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.
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.
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.
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.
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.
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.).
This chapter addresses a special category of cases in which an asserted patent is, or has been declared to be, essential to the implementation of a collaboratively-developed voluntary consensus standard, and the holder of that patent has agreed to license it to implementers of the standard on terms that are fair, reasonable and non-discriminatory (FRAND). In this chapter, we explore how the existence of such a FRAND commitment may affect a patent holder’s entitlement to monetary damages and injunctive relief. In addition to issues of patent law, remedies law and contract law, we consider the effect of competition law on this issue.
