Services (général)

QoS-predictions service: infrastructural support for proactive QoS- and context-aware mobile services


Today's mobile data applications aspire to deliver services to a user anywhere – anytime while fulfilling his Quality of Service (QoS) requirements. However, the success of the service delivery heavily relies on the QoS offered by the underlying networks. As the services operate in a heterogeneous networking environment, we argue that the generic information about the networks' offered-QoS may enable an anyhow mobile service delivery based on an intelligent (proactive) selection of ‘any' network available in the user's context (location and time). Towards this direction, we develop a QoS-predictions service provider, which includes functionality for the acquisition of generic offered-QoS information and which, via a multidimensional processing and history-based reasoning, will provide predictions of the expected offered-QoS in a reliable and timely manner. We acquire the generic QoS-information from distributed mobile services' components quantitatively (actively and passively) measuring the applicationlevel QoS, while the reasoning is based on statistical data mining and pattern recognition techniques.

On the feasibility and privacy benefits of on-device data mining for opportunistic crowd-sensing and service self-provisioning


The average mobile device includes several sensors as a standard feature. Moreover, it roams with its owner, and can be used to collect context information on their behalf. It is often vital to collect data in order to create realistic models that might help us understand and predict the world. However, sharing personal data increases the chance of a user’s privacy being compromised by revealing their identity. In this thesis we show that most of the sensor data on a device should be handled with caution due to their potential to be a privacy threat and propose solutions for service self-provisioning for measuring location tracking information through unaided triangulation, and location context by using cell ID traces. When data absolutely needs to reach a third party, we show that opportunistic mixing strategies can be effective in anonymizing the source of the data.

DelibAnalysis: understanding online deliberation through automated discourse quality analysis and topic modeling


The thesis examines political discourse quality online and proposes a methodology for analyzing online conversations in an automated way. The study builds on Habermas' work by examining the quality of the public sphere in a digital age. Primarily, it examines the portion of the public sphere which deals with political discussions on online platforms. The proposed technique, DelibAnalysis, is a combination of random forests classification and k-means clustering using term-frequency inverse-document-frequency. The DelibAnalysis methodology is applied to a diverse dataset of online conversations between citizens and elected representatives in Canada, the United States and the United Kingdom using Facebook and blog platforms. This analysis is used to derive insights about the state of the online public sphere and the differences between platforms and discussion frameworks. The objective of this research is to provide a systematic framework for the semi-automated discourse quality analysis of large datasets, and in applying this framework, to yield insight into the structure and features of political discussions online.

Introducing spatial coverage in a semantic repository model


In this thesis, we propose a model for semantic digital libraries with a geospatial context and a definition of coverage as key concept. We present the document and spatial resource model. We define the annotation model and more particularly the geographic coverage that detail and define the location of each resource taking into account its type. Finally, we present the query model and matching process where the geospatial context is an essential feature. To validate this model, we develop some use cases and implementation. We first focus on annotating documents and precisely locating the documents within the spatial resource. To do so, we describe the implementation of the annotation model, presented in the digital library model, especially the geo-semantic knowledge resources alignment. Then we present the methodology and implementation of a new technique to extract geographic information and place semantic from tags issued of volunteered geographic information (VGI) sources. This technique is based on a categorisation system, with a non-statistical knowledge-based approach. This extraction can partly automate the definition of the geographic coverage for the digital library resources, or be used to enhance semantically or complete 3D models and geo services.

Artificial agents as social companions: design guidelines for emotional interactions


Virtual and robotic agents are becoming increasingly prominent, taking on a variety of everyday life roles (i.e., assistants, tutors, coaches, companions). Displaying social and affective behaviour is a necessary requirement when agents need to interact and collaborate with humans. Nevertheless, current agent prototypes lack important skills, such as recognising human emotions, adapting to them and expressing appropriate affective states. This dissertation addresses issues related to these challenges. First, research is surveyed which investigates the use of psychophysiology for affect recognition. Next, empirical work is presented which investigates the multimodal expression of emotions through robotic embodiment. Finally, a use-case is presented, where a virtual agent takes the role of a companion for older adults. An evaluation study is discussed, highlighting the effects of the agent’s socio-affective capabilities on interactions and long-term user-engagement. The dissertation concludes with a set of guidelines for the design of natural, believable, effective and acceptable human-agent interactions.

Fast prototyping and deformation of virtual humans


The creation of virtual representations of real humans is a challenging task that has been investigated for the last three decades. It utilizes a multi-dimensional approach that is used extensively in computer graphics and computer animation applications, and it also involves various fields. This work focuses on facilitating and improving the process of the representation and animation of virtual humans so that they can be used in a wide range of real-time applications. Investigations and contributions to the different steps of the virtual human creation and animation pipeline are detailed in this thesis. The aim of this work is to improve some of the existing procedures involved in the creation of a virtual human by reducing the cost factor, enhancing automation and improving realism. Within this work, we focus on three main areas of virtual human creation: body modelling, virtual clothing, and real-time body deformation.

Indoor occupancy sensing with ultrasounds


As human beings, we rely on audible sounds as one way to communicate between each other and to infer information about our surrounding environment. Similarly, ultrasounds are used by some species in the animal kingdom to sense objects around them and get relevant information about their environment. In this thesis, we build on the inherent characteristics of ultrasounds and explore their application in occupancy sensing of indoor spaces, as ultrasounds exhibit interesting advantages compared to other technologies. Specifically, we design methods and algorithms to generate and process ultrasonic signals and infer the room occupancy, and we develop systems to evaluate their performance. Throughout the work, we address the implementation of our methods using commodity hardware, we pay attention to design algorithms that are computationally efficient, and we evaluate their time and space complexity. We focus on the reusability aspects in our designs, with the aim of bringing the technology to a wide range of existing and potential commercial devices, that would be able to implement our methods and algorithms seamlessly, and offer insights for new applications (like improving users' experience, enhancing home automation, etc.).

Patient-specific multi-parametric computational model of lower limb muscle function from PET/MRI studies


Le but de la présente étude est d'étudier et de développer un modèle multidimensionnel des muscles des membres inférieurs spécifique pour le patient. Ce modèle combine des données anatomiques tridimensionnelles et des informations dynamiques fonctionnelles concernant la déformation musculaire, acquises à l'aide de l'imagerie PET et MRI.

Dans quelle mesure la mise en place des navettes autonomes dans les zones périphériques de Genève pourrait remplacer l’utilisation des véhicules privés ?


Ce travail est basé sur un avant-projet nommé « AVENUE » (Autonomous Vehicles to Evolve to a New Urban Experience) proposé à la Commission européenne des transports et de mobilité. Il s’agit d’un projet qui a pour but de démonter l’utilité que pourraient avoir les véhicules autonomes dans le cadre des transports publics et de mettre en lumière les divers avantages pratiques, économiques, environnementaux et sociaux qu’ils pourraient procurer. Le travail suivant tente avant tout d’explorer l’étendue du potentiel d’une nouvelle technologie appelé « Navette autonome » qui s’inscrit dans le cadre des véhicules autonomes. Cette technologie est, pour le moment, peu connue du grand public, alors qu’elle pourrait pourtant être la solution de demain en termes de mobilité. Ce travail aborde ce sujet de manière qualitative, le but étant de pousser la réflexion et de se poser de nouvelles questions sur les modalités, ainsi que sur l’emploi d’une technologie en développement ; ce travail ne vise donc pas à créer un business plan. Par conséquent, les coûts ne seront que très peu discutés. Par ailleurs, de manière volontaire, cette recherche ne s’intéressera pas aux véhicules autonomes en soit, car de nombreux articles traitent d’ores et déjà de ce sujet. Ce travail se concentre sur un thème précis sur lequel très peu d’articles ont été écrits. De plus, ce travail permet de mettre sous loupe la population des zones périphériques, ainsi que leurs besoins liés à la mobilité. En effet, cette population a tendance à être mise à l’écart par les transports publics et est ainsi poussée vers l’utilisation de véhicules privés. Ce travail essaie de se plonger dans le quotidien des habitants de la périphérie dans le but de découvrir les problèmes auxquels ils font face en matière de mobilité.

MetaSelf - A Framework for Designing and Controlling Self-Adaptive and Self-Organising Systems


This paper proposes a unifying framework for the engineering of dependable self-adaptive (SA) and self-organising (SO) systems. We first identify requirements for designing and building such SA and SO systems. Second, we propose a generic framework combining design-time and run-time features which permit the definition and analysis at design-time of mechanisms that both ensure and constrain the run-time behaviour of an SA or SO system, thereby providing some assurance of its self-* capabilities. We show how this framework applies to two different systems: (1) a dynamically resilient Web service system (2) design of an industrial assembly system with both SA and SO capabilities.


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