847 resultados para Context-aware systems
Resumo:
Future emerging market trends head towards positioning based services placing a new perspective on the way we obtain and exploit positioning information. On one hand, innovations in information technology and wireless communication systems enabled the development of numerous location based applications such as vehicle navigation and tracking, sensor networks applications, home automation, asset management, security and context aware location services. On the other hand, wireless networks themselves may bene t from localization information to improve the performances of di erent network layers. Location based routing, synchronization, interference cancellation are prime examples of applications where location information can be useful. Typical positioning solutions rely on measurements and exploitation of distance dependent signal metrics, such as the received signal strength, time of arrival or angle of arrival. They are cheaper and easier to implement than the dedicated positioning systems based on ngerprinting, but at the cost of accuracy. Therefore intelligent localization algorithms and signal processing techniques have to be applied to mitigate the lack of accuracy in distance estimates. Cooperation between nodes is used in cases where conventional positioning techniques do not perform well due to lack of existing infrastructure, or obstructed indoor environment. The objective is to concentrate on hybrid architecture where some nodes have points of attachment to an infrastructure, and simultaneously are interconnected via short-range ad hoc links. The availability of more capable handsets enables more innovative scenarios that take advantage of multiple radio access networks as well as peer-to-peer links for positioning. Link selection is used to optimize the tradeo between the power consumption of participating nodes and the quality of target localization. The Geometric Dilution of Precision and the Cramer-Rao Lower Bound can be used as criteria for choosing the appropriate set of anchor nodes and corresponding measurements before attempting location estimation itself. This work analyzes the existing solutions for node selection in order to improve localization performance, and proposes a novel method based on utility functions. The proposed method is then extended to mobile and heterogeneous environments. Simulations have been carried out, as well as evaluation with real measurement data. In addition, some speci c cases have been considered, such as localization in ill-conditioned scenarios and the use of negative information. The proposed approaches have shown to enhance estimation accuracy, whilst signi cantly reducing complexity, power consumption and signalling overhead.
Resumo:
In the vision of Mark Weiser on ubiquitous computing, computers are disappearing from the focus of the users and are seamlessly interacting with other computers and users in order to provide information and services. This shift of computers away from direct computer interaction requires another way of applications to interact without bothering the user. Context is the information which can be used to characterize the situation of persons, locations, or other objects relevant for the applications. Context-aware applications are capable of monitoring and exploiting knowledge about external operating conditions. These applications can adapt their behaviour based on the retrieved information and thus to replace (at least a certain amount) the missing user interactions. Context awareness can be assumed to be an important ingredient for applications in ubiquitous computing environments. However, context management in ubiquitous computing environments must reflect the specific characteristics of these environments, for example distribution, mobility, resource-constrained devices, and heterogeneity of context sources. Modern mobile devices are equipped with fast processors, sufficient memory, and with several sensors, like Global Positioning System (GPS) sensor, light sensor, or accelerometer. Since many applications in ubiquitous computing environments can exploit context information for enhancing their service to the user, these devices are highly useful for context-aware applications in ubiquitous computing environments. Additionally, context reasoners and external context providers can be incorporated. It is possible that several context sensors, reasoners and context providers offer the same type of information. However, the information providers can differ in quality levels (e.g. accuracy), representations (e.g. position represented in coordinates and as an address) of the offered information, and costs (like battery consumption) for providing the information. In order to simplify the development of context-aware applications, the developers should be able to transparently access context information without bothering with underlying context accessing techniques and distribution aspects. They should rather be able to express which kind of information they require, which quality criteria this information should fulfil, and how much the provision of this information should cost (not only monetary cost but also energy or performance usage). For this purpose, application developers as well as developers of context providers need a common language and vocabulary to specify which information they require respectively they provide. These descriptions respectively criteria have to be matched. For a matching of these descriptions, it is likely that a transformation of the provided information is needed to fulfil the criteria of the context-aware application. As it is possible that more than one provider fulfils the criteria, a selection process is required. In this process the system has to trade off the provided quality of context and required costs of the context provider against the quality of context requested by the context consumer. This selection allows to turn on context sources only if required. Explicitly selecting context services and thereby dynamically activating and deactivating the local context provider has the advantage that also the resource consumption is reduced as especially unused context sensors are deactivated. One promising solution is a middleware providing appropriate support in consideration of the principles of service-oriented computing like loose coupling, abstraction, reusability, or discoverability of context providers. This allows us to abstract context sensors, context reasoners and also external context providers as context services. In this thesis we present our solution consisting of a context model and ontology, a context offer and query language, a comprehensive matching and mediation process and a selection service. Especially the matching and mediation process and the selection service differ from the existing works. The matching and mediation process allows an autonomous establishment of mediation processes in order to transfer information from an offered representation into a requested representation. In difference to other approaches, the selection service selects not only a service for a service request, it rather selects a set of services in order to fulfil all requests which also facilitates the sharing of services. The approach is extensively reviewed regarding the different requirements and a set of demonstrators shows its usability in real-world scenarios.
Resumo:
Context-aware multimodal interactive systems aim to adapt to the needs and behavioural patterns of users and offer a way forward for enhancing the efficacy and quality of experience (QoE) in human-computer interaction. The various modalities that constribute to such systems each provide a specific uni-modal response that is integratively presented as a multi-modal interface capable of interpretation of multi-modal user input and appropriately responding to it through dynamically adapted multi-modal interactive flow management , This paper presents an initial background study in the context of the first phase of a PhD research programme in the area of optimisation of data fusion techniques to serve multimodal interactivite systems, their applications and requirements.
Resumo:
This paper proposes a conceptual model of a context-aware group support system (GSS) to assist local council employees to perform collaborative tasks in conjunction with inter- and intra-organisational stakeholders. Most discussions about e-government focus on the use of ICT to improve the relationship between government and citizen, not on the relationship between government and employees. This paper seeks to expose the unique culture of UK local councils and to show how a GSS could support local government employer and employee needs.
Resumo:
This paper proposes a conceptual model of a context-aware group support system (GSS) to assist local council employees to perform collaborative tasks in conjunction with inter- and intra-organisational stakeholders. Most discussions about e-government focus on the use of ICT to improve the relationship between government and citizen, not on the relationship between government and employees. This paper seeks to expose the unique culture of UK local councils and to show how a GSS could support local government employer and employee needs.
Resumo:
Programa de Doctorado: Ingeniería de Telecomunicación Avanzada.
Resumo:
Context-aware computing is currently considered the most promising approach to overcome information overload and to speed up access to relevant information and services. Context-awareness may be derived from many sources, including user profile and preferences, network information, sensor analysis; usually context-awareness relies on the ability of computing devices to interact with the physical world, i.e. with the natural and artificial objects hosted within the "environment”. Ideally, context-aware applications should not be intrusive and should be able to react according to user’s context, with minimum user effort. Context is an application dependent multidimensional space and the location is an important part of it since the very beginning. Location can be used to guide applications, in providing information or functions that are most appropriate for a specific position. Hence location systems play a crucial role. There are several technologies and systems for computing location to a vary degree of accuracy and tailored for specific space model, i.e. indoors or outdoors, structured spaces or unstructured spaces. The research challenge faced by this thesis is related to pedestrian positioning in heterogeneous environments. Particularly, the focus will be on pedestrian identification, localization, orientation and activity recognition. This research was mainly carried out within the “mobile and ambient systems” workgroup of EPOCH, a 6FP NoE on the application of ICT to Cultural Heritage. Therefore applications in Cultural Heritage sites were the main target of the context-aware services discussed. Cultural Heritage sites are considered significant test-beds in Context-aware computing for many reasons. For example building a smart environment in museums or in protected sites is a challenging task, because localization and tracking are usually based on technologies that are difficult to hide or harmonize within the environment. Therefore it is expected that the experience made with this research may be useful also in domains other than Cultural Heritage. This work presents three different approaches to the pedestrian identification, positioning and tracking: Pedestrian navigation by means of a wearable inertial sensing platform assisted by the vision based tracking system for initial settings an real-time calibration; Pedestrian navigation by means of a wearable inertial sensing platform augmented with GPS measurements; Pedestrian identification and tracking, combining the vision based tracking system with WiFi localization. The proposed localization systems have been mainly used to enhance Cultural Heritage applications in providing information and services depending on the user’s actual context, in particular depending on the user’s location.
Resumo:
Today, Digital Systems and Services for Technology Supported Learning and Education are recognized as the key drivers to transform the way that individuals, groups and organizations “learn” and the way to “assess learning” in 21st Century. These transformations influence: Objectives - moving from acquiring new “knowledge” to developing new and relevant “competences”; Methods – moving from “classroom” based teaching to “context-aware” personalized learning; and Assessment – moving from “life-long” degrees and certifications to “on-demand” and “in-context” accreditation of qualifications. Within this context, promoting Open Access to Formal and Informal Learning, is currently a key issue in the public discourse and the global dialogue on Education, including Massive Open Online Courses (MOOCs) and Flipped School Classrooms. This volume on Digital Systems for Open Access to Formal and Informal Learning contributes to the international dialogue between researchers, technologists, practitioners and policy makers in Technology Supported Education and Learning. It addresses emerging issues related with both theory and practice, as well as, methods and technologies that can support Open Access to Formal and Informal Learning. In the twenty chapters contributed by international experts who are actively shaping the future of Educational Technology around the world, topics such as: - The evolution of University Open Courses in Transforming Learning - Supporting Open Access to Teaching and Learning of People with Disabilities - Assessing Student Learning in Online Courses - Digital Game-based Learning for School Education - Open Access to Virtual and Remote Labs for STEM Education - Teachers’ and Schools’ ICT Competence Profiling - Web-Based Education and Innovative Leadership in a K-12 International School Setting are presented. An in-depth blueprint of the promise, potential, and imminent future of the field, Digital Systems for Open Access to Formal and Informal Learning is necessary reading for researchers and practitioners, as well as, undergraduate and postgraduate students, in educational technology.
Resumo:
The design and development of spoken interaction systems has been a thoroughly studied research scope for the last decades. The aim is to obtain systems with the ability to interact with human agents with a high degree of naturalness and efficiency, allowing them to carry out the actions they desire using speech, as it is the most natural means of communication between humans. To achieve that degree of naturalness, it is not enough to endow systems with the ability to accurately understand the user’s utterances and to properly react to them, even considering the information provided by the user in his or her previous interactions. The system has also to be aware of the evolution of the conditions under which the interaction takes place, in order to act the most coherent way as possible at each moment. Consequently, one of the most important features of the system is that it has to be context-aware. This context awareness of the system can be reflected in the modification of the behaviour of the system taking into account the current situation of the interaction. For instance, the system should decide which action it has to carry out, or the way to perform it, depending on the user that requests it, on the way that the user addresses the system, on the characteristics of the environment in which the interaction takes place, and so on. In other words, the system has to adapt its behaviour to these evolving elements of the interaction. Moreover that adaptation has to be carried out, if possible, in such a way that the user: i) does not perceive that the system has to make any additional effort, or to devote interaction time to perform tasks other than carrying out the requested actions, and ii) does not have to provide the system with any additional information to carry out the adaptation, which could imply a lesser efficiency of the interaction, since users should devote several interactions only to allow the system to become adapted. In the state-of-the-art spoken dialogue systems, researchers have proposed several disparate strategies to adapt the elements of the system to different conditions of the interaction (such as the acoustic characteristics of a specific user’s speech, the actions previously requested, and so on). Nevertheless, to our knowledge there is not any consensus on the procedures to carry out these adaptation. The approaches are to an extent unrelated from one another, in the sense that each one considers different pieces of information, and the treatment of that information is different taking into account the adaptation carried out. In this regard, the main contributions of this Thesis are the following ones: Definition of a contextualization framework. We propose a unified approach that can cover any strategy to adapt the behaviour of a dialogue system to the conditions of the interaction (i.e. the context). In our theoretical definition of the contextualization framework we consider the system’s context as all the sources of variability present at any time of the interaction, either those ones related to the environment in which the interaction takes place, or to the human agent that addresses the system at each moment. Our proposal relies on three aspects that any contextualization approach should fulfill: plasticity (i.e. the system has to be able to modify its behaviour in the most proactive way taking into account the conditions under which the interaction takes place), adaptivity (i.e. the system has also to be able to consider the most appropriate sources of information at each moment, both environmental and user- and dialogue-dependent, to effectively adapt to the conditions aforementioned), and transparency (i.e. the system has to carry out the contextualizaton-related tasks in such a way that the user neither perceives them nor has to do any effort in providing the system with any information that it needs to perform that contextualization). Additionally, we could include a generality aspect to our proposed framework: the main features of the framework should be easy to adopt in any dialogue system, regardless of the solution proposed to manage the dialogue. Once we define the theoretical basis of our contextualization framework, we propose two cases of study on its application in a spoken dialogue system. We focus on two aspects of the interaction: the contextualization of the speech recognition models, and the incorporation of user-specific information into the dialogue flow. One of the modules of a dialogue system that is more prone to be contextualized is the speech recognition system. This module makes use of several models to emit a recognition hypothesis from the user’s speech signal. Generally speaking, a recognition system considers two types of models: an acoustic one (that models each of the phonemes that the recognition system has to consider) and a linguistic one (that models the sequences of words that make sense for the system). In this work we contextualize the language model of the recognition system in such a way that it takes into account the information provided by the user in both his or her current utterance and in the previous ones. These utterances convey information useful to help the system in the recognition of the next utterance. The contextualization approach that we propose consists of a dynamic adaptation of the language model that is used by the recognition system. We carry out this adaptation by means of a linear interpolation between several models. Instead of training the best interpolation weights, we make them dependent on the conditions of the dialogue. In our approach, the system itself will obtain these weights as a function of the reliability of the different elements of information available, such as the semantic concepts extracted from the user’s utterance, the actions that he or she wants to carry out, the information provided in the previous interactions, and so on. One of the aspects more frequently addressed in Human-Computer Interaction research is the inclusion of user specific characteristics into the information structures managed by the system. The idea is to take into account the features that make each user different from the others in order to offer to each particular user different services (or the same service, but in a different way). We could consider this approach as a user-dependent contextualization of the system. In our work we propose the definition of a user model that contains all the information of each user that could be potentially useful to the system at a given moment of the interaction. In particular we will analyze the actions that each user carries out throughout his or her interaction. The objective is to determine which of these actions become the preferences of that user. We represent the specific information of each user as a feature vector. Each of the characteristics that the system will take into account has a confidence score associated. With these elements, we propose a probabilistic definition of a user preference, as the action whose likelihood of being addressed by the user is greater than the one for the rest of actions. To include the user dependent information into the dialogue flow, we modify the information structures on which the dialogue manager relies to retrieve information that could be needed to solve the actions addressed by the user. Usage preferences become another source of contextual information that will be considered by the system towards a more efficient interaction (since the new information source will help to decrease the need of the system to ask users for additional information, thus reducing the number of turns needed to carry out a specific action). To test the benefits of the contextualization framework that we propose, we carry out an evaluation of the two strategies aforementioned. We gather several performance metrics, both objective and subjective, that allow us to compare the improvements of a contextualized system against the baseline one. We will also gather the user’s opinions as regards their perceptions on the behaviour of the system, and its degree of adaptation to the specific features of each interaction. Resumen El diseño y el desarrollo de sistemas de interacción hablada ha sido objeto de profundo estudio durante las pasadas décadas. El propósito es la consecución de sistemas con la capacidad de interactuar con agentes humanos con un alto grado de eficiencia y naturalidad. De esta manera, los usuarios pueden desempeñar las tareas que deseen empleando la voz, que es el medio de comunicación más natural para los humanos. A fin de alcanzar el grado de naturalidad deseado, no basta con dotar a los sistemas de la abilidad de comprender las intervenciones de los usuarios y reaccionar a ellas de manera apropiada (teniendo en consideración, incluso, la información proporcionada en previas interacciones). Adicionalmente, el sistema ha de ser consciente de las condiciones bajo las cuales transcurre la interacción, así como de la evolución de las mismas, de tal manera que pueda actuar de la manera más coherente en cada instante de la interacción. En consecuencia, una de las características primordiales del sistema es que debe ser sensible al contexto. Esta capacidad del sistema de conocer y emplear el contexto de la interacción puede verse reflejada en la modificación de su comportamiento debida a las características actuales de la interacción. Por ejemplo, el sistema debería decidir cuál es la acción más apropiada, o la mejor manera de llevarla a término, dependiendo del usuario que la solicita, del modo en el que lo hace, etcétera. En otras palabras, el sistema ha de adaptar su comportamiento a tales elementos mutables (o dinámicos) de la interacción. Dos características adicionales son requeridas a dicha adaptación: i) el usuario no ha de percibir que el sistema dedica recursos (temporales o computacionales) a realizar tareas distintas a las que aquél le solicita, y ii) el usuario no ha de dedicar esfuerzo alguno a proporcionar al sistema información adicional para llevar a cabo la interacción. Esto último implicaría una menor eficiencia de la interacción, puesto que los usuarios deberían dedicar parte de la misma a proporcionar información al sistema para su adaptación, sin ningún beneficio inmediato. En los sistemas de diálogo hablado propuestos en la literatura, se han propuesto diferentes estrategias para llevar a cabo la adaptación de los elementos del sistema a las diferentes condiciones de la interacción (tales como las características acústicas del habla de un usuario particular, o a las acciones a las que se ha referido con anterioridad). Sin embargo, no existe una estrategia fija para proceder a dicha adaptación, sino que las mismas no suelen guardar una relación entre sí. En este sentido, cada una de ellas tiene en cuenta distintas fuentes de información, la cual es tratada de manera diferente en función de las características de la adaptación buscada. Teniendo en cuenta lo anterior, las contribuciones principales de esta Tesis son las siguientes: Definición de un marco de contextualización. Proponemos un criterio unificador que pueda cubrir cualquier estrategia de adaptación del comportamiento de un sistema de diálogo a las condiciones de la interacción (esto es, el contexto de la misma). En nuestra definición teórica del marco de contextualización consideramos el contexto del sistema como todas aquellas fuentes de variabilidad presentes en cualquier instante de la interacción, ya estén relacionadas con el entorno en el que tiene lugar la interacción, ya dependan del agente humano que se dirige al sistema en cada momento. Nuestra propuesta se basa en tres aspectos que cualquier estrategia de contextualización debería cumplir: plasticidad (es decir, el sistema ha de ser capaz de modificar su comportamiento de la manera más proactiva posible, teniendo en cuenta las condiciones en las que tiene lugar la interacción), adaptabilidad (esto es, el sistema ha de ser capaz de considerar la información oportuna en cada instante, ya dependa del entorno o del usuario, de tal manera que adecúe su comportamiento de manera eficaz a las condiciones mencionadas), y transparencia (que implica que el sistema ha de desarrollar las tareas relacionadas con la contextualización de tal manera que el usuario no perciba la manera en que dichas tareas se llevan a cabo, ni tampoco deba proporcionar al sistema con información adicional alguna). De manera adicional, incluiremos en el marco propuesto el aspecto de la generalidad: las características del marco de contextualización han de ser portables a cualquier sistema de diálogo, con independencia de la solución propuesta en los mismos para gestionar el diálogo. Una vez hemos definido las características de alto nivel de nuestro marco de contextualización, proponemos dos estrategias de aplicación del mismo a un sistema de diálogo hablado. Nos centraremos en dos aspectos de la interacción a adaptar: los modelos empleados en el reconocimiento de habla, y la incorporación de información específica de cada usuario en el flujo de diálogo. Uno de los módulos de un sistema de diálogo más susceptible de ser contextualizado es el sistema de reconocimiento de habla. Este módulo hace uso de varios modelos para generar una hipótesis de reconocimiento a partir de la señal de habla. En general, un sistema de reconocimiento emplea dos tipos de modelos: uno acústico (que modela cada uno de los fonemas considerados por el reconocedor) y uno lingüístico (que modela las secuencias de palabras que tienen sentido desde el punto de vista de la interacción). En este trabajo contextualizamos el modelo lingüístico del reconocedor de habla, de tal manera que tenga en cuenta la información proporcionada por el usuario, tanto en su intervención actual como en las previas. Estas intervenciones contienen información (semántica y/o discursiva) que puede contribuir a un mejor reconocimiento de las subsiguientes intervenciones del usuario. La estrategia de contextualización propuesta consiste en una adaptación dinámica del modelo de lenguaje empleado en el reconocedor de habla. Dicha adaptación se lleva a cabo mediante una interpolación lineal entre diferentes modelos. En lugar de entrenar los mejores pesos de interpolación, proponemos hacer los mismos dependientes de las condiciones actuales de cada diálogo. El propio sistema obtendrá estos pesos como función de la disponibilidad y relevancia de las diferentes fuentes de información disponibles, tales como los conceptos semánticos extraídos a partir de la intervención del usuario, o las acciones que el mismo desea ejecutar. Uno de los aspectos más comúnmente analizados en la investigación de la Interacción Persona-Máquina es la inclusión de las características específicas de cada usuario en las estructuras de información empleadas por el sistema. El objetivo es tener en cuenta los aspectos que diferencian a cada usuario, de tal manera que el sistema pueda ofrecer a cada uno de ellos el servicio más apropiado (o un mismo servicio, pero de la manera más adecuada a cada usuario). Podemos considerar esta estrategia como una contextualización dependiente del usuario. En este trabajo proponemos la definición de un modelo de usuario que contenga toda la información relativa a cada usuario, que pueda ser potencialmente utilizada por el sistema en un momento determinado de la interacción. En particular, analizaremos aquellas acciones que cada usuario decide ejecutar a lo largo de sus diálogos con el sistema. Nuestro objetivo es determinar cuáles de dichas acciones se convierten en las preferencias de cada usuario. La información de cada usuario quedará representada mediante un vector de características, cada una de las cuales tendrá asociado un valor de confianza. Con ambos elementos proponemos una definición probabilística de una preferencia de uso, como aquella acción cuya verosimilitud es mayor que la del resto de acciones solicitadas por el usuario. A fin de incluir la información dependiente de usuario en el flujo de diálogo, llevamos a cabo una modificación de las estructuras de información en las que se apoya el gestor de diálogo para recuperar información necesaria para resolver ciertos diálogos. En dicha modificación las preferencias de cada usuario pasarán a ser una fuente adicional de información contextual, que será tenida en cuenta por el sistema en aras de una interacción más eficiente (puesto que la nueva fuente de información contribuirá a reducir la necesidad del sistema de solicitar al usuario información adicional, dando lugar en consecuencia a una reducción del número de intervenciones necesarias para llevar a cabo una acción determinada). Para determinar los beneficios de las aplicaciones del marco de contextualización propuesto, llevamos a cabo una evaluación de un sistema de diálogo que incluye las estrategias mencionadas. Hemos recogido diversas métricas, tanto objetivas como subjetivas, que nos permiten determinar las mejoras aportadas por un sistema contextualizado en comparación con el sistema sin contextualizar. De igual manera, hemos recogido las opiniones de los participantes en la evaluación acerca de su percepción del comportamiento del sistema, y de su capacidad de adaptación a las condiciones concretas de cada interacción.
Resumo:
The LifeWear-Mobilized Lifestyle with Wearables (Lifewear) project attempts to create Ambient Intelligence (AmI) ecosystems by composing personalized services based on the user information, environmental conditions and reasoning outputs. Two of the most important benefits over traditional environments are 1) take advantage of wearable devices to get user information in a nonintrusive way and 2) integrate this information with other intelligent services and environmental sensors. This paper proposes a new ontology composed by the integration of users and services information, for semantically representing this information. Using an Enterprise Service Bus, this ontology is integrated in a semantic middleware to provide context-aware personalized and semantically annotated services, with discovery, composition and orchestration tasks. We show how these services support a real scenario proposed in the Lifewear project.
Resumo:
En esta Tesis se presentan dos líneas de investigación relacionadas y que contribuyen a las áreas de Interacción Hombre-Tecnología (o Máquina; siglas en inglés: HTI o HMI), lingüística computacional y evaluación de la experiencia del usuario. Las dos líneas en cuestión son el diseño y la evaluación centrada en el usuario de sistemas de Interacción Hombre-Máquina avanzados. En la primera parte de la Tesis (Capítulos 2 a 4) se abordan cuestiones fundamentales del diseño de sistemas HMI avanzados. El Capítulo 2 presenta una panorámica del estado del arte de la investigación en el ámbito de los sistemas conversacionales multimodales, con la que se enmarca el trabajo de investigación presentado en el resto de la Tesis. Los Capítulos 3 y 4 se centran en dos grandes aspectos del diseño de sistemas HMI: un gestor del diálogo generalizado para tratar la Interacción Hombre-Máquina multimodal y sensible al contexto, y el uso de agentes animados personificados (ECAs) para mejorar la robustez del diálogo, respectivamente. El Capítulo 3, sobre gestión del diálogo, aborda el tratamiento de la heterogeneidad de la información proveniente de las modalidades comunicativas y de los sensores externos. En este capítulo se propone, en un nivel de abstracción alto, una arquitectura para la gestión del diálogo con influjos heterogéneos de información, apoyándose en el uso de State Chart XML. En el Capítulo 4 se presenta una contribución a la representación interna de intenciones comunicativas, y su traducción a secuencias de gestos a ejecutar por parte de un ECA, diseñados específicamente para mejorar la robustez en situaciones de diálogo críticas que pueden surgir, por ejemplo, cuando se producen errores de entendimiento en la comunicación entre el usuario humano y la máquina. Se propone, en estas páginas, una extensión del Functional Mark-up Language definido en el marco conceptual SAIBA. Esta extensión permite representar actos comunicativos que realizan intenciones del emisor (la máquina) que no se pretende sean captadas conscientemente por el receptor (el usuario humano), pero con las que se pretende influirle a éste e influir el curso del diálogo. Esto se consigue mediante un objeto llamado Base de Intenciones Comunicativas (en inglés, Communication Intention Base, o CIB). La representación en el CIB de intenciones “no claradas” además de las explícitas permite la construcción de actos comunicativos que realizan simultáneamente varias intenciones comunicativas. En el Capítulo 4 también se describe un sistema experimental para el control remoto (simulado) de un asistente domótico, con autenticación de locutor para dar acceso, y con un ECA en el interfaz de cada una de estas tareas. Se incluye una descripción de las secuencias de comportamiento verbal y no verbal de los ECAs, que fueron diseñados específicamente para determinadas situaciones con objeto de mejorar la robustez del diálogo. Los Capítulos 5 a 7 conforman la parte de la Tesis dedicada a la evaluación. El Capítulo 5 repasa antecedentes relevantes en la literatura de tecnologías de la información en general, y de sistemas de interacción hablada en particular. Los principales antecedentes en el ámbito de la evaluación de la interacción sobre los cuales se ha desarrollado el trabajo presentado en esta Tesis son el Technology Acceptance Model (TAM), la herramienta Subjective Assessment of Speech System Interfaces (SASSI), y la Recomendación P.851 de la ITU-T. En el Capítulo 6 se describen un marco y una metodología de evaluación aplicados a la experiencia del usuario con sistemas HMI multimodales. Se desarrolló con este propósito un novedoso marco de evaluación subjetiva de la calidad de la experiencia del usuario y su relación con la aceptación por parte del mismo de la tecnología HMI (el nombre dado en inglés a este marco es Subjective Quality Evaluation Framework). En este marco se articula una estructura de clases de factores subjetivos relacionados con la satisfacción y aceptación por parte del usuario de la tecnología HMI propuesta. Esta estructura, tal y como se propone en la presente tesis, tiene dos dimensiones ortogonales. Primero se identifican tres grandes clases de parámetros relacionados con la aceptación por parte del usuario: “agradabilidad ” (likeability: aquellos que tienen que ver con la experiencia de uso, sin entrar en valoraciones de utilidad), rechazo (los cuales sólo pueden tener una valencia negativa) y percepción de utilidad. En segundo lugar, este conjunto clases se reproduce para distintos “niveles, o focos, percepción del usuario”. Éstos incluyen, como mínimo, un nivel de valoración global del sistema, niveles correspondientes a las tareas a realizar y objetivos a alcanzar, y un nivel de interfaz (en los casos propuestos en esta tesis, el interfaz es un sistema de diálogo con o sin un ECA). En el Capítulo 7 se presenta una evaluación empírica del sistema descrito en el Capítulo 4. El estudio se apoya en los mencionados antecedentes en la literatura, ampliados con parámetros para el estudio específico de los agentes animados (los ECAs), la auto-evaluación de las emociones de los usuarios, así como determinados factores de rechazo (concretamente, la preocupación por la privacidad y la seguridad). También se evalúa el marco de evaluación subjetiva de la calidad propuesto en el capítulo anterior. Los análisis de factores efectuados revelan una estructura de parámetros muy cercana conceptualmente a la división de clases en utilidad-agradabilidad-rechazo propuesta en dicho marco, resultado que da cierta validez empírica al marco. Análisis basados en regresiones lineales revelan estructuras de dependencias e interrelación entre los parámetros subjetivos y objetivos considerados. El efecto central de mediación, descrito en el Technology Acceptance Model, de la utilidad percibida sobre la relación de dependencia entre la intención de uso y la facilidad de uso percibida, se confirma en el estudio presentado en la presente Tesis. Además, se ha encontrado que esta estructura de relaciones se fortalece, en el estudio concreto presentado en estas páginas, si las variables consideradas se generalizan para cubrir más ampliamente las categorías de agradabilidad y utilidad contempladas en el marco de evaluación subjetiva de calidad. Se ha observado, asimismo, que los factores de rechazo aparecen como un componente propio en los análisis de factores, y además se distinguen por su comportamiento: moderan la relación entre la intención de uso (que es el principal indicador de la aceptación del usuario) y su predictor más fuerte, la utilidad percibida. Se presentan también resultados de menor importancia referentes a los efectos de los ECAs sobre los interfaces de los sistemas de diálogo y sobre los parámetros de percepción y las valoraciones de los usuarios que juegan un papel en conformar su aceptación de la tecnología. A pesar de que se observa un rendimiento de la interacción dialogada ligeramente mejor con ECAs, las opiniones subjetivas son muy similares entre los dos grupos experimentales (uno interactuando con un sistema de diálogo con ECA, y el otro sin ECA). Entre las pequeñas diferencias encontradas entre los dos grupos destacan las siguientes: en el grupo experimental sin ECA (es decir, con interfaz sólo de voz) se observó un efecto más directo de los problemas de diálogo (por ejemplo, errores de reconocimiento) sobre la percepción de robustez, mientras que el grupo con ECA tuvo una respuesta emocional más positiva cuando se producían problemas. Los ECAs parecen generar inicialmente expectativas más elevadas en cuanto a las capacidades del sistema, y los usuarios de este grupo se declaran más seguros de sí mismos en su interacción. Por último, se observan algunos indicios de efectos sociales de los ECAs: la “amigabilidad ” percibida los ECAs estaba correlada con un incremento la preocupación por la seguridad. Asimismo, los usuarios del sistema con ECAs tendían más a culparse a sí mismos, en lugar de culpar al sistema, de los problemas de diálogo que pudieran surgir, mientras que se observó una ligera tendencia opuesta en el caso de los usuarios del sistema con interacción sólo de voz. ABSTRACT This Thesis presents two related lines of research work contributing to the general fields of Human-Technology (or Machine) Interaction (HTI, or HMI), computational linguistics, and user experience evaluation. These two lines are the design and user-focused evaluation of advanced Human-Machine (or Technology) Interaction systems. The first part of the Thesis (Chapters 2 to 4) is centred on advanced HMI system design. Chapter 2 provides a background overview of the state of research in multimodal conversational systems. This sets the stage for the research work presented in the rest of the Thesis. Chapers 3 and 4 focus on two major aspects of HMI design in detail: a generalised dialogue manager for context-aware multimodal HMI, and embodied conversational agents (ECAs, or animated agents) to improve dialogue robustness, respectively. Chapter 3, on dialogue management, deals with how to handle information heterogeneity, both from the communication modalities or from external sensors. A highly abstracted architectural contribution based on State Chart XML is proposed. Chapter 4 presents a contribution for the internal representation of communication intentions and their translation into gestural sequences for an ECA, especially designed to improve robustness in critical dialogue situations such as when miscommunication occurs. We propose an extension of the functionality of Functional Mark-up Language, as envisaged in much of the work in the SAIBA framework. Our extension allows the representation of communication acts that carry intentions that are not for the interlocutor to know of, but which are made to influence him or her as well as the flow of the dialogue itself. This is achieved through a design element we have called the Communication Intention Base. Such r pr s ntation of “non- clar ” int ntions allows th construction of communication acts that carry several communication intentions simultaneously. Also in Chapter 4, an experimental system is described which allows (simulated) remote control to a home automation assistant, with biometric (speaker) authentication to grant access, featuring embodied conversation agents for each of the tasks. The discussion includes a description of the behavioural sequences for the ECAs, which were designed for specific dialogue situations with particular attention given to the objective of improving dialogue robustness. Chapters 5 to 7 form the evaluation part of the Thesis. Chapter 5 reviews evaluation approaches in the literature for information technologies, as well as in particular for speech-based interaction systems, that are useful precedents to the contributions of the present Thesis. The main evaluation precedents on which the work in this Thesis has built are the Technology Acceptance Model (TAM), the Subjective Assessment of Speech System Interfaces (SASSI) tool, and ITU-T Recommendation P.851. Chapter 6 presents the author’s work in establishing an valuation framework and methodology applied to the users’ experience with multimodal HMI systems. A novel user-acceptance Subjective Quality Evaluation Framework was developed by the author specifically for this purpose. A class structure arises from two orthogonal sets of dimensions. First we identify three broad classes of parameters related with user acceptance: likeability factors (those that have to do with the experience of using the system), rejection factors (which can only have a negative valence) and perception of usefulness. Secondly, the class structure is further broken down into several “user perception levels”; at the very least: an overall system-assessment level, task and goal-related levels, and an interface level (e.g., a dialogue system with or without an ECA). An empirical evaluation of the system described in Chapter 4 is presented in Chapter 7. The study was based on the abovementioned precedents in the literature, expanded with categories covering the inclusion of an ECA, the users’ s lf-assessed emotions, and particular rejection factors (privacy and security concerns). The Subjective Quality Evaluation Framework proposed in the previous chapter was also scrutinised. Factor analyses revealed an item structure very much related conceptually to the usefulness-likeability-rejection class division introduced above, thus giving it some empirical weight. Regression-based analysis revealed structures of dependencies, paths of interrelations, between the subjective and objective parameters considered. The central mediation effect, in the Technology Acceptance Model, of perceived usefulness on the dependency relationship of intention-to-use with perceived ease of use was confirmed in this study. Furthermore, the pattern of relationships was stronger for variables covering more broadly the likeability and usefulness categories in the Subjective Quality Evaluation Framework. Rejection factors were found to have a distinct presence as components in factor analyses, as well as distinct behaviour: they were found to moderate the relationship between intention-to-use (the main measure of user acceptance) and its strongest predictor, perceived usefulness. Insights of secondary importance are also given regarding the effect of ECAs on the interface of spoken dialogue systems and the dimensions of user perception and judgement attitude that may have a role in determining user acceptance of the technology. Despite observing slightly better performance values in the case of the system with the ECA, subjective opinions regarding both systems were, overall, very similar. Minor differences between two experimental groups (one interacting with an ECA, the other only through speech) include a more direct effect of dialogue problems (e.g., non-understandings) on perceived dialogue robustness for the voice-only interface test group, and a more positive emotional response for the ECA test group. Our findings further suggest that the ECA generates higher initial expectations, and users seem slightly more confident in their interaction with the ECA than do those without it. Finally, mild evidence of social effects of ECAs was also found: the perceived friendliness of the ECA increased security concerns, and ECA users may tend to blame themselves rather than the system when dialogue problems are encountered, while the opposite may be true for voice-only users.
Resumo:
Cyber-Physical Systems need to handle increasingly complex tasks, which additionally, may have variable operating conditions over time. Therefore, dynamic resource management to adapt the system to different needs is required. In this paper, a new bus-based architecture, called ARTICo3, which by means of Dynamic Partial Reconfiguration, allows the replication of hardware tasks to support module redundancy, multi-thread operation or dual-rail solutions for enhanced side-channel attack protection is presented. A configuration-aware data transaction unit permits data dispatching to more than one module in parallel, or provide coalesced data dispatching among different units to maximize the advantages of burst transactions. The selection of a given configuration is application independent but context-aware, which may be achieved by the combination of a multi-thread model similar to the CUDA kernel model specification, combined with a dynamic thread/task/kernel scheduler. A multi-kernel application for face recognition is used as an application example to show one scenario of the ARTICo3 architecture.
Resumo:
Pervasive computing applications must be sufficiently autonomous to adapt their behaviour to changes in computing resources and user requirements. This capability is known as context-awareness. In some cases, context-aware applications must be implemented as autonomic systems which are capable of dynamically discovering and replacing context sources (sensors) at run-time. Unlike other types of application autonomy, this kind of dynamic reconfiguration has not been sufficiently investigated yet by the research community. However, application-level context models are becoming common, in order to ease programming of context-aware applications and support evolution by decoupling applications from context sources. We can leverage these context models to develop general (i.e., application-independent) solutions for dynamic, run-time discovery of context sources (i.e., context management). This paper presents a model and architecture for a reconfigurable context management system that supports interoperability by building on emerging standards for sensor description and classification.
Resumo:
Pervasive systems need to be context aware and need to adapt to context changes, including network disconnections and changes in network Quality of Service (QoS). Vertical handover (handover between heterogeneous networks) is one of possible adaptation methods. It allows users to roam freely between heterogeneous networks while maintaining continuity of their applications. This paper proposes a vertical handover approach suitable for multimedia applications in pervasive systems. It describes the adaptability decision making process which uses vertical handovers to support users mobility and provision of QoS suitable for users’ applications. The process evaluates context information regarding user devices, User location, network environment, and user perceived QoS of applications.