SYNTHESIS OF POLY(ISOBORNYL METHACRYLATE) AND RELATED BLOCK COPOLYMERS AND THEIR APPLICATION FOR THE REINFORCEMENT OF STYRENE BUTADIENE RUBBER

Doctoral thesis (2022)

Die Förderung von Wohlbefinden und Gesundheit als Aufgabe der Jugendarbeit

Conference given outside the academic context (2022)

Context, Prioritization, and Unexpectedness: Factors Influencing User Attitudes About Infographic and Comic Consent

in Web Conference Companion Volume (ACM) (2022, April 26)

Being asked to consent to data sharing is a ubiquitous experience in digital services - yet it is very rare to encounter a well designed consent experience. Considering the momentum and importance of a ... [more ▼]

Being asked to consent to data sharing is a ubiquitous experience in digital services - yet it is very rare to encounter a well designed consent experience. Considering the momentum and importance of a European data space where personal information freely and easily flows across organizations, sectors and Member States, solving the long-discussed thorny issue of "how to get consent right" cannot be postponed any further. In this paper, we describe the first findings from a study based on 24 semi-structured interviews investigating participants’ expectations and opinions toward consent in a data sharing scenario with a data trustee. We analyzed various dimensions of a consent form redesigned as a comic and an infographic, including language, information design, content and the writer-reader relationship. The results provide insights into the complexity of elements that should be considered when asking individuals to freely and mindfully disclose their data, especially sensitive information. [less ▲]

User Experience Design for Cybersecurity & Privacy: addressing user misperceptions of system security and privacy

Doctoral thesis (2022)

The increasing magnitude and sophistication of malicious cyber activities by various threat actors poses major risks to our increasingly digitized and inter-connected societies. However, threats can also ... [more ▼]

The increasing magnitude and sophistication of malicious cyber activities by various threat actors poses major risks to our increasingly digitized and inter-connected societies. However, threats can also come from non-malicious users who are being assigned too complex security or privacy-related tasks, who are not motivated to comply with security policies, or who lack the capability to make good security decisions. This thesis posits that UX design methods and practices are necessary to complement security and privacy engineering practices in order to (1) identify and address user misperceptions of system security and privacy; and (2) inform the design of secure systems that are useful and appealing from end-users’ perspective. The first research objective in this thesis is to provide new empirical accounts of UX aspects in three distinct contexts that encompass security and privacy considerations, namely: cyber threat intelligence, secure and private communication, and digital health technology. The second objective is to empirically contribute to the growing research domain of mental models in security and privacy by investigating user perceptions and misperceptions in the afore-mentioned contexts. Our third objective is to explore and propose methodological approaches to incorporating users’ perceptions and misperceptions in the socio-technical security analyses of systems. Qualitative and quantitative user research methods with experts as well as end users of the applications and systems under investigation were used to achieve the first two objectives. To achieve the third objective, we also employed simulation and computational methods. Cyber Threat Intelligence: CTI sharing platforms Reporting on a number of user studies conducted over a period of two years, this thesis offers a unique contribution towards understanding the constraining and enabling factors of security information sharing within one of the leading CTI sharing platforms, called MISP. Further, we propose a conceptual workflow and toolchain that would seek to detect user (mis)perceptions of key tasks in the context of CTI sharing, such as verifying whether users have an accurate comprehension of how far information travels when shared in a CTI sharing platform, and discuss the benefits of our socio-technical approach as a potential security analysis tool, simulation tool, or educational / training support tool. Secure & Private Communication: Secure Email We propose and describe multi-layered user journeys, a conceptual framework that serves to capture the interaction of a user with a system as she performs certain goals along with the associated user beliefs and perceptions about specific security or privacy-related aspects of that system. We instantiate the framework within a use case, a recently introduced secure email system called p≡p, and demonstrate how the approach can be used to detect misperceptions of security and privacy by comparing user opinions and behavior against system values and objective technical guarantees offered by the system. We further present two sets of user studies focusing on the usability and effectiveness of p≡p’s security and privacy indicators and their traffic-light inspired metaphor to represent different privacy states and guarantees. Digital Health Technology: Contact Tracing Apps Considering human factors when exploring the adoption as well as the security and privacy aspects of COVID-19 contact tracing apps is a timely societal challenge as the effectiveness and utility of these apps highly depend on their widespread adoption by the general population. We present the findings of eight focus groups on the factors that impact people’s decisions to adopt, or not to adopt, a contact tracing app, conducted with participants living in France and Germany. We report how our participants perceived the benefits, drawbacks, and threat model of the contact tracing apps in their respective countries, and discuss the similarities and differences between and within the study groups. Finally, we consolidate the findings from these studies and discuss future challenges and directions for UX design methods and practices in cybersecurity and digital privacy. [less ▲]

Data Analysis for Insurance: Recommendation System Based on a Multivariate Hawkes Process

Doctoral thesis (2022)

The objective of the thesis is to build a recommendation system for insurance. By observing the behaviour and the evolution of a customer in the insurance context, customers seem to modify their insurance ... [more ▼]

The objective of the thesis is to build a recommendation system for insurance. By observing the behaviour and the evolution of a customer in the insurance context, customers seem to modify their insurance cover when a significant event happens in their life. In order to take into account the influence of life events (e.g. marriage, birth, change of job) on the insurance covering selection from customers, we model the recommendation system with a Multivariate Hawkes Process (MHP), which includes several specific features aiming to compute relevant recommendations to customers from a Luxembourgish insurance company. Several of these features are intent to propose a personalized background intensity for each customer thanks to a Machine Learning model, to use triggering functions suited for insurance data or to overcome flaws in real-world data by adding a specific penalization term in the objective function. We define a complete framework of Multivariate Hawkes Processes with a Gamma density excitation function (i.e. estimation, simulation, goodness-of-fit) and we demonstrate some mathematical properties (i.e. expectation, variance) about the transient regime of the process. Our recommendation system has been back-tested over a full year. Observations from model parameters and results from this back-test show that taking into account life events by a Multivariate Hawkes Process allows us to improve significantly the accuracy of recommendations. The thesis is presented in five chapters. Chapter 1 explains how the background intensity of the Multivariate Hawkes Process is computed thanks to a Machine Learning algorithm, so that each customer has a personalized recommendation. Chapter 1 is shown an extended version of the method presented in [1], in which the method is used to make the algorithm explainable. Chapter 2 presents a Multivariate Hawkes Processes framework in order to compute the dependency between the propensity to accept a recommendation and the occurrence of life events: definitions, notations, simulation, estimation, properties, etc. Chapter 3 presents several results of the recommendation system: estimated parameters of the model, effects of contributions, backtesting of the model’s accuracy, etc. Chapter 4 presents the implementation of our work into a R package. Chapter 5 concludes on the contributions and perspectives opened by the thesis. [less ▲]

Federated Geometric Monte Carlo Clustering to Counter Non-IID Datasets

E-print/Working paper (2022)

Federated learning allows clients to collaboratively train models on datasets that are acquired in different locations and that cannot be exchanged because of their size or regulations. Such collected ... [more ▼]

Federated learning allows clients to collaboratively train models on datasets that are acquired in different locations and that cannot be exchanged because of their size or regulations. Such collected data is increasingly non-independent and non- identically distributed (non-IID), negatively affecting training accuracy. Previous works tried to mitigate the effects of non- IID datasets on training accuracy, focusing mainly on non-IID labels, however practical datasets often also contain non-IID features. To address both non-IID labels and features, we propose FedGMCC1, a novel framework where a central server aggregates client models that it can cluster together. FedGMCC clustering relies on a Monte Carlo procedure that samples the output space of client models, infers their position in the weight space on a loss manifold and computes their geometric connection via an affine curve parametrization. FedGMCC aggregates connected models along their path connectivity to produce a richer global model, incorporating knowledge of all connected client models. FedGMCC outperforms FedAvg and FedProx in terms of convergence rates on the EMNIST62 and a genomic sequence classification datasets (by up to +63%). FedGMCC yields an improved accuracy (+4%) on the genomic dataset with respect to CFL, in high non-IID feature space settings and label incongruency. [less ▲]

The Role of Country-Level Availability and Generosity of Healthcare Services, and Old-Age Ageism for Missed Healthcare during the COVID-19 Pandemic Control Measures in Europe

in Journal of Aging and Health (2022)

Objectives: The effects of the COVID-19 outbreak on non-COVID-19-related healthcare need further investigation. Methods: Using the Survey of Health, Ageing and Retirement in Europe’s COVID-19 module (2020 ... [more ▼]

Objectives: The effects of the COVID-19 outbreak on non-COVID-19-related healthcare need further investigation. Methods: Using the Survey of Health, Ageing and Retirement in Europe’s COVID-19 module (2020) (N = 57,025), country-level data from the European Social Survey (2008) and OECD (2020), and logistic regressions, this study examines predictors of older Europeans’ forgone, postponed, and denied healthcare during the pandemic. Results: Country-level availability of physicians, healthcare systems’ generosity, and beliefs that older persons burden healthcare systems all increased forgone healthcare. Healthcare system generosity increased postponed and denied healthcare. Greater medical resources decreased denied healthcare. Furthermore, missed healthcare varied by individual-level gender (higher rates among women), age, education, and health. Discussion: This study reveals predictors of missed healthcare during the pandemic. To decrease unintended health consequences of a pandemic, both individual-level determinants, such as gender and health, and contextual-level determinants, such as healthcare systems’ characteristics, should be considered in research and practice. [less ▲]

The positional value of education in the Americas: dynamics of inequality in labour market returns for highly unequal countries, 2000-2019

Scientific Conference (2022, April 22)

The article examines how the labour market value of education has changed in the context of the expansion of higher education. However, one drawback is understanding how it generates differences between ... [more ▼]

The article examines how the labour market value of education has changed in the context of the expansion of higher education. However, one drawback is understanding how it generates differences between high and low-skilled labour markets, particularly in contexts of high inequality and informality. This could be linked to specific mechanisms by which employers value educational credentials as signalled skills. Using the Luxembourg Income Study (LIS), we analyse trends over two decades in 11 American countries. Our results confirm the previous results for the claim that education has become increasingly positional, compared with the absolute model of education. However, we find that the relative gains in wages for workers with higher levels of education, as the pool of higher education graduates expand over time, increased only slightly in high-skilled occupations, while their relative gains decreased for lower-skilled occupations. This trend is present in both absolute and positional models of education. Moreover, when looking at the structure of labour markets in terms of the linkage between educational credentials and occupational groups, we higher the tertiary education specificity of occupations, the higher the earnings for workers with advantaged positions. These findings are consistent with processes of displacement of low-skilled workers due to increasing competition among highly educated workers, from the positional model of education. [less ▲]

Marina Hands sur la scène théâtrale française : la légitimité d'une « parole autorisée »

in Théâtres du Monde (2022)

Fille de Ludmila Mikaël et de Terry Hands, Marina Hands se voit décerner, en 2019, le « prix du Brigadier » pour le rôle de Marina dans Sœurs (Marina & Audrey) de Pascal Rambert. Comment Marina Hands ... [more ▼]

Fille de Ludmila Mikaël et de Terry Hands, Marina Hands se voit décerner, en 2019, le « prix du Brigadier » pour le rôle de Marina dans Sœurs (Marina & Audrey) de Pascal Rambert. Comment Marina Hands parvient-elle à s’imposer en tant que femme et artiste, étant elle-même fille d’artistes ? En d’autres termes, que se passe-t-il pour elle en coulisses et derrière la scène ? L’article, divisé en trois parties, que l’on souhaite vous proposer, en vue d’apporter humblement et modestement notre pierre à l’édifice du numéro 32 de Théâtres du Monde, entend répondre à ces deux questions centrales. Pour ce faire, nous envisagerons, tout d’abord, Marina Hands, l’artiste, et sa réaction face à ce prix. Ensuite, nous aborderons Marina Hands, la femme, en tant que fille d’artistes. Nous nous focaliserons ainsi sur le lien sororal qui l’unit à sa mère, Ludmila Mikaël. Nous en viendrons, in fine, à la sororité existant entre elle et Audrey Bonnet, interprète d’Audrey dans le spectacle rambertien précité. [less ▲]

Metal-oxide nanostructures for low-power gas sensors

Doctoral thesis (2022)

For gas sensing applications, metal oxide (MOx) nanostructures have demonstrated attractive properties due their large surface-over-volume ratio, combined with the possibility to use multiple materials ... [more ▼]

For gas sensing applications, metal oxide (MOx) nanostructures have demonstrated attractive properties due their large surface-over-volume ratio, combined with the possibility to use multiple materials and multi-functional properties. For MOx chemiresistive gas sensors, the temperature activated interaction of atmospheric oxygen with MOx surface plays a major role in the sensor kinetics as it leads to oxygen adsorption-desorption reactions, that eventually affects the gas sensing performance. Thus, MOx sensors are operated at high temperatures to achieve the desired sensitivity. This high temperature operation of MOx sensors limits their application in explosive gas detection, reduces the sensor lifetime and causes power consumption. To overcome these drawbacks of MOx sensors, researchers have proposed the use of heterostructures and light activation as alternatives. In this thesis, we aim to develop low power consuming MOx sensors using these solutions. We show the template-free bottom-up synthesis and shape control of copper hydroxide-based nanostructures grown in liquid phase which act as templates for formation of CuO nanostructures. Precise control over the pH of the solution and the reaction temperature led to intended tuning of the morphology and chemical composition of the nanostructures. We contemplate upon the rationale behind this change in shape and material as CuO nanostructures are further used in a heterostructure. We discuss synthesis and characterisation of CuO bundles and Cu2O truncated cubes, former of which lead to very interesting gas sensing properties and application. Devices made from CuO bundles network are investigated for their electrical and oxygen adsorption- desorption properties as a gas sensor. It was observed that the sensor has faster response and recovery in as deposited condition in comparison to annealed sensor. A detailed inspection of response and recovery curves enabled us to derive parameters like time constants, reaction constants and diffusion coefficients for CuO bundles, an analysis that is scarcely performed on p-type materials. Investigation of the derived parameters, role of network junctions and a hydroxylated CuO surface leads us to discuss the hypotheses for the contributing processes. CuO bundles show conduction transients upon exposure to reducing gas H2 and temperature-based inversion of response upon exposure to reducing gas CO. This has not been reported in literature for CuO exposed to H2 and/or CO. Armed with this fundamental knowledge of gas sensing, we choose ZnO, n type transducer material, and CuO, p type materials with lower band gap and higher absorption in the visible range to synthesise a heterostructure. However, sol-gel synthesis of ZnO and CuO nanostructures have different reactions parameters, like temperature, pH, etc., and do not show natural affinity to grow on the other material. These challenges are overcome by implementing a stepped synthesis procedure to fabricate a heterostructure with Cu-based nanoplatelets on ZnO Nanorods, also represented as CuO@ZnO heterostructure in this thesis. We finally demonstrate electrical and functional characterisation of CuO@ZnO heterostructure. The heterostructure responds differently to tested gasses as compared to its constituent nanostructure ZnO nanorods and a reference CuO nanostructure, CuO bundles. This is an unexpected result as heterostructures usually show response type similar to their base material but with an enhanced sensor response. We present a possible application of e-nose that can differentiate qualitatively between CO, NO2 and ethanol, using the heterostructure, ZnO nanorods and CuO bundles together. [less ▲]