Luxembourg. Key contextual data

Report (2023)

Luxembourg. ECEC Workforce profile

Report (2023)

Why do historians collect new sources? War Experiences in Luxembourg. The Second World War and Today

Speeches/Talks (2023)

The military offensive launched by the Russian Federation against Ukraine in the early hours of 24 February 2022 and the ensuing war on Ukrainian territory have resulted in immense human suffering, a ... [more ▼]

The military offensive launched by the Russian Federation against Ukraine in the early hours of 24 February 2022 and the ensuing war on Ukrainian territory have resulted in immense human suffering, a humanitarian tragedy and incalculable material damage. The violation of a country’s territorial integrity and sovereignty – an act in clear breach of the United Nations Charter – has shattered the shared framework of values and principles fostered by multilateralism after the Second World War in the hope of achieving world peace, while leading to an unprecedented outpouring of solidarity for Ukraine and the plight of its people from Western democracies and European and international organisations, including NATO, the UN, the European Union and the Council of Europe, and their Member States and private initiatives. As contemporary history is turned on its head, historians, driven by the duty of memory, are stepping up to explain the origins of the conflict, identify the various players, provide an objective analysis of the consequences, record the memories of eyewitnesses and victims – with oral history proving a precious tool –, preserve historical sources and, above all, reflect on the role that intellectual effort can play in paving the way for a return to peace in the new world order taking shape before our eyes. [less ▲]

Maschinelles Lernen in der automatischen Auswertung von Punktwolken: Beispiele der Erfahrungen an der Universität Luxemburg

Scientific Conference (2023, October 07)

Transkultureller Theaterschauplatz: Grenzen und die Odyssee Fliehender – Interdisziplinäre Überlegungen

Book published by Melusa Press (2023)

Der vorliegende Sammelband versammelt kritische Forschungsansätze sowohl aus verschiedenen akademischen Disziplinen – der Theater-, Medien , Film-, Literaturwissenschaften sowie der Soziologie, der ... [more ▼]

Der vorliegende Sammelband versammelt kritische Forschungsansätze sowohl aus verschiedenen akademischen Disziplinen – der Theater-, Medien , Film-, Literaturwissenschaften sowie der Soziologie, der Erziehungswissenschaften – als auch der praxisbezogenen Theaterpädagogik und der Sozialen Arbeit. Anliegen ist es, die interdisziplinäre Forschung und einen integrativen Forschungsansatz für den Sammelband fruchtbar zu machen, um so den gegenseitigen akademischen und praktischen Transfer von Wissen hervorzuheben und die Kluft zwischen Wissen und Praxis in Bezug auf Wissenschaft, Theater und Migration zu überwinden: Dabei geht es um die Analyse des komplexen Themenfeldes, das die gegenwärtigen Migrationsbewegungen ins Zentrum der internationalen und interdisziplinären Diskussionen rückt. [less ▲]

Multi-label Deepfake Classification

in IEEE Workshop on Multimedia Signal Processing (2023, September 27)

In this paper, we investigate the suitability of current multi-label classification approaches for deepfake detection. With the recent advances in generative modeling, new deepfake detection methods have ... [more ▼]

In this paper, we investigate the suitability of current multi-label classification approaches for deepfake detection. With the recent advances in generative modeling, new deepfake detection methods have been proposed. Nevertheless, they mostly formulate this topic as a binary classification problem, resulting in poor explainability capabilities. Indeed, a forged image might be induced by multi-step manipulations with different properties. For a better interpretability of the results, recognizing the nature of these stacked manipulations is highly relevant. For that reason, we propose to model deepfake detection as a multi-label classification task, where each label corresponds to a specific kind of manipulation. In this context, state-of-the-art multi-label image classification methods are considered. Extensive experiments are performed to assess the practical use case of deepfake detection. [less ▲]

Digital History and the Politics of Digitisation

Scientific Conference (2023, September 14)

This paper will explore a key question for historians today: what are the politics of cultural heritage digitisation and its implications for historical research? And how to assess this from a global ... [more ▼]

This paper will explore a key question for historians today: what are the politics of cultural heritage digitisation and its implications for historical research? And how to assess this from a global perspective? In a research environment that increasingly privileges what is available online, the questions of why, where, and how we can access what we can access, and how it affects historical research have become ever more urgent. My talk will outline a framework through which to contextualize the politics of (digital) heritage preservation, and a model to analyze its most important political dimensions. To add some historical perspective, I will put this discussion in the broader context of the ways in which technology has shaped historical research practices and knowledge production, not just in the past two decades but in fact already since the late 19th century. [less ▲]

A Systematic Review of Identity and Access Management Requirements in Enterprises and Potential Contributions of Self-Sovereign Identity

in Business and Information Systems Engineering (2023)

Digital identity and access management (IAM) poses significant challenges for companies. Cyberattacks and resulting data breaches frequently have their root cause in enterprises' IAM systems. During the ... [more ▼]

Digital identity and access management (IAM) poses significant challenges for companies. Cyberattacks and resulting data breaches frequently have their root cause in enterprises' IAM systems. During the COVID-19 pandemic, issues with the remote authentication of employees working from home highlighted the need for better IAM solutions. Using a design science research approach, the paper reviews the requirements for IAM systems from an enterprise perspective and identifies the potential benefits of self-sovereign identity (SSI) – an emerging, passwordless paradigm in identity management that provides end users with cryptographic attestations stored in digital wallet apps. To do so, this paper first conducts a systematic literature review followed by an interview study and categorizes IAM system requirements according to security and compliance, operability, technology, and user aspects. In a second step, it presents an SSI-based prototype for IAM, whose suitability for addressing IAM challenges was assessed by twelve domain experts. The results suggest that the SSI-based authentication of employees can address requirements in each of the four IAM requirement categories. SSI can specifically improve manageability and usability aspects and help implement acknowledged best practices such as the principle of least privilege. Nonetheless, the findings also reveal that SSI is not a silver bullet for all of the challenges that today’s complex IAM systems face. [less ▲]

Teacher-Student Relationships and Student Outcomes: A Systematic Review of Meta-Analyses and Second-Order Meta-Analysis

E-print/Working paper (2023)

Teacher-student relationships (TSRs) play a vital role in establishing a positive school climate and promoting positive student outcomes. Several meta-analyses have suggested significant associations ... [more ▼]

Teacher-student relationships (TSRs) play a vital role in establishing a positive school climate and promoting positive student outcomes. Several meta-analyses have suggested significant associations between TSRs and, for example, academic achievement, a lack of disruptive behavior, school engagement, peer relationships, motivation, executive functions, and general well-being. However, these meta-analyses have differed substantially in TSR-outcome relationships, moderators, and quality, thus complicating the interpretation of these findings. In this preregistered systematic review of meta-analyses plus original second-order meta-analyses (SOMAs), we aimed to (a) synthesize the meta-analytic evidence on relationships between TSRs and student outcomes, (b) map influential moderators of these relationships, and (c) assess the methodological quality of the meta-analyses. We synthesized over 70 years of educational research in 24 meta-analyses encompassing a total of 116 effect sizes based on more than 2 million prekindergarten and K-12 students. We conducted several three-level SOMAs and found that TSRs had similar strong significant relationships with eight clusters of outcomes: academic achievement, academic emotions, appropriate student behavior, behavior problems, executive functions and self-control, motivation, school belonging and engagement, and student well-being. Age, gender, and informant (student-, peer-, or teacher-assessments) were the most frequently examined moderators in prior research, and our moderator analyses suggested student grade level and social minority status as moderators. We further found large differences in quality between the meta-analyses, and these differences were not associated with the TSR-outcome relationships. These results map the field of TSR research; present their relationships, moderators, and meta-analytic quality; and show how TSRs can contribute to improving outcomes in students via relationship building. Future research should follow meta-analytic open science procedures to improve quality and reproducibility. [less ▲]

ML-based Compliance Verification of Data Processing Agreements against GDPR

Scientific Conference (2023, September 08)

Most current software systems involve processing personal data, an activity that is regulated in Europe by the general data protection regulation (GDPR) through data processing agreements (DPAs ... [more ▼]

Most current software systems involve processing personal data, an activity that is regulated in Europe by the general data protection regulation (GDPR) through data processing agreements (DPAs). Developing compliant software requires adhering to DPA-related requirements in GDPR. Verifying the compliance of DPAs entirely manually is however time-consuming and error-prone. In this paper, we propose an automation strategy based on machine learning (ML) for checking GDPR compliance in DPAs. Specifically, we create, based on existing work, a comprehensive conceptual model that describes the information types pertinent to DPA compliance. We then develop an automated approach that detects breaches of compliance by predicting the presence of these information types in DPAs. On an evaluation set of 30 real DPAs, our approach detects 483 out of 582 genuine violations while introducing 93 false violations, achieving thereby a precision of 83.9% and recall of 83.0%. We empirically compare our approach against an existing approach which does not employ ML but relies on manually-defined rules. Our results indicate that the two approaches perform on par. Therefore, to select the right solution in a given context, we discuss differentiating factors like the availability of annotated data and legal experts, and adaptation to regulation changes. [less ▲]