics considered encompass the following personal affective, cognitive and behavioral attributes: preferences and habits in relation to the content, knowledge of the involved technologies, tendency to get emotionally involved and tendency to get absorbed in an activity and block out external distractors and the big five personality traits extraversion, agreeableness, conscientiousness, neuroticism and openness to experience. At the overall level, we found that participants preferred binaural audio than standard stereo audio and that sensory effects increase significantly the level of Spatial Presence. Several heterogeneous effects were also revealed as a result of our experimental manipulations. Interestingly, these effects were not equally distributed across the quality and Presence measures analyzed. Whereas binaural audio was foud to have an influence on the majority of the quality and Presence measures considered, the effects of sensory effects and of interaction with additional content through the tablet device concentrate mainly on the dimensions of Presence and on quality measures, respectively. The magnitude of these effects was modulated by individual’s characteristics, such as: preferences in relation to the content, frequency of viewing similar content, knowledge of involved technologies, gender, tendency to get emotionally involved, tendency to absorption and levels of agreeableness, conscientiousness and openness to experience. The personal characteristics collected in our experiment explained most of the variation in the dependent variables, confirming the frequently neglected role of individual differences on the media experience. Preferences in relation to the content, knowledge of involved technologies and tendency to get emotionally involved were among the user variables with the most generalized influence. In particular, the former two features seem to present a conflict in the allocation of attentional resources towards the media content versus the technical features of the system, respectively. Additionally, football fans’ experience seems to be modulated by emotional processes whereas for not fans, cognitive processes (and in particular those related to quality judgment) prevail.

Human activity recognition by inertial signals obtained from a smartphone

Human Activity Recognition (HAR) is an emerging research field with the aim to identify the actions carried out by a person given a set of observations and the surrounding environment. The wide growth in this research field inside the scientific community is mainly explained by the high number of applications that are arising in the last years. A great part of the most promising applications are related to the healthcare field, where it is possible to track the mobility of patients with motor dysfunction as also the physical activity in patients with cardiovascular risk. Until a few years ago, by using distinct kind of sensors, a patient follow-up was possible. However, far from being a long-term solution and with the smartphone irruption, that monitoring can be achieved in a non-invasive way by using the embedded smartphone’s sensors. For these reasons this Final Degree Project arises with the main target to evaluate new feature extraction techniques in order to carry out an activity and user recognition, and also an activity segmentation. The recognition is done thanks to the inertial signals integration obtained by two widespread sensors in the greater part of smartphones: accelerometer and gyroscope. In particular, six different activities are evaluated walking, walking-upstairs, walking-downstairs, sitting, standing and lying. Furthermore, a segmentation task is carried out taking into account the activities performed by thirty users. This can be done by using Hidden Markov Models and also a set of tools tested satisfactory in speech recognition: HTK (Hidden Markov Model Toolkit).

The Tube on YouTube: TV Series, Media Strategies, and User Tactics in a Transmedia Environment

This study analyzes the traffic generated on YouTube around television series. We selected a sample of 314 short YouTube videos about 21 Spanish TV series that premiered in 2013 by Spain’s three most popular mainstream television networks (Telecinco, Antena 3, and La1). These videos, which together received more than 24 million views, were classified according to two key variables: the nature (official or nonofficial) of the YouTube channel on which they were located and the exclusivity of their content (already broadcast on TV or Web exclusive). The analysis allows us to characterize the strategies used by TV networks on YouTube and the activity of fans as well as their efforts in the construction of a transmedia narrative universe around TV series.