Press discourses on ecological crises in the UK, Israel, and Hungary

This article explores the relationships between political projects of belonging and approaches to environmental and climate ecological crises via comparing centre-right and centre-left newspapers in the UK, Israel and Hungary. Our theoretical framework draws on Nira Yuval-Davis's work on the politics of belonging as a way of understanding and framing the different political projects that accompany reporting on ecological issues. Focusing on selected national and international case studies on these issues at the centre of public debate during the last two decades, the paper explores and compares these relationships by examining the eco-relational, spatial, temporal and normative framing dimensions of the political projects of belonging as expressed in these articles. The findings of the analysis show that, despite different cultural and historical contexts, the most significant dividing line is not among countries but between the different political projects of belonging of the newspapers. This can be seen even when dealing with country-specific, rather than international, case studies. Overall, centre-right newspapers tend to focus on narrow nationalist interests concerning the climate crisis and do not produce discourses of urgency to resolve the crisis except when reporting on major international political agendas. They are also more inclined to focus on the economic aspects of such efforts and how they would affect the “people”. The centre-left press, on the other hand, tends to prioritise ecological issues much more; it has wider global and planetary interdependent constructions of belonging and engages in the production of discourses of urgency in an attempt to solve the crisis and avoid future catastrophes. However, even in the centre-left press, especially in the UK, a tendency to remain within a western-centric perspective was observed

Who is the average user? How people with visual impairments experience digital services

This thesis investigates the connections between the process of designing digital services on the one hand and the personal accounts of five people with visual impairment who use digital services on the other. Design plays a significant role in causing or mitigating disability in society through the shape and function of products, services, and the built environment. To better understand how products and services cause disability, I analyse disability as a multifactorial phenomenon which emerges through the interplay of personal, social, and environmental factors. I first review three models of disability from the field of disability studies, and, secondly, the design process through the review of inclusive design frameworks. Based on this analysis, I discuss how inclusive design frameworks fail to address the individual needs of people with impairments by generalising their challenges; and how the official interpretation of disability has developed into defining disability as a basic human experience. This research follows a grounded theory approach which utilises the accounts of five people with visual impairment to discuss their ability to access digital content, and, the role of design and technology in mitigating disability. Based on their accounts, I argue that design can mitigate disability and, thus, increase the independence of people with impairments. Furthermore, concrete examples of their interaction with digital services will help to organise factors that cause a positive or negative user experience for people with visual impairment. This thesis concludes with the suggestion of a new approach for designing inclusive products and services. This approach aims to consider the factors constituting the personal experience of accessibility, such as the use of assistive technology, the effects of physical impairments, and the availability of technology. Through this approach, designers can distinguish vulnerable user groups on a case-specific basis and, consequently, mitigate exclusion during the design process. In addition to improving the design process, this thesis argues that interacting with people with impairments, e.g., in the work environment, serves as an indispensable educative function to understand the requirements for building accessible products and services, and, thereby, develops an inclusive and diverse society

Localization using Distance Geometry : Minimal Solvers and Robust Methods for Sensor Network Self-Calibration

In this thesis, we focus on the problem of estimating receiver and sender node positions given some form of distance measurements between them. This kind of localization problem has several applications, e.g., global and indoor positioning, sensor network calibration, molecular conformations, data visualization, graph embedding, and robot kinematics. More concretely, this thesis makes contributions in three different areas.First, we present a method for simultaneously registering and merging maps. The merging problem occurs when multiple maps of an area have been constructed and need to be combined into a single representation. If there are no absolute references and the maps are in different coordinate systems, they also need to be registered. In the second part, we construct robust methods for sensor network self-calibration using both Time of Arrival (TOA) and Time Difference of Arrival (TDOA) measurements. One of the difficulties is that corrupt measurements, so-called outliers, are present and should be excluded from the model fitting. To achieve this, we use hypothesis-and-test frameworks together with minimal solvers, resulting in methods that are robust to noise, outliers, and missing data. Several new minimal solvers are introduced to accommodate a range of receiver and sender configurations in 2D and 3D space. These solvers are formulated as polynomial equation systems which are solvedusing methods from algebraic geometry.In the third part, we focus specifically on the problems of trilateration and multilateration, and we present a method that approximates the Maximum Likelihood (ML) estimator for different noise distributions. The proposed approach reduces to an eigendecomposition problem for which there are good solvers. This results in a method that is faster and more numerically stable than the state-of-the-art, while still being easy to implement. Furthermore, we present a robust trilateration method that incorporates a motion model. This enables the removal of outliers in the distance measurements at the same time as drift in the motion model is canceled