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See detailEsclavage, servitude, travail forcé : constitution et évolution d’un cadre conceptuel
Erpelding, Michel UL

in Marchadier, Fabien (Ed.) La prohibition de l'esclavage (in press)

This chapter examines the emergence, definition and evolution of the concepts of slavery, forced labour and servitude in international law.

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See detailLearning-Assisted User Clustering in Cell-Free Massive MIMO-NOMA Networks
Le, Quang Nhat; Nguyen, van Dinh UL; Dobre, Octavia A. et al

in IEEE Transactions on Vehicular Technology (in press)

The superior spectral efficiency (SE) and user fairness feature of non-orthogonal multiple access (NOMA) systems are achieved by exploiting user clustering (UC) more efficiently. However, a random UC ... [more ▼]

The superior spectral efficiency (SE) and user fairness feature of non-orthogonal multiple access (NOMA) systems are achieved by exploiting user clustering (UC) more efficiently. However, a random UC certainly results in a suboptimal solution while an exhaustive search method comes at the cost of high complexity, especially for systems of medium-to-large size. To address this problem, we develop two efficient unsupervised machine learning based UC algorithms, namely k-means++ and improved k-means++, to effectively cluster users into disjoint clusters in cell-free massive multiple-input multiple-output (CFmMIMO) system. Adopting full-pilot zero-forcing at access points (APs) to comprehensively assess the system performance, we formulate the sum SE optimization problem taking into account power constraints at APs, necessary conditions for implementing successive interference cancellation, and required SE constraints at user equipments. The formulated optimization problem is highly non-convex, and thus, it is difficult to obtain the global optimal solution. Therefore, we develop a simple yet efficient iterative algorithm for its solution. In addition, the performance of collocated massive MIMO-NOMA (COmMIMO-NOMA) system is also characterized. Numerical results are provided to show the superior performance of the proposed UC algorithms compared to baseline schemes. The effectiveness of applying NOMA in CFmMIMO and COmMIMO systems is also validated. [less ▲]

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See detailMeasuring agreement: How to arrive at reliable measures of opinion congruence between voters and parties.
Lesschaeve, Christophe UL; Padmos, Lars

in Representation (in press)

The extent to which voters and parties agree on policies is an important way through which political scientists have empirically studied political representation. This opinion congruence is most often ... [more ▼]

The extent to which voters and parties agree on policies is an important way through which political scientists have empirically studied political representation. This opinion congruence is most often measured by comparing preferences on a number of policy statements. While the selection of policy statements has not escaped scholarly attention, its impact on the reliability of congruence scores, i.e. the degree to which similar levels of opinion congruence are found when different samples of policy statements are used, has been less investigated. This article looks at which factors of statements samples and voters affect the reliability of congruence measures. It does so by simulating over 5 million opinion congruence scores on the basis of a dataset containing 134 voter and party policy preferences. It finds that both the number of statements and their topic diversity positively affect the reliability of congruence estimates. In addition, the congruence estimates of politically less sophisticated voters are more reliable but only when many left-right policy statements are included in the statement selection. Finally, explorative analyses suggest that increasing topic diversity also increases the validity of congruence measures. [less ▲]

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See detailA theory-driven design framework for smartphone applications to support healthy and sustainable grocery shopping
Blanke, Julia UL; Billieux, Joel; Vögele, Claus UL

in Human Behavior and Emerging Technologies (in press)

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See detailAI-enabled Automation for Completeness Checking of Privacy Policies
Amaral Cejas, Orlando UL; Abualhaija, Sallam UL; Torre, Damiano et al

in IEEE Transactions on Software Engineering (in press)

Technological advances in information sharing have raised concerns about data protection. Privacy policies containprivacy-related requirements about how the personal data of individuals will be handled by ... [more ▼]

Technological advances in information sharing have raised concerns about data protection. Privacy policies containprivacy-related requirements about how the personal data of individuals will be handled by an organization or a software system (e.g.,a web service or an app). In Europe, privacy policies are subject to compliance with the General Data Protection Regulation (GDPR). Aprerequisite for GDPR compliance checking is to verify whether the content of a privacy policy is complete according to the provisionsof GDPR. Incomplete privacy policies might result in large fines on violating organization as well as incomplete privacy-related softwarespecifications. Manual completeness checking is both time-consuming and error-prone. In this paper, we propose AI-based automationfor the completeness checking of privacy policies. Through systematic qualitative methods, we first build two artifacts to characterizethe privacy-related provisions of GDPR, namely a conceptual model and a set of completeness criteria. Then, we develop anautomated solution on top of these artifacts by leveraging a combination of natural language processing and supervised machinelearning. Specifically, we identify the GDPR-relevant information content in privacy policies and subsequently check them against thecompleteness criteria. To evaluate our approach, we collected 234 real privacy policies from the fund industry. Over a set of 48 unseenprivacy policies, our approach detected 300 of the total of 334 violations of some completeness criteria correctly, while producing 23false positives. The approach thus has a precision of 92.9% and recall of 89.8%. Compared to a baseline that applies keyword searchonly, our approach results in an improvement of 24.5% in precision and 38% in recall. [less ▲]

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See detailTest Case Selection and Prioritization Using Machine Learning: A Systematic Literature Review
Pan, Rongqi; Bagherzadeh, Mojtaba; Ghaleb, Taher et al

in Empirical Software Engineering (in press)

Regression testing is an essential activity to assure that software code changes do not adversely a ect existing functionalities. With the wide adoption of Continuous Integration (CI) in software projects ... [more ▼]

Regression testing is an essential activity to assure that software code changes do not adversely a ect existing functionalities. With the wide adoption of Continuous Integration (CI) in software projects, which increases the frequency of running software builds, running all tests can be time-consuming and resource-intensive. To alleviate that problem, Test case Selection and Prioritiza- tion (TSP) techniques have been proposed to improve regression testing by selecting and prioritizing test cases in order to provide early feedback to developers. In recent years, researchers have relied on Machine Learning (ML) techniques to achieve e ective TSP (ML-based TSP). Such techniques help combine information about test cases, from partial and imperfect sources, into accurate prediction models. This work conducts a systematic literature review focused on ML-based TSP techniques, aiming to perform an in-depth analysis of the state of the art, thus gaining insights regarding fu- ture avenues of research. To that end, we analyze 29 primary studies published from 2006 to 2020, which have been identi ed through a systematic and documented process. This paper addresses ve research questions addressing variations in ML-based TSP techniques and feature sets for training and testing ML models, alternative metrics used for evaluating the techniques, the performance of techniques, and the reproducibility of the published studies. We summarize the results related to our research questions in a high-level summary that can be used as a taxonomy for classifying future TSP studies. [less ▲]

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See detailReinforcement Learning for Test Case Prioritization
Bagherzadeh, Mojtaba; Kahani, Nafiseh; Briand, Lionel UL

in IEEE Transactions on Software Engineering (in press)

Continuous Integration (CI) context significantly reduces integration problems, speeds up development time, and shortens release time. However, it also introduces new challenges for quality assurance ... [more ▼]

Continuous Integration (CI) context significantly reduces integration problems, speeds up development time, and shortens release time. However, it also introduces new challenges for quality assurance activities, including regression testing, which is the focus of this work. Though various approaches for test case prioritization have shown to be very promising in the context of regression testing, specific techniques must be designed to deal with the dynamic nature and timing constraints of CI. Recently, Reinforcement Learning (RL) has shown great potential in various challenging scenarios that require continuous adaptation, such as game playing, real-time ads bidding, and recommender systems. Inspired by this line of work and building on initial efforts in supporting test case prioritization with RL techniques, we perform here a comprehensive investigation of RL-based test case prioritization in a CI context. To this end, taking test case prioritization as a ranking problem, we model the sequential interactions between the CI environment and a test case prioritization agent as an RL problem, using three alternative ranking models. We then rely on carefully selected and tailored state-of-the-art RL techniques to automatically and continuously learn a test case prioritization strategy, whose objective is to be as close as possible to the optimal one. Our extensive experimental analysis shows that the best RL solutions provide a significant accuracy improvement over previous RL-based work, with prioritization strategies getting close to being optimal, thus paving the way for using RL to prioritize test cases in a CI context. [less ▲]

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See detailAlgorithmic Trading in Experimental Markets with Human Traders: A Literature Survey
Neugebauer, Tibor UL; Nekrasova, Elizaveta UL; Bao, Te et al

in HANDBOOK OF EXPERIMENTAL FINANCE (in press)

This chapter surveys the nascent experimental research on the interaction between human and algorithmic (bot) traders in experimental markets. We first discuss studies in which algorithmic traders are in ... [more ▼]

This chapter surveys the nascent experimental research on the interaction between human and algorithmic (bot) traders in experimental markets. We first discuss studies in which algorithmic traders are in the researcher’s hands. Specifically, the researcher assigns computer agents as traders in the market. We then followed it up by discussing studies in which the researcher allows human traders to decide whether to employ algorithms for trading or to trade by themselves. The paper introduces the types and performances of algorithmic traders that interact with human subjects in the laboratory, including zero-intelligent traders, arbitragers, fundamentalists, adaptive algorithms, and manipulators. We find that whether algorithm traders earn more profit than human traders crucially depends on the asset’s fundamental value process and the market environment. The potential impact of interactions with algorithms on the investor’s psychology is also discussed. [less ▲]

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See detailPrincipe de précaution (et changement climatique)
Donati, Alessandra UL

in Torre-Schaub M. e.a. (eds.), Dictionnaire du changement climatique (in press)

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See detailThe precautionary principle under EU law: a postmodern principle in a post-truth era
Donati, Alessandra UL

in Farah, Paolo (Ed.) Science, Policy and International Law (in press)

We live in a post-truth society, where “objective facts are less influential in shaping public opinion than appeals to emotion and personal belief.” In this context, the core claim of this chapter is that ... [more ▼]

We live in a post-truth society, where “objective facts are less influential in shaping public opinion than appeals to emotion and personal belief.” In this context, the core claim of this chapter is that to understand the definition and implications of the post-truth society, it is necessary to analyze the theoretical framework under which the concept of post-truth emerged: post-modernism. Under the theoretical framework of post-modernism, the analysis of the precautionary principle is utterly significant since it can be defined as a “paradigmatic principle” of post-modern law. Indeed, as this chapter will demonstrate, the precautionary principle shares the same features of flexibility (in its double dimension of smooth and adaptable principle) and complexity (as an interdisciplinary principle negotiated by scientific experts and political decision-makers) that belong to post-modern principles. [less ▲]

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See detailCOVID-19 Compliance Behaviors of Older People: The Role of Cognitive and Non-Cognitive Skills
Clark, Andrew; d'Ambrosio, Conchita UL; Onur, Ilke et al

in Economics Letters (in press)

This paper examines the empirical relationship between individuals’ cognitive and non-cognitive abilities and COVID-19 compliance behaviors using cross-country data from the Survey of Health, Ageing and ... [more ▼]

This paper examines the empirical relationship between individuals’ cognitive and non-cognitive abilities and COVID-19 compliance behaviors using cross-country data from the Survey of Health, Ageing and Retirement in Europe (SHARE). We find that both cognitive and non-cognitive skills predict responsible health behaviors during the COVID-19 crisis. Episodic memory is the most important cognitive skill, while conscientiousness and neuroticism are the most significant personality traits. There is also some evidence of a role for an internal locus of control in compliance. [less ▲]

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See detailNeo-institutional Approaches to Understanding How Higher Education Transforms Society and the World of Work
Fernandez, Frank; Powell, Justin J W UL

in Côté, James; Pickard, Sarah (Eds.) Routledge Handbook of the Sociology of Higher Education (in press)

The strong growth of higher education and its role as an institution have contributed to the creation of a schooled society, a world in which our daily lives, organizations, politics, and economies are ... [more ▼]

The strong growth of higher education and its role as an institution have contributed to the creation of a schooled society, a world in which our daily lives, organizations, politics, and economies are affected by systems of education. Neo-institutional and comparative perspectives facilitate our understanding of the global transition from elite to mass to universal higher education driving the global knowledge society. Higher-education systems respond to diverse stakeholders even as they (re)shape the experiences, expectations, and demands of society. Education is not merely responsive to other institutions, such as economies and governments, but rather transforms the very nature of work and social life. Using neo-institutional theorizing, we explain broad global patterns, such as the emergence of higher education as a core social institution. This institution, in turn, has influenced societies by encouraging greater emphasis on science production, thereby enabling the scientization of social problems and facilitating the spread of cultural values around equality. Simultaneously, myriad differences and disparities between countries and among social groups persist. Finally, neo-institutional theorizing may usefully inform future research to study the evolution of schooled societies worldwide. [less ▲]

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See detailAn Evolving International Research Collaboration Network: Spatial and Thematic Developments in Co-Authored Higher Education Research, 1998–2018
Fu, Yuan-Chih; Marques, Marcelo; Tseng, Yuen-Hsien et al

in Scientometrics (in press)

Co-authored research articles in the disciplinarily heterogeneous field of higher education have dramatically increased in this century, largely driven, as in other fields, by rising international co ... [more ▼]

Co-authored research articles in the disciplinarily heterogeneous field of higher education have dramatically increased in this century, largely driven, as in other fields, by rising international co-authorships. We examine this evolving international collaboration network in higher education research over two decades. To do so, we apply automated bibliometric topic identification and social network analysis of 9,067 papers in 13 core higher education journals (1998–2018). Remarkable expansion in the volume of papers and co-authorships has, surprisingly, not resulted in a more diverse network. Rather, existing co-authorship patterns are strengthened, with the dominance of scholars from a few Anglophone countries largely maintained. Researchers globally seek to co-author with leading scholars in these countries, especially the US, UK, and Australia—at least when publishing in the leading general HE journals based there. Further, the two-mode social network analysis of countries and topics suggests that while Anglophone countries have led the development of higher education research, China and Germany, as leading research-producing countries, are increasingly influential within this world-spanning network. Topically, the vast majority of co-authored papers in higher education research focuses on individual-level phenomena, with organizational and system-level or country-level analysis constituting a (much) smaller proportion, despite policymakers’ emphasis on cross-national comparisons and the growing importance of university actorhood. We discuss implications thereof for the future of the multidisciplinary higher education field. [less ▲]

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See detailEvaluating Universal Student Mobility: Contrasting Policy Discourse and Student Narratives in Luxembourg
Kmiotek-Meier, Emilia; Powell, Justin J W UL

in International Studies in Sociology of Education (in press)

For decades, Luxembourg did without its own national university. Before and after the Luxembourg’s founding (UL) (2003), tertiary education and the status of being a Luxembourgish student have been ... [more ▼]

For decades, Luxembourg did without its own national university. Before and after the Luxembourg’s founding (UL) (2003), tertiary education and the status of being a Luxembourgish student have been closely linked to international student mobility (ISM). This long-standing tradition was maintained in the new university via compulsory ISM—to bolster the national elite’s European networks and internationalization. Focusing on ISM from Luxembourg—based on analysis of policy documents regarding the UL’s foundation and state allowances for students—we show that policymakers strongly favored ISM. We confront this policy agenda with the perspectives and self-identification of both credit and degree mobile Luxembourgish students. In narrative interviews, students did not always view compulsory ISM as positively as did policymakers. For students, the quality of a stay abroad is much more important—a perspective lacking in the state’s quantity-driven agenda. In the country with the highest ISM rates globally, constraints remain to achieve equity in ISM. [less ▲]

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See detailRefining Weakly-Supervised Free Space Estimation through Data Augmentation and Recursive Training
Robinet, François UL; Frank, Raphaël UL

in Proceedings of BNAIC/BeneLearn 2021 (in press)

Free space estimation is an important problem for autonomous robot navigation. Traditional camera-based approaches rely on pixel-wise ground truth annotations to train a segmentation model. To cover the ... [more ▼]

Free space estimation is an important problem for autonomous robot navigation. Traditional camera-based approaches rely on pixel-wise ground truth annotations to train a segmentation model. To cover the wide variety of environments and lighting conditions encountered on roads, training supervised models requires large datasets. This makes the annotation cost prohibitively high. In this work, we propose a novel approach for obtaining free space estimates from images taken with a single road-facing camera. We rely on a technique that generates weak free space labels without any supervision, which are then used as ground truth to train a segmentation model for free space estimation. We study the impact of different data augmentation techniques on the performances of free space predictions, and propose to use a recursive training strategy. Our results are benchmarked using the Cityscapes dataset and improve over comparable published work across all evaluation metrics. Our best model reaches 83.64% IoU (+2.3%), 91:75% Precision (+2.4%) and 91.29% Recall (+0.4%). These results correspond to 88.8% of the IoU, 94.3% of the Precision and 93.1% of the Recall obtained by an equivalent fully-supervised baseline, while using no ground truth annotation. Our code and models are freely available online. [less ▲]

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See detailThe Fragmentation of International Investment and Tax Dispute Settlement: A Good Idea?
Garcia Olmedo, Javier UL

in Leiden Journal of International Law (in press)

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See detailOn unavoidable families of meromorphic functions
Meyrath, Thierry UL

in Canadian Mathematical Bulletin (in press)

We prove several results on unavoidable families of meromorphic functions. For instance, we give new examples of families of cardinality three that are unavoidable with respect to the set of meromorphic ... [more ▼]

We prove several results on unavoidable families of meromorphic functions. For instance, we give new examples of families of cardinality three that are unavoidable with respect to the set of meromorphic functions on $\C$. We further obtain families consisting of less than three functions that are unavoidable with respect to certain subsets of meromorphic functions. In the other direction, we show that for every meromorphic function $f$, there exists an entire function that avoids $f$ on $\C$. [less ▲]

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See detailFostering experimental and computational synergy to modulate hyperinflammation
Del Sol Mesa, Antonio UL

in Trends in Immunology (in press)

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See detailUncertainty-driven symmetry-breaking and stochastic stability in a generic differential game of lobbying
Boucekkine, Raouf; Fabien, Prieur; Ruan, Weihua et al

in Economic Theory (in press)

We study a 2-players stochastic differential game of lobbying. Players invest in lobbying activities to alter the legislation in her own benefit. The payoffs are quadratic and uncertainty is driven by a ... [more ▼]

We study a 2-players stochastic differential game of lobbying. Players invest in lobbying activities to alter the legislation in her own benefit. The payoffs are quadratic and uncertainty is driven by a Wiener process. We consider the Nash symmetric game where players face the same cost and extract symmetric payoffs, and we solve for Markov Perfect Equilibria (MPE) in the class of affine functions. First, we prove a general sufficient (catching up) optimality condition for two-players stochastic games with uncertainty driven by Wiener processes. Second, we prove that the number and nature of MPE depend on the extent of uncertainty (i.e the variance of the Wiener processes). In particular, we prove that while a symmetric MPE always exists, two asymmetric MPE emerge if and only if uncertainty is large enough. Third, we study the stochastic stability of all the equilibria. We notably find, that the state converges to a stationary invariant distribution under asymmetric MPE. Fourth, we study the implications for rent dissipation asymptotically and compare the outcomes of symmetric vs asymmetric MPE in this respect, ultimately enhancing again the role of uncertainty. [less ▲]

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