In this paper, we study the finite sample accuracy of confidence intervals for index functional built via parametric bootstrap, in the case of inequality indices. To estimate the parameters of the assumed parametric data generating distribution, we propose a Generalized Method of Moment estimator that targets the quantity of interest, namely the considered inequality index. Its primary advantage is that the scale parameter does not need to be estimated to perform parametric bootstrap, since inequality measures are scale invariant. The very good finite sample coverages that are found in a simulation study suggest that this feature provides an advantage over the parametric bootstrap using the maximum likelihood estimator. We also find that overall, a parametric bootstrap provides more accurate inference than its non or semi-parametric counterparts, especially for heavy tailed income distributions.
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.
