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See detailOn the Composition and Limitations of Publicly Available COVID-19 X-Ray Imaging Datasets
Garcia Santa Cruz, Beatriz UL; Sölter, Jan UL; Bossa, Matias Nicolas UL et al

E-print/Working paper (2020)

 Machine learning based methods for diagnosis and progression prediction of COVID-19 from imaging data have gained significant attention in the last months, in particular by the use of deep learning ... [more ▼]

 Machine learning based methods for diagnosis and progression prediction of COVID-19 from imaging data have gained significant attention in the last months, in particular by the use of deep learning models. In this context hundreds of models where proposed with the majority of them trained on public datasets. Data scarcity, mismatch between training and target population, group imbalance, and lack of documentation are important sources of bias, hindering the applicability of these models to real-world clinical practice. Considering that datasets are an essential part of model building and evaluation, a deeper understanding of the current landscape is needed. This paper presents an overview of the currently public available COVID-19 chest X-ray datasets. Each dataset is briefly described and potential strength, limitations and interactions between datasets are identified. In particular, some key properties of current datasets that could be potential sources of bias, impairing models trained on them are pointed out. These descriptions are useful for model building on those datasets, to choose the best dataset according the model goal, to take into account the specific limitations to avoid reporting overconfident benchmark results, and to discuss their impact on the generalisation capabilities in a specific clinical setting. [less ▲]

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See detailGeneralized Langevin equations and memory effects in non-equilibrium statistical physics
Meyer, Hugues UL

Doctoral thesis (2020)

The dynamics of many-body complex processes is a challenge that many scientists from various fields have to face. Reducing the complexity of systems involving a large number of bodies in order to reach a ... [more ▼]

The dynamics of many-body complex processes is a challenge that many scientists from various fields have to face. Reducing the complexity of systems involving a large number of bodies in order to reach a simple description for observables captur- ing the main features of the process is a difficult task for which different approaches have been proposed over the past decades. In this thesis we introduce new tools to describe the coarse-grained dynamics of arbitrary observables in non-equilibrium processes. Following the projection operator formalisms introduced first by Mori and Zwanzig, and later on by Grabert, we first derive a non-stationary Generalized Langevin Equation that we prove to be valid in a wide spectrum of cases. This includes in particular driven processes as well as explicitly time-dependent observ- ables. The equation exhibits a priori memory effects, controlled by a so-called non- stationary memory kernel. Because the formalism does not provide extensive infor- mation about the memory kernel in general, we introduce a set of numerical meth- ods aimed at evaluating it from Molecular Dynamics simulation data. These proce- dures range from simple dimensionless estimations of the strength of the memory to the determination of the entire kernel. Again, the methods introduced are very general and require as input a small number of quantities directly computable from numerical of experimental timeseries. We finally conclude this thesis by using the projection operator formalisms to derive an equation of motion for work and heat in dissipative processes. This is done in two different ways, either by using well-known integral fluctuation theorems, or by explicitly splitting the dynamics into adiabatic and dissipative parts. [less ▲]

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See detailRadio Feature "100 Jahre Ostbelgien" Folge 8: Von Geschichtspolitik und Erinnerungskulturen
Brüll, Christoph UL; Fickers, Andreas UL

Speeches/Talks (2020)

Bis heute beherrscht die Meistererzählung der Ostbelgier als "Opfer" und "Spielball der Geschichte" den öffentlichen Diskurs, wenn es um die Bedeutung der Vergangenheit geht. In der achten und letzten ... [more ▼]

Bis heute beherrscht die Meistererzählung der Ostbelgier als "Opfer" und "Spielball der Geschichte" den öffentlichen Diskurs, wenn es um die Bedeutung der Vergangenheit geht. In der achten und letzten Folge von "100 Jahre Ostbelgien" zeigen die Historiker Andreas Fickers und Christoph Brüll, dass sich in der Auseinandersetzung mit dieser Vergangenheit tiefsitzende Ängste und Sorgen spiegeln. Mentalitätshistorisch gesehen können sie als eine Abfolge von Angstregimen gedeutet werden. [less ▲]

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Peer Reviewed
See detailTerritorial patterns and relations in Austria
Szendrei, Greta UL; Evrard, Estelle UL; Nienaber, Birte UL et al

E-print/Working paper (2020)

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See detailDeep Learning to Predict the Feasibility of Priority-Based Ethernet Network Configurations
Mai, Tieu Long UL; Navet, Nicolas UL

Report (2020)

This study is a contribution towards leveraging deep learning to further automate the design of communication architectures used in critical systems and, ultimately, design systems that are more efficient ... [more ▼]

This study is a contribution towards leveraging deep learning to further automate the design of communication architectures used in critical systems and, ultimately, design systems that are more efficient in terms of resource usage. Two well identified use-cases of deep-learning, and AI at large, in the design of critical systems are 1) fast prediction techniques that can replace, at some stages of the design, exact approaches, and 2) technology-agnostic configuration algorithms, {\it i.e.} algorithms not relying on extensive domain knowledge. This paper contributes to the first use-case and presents what is, to the best of our knowledge, the first deep learning model for feasibility prediction of real-time Ethernet networks. Machine learning has been recently applied in real-time systems to predict whether Ethernet network configurations are feasible in terms of meeting deadline constraints without executing conventional schedulability analysis. However, the existing prediction techniques require domain expertise to choose the relevant input features and may perform poorly when topologies or traffic patterns differ significantly from the ones in the training data. To overcome these problems, we propose a Graph Neural Network (GNN) prediction model that synthesizes relevant features directly from the raw data. This deep learning model possesses the ability to exploit relations among flows, links, and queues in switched Ethernet networks, and, over the 13 testing sets used in this work, has proven an ability to generalize beyond the training data that is significantly superior to traditional ML algorithms. We also explore the use of ensembles of GNNs and show that it enhances the robustness of the predictions. An evaluation on heterogeneous testing sets comprising actual automotive networks, shows that ensembles of 32 GNN models features a prediction accuracy ranging from 79.3% to 90% for Ethernet networks using priorities as the Quality-of-Service mechanism. The use of ensemble models provides a speedup factor ranging from 77 to 1715 compared to schedulability analysis. Such speed-up factors unlock new possibilities for design-space exploration and the development of near-interactive design tools. A practical advantage of our model is that it automates the feature engineering process, and does not require domain expertise. In that regard, the model could potentially be efficient in other areas of real-time computing. [less ▲]

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See detailAn Algebraic Formulation of the Division Property: Revisiting Degree Evaluations, Cube Attacks, and Key-Independent Sums
Hu, Kai; Sun, Siwei; Wang, Meiqin et al

in 26th Annual International Conference on the Theory and Application of Cryptology and Information Security- ASIACRYPT 2020 (2020, August 16)

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See detailAn Algebraic Attack on Ciphers with Low-Degree Round Functions: Application to Full MiMC
Eichlseder, Maria; Grassi, Lorenzo; Lüftenegger, Reinhard et al

in 26th Annual International Conference on the Theory and Application of Cryptology and Information Security - ASIACRYPT 2020 (2020, August 16)

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See detailPredicting functional effects of missense variants in voltage-gated sodium and calcium channels
Heyne, Henrike O.; Baez-Nieto, David; Iqbal, Sumaiya et al

in Science Translational Medicine (2020), 12(556), 6848

Malfunctions of voltage-gated sodium and calcium channels (encoded by SCNxA and CACNA1x family genes, respectively) have been associated with severe neurologic, psychiatric, cardiac, and other diseases ... [more ▼]

Malfunctions of voltage-gated sodium and calcium channels (encoded by SCNxA and CACNA1x family genes, respectively) have been associated with severe neurologic, psychiatric, cardiac, and other diseases. Altered channel activity is frequently grouped into gain or loss of ion channel function (GOF or LOF, respectively) that often corresponds not only to clinical disease manifestations but also to differences in drug response. Experimental studies of channel function are therefore important, but laborious and usually focus only on a few variants at a time. On the basis of known gene-disease mechanisms of 19 different diseases, we inferred LOF (n = 518) and GOF (n = 309) likely pathogenic variants from the disease phenotypes of variant carriers. By training a machine learning model on sequence- and structure-based features, we predicted LOF or GOF effects [area under the receiver operating characteristics curve (ROC) = 0.85] of likely pathogenic missense variants. Our LOF versus GOF prediction corresponded to molecular LOF versus GOF effects for 87 functionally tested variants in SCN1/2/8A and CACNA1I (ROC = 0.73) and was validated in exome-wide data from 21,703 cases and 128,957 controls. We showed respective regional clustering of inferred LOF and GOF nucleotide variants across the alignment of the entire gene family, suggesting shared pathomechanisms in the SCNxA/CACNA1x family genes. [less ▲]

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See detailAnalysing the SWECOM Standard for Designing a DevOps Education Programme
Capozucca, Alfredo UL; Guelfi, Nicolas UL

in In: Bruel JM., Capozucca A., Mazzara M., Meyer B., Naumchev A., Sadovykh A. (eds) Frontiers in Software Engineering Education. FISEE 2019. Lecture Notes in Computer Science (2020), 12271

Developing academic education programmes for software engineers is a difficult task mainly due to three main factors: (1) ever-changing information and communication technologies produced by the industry ... [more ▼]

Developing academic education programmes for software engineers is a difficult task mainly due to three main factors: (1) ever-changing information and communication technologies produced by the industry and meant for citizens living in digital disruptions age, (2) lack of official or de-facto standards for the software engineering domain, (3) slow pace of the standardisation bodies and of the academia for deploying standard competence frameworks or education programmes. This applies more especially to DevOps which regroups a set of skills being the most demanded today by the job market. This paper is a first attempt to introduce a standard based development process to derive a DevOps education programme for graduate education. It is introduced as a generic process mainly based on the SWECOM standard. This process is applied to generate a proposal for a significant DevOps graduate academic programme definition in a comprehensive and, most importantly, in a skill oriented manner. [less ▲]

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See detailFrontiers in Software Engineering Education
Bruel, Jean-Michel; Capozucca, Alfredo UL; Mazzara, Manuel et al

Book published by Springer (2020)

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See detailRIVER MORPHOLOGY MONITORING OF A SMALL-SCALE ALPINE RIVERBED USING DRONE PHOTOGRAMMETRY AND LIDAR
Backes, Dietmar UL; Smigaj, Magdalena; Schimka, Marian et al

in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2020, August 12), XLIII-B2-2020 Article Metrics Related articles(1017), 1024

An efficient alternative to labour-intensive terrestrial and costly airborne surveys is the use of small, inexpensive Unmanned Aerial Vehicles (UAVs) or Remotely Piloted Aerial Systems (RPAS). These low ... [more ▼]

An efficient alternative to labour-intensive terrestrial and costly airborne surveys is the use of small, inexpensive Unmanned Aerial Vehicles (UAVs) or Remotely Piloted Aerial Systems (RPAS). These low-altitude remote sensing platforms, commonly known as drones, can carry lightweight optical and LiDAR sensors. Even though UAV systems still have limited endurance, they can provide a flexible and relatively inexpensive monitoring solution for a limited area of interest. This study investigated the applicability of monitoring the morphology of a frequently changing glacial stream using high-resolution topographic surface models derived from low-altitude UAV-based photogrammetry and LiDAR. An understanding of river-channel morphology and its response to anthropogenic and natural disturbances is imperative for effective watershed management and conservation. We focus on the data acquisition, processing workflow and highlight identified challenges and shortcomings. Additionally, we demonstrate how LiDAR data acquisition simulations can help decide which laser scanning approach to use and help optimise data collection to ensure full coverage with desired level of detail. Lastly, we showcase a case study of 3D surface change analysis in an alpine stream environment with UAV-based photogrammetry. The datasets used in this study were collected as part of the ISPRS Summer School of Alpine Research, which will continue to add new data layers on a biyearly basis. This growing data repository is freely available for research. [less ▲]

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See detailInfluence of Thermal Energy Storage and Heat Pump Parametrization for Demand-Side-Management in a Nearly-Zero-Energy-Building using Model Predictive Control
Bechtel, Steffen UL; Rafii-Tabrizi, Sasan UL; Scholzen, Frank UL et al

in Energy and Buildings (2020), 226

The rollout of the supply dependent generators wind turbines and photovoltaics leads to a flexibility demand that can be adressed from the consumer side, via Demand-Side-Management, as well. In single ... [more ▼]

The rollout of the supply dependent generators wind turbines and photovoltaics leads to a flexibility demand that can be adressed from the consumer side, via Demand-Side-Management, as well. In single family houses, the heat pump, in combination with thermal energy storage, can shift their energy comsumption according to price signals in order to reduce consumer costs. This paper analyses the impact of different heat storage sizes and heat pump powers on cost savings and shifting potential, focussing on the Luxembourgish context, when variable electricity prices based on the electricity market are applied. A model predictive controller determines the cost-optimal operating cycles of the heat pump. The building’s heat demand is predicted with the help of a neural network. The results of the parametric study show significant differences in energy efficiency and cost savings. Furthermore limitations of taking advantage of variable electicity prices due to the price structure are disclosed. The cost savings however do not give a sufficient incentive for the consumer to invest in optimizing the heating system for Demand-Side-Management purposes. By consequence, the potential and the efficiency of Demand-Side-Management are limited and further incentives are necessary. [less ▲]

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See detailThe application of factorial surveys to study recruiters’ hiring intentions: comparing designs based on hypothetical and real vacancies
Gutfleisch, Tamara Rebecca UL; Samuel, Robin UL; Sacchi, Stefan

in Quality and Quantity (2020)

Factorial survey experiments have been widely used to study recruiters’ hiring intentions. Respondents are asked to evaluate hypothetical applicant descriptions, which are experimentally manipulated, for ... [more ▼]

Factorial survey experiments have been widely used to study recruiters’ hiring intentions. Respondents are asked to evaluate hypothetical applicant descriptions, which are experimentally manipulated, for hypothetical job descriptions. However, this methodology has been criticized for putting respondents in hypothetical situations that often only partially correspond to real-life hiring situations. It has been proposed that this criticism can be overcome by sampling real-world vacancies and the recruiters responsible for filling them. In such an approach, only the applicants’ descriptions are hypothetical; respondents are asked about a real hiring problem, which might increase internal and external validity. In this study, we test whether using real vacancies triggers more valid judgments compared to designs based on hypothetical vacancies. The growing number of factorial survey experiments conducted in employer studies makes addressing this question relevant, both for methodological and practical reasons. However, despite the potential implications for the validity of data, it has been neglected so far.We conducted a factorial survey experiment in Luxembourg, in which respondents evaluated hypothetical applicants referring either to a currently vacant position in their company or to a hypothetical job. Overall, we found little evidence for differences in responses by the design of the survey experiment. However, the use of real vacancies might prove beneficial depending on the research interest.We hope that our comparison of designs using real and hypothetical vacancies contributes to the emerging methodological inquiry on the possibilities and limits of using factorial survey experiments in research on hiring. [less ▲]

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See detailUne crise révélatrice. (Pandémie du Covid-19 : Quel rôle pour l’Union européenne ?)
Danescu, Elena UL

Article for general public (2020)

La pandémie du Covid-19 dont l’Europe a un temps été l’épicentre, a entrainé de lourdes conséquences pour la santé et la vie quotidienne des citoyens. Les 27 membres de l’UE ont pris de mesures nationales ... [more ▼]

La pandémie du Covid-19 dont l’Europe a un temps été l’épicentre, a entrainé de lourdes conséquences pour la santé et la vie quotidienne des citoyens. Les 27 membres de l’UE ont pris de mesures nationales exceptionnelles (état d'urgence, confinement, limitation de l'activité économique et des déplacements, fermeture des frontières) en agissant en ordre dispersé. L’Union a été épinglée pour son manque de répondant .Mais quelles sont ses prérogatives en matière sanitaire? Qu’est-ce que l’UE peut faire – et ne peut pas faire – lorsqu’elle est confrontée à une crise de cette magnitude? [less ▲]

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See detailMUSIC EDUCATION IN TIMES OF CORONA. Some Considerations about Music Education and the Content-based Research Programme of the Hungarian Academy of Sciences
Sagrillo, Damien François UL

in Magyar Tudomány (2020), 181(8), 1048-1052

This essay was written at a time when the coronavirus crisis was at its height. For many peo-ple being confined to their homes is a new experience in their lives. There is hardly anyone on the street. The ... [more ▼]

This essay was written at a time when the coronavirus crisis was at its height. For many peo-ple being confined to their homes is a new experience in their lives. There is hardly anyone on the street. The soundscape outside changes, and we experience for the first time what silence means. No one knows how this crisis will end, but among all the negative consequences that humankind will have to face there will be a positive outcome too – it will sharpen the eyesight for new offers and opportunities in delivering knowledge, also for music education [less ▲]

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See detailCovid-19 et le respect des droits humains: Une obligation pour l'état, une responsabilité pour les entreprises
Baglayan, Basak UL; Bichler, Marc

in Revue Luxembourgeoise de Droit Public (2020), (6),

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See detailThe Importance of Computational Modeling in Stem Cell Research
Del Sol Mesa, Antonio UL

in Trends in Biotechnology (2020)

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See detailPostwachstumsgeographien – Mehr Räume für Alternativen!
Lange, Bastian; Hülz, Martina; Schmid, Benedikt et al

in Corona Blog (2020)

Detailed reference viewed: 30 (0 UL)