References of "Scientific congresses, symposiums and conference proceedings"
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See detailBulk and surface characterisation techniques of solar absorbers: general discussion
Dale, Phillip UL; Siebentritt, Susanne UL; sood et al

in Faraday Discussions (2022)

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See detailBreaking and Fixing Vote Privacy of the Estonian E-Voting Protocol IVXV
Mueller, Johannes UL

in Workshop on Advances in Secure Electronic Voting 2022 (2022)

We revisit the e-voting protocol IVXV that is used for legally-binding political elections in Estonia from a privacy perspective. We demonstrate that IVXV is vulnerable to attacks against vote privacy in ... [more ▼]

We revisit the e-voting protocol IVXV that is used for legally-binding political elections in Estonia from a privacy perspective. We demonstrate that IVXV is vulnerable to attacks against vote privacy in those threat scenarios that were considered for IVXV originally. We explain how to improve IVXV so that it protects against the privacy issues we discovered. [less ▲]

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See detailIs this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness
Tian, Haoye UL; Tang, Xunzhu UL; Habib, Andrew UL et al

in Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness (2022)

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See detailWortverbindungen in Paraphrase und Argumentation: Eine Untersuchung an Texten von Studierenden mit L2 Deutsch
Huemer, Birgit UL

in Jahrbuch für Internationale Germanistik. Wege der Germanistik in transkultureller Perspektive (2022)

In diesem Beitrag wird der Umgang mit wissenschaftssprachlichen Wortverbindungen in den beiden Textmustern Paraphrase und Argumentation von Texten luxemburgischer Studienanfänger der Germanistik mit L2 ... [more ▼]

In diesem Beitrag wird der Umgang mit wissenschaftssprachlichen Wortverbindungen in den beiden Textmustern Paraphrase und Argumentation von Texten luxemburgischer Studienanfänger der Germanistik mit L2 Deutsch genau unter die Lupe genommen. Dafür wird ein Korpus von 37 Lernendentexten nach korpuslinguistischen Kriterien aufbereitet und qualitativ analysiert. Es wird untersucht, welche Wortverbindungen für die beiden Textmuster typisch sind, welche Wortverbindungen bereits beherrscht werden und wo Schwierigkeiten auftreten. Die Untersuchung ergibt, dass die Verwendung von Wortverbindungen textmusterspezifisch ist. Die Fehleranalyse zeigt außerdem, dass von 195 verwendeten Wortverbindungen fast ein Drittel fehlerhaft sind. Dabei treten die größten Schwierigkeiten bei der Trennung zwischen Alltagssprache/Umgangssprache und Wissenschaftssprache auf. Als Maßnahmen für den Unterricht wird das Arbeiten mit Wortverbindungslisten, das selbstständige Ergänzen solcher Listen durch Analysen wissenschaftlicher Mustertexte, die Selbstkontrolle am Eigentext und das Arbeiten mit Korpora empfohlen. [less ▲]

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See detailAutonomous Reconfigurable Intelligent Surfaces Through Wireless Energy Harvesting
Ntontin, Konstantinos UL; Boulogeorgos, Apostolos-Alexandros A.; Björnson, Emil et al

Scientific Conference (2022)

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See detailUnlimited Sampling for FMCW Radars: A Proof of Concept
Feuillen, Thomas; Alaeekerahroodi, Mohammad UL; Bhandari, Ayush et al

in 2022 IEEE Radar Conference (RadarConf22) (2022)

High-resolution FMCW radar systems are becoming an integral aspect of applications ranging from automotive safety and autonomous driving to health monitoring of infants and the elderly. This integration ... [more ▼]

High-resolution FMCW radar systems are becoming an integral aspect of applications ranging from automotive safety and autonomous driving to health monitoring of infants and the elderly. This integration provides challenging scenarios that require radars with extremely high dynamic range (HDR) ADCs; these ADCs need to avoid saturation while offering high-performance and high-fidelity data-acquisition. The recent concept of Unlimited Sensing allows one to achieve high dynamic range (HDR) acquisition by recording low dynamic range, modulo samples. Interestingly, oversampling of these folded measurements, with a sampling rate independent of the modulo threshold, is sufficient to guarantee their perfect reconstruction for band-limited signals. This contrasts with the traditional methodology of increasing the dynamic range by adding a programmable-gain amplifier or operating multiple ADCs in parallel. This paper demonstrates an FMCW radar prototype that utilises the unlimited sampling strategy. Our hardware experiments show that even with the use of a modulo measurements of lower precision, the US reconstruction is able to match the performances of the conventional acquisition. Furthermore, our real-time processing capability demonstrates that our “proof-of-concept” approach is a viable solution for HDR FMCW radar signal processing, thus opening a pathway for future hardware-software optimization and integration of this technology with other mainstream systems. [less ▲]

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See detailIs Eve nearby? Analysing protocols under the distant-attacker assumption
Gil Pons, Reynaldo UL; Horne, Ross James UL; Mauw, Sjouke UL et al

in IEEE Computer Security Foundations Symposium, August 7 - 10, 2022, Haifa, Israel (2022)

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See detailExploiting Prototypical Explanations for Undersampling Imbalanced Datasets
Arslan, Yusuf UL; Allix, Kevin UL; Lefebvre, Clément et al

in 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA) (2022)

Among the reported solutions to the class imbalance issue, the undersampling approaches, which remove instances of insignificant samples from the majority class, are quite prevalent. However, the ... [more ▼]

Among the reported solutions to the class imbalance issue, the undersampling approaches, which remove instances of insignificant samples from the majority class, are quite prevalent. However, the undersampling approaches may discard significant patterns in the datasets. A prototype, which is always an actual sample from the data, represents a group of samples in the dataset. Our hypothesis is that prototypes can fill the missing significant patterns that are discarded by undersampling methods and help to improve model performance. To confirm our intuition, we articulate prototypes to undersampling methods in the machine learning pipeline. We show that there is a statistically significant difference between the AUPR and AUROC results of undersampling methods and our approach. [less ▲]

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See detailThe Value of non-formal education form the perspective of young people
Biewers, Sandra UL; Weis, Daniel UL; Latz, Anita UL

in Carmo, Mafalda (Ed.) Education and New Developments 2022 - book of abstracts (2022)

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See detailDebiased Label Aggregation for Subjective Crowdsourcing Tasks
Wallace, Shaun; Cai, Tianyuan; Le, Brendan et al

in Extended Abstracts of the SIGCHI Conference on Human Factors in Computing Systems (CHI EA) (2022)

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See detailHow Efficient are Replay Attacks against Vote Privacy? A Formal Quantitative Analysis
Mestel, David UL; Mueller, Johannes UL; Reisert, Pascal

in 35th IEEE Computer Security Foundations Symposium (2022)

Replay attacks are among the most well-known attacks against vote privacy. Many e-voting systems have been proven vulnerable to replay attacks, including systems like Helios that are used in real ... [more ▼]

Replay attacks are among the most well-known attacks against vote privacy. Many e-voting systems have been proven vulnerable to replay attacks, including systems like Helios that are used in real practical elections. Despite their popularity, it is commonly believed that replay attacks are inefficient but the actual threat that they pose to vote privacy has never been studied formally. Therefore, in this paper, we precisely analyze for the first time how efficient replay attacks really are. We study this question from commonly used and complementary perspectives on vote privacy, showing as an independent contribution that a simple extension of a popular game-based privacy definition corresponds to a strong entropy-based notion. Our results demonstrate that replay attacks can be devastating for a voter's privacy even when an adversary's resources are very limited. We illustrate our formal findings by applying them to a number of real-world elections, showing that a modest number of replays can result in significant privacy loss. Overall, our work reveals that, contrary to a common belief, replay attacks can be very efficient and must therefore be considered a serious threat. [less ▲]

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See detailProportionalitätsrechner für Menschen mit einer Dyskalkulie
Perucca, Antonella UL; Ronk, Pit Ferdy UL

Scientific Conference (2022)

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See detailIntegrated Trajectory Optimization and Cubature Kalman Filter for UAV-Based Target Tracking with Unknown Initial Position
Xu, Sheng; Wu, Linlong UL; MR, Bhavani Shankar et al

in 2022 IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM) (2022)

This paper investigates the target localization/tracking by angle-of-arrival (AOA) sensors carried on an unmanned aerial vehicle (UAV). In many practical applications, the UAV's own position is not ... [more ▼]

This paper investigates the target localization/tracking by angle-of-arrival (AOA) sensors carried on an unmanned aerial vehicle (UAV). In many practical applications, the UAV's own position is not available, since the global position system (GPS) can hardly work in the indoor environment or interference region. Therefore, considering the unknown initial position of the UAV, a modified cubature Kalman filter (CKF) is developed to estimate both the target states and UAV's initial position jointly by leveraging a benchmark anchor. To further improve the estimation efficiency, we propose an algorithm to optimize the UAV flying trajectory by minimizing the the trace of the estimation covariance matrix in the CKF. According to the simulation results, an observation is found that the UAV will keeping flying alternatively between the anchor and target to guarantee the estimation performance. [less ▲]

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See detailLa loyauté dans l'interprétation des accords internationaux
Neframi, Eleftheria UL

in Delile, Jean Felix (Ed.) La loyauté dans l'action extérieure de l'Union européenne (2022)

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See detailAndorra: eine Einherrschaft? Monarch: ein Einzelorgan? Der Verfall des Begriffsmerkmals „monos“ in Europas sogenannten „Monarchien“
Heuschling, Luc UL

in Bussjäger, Peter; Gamper, Anna (Eds.) 100 Jahre Liechtensteinische Verfassung (2022)

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See detailGeometrie der römischen Mosaiken
Perucca, Antonella UL

Scientific Conference (2022)

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See detailA Framework of Hyper-Heuristics based on Q-Learning
Duflo, Gabriel UL; Danoy, Grégoire UL; Talbi, El-Ghazali UL et al

in International Conference in Optimization and Learning (OLA2022) (2022)

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See detailWhat if data protection embraced foresight and speculative design?
Rossi, Arianna UL; Chatellier, Regis; Leucci, Stefano et al

in DRS2022: Bilbao (2022)

Due to rapid technological advancements and the growing “datafication” of our societies, individuals’ privacy constitutes an increasingly explored speculative space for regulators, researchers ... [more ▼]

Due to rapid technological advancements and the growing “datafication” of our societies, individuals’ privacy constitutes an increasingly explored speculative space for regulators, researchers, practitioners, designers and artists. This article reports two experiences at a national and an international data protection authority (i.e., the Commission Nationale de l'Informatique et des Libertés - CNIL - and the European Data Protection Supervisor - EDPS - respectively), where foresight methods and speculative design are employed in policy-making with the goal of anticipating technological trends, their implications for society and their impact on regulations, as well as the effects of existing and upcoming laws on emerging technologies. Such initiatives can enhance strategic proactive abilities, raise public awareness of privacy issues and engender a participatory approach to the design of policies. They can also inspire the research, education and practice of legal design. [less ▲]

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See detailAdversarial Robustness in Multi-Task Learning: Promises and Illusions
Ghamizi, Salah UL; Cordy, Maxime UL; Papadakis, Mike UL et al

in Proceedings of the thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22) (2022)

Vulnerability to adversarial attacks is a well-known weakness of Deep Neural networks. While most of the studies focus on single-task neural networks with computer vision datasets, very little research ... [more ▼]

Vulnerability to adversarial attacks is a well-known weakness of Deep Neural networks. While most of the studies focus on single-task neural networks with computer vision datasets, very little research has considered complex multi-task models that are common in real applications. In this paper, we evaluate the design choices that impact the robustness of multi-task deep learning networks. We provide evidence that blindly adding auxiliary tasks, or weighing the tasks provides a false sense of robustness. Thereby, we tone down the claim made by previous research and study the different factors which may affect robustness. In particular, we show that the choice of the task to incorporate in the loss function are important factors that can be leveraged to yield more robust models. [less ▲]

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See detailTime vs. Unit Cell Splitting for Autonomous Reconfigurable Intelligent Surfaces
Ntontin, Konstantinos UL; Boulogeorgos, Alexandros-Apostolos A.; Abdullah, Zaid UL et al

Scientific Conference (2022)

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See detailMORL/D: Multi-Objective Reinforcement Learning based on Decomposition
Felten, Florian UL; Talbi, El-Ghazali UL; Danoy, Grégoire UL

in International Conference in Optimization and Learning (OLA2022) (2022)

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See detailTSCom-Net: Coarse-to-Fine 3D Textured Shape Completion Network
Karadeniz, Ahmet Serdar UL; Ali, Sk Aziz UL; Kacem, Anis UL et al

in Karadeniz, Ahmet Serdar; Ali, Sk Aziz; Kacem, Anis (Eds.) et al TSCom-Net: Coarse-to-Fine 3D Textured Shape Completion Network (2022)

Reconstructing 3D human body shapes from 3D partial textured scans remains a fundamental task for many computer vision and graphics applications – e.g., body animation, and virtual dressing. We propose a ... [more ▼]

Reconstructing 3D human body shapes from 3D partial textured scans remains a fundamental task for many computer vision and graphics applications – e.g., body animation, and virtual dressing. We propose a new neural network architecture for 3D body shape and highresolution texture completion – TSCom-Net – that can reconstruct the full geometry from mid-level to high-level partial input scans. We decompose the overall reconstruction task into two stages – first, a joint implicit learning network (SCom-Net and TCom-Net) that takes a voxelized scan and its occupancy grid as input to reconstruct the full body shape and predict vertex textures. Second, a high-resolution texture completion network, that utilizes the predicted coarse vertex textures to inpaint the missing parts of the partial ‘texture atlas’. A Thorough experimental evaluation on 3DBodyTex.V2 dataset shows that our method achieves competitive results with respect to the state-of-the-art while generalizing to different types and levels of partial shapes. The proposed method has also ranked second in the track1 of SHApe Recovery from Partial textured 3D scans (SHARP [37 , 2]) 2022 1 challenge1. [less ▲]

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See detailLes cours dans la "monarchie composite" des Luxembourg, 1308-1355 (Henri VII, Jean et Charles IV)
Margue, Michel UL; Adde, Eloïse; Salemme, Timothy UL

in Modèles, réseaux et échanges curiaux au Moyen Âge (2022)

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See detailPrinciples for setting single or multiline bus holding control based on network characteristics
Laskaris, Georgios; Cats, Oded; Jenelius, Erik et al

Scientific Conference (2022)

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See detailPerformance Evaluation of Forward Link Packet Scheduling in Satellite Communication Systems with Carrier Aggregation
Al-Hraishawi, Hayder UL; Lagunas, Eva UL; Kumar, Sumit UL et al

Scientific Conference (2022)

The rapidly growing demand for increased data rates and spectrum scarcity in satellite communication systems require new paradigms to effectively utilize radio resources. Of many candidate techniques ... [more ▼]

The rapidly growing demand for increased data rates and spectrum scarcity in satellite communication systems require new paradigms to effectively utilize radio resources. Of many candidate techniques, carrier aggregation (CA) is a promising solution that combines multiple carriers across the available spectrum to achieve a substantial increase in peak data rate and improve user experience. The concept of CA was introduced in 3GPP standards for the terrestrial communication systems and has been successfully deployed and commercialized worldwide. Recently, satellite communication community has investigated the requirements for adopting CA technique to satellite infrastructures. In this setting, aggregating multiple heterogeneous satellite links to boost a single-user peak throughput requires an efficient data packet scheduler at the gateway in order to avoid the out-of-order packet issues and the subsequent queuing delays at the receiver side. Thereby, several research efforts have been devoted to circumvent this challenge through developing packet schedulers that are aiming at delivering data packets without perturbing their original transmission order. In this paper, the performance of the developed schedulers is evaluated using end-to-end system simulations to investigate the impact of different network metrics. The obtained results demonstrate the design tradeoffs and summarize the pros and cons of the schedulers. [less ▲]

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See detailIdentifying the Major Causes Associated to Rail Intermodal Operation Disruptions Using Causal Machine Learning
Pineda Jaramillo, Juan Diego UL; McDonald, William; Zheng, Wei et al

in Transportation Research Board 101st Annual Meeting (2022)

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See detailDigitizing Inclusion in a Changing World: Comparing insights into four European countries for matching new global realities
Andersen, Katja Natalie UL; Vogt, Michaela; Bagger, Anette et al

Scientific Conference (2022)

Inclusion and digitalization are among the driving forces in global discourses on education and learning. These global realities cause extensive transformations at local, national, and international ... [more ▼]

Inclusion and digitalization are among the driving forces in global discourses on education and learning. These global realities cause extensive transformations at local, national, and international levels. At the same time, the goal of inclusion is directly interwoven with local conditions, understandings, and historically grown valuations. The concept oscillates between universally shared norms and highly divergent local implementations. Regarding the focus of the symposium it can be assumed that especially in the course of digitalization as one main reaction of the corona pandemic, learning materials are not only expected to be inclusion oriented but also need to be combinable with digital demands to address alls kinds of inequalities amongst students appropriately. Learning materials thus are a central momentum to expatiate on transformations of a changing world. In correspondence with the congress theme, the symposium will therefore discuss how a reflection on centrifugal forces of interdependence and individuality can be located in the context of the immediate everyday life in schools and educational practice. In order to be able to discuss these tensions and current changes within educational practices starting from learning materials, an anchor point is needed in order to open up the international comparison of local specifics. The anchor point for this symposium is a criteria catalog which enables the international comparison of learning materials in their cultural contexts and provides a visualization of local particularities in the field of learning materials (Vogt et al. 2021). If these results are put into relation with the inclusive landscapes in different countries, further insights of relevance for inclusion as a global topic can be generated. The data basis springs from the ITM project (2018-2021, funded by Erasmus+) and other international collections of material. Speakers with expertise in regard to the triangulation of learning materials, inclusion and digitalization from four European universities (Ostrava, Czech Republic; Bielefeld, Germany; Luxemburg and Örebro, Sweden) present their findings in the symposium, more in-depth talks about national perspectives as well as a concluding wrap up. The following research questions are a guideline for each section of the symposium: 1. What are the local specifics and constellations as well as understandings of inclusion as a global reality that are being mirrored in teaching material? 2. How can the international comparison of teaching material impact the advancement of inclusion on a local level? 3. How can international comparative educational research become a driving force in the productive negotiation of globally relevant tensions? The contributions are methodologically based on group discussions and expert interviews about selected learning materials, their quality and criteria for evaluating them. These exchanges have been evaluated with the qualitative content analysis by Mayring (2015). Discourse analysis and context analysis were applied. Furthermore, source corpora of learning material were developed and materials were examined using a qualitative content analysis. This refers to the ITM project from Luxembourg, Örebro and Bielefeld University (Erasmus funding line, 2018-2021) as well as the contribution by Ostrava University. The material mainly comes from primary school education and takes into account various subjects, e.g. mathematics and natural sciences. By looking at the results of the interviews and the analysis of teaching materials as well as on the findings about the cultural and local conditions the presenters were able to develop a deeper understanding about how learning materials are set up for inclusive learning processes and about the underpinning understanding of inclusion in different cultural settings. This is the needed foundation to contextualize everyday practices of teaching and learning with the demands of education within the digital condition. [less ▲]

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See detailConvergence time analysis of Asynchronous Distributed Artificial Neural Networks
Dalle Lucca Tosi, Mauro UL; Ellampallil Venugopal, Vinu; Theobald, Martin UL

in 5th Joint International Conference on Data Science Management of Data (9th ACM IKDD CODS and 27th COMAD) (2022)

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See detailVerifiable Decryption in the Head
Gjosteen, Kristian; Haines, Thomas; Mueller, Johannes UL et al

in ACISP 2022 (2022)

In this work we present a new approach to verifiable decryption which converts a 2-party passively secure distributed decryption protocol into a 1-party proof of correct decryption. This leads to an ... [more ▼]

In this work we present a new approach to verifiable decryption which converts a 2-party passively secure distributed decryption protocol into a 1-party proof of correct decryption. This leads to an efficient and simple verifiable decryption scheme for lattice-based cryptography, especially for large sets of ciphertexts; it has small size and lightweight computations as we reduce the need of zero-knowledge proofs for each ciphertext. We believe the flexibility of the general technique is interesting and provides attractive trade-offs between complexity and security, in particular for the interactive variant with smaller soundness. Finally, the protocol requires only very simple operations, making it easy to correctly and securely implement in practice. We suggest concrete parameters for our protocol and give a proof of concept implementation, showing that it is highly practical. [less ▲]

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See detailDeXTER: A post-authentic approach to heritage visualisation
Viola, Lorella UL

Scientific Conference (2022)

Cultural heritage institutions and academics are resorting more and more to visual representations of cultural heritage material as a way to enhance access to collections for users’ appreciation and ... [more ▼]

Cultural heritage institutions and academics are resorting more and more to visual representations of cultural heritage material as a way to enhance access to collections for users’ appreciation and research purposes (Windhager et al., 2019). However, scholars have pointed out (Drucker, 2011; 2013; 2014; 2020; Windhager et al., 2019) how a critical approach to visualisation is still largely missing and how on the whole, user-interface (UI) design still shows a functional and task-driven approach, oriented towards satisfying a need for information rather than towards eliciting curiosity, engagement and reflection. With this presentation, I aim to contribute to the urgent need for the establishment of a critical data and visualisation literacy in current task-driven approaches to interface design which continue to see the user as a consumer and to operate within a problem solver model. Drawing on critical posthumanities (Braidotti, 2017; 2019), I here propose a critical framework to digital cultural heritage and digital cultural heritage visualisation. With this approach —which I labelled “postauthentic framework” (Viola, 2021) —I want to initiate a discussion and critique of the fetishization of empriricism and technical objectivity in digital knowledge creation. To exemplify how the post-authentic framework works in practice, I present the design choices for developing the tool DeXTER – DeepteXTminER, an interactive visualisation app to explore enriched cultural heritage material. The discussion will revolve around the challenges facing product design, with specific reference to visualising the ambiguities and uncertainties of network analysis (NA) and sentiment analysis (SA). DeXTER is currently loaded with Chroniclitaly 3.0 (Viola and Fiscarelli, 2021a), a digital heritage collection of Italian American newspapers published in the USA by Italian immigrants between 1897 and 1936. [less ▲]

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See detailGeodetic climate research in the Austrian Alps
Ullrich, Christian; Francis, Olivier UL; Tabibi, Sajad UL et al

Scientific Conference (2022)

The Federal Office of Metrology and Surveying (BEV) in Austria is responsible for the geodetic reference system like gravity and height reference frame. Some of these gravity reference stations are ... [more ▼]

The Federal Office of Metrology and Surveying (BEV) in Austria is responsible for the geodetic reference system like gravity and height reference frame. Some of these gravity reference stations are monitored regularly by different geodetic terrestrial techniques. The gravity data on some stations show variations and/or changes in gravity. In this presentation, the alpine geodetic reference stations Obergurgl and Franz-Josefs- Höhe in the Austrian eastern Alps will be presented. Both stations are investigated with different geodetic terrestrial techniques in a cooperation of the University of Luxemburg with BEV. Global warming and associated climate change during the last century and recent decades are among the main reasons for glacier retreat in the Alps. Absolute gravity measurements have been regularly performed in the Austrian Eastern Alps since 1987 in the Ötztal Valley at Obergurgl. In addition, absolute gravity has been regularly observed at Obergurgl from 1987 to 2009 with the absolute gravimeter JILAg6. From 2010, the absolute gravity measurements were continued with the highest accurate absolute gravimeters FG5 from BEV and FG5x from University of Luxemburg. The newest gravity data show again a small increase of gravity. Additionally, a permanent GNSS station was established in 2019 to record information about the assumed vertical uplift at this station. A second alpine research station was established near the Pasterze Glacier at Großglockner Mountain in 2019. The Pasterze Glacier is one of the largest glaciers in the eastern Alps and is in the vicinity of the highest mountain of Austria, the Großglockner. The station is monitored by repeated absolute gravity measurements and is equipped with a permanent GNSS station. In addition, precise leveling measurements were also tied to this station. In this contribution, initial results of the geodetic research like the gravity results, precise leveling and GNSS measurements will be presented. In the future, gravity data will be quantitively compared to ice mass balance information derived from glacier inventories. A Geodetic Global Navigation Satellite System reflectometry (GNSS-R) antenna will also be installed to study glacier-ice change. A third station at an altitude of 3300 m is planned and will be checked for operating absolute gravity measurements there. The geodynamical processes like vertical uplift and postglacial deformation will be investigated together with glacier retreat on these stations. [less ▲]

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See detailEspaces (in)sensibles : l'appropriation en didactique comparée
Thiltges, Sébastian UL; Raus, Tonia

in Thiltges, Sébastian; Raus, Tonia (Eds.) spaces (in)sensibles : l'appropriation en didactique comparée (2022)

La nouvelle d'anticipation « Une voix dans le silence » (trad.) de Yorick Schmit sensibilise les lecteurs aux bouleversements environnementaux, psychologiques et affectifs engendrés par une catastrophe ... [more ▼]

La nouvelle d'anticipation « Une voix dans le silence » (trad.) de Yorick Schmit sensibilise les lecteurs aux bouleversements environnementaux, psychologiques et affectifs engendrés par une catastrophe nucléaire. Partant d'une lecture écopoétique, nous imaginons l'étude de ce récit en langue luxembourgeoise en cours de français, afin d'exploiter la tension ainsi créée par le dispositif translinguistique et interculturel. Dans une double perspective de didactique des langues et de la littérature, nous interrogeons dès lors le rôle du sensible dans le développement du plurilinguisme dans l'enseignement-apprentissage de la littérature. Pour ce faire, notre approche de didactique comparée se fonde sur le paradigme de l'appropriation en tant que concept à la fois linguistique et littéraire : le lecteur devient sensible en faisant sien le récit lu, dans un corps à corps avec la matérialité du texte écrit dans une langue familière en tant que langue véhiculaire mais étrangère en tant que langue littéraire, favorisant ainsi une prise de conscience des sens de la langue et du texte. [less ▲]

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See detailImproving Pulse-Compression Weather Radar via the Joint Design of Subpulses and Extended Mismatch Filter
Wu, Linlong UL; Alaeekerahroodi, Mohammad UL; Mysore Rama Rao, Bhavani Shankar UL

in IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium (2022)

Pulse compression can enhance both the performance in range resolution and sensitivity for weather radar. However, it will introduce the issue of high sidelobes if not delicately implemented. Motivated by ... [more ▼]

Pulse compression can enhance both the performance in range resolution and sensitivity for weather radar. However, it will introduce the issue of high sidelobes if not delicately implemented. Motivated by this fact, we focus on the pulse compression design for weather radar in this paper. Specifically, we jointly design both the subpulse codes and extended mismatch filter based on the alternating direction method of multipliers (ADMM). This joint design will yield a pulse compression with low sidelobes, which equivalently implies a high signal-to-interference-plus-noise ratio (SINR) and a low estimation error on meteorological reflectivity. The experiment results demonstrate the efficacy of the proposed pulse compression strategy since its achieved meteorological reflectivity estimations are highly similar to the ground truth. [less ▲]

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See detailBelElect: A New Dataset for Bias Research from a ”Dark” Platform
Hoehn, Sviatlana UL; Mauw, Sjouke UL; Asher, Nicholas

in Vol. 16 (2022): Proceedings of the Sixteenth International AAAI Conference on Web and Social Media (2022)

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See detailCombining Relaying and Reflective Surfaces: Power Consumption and Energy Efficiency Analysis
Abdullah, Zaid UL; Alexandropoulos, George C.; Kisseleff, Steven UL et al

in IEEE Global Communication Conference, Rio de Janeiro, Brazil (2022)

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See detailGustav: Cross-device Cross-computer Synchronization of Sensory Signals
Latifzadeh, Kayhan UL; Leiva, Luis A. UL

in Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (2022)

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See detailDigital Simulator of the Human Arteries
Torres Gómez, Jorge; Gonzalez Rios, Jorge Luis UL; Dressler, Falko

in European Wireless (EW 2022) (2022)

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See detailGiving talents a voice: Talent management n the aerospace industry
Usanova, Ksenia UL; Geraudel, Mickaël UL

Scientific Conference (2022)

Although Talent Management (TM) has been studied for the last two decades, the empirical knowledge represents highly managerial view on the phenomenon. Those important studies that investigated TM from ... [more ▼]

Although Talent Management (TM) has been studied for the last two decades, the empirical knowledge represents highly managerial view on the phenomenon. Those important studies that investigated TM from both managers’ and talents’ perspectives are scarce and quite fragmented since they focus only on one or two components of TM. In this work, we try to examine TM holistically by focusing on five main TM components together – talent definition, TM goals, attraction, development and retention of talents – through the perspectives of managers and talented individuals. To that end, we interviewed 40 talents and their managers in the aerospace industry in Luxembourg. We identified shared, exclusively managers’ and exclusively talents’ views of TM and named them “functional”, “pragmatic” and “romanticized” respectively. By combining the shared view and expected views, we propose an ideal TM for talent and an ideal TM for managers. [less ▲]

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See detailµBert: Mutation Testing using Pre-Trained Language Models
Degiovanni, Renzo Gaston UL; Papadakis, Mike UL

in Degiovanni, Renzo Gaston; Papadakis, Mike (Eds.) µBert: Mutation Testing using Pre-Trained Language Models (2022)

We introduce µBert, a mutation testing tool that uses a pre-trained language model (CodeBERT) to generate mutants. This is done by masking a token from the expression given as input and using CodeBERT to ... [more ▼]

We introduce µBert, a mutation testing tool that uses a pre-trained language model (CodeBERT) to generate mutants. This is done by masking a token from the expression given as input and using CodeBERT to predict it. Thus, the mutants are generated by replacing the masked tokens with the predicted ones. We evaluate µBert on 40 real faults from Defects4J and show that it can detect 27 out of the 40 faults, while the baseline (PiTest) detects 26 of them. We also show that µBert can be 2 times more cost-effective than PiTest, when the same number of mutants are analysed. Additionally, we evaluate the impact of µBert's mutants when used by program assertion inference techniques, and show that they can help in producing better specifications. Finally, we discuss about the quality and naturalness of some interesting mutants produced by µBert during our experimental evaluation. [less ▲]

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See detailIntJect: Vulnerability Intent Bug Seeding
PETIT, Benjamin; Khanfir, Ahmed UL; Soremekun, Ezekiel UL et al

in 22nd IEEE International Conference on Software Quality, Reliability, and Security (2022)

Studying and exposing software vulnerabilities is important to ensure software security, safety, and reliability. Software engineers often inject vulnerabilities into their programs to test the ... [more ▼]

Studying and exposing software vulnerabilities is important to ensure software security, safety, and reliability. Software engineers often inject vulnerabilities into their programs to test the reliability of their test suites, vulnerability detectors, and security measures. However, state-of-the-art vulnerability injection methods only capture code syntax/patterns, they do not learn the intent of the vulnerability and are limited to the syntax of the original dataset. To address this challenge, we propose the first intent-based vulnerability injection method that learns both the program syntax and vulnerability intent. Our approach applies a combination of NLP methods and semantic-preserving program mutations (at the bytecode level) to inject code vulnerabilities. Given a dataset of known vulnerabilities (containing benign and vulnerable code pairs), our approach proceeds by employing semantic-preserving program mutations to transform the existing dataset to semantically similar code. Then, it learns the intent of the vulnerability via neural machine translation (Seq2Seq) models. The key insight is to employ Seq2Seq to learn the intent (context) of the vulnerable code in a manner that is agnostic of the specific program instance. We evaluate the performance of our approach using 1275 vulnerabilities belonging to five (5) CWEs from the Juliet test suite. We examine the effectiveness of our approach in producing compilable and vulnerable code. Our results show that INTJECT is effective, almost all (99%) of the code produced by our approach is vulnerable and compilable. We also demonstrate that the vulnerable programs generated by INTJECT are semantically similar to the withheld original vulnerable code. Finally, we show that our mutation-based data transformation approach outperforms its alternatives, namely data obfuscation and using the original data. [less ▲]

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See detailLove at First Sight? A User Experience Study of Self-Sovereign Identity Wallets
Sartor, Sebastian; Sedlmeir, Johannes UL; Rieger, Alexander UL et al

in 30th European Conference on Information Systems (ECIS 2022) (2022)

Today’s systems for digital identity management exhibit critical security, efficiency, and privacy issues. A new paradigm, called Self-Sovereign Identity (SSI), addresses these shortcomings by equipping ... [more ▼]

Today’s systems for digital identity management exhibit critical security, efficiency, and privacy issues. A new paradigm, called Self-Sovereign Identity (SSI), addresses these shortcomings by equipping users with mobile wallets and empowering them to manage their digital identities. Various companies and governments back this paradigm and promote its development and diffusion. User experience often plays a subordinate role in these efforts, even though it is crucial for user satisfaction and adoption. We thus conduct a comprehensive user experience study of four prominent SSI wallets using a mixed-method approach that involves moderated and remote interviews and the User Experience Questionnaire (UEQ). We find that the examined wallets already provide a decent level of user experience, yet further improvements need to be done. In particular, the examined wallets do not make their novelty and benefits sufficiently apparent to users. Our analysis contributes to user experience research and offers guidance for SSI practitioners. [less ▲]

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See detailStochastic porous media, towards a digital meniscus
Obeidat, Anas UL; Zilian, Andreas UL

in Bulletin of the American Physical Society (2022)

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See detailElysium: Context-Aware Bytecode-Level Patching to Automatically Heal Vulnerable Smart Contracts
Ferreira Torres, Christof UL; Jonker, Hugo; State, Radu UL

in International Symposium on Research in Attacks, Intrusions and Defenses, Limassol, Cyprus 26-28 October 2022 (2022)

Fixing bugs is easiest by patching source code. However, source code is not always available: only 0.3% of the ∼49M smart contracts that are currently deployed on Ethereum have their source code publicly ... [more ▼]

Fixing bugs is easiest by patching source code. However, source code is not always available: only 0.3% of the ∼49M smart contracts that are currently deployed on Ethereum have their source code publicly available. Moreover, since contracts may call functions from other contracts, security flaws in closed-source contracts may affect open-source contracts as well. However, current state-of-the-art approaches that operate on closed-source contracts (i.e., EVM bytecode), such as EVMPatch and SmartShield, make use of purely hard-coded templates that leverage fix patching patterns. As a result, they cannot dynamically adapt to the bytecode that is being patched, which severely limits their flexibility and scalability. For instance, when patching integer overflows using hard-coded templates, a particular patch template needs to be employed as the bounds to be checked are different for each integer size (i.e., one template for uint256, another template for uint64, etc.). In this paper, we propose Elysium, a scalable approach towards automatic smart contract repair at the bytecode level. Elysium combines template-based and semantic-based patching by inferring context information from bytecode. Elysium is currently able to patch 7 different types of vulnerabilities in smart contracts automatically and can easily be extended with new templates and new bug-finding tools. We evaluate its effectiveness and correctness using 3 different datasets by replaying more than 500K transactions on patched contracts. We find that Elysium outperforms existing tools by patching at least 30% more contracts correctly. Finally, we also compare the overhead of Elysium in terms of deployment and transaction cost. In comparison to other tools, we find that generally Elysium minimizes the runtime cost (i.e., transaction cost) up to a factor of 1.7, for only a marginally higher deployment cost, where deployment cost is a one-time cost as compared to the runtime cost. [less ▲]

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See detailPhysics-Based Cognitive Radar Modeling and Parameter Estimation
Sedighi, Saeid UL; Mysore Rama Rao, Bhavani Shankar UL; Mishra, Kumar Vijay et al

in IEEE Radar Conference (2022)

We consider the problem of channel response estimation in cognitive fully adaptive radar (CoFAR). We show that this problem can be expressed as a constrained channel estimation problem exploiting the ... [more ▼]

We consider the problem of channel response estimation in cognitive fully adaptive radar (CoFAR). We show that this problem can be expressed as a constrained channel estimation problem exploiting the similarity between the channel impulse responses (CIRs) of the adjacent channels. We develop a constrained CIR estimation (CCIRE) algorithm enhancing estimation performance compared to the unconstrained CIR estimation where the similarity between the CIRs of the adjacent channels is not employed. Further, we we derive the Cram\'{e}r-Rao bound (CRB) for the CCIRE and show the optimality of the proposed CCIRE through comparing its performance with the derived CRB. [less ▲]

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See detailAccelerated Consensus ADMM for Widely Distributed Radar Imaging
Murtada, Ahmed Abdelnaser Elsayed UL; Mysore Rama Rao, Bhavani Shankar UL; Hu, Ruizhi UL et al

in 2022 IEEE Radar Conference (RadarConf22) Proceedings (2022)

Widely distributed radar systems are expected to enhance radar imaging performance due to their ability to capture diverse spatial scattering proprieties. Optimization-based sub-aperture imaging methods ... [more ▼]

Widely distributed radar systems are expected to enhance radar imaging performance due to their ability to capture diverse spatial scattering proprieties. Optimization-based sub-aperture imaging methods are used to adopt the isotropic scattering assumption within a narrow angular extent and reconstruct the scene image by fusing sub-aperture images. A previously proposed method based on consensus alternating direction method of multipliers (CADMM) provides a joint reconstruction of sub-aperture images along with a global image that represents the anisotropic scene. In this paper, we propose a modified version of CADMM which features lower complexity and faster convergence. By gradually learning the scene support during the iterative reconstruction, our proposed algorithm focuses on the image portion that contains the scattering targets and updates the sub-images accordingly. It also reduces the communication cost between the distributed sensors which need to exchange local image updates during CADMM iterations. [less ▲]

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See detailDual-Function Radar-Communication Systems with Constant-Modulus and Similarity Constraints
Tsinos, Christos UL; Arora, Aakash UL; Chatzinotas, Symeon UL et al

in IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM) (2022)

In this paper, the problem of joint transmit waveform and receive filter design for dual-function radar-communication (DFRC) systems is studied. A multiple antenna base station (BS) serving multiple ... [more ▼]

In this paper, the problem of joint transmit waveform and receive filter design for dual-function radar-communication (DFRC) systems is studied. A multiple antenna base station (BS) serving multiple single antenna users on the downlink is assumed. Furthermore, the BS simultaneously accommodates sensing capabilities in the form of point-like target detection from the reflected return signals in a signal-dependent interference environment. The core objective of the present paper is to design the optimal waveform and radar receive filter such that the derived waveform satisfies constant-modulus and similarity to known waveform constraints that are of particular importance to the radar's part operation. The proposed designs are derived through the solution to difficult non-convex optimization problems. To that end, novel algorithmic solutions with guaranteed convergence are developed for the solution of the aforementioned problems. The effectiveness of the proposed solutions is verified via simulations. [less ▲]

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See detailJoint Communications and Sensing for Hybrid Massive MIMO LEO Satellite Systems With Beam Squint
Qiang, Xiaoyu; You, Li; Tsinos, Christos UL et al

in 2022 IEEE International Conference on Communications Workshops (ICC Workshops) (2022)

To improve the efficient utilization of spectral and hardware resources, joint communications and sensing (JCS) has drawn extensive attention. Most existing JCS works focus on terrestrial networks and can ... [more ▼]

To improve the efficient utilization of spectral and hardware resources, joint communications and sensing (JCS) has drawn extensive attention. Most existing JCS works focus on terrestrial networks and can not be straightforwardly applied in satellite systems due to the significantly different electromagnetic wave propagation properties. In this work, we investigate the application of JCS in massive multiple-input multiple-output (MIMO) low earth orbit (LEO) satellite systems. We first charac-terize the statistical wave propagation properties by considering beam squint effects. Based on this analysis, we propose a beam squint-aware JCS technique for hybrid analog/digital massive MIMO LEO satellite systems exploiting statistical channel s-tate information. Simulation results demonstrate that both the wireless communications and target sensing can be operated simultaneously with satisfactory performance, and the beam squint effects can be efficiently mitigated with the proposed method in typical LEO satellite systems. [less ▲]

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See detailSharing Big Data in Health Care: Focus on the Role Played by Co-regulatory Instruments in Light of the New European Health Data Space
Vigna, Francesco UL

in Tom, Goffin; Tom, Balthazar (Eds.) Book of Proceedings: Eighth European Conference on Health Law (2022)

Big data and AI are revolutionizing data processing in health care. The new paradigm of data-driven decision making will lead primary activities, such as the provision of care services, as well as ... [more ▼]

Big data and AI are revolutionizing data processing in health care. The new paradigm of data-driven decision making will lead primary activities, such as the provision of care services, as well as secondary health care purposes, like clini-cal research. However, the extraction of knowledge from big data in health care depends on the possibility for stakeholders to share and connect datasets in compliance with data protection law requirements. In this regard, the EU Data Strategy seeks to foster data sharing for public benefit. The EU Commission, in the preparatory works for the European Health Data Space, has stressed that issues related to GDPR compliance could hinder the sharing and the re-use of data in health care. Namely, two order of problems may be highlighted in this perspective: 1) the special regime for health data pro-cessing in GDPR, which allows MS to add even stricter data protection rules; 2) margins of choice for data controllers and processors about how to implement technical and organisational measures for reaching GDPR compliance, according to the risk-based approach. According to the EU Commission, legal uncertainty might be mitigated by adopting co-regulatory measures, such as a Code of Conduct for the sharing of health data. A Code of Conduct (articles 40 and 41 GDPR) could establish common ways to interpret and comply with loose GDPR requirements and prin-ciples, therefore creating harmonization. However, given the legal fragmentation typical of the health domain among MS, the elaboration of an EU-wide Code of Conduct for personal data processing could not bring the desired effects. More-over, some doubts concern the lack of legal effects produced by a Code of Conduct on the burden of proof for data controllers. Finally, also costs and complexities linked to the elaboration of GDPR co-regulatory instruments may hamper the diffusion of these mechanisms. The paper discusses opportunities and limits of GDPR co-regulatory mecha-nisms, considering the forthcoming European Health Data Space. It is argued that despite legal and governance reasoning are theoretically correct about the role of these instruments, their spread is limited once the reasoning is linked to market and economic aspects. [less ▲]

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See detailTranslational Challenges of Biomedical Machine Learning Solutions in Clinical and Laboratory Settings
Vega Moreno, Carlos Gonzalo UL; Kratochvil, Miroslav UL; Satagopam, Venkata UL et al

in Bioinformatics and Biomedical Engineering (2022)

The ever increasing use of artificial intelligence (AI) methods in biomedical sciences calls for closer inter-disciplinary collaborations that transfer the domain knowledge from life scientists to ... [more ▼]

The ever increasing use of artificial intelligence (AI) methods in biomedical sciences calls for closer inter-disciplinary collaborations that transfer the domain knowledge from life scientists to computer science researchers and vice-versa. We highlight two general areas where the use of AI-based solutions designed for clinical and laboratory settings has proven problematic. These are used to demonstrate common sources of translational challenges that often stem from the differences in data interpretation between the clinical and research view, and the unmatched expectations and requirements on the result quality metrics. We outline how explicit interpretable inference reporting might be used as a guide to overcome such translational challenges. We conclude with several recommendations for safer translation of machine learning solutions into real-world settings. [less ▲]

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See detailNon-Admissibility in abstract argumentation
Dvorak, Wolfgang; Rienstra, Tjitze; van der Torre, Leon UL et al

in Frontiers in Artificial Intelligence and Applications (2022), 353

In this paper, we give an overview of several recent proposals for non-Admissible non-naive semantics for abstract argumentation frameworks. We highlight the similarities and differences between weak ... [more ▼]

In this paper, we give an overview of several recent proposals for non-Admissible non-naive semantics for abstract argumentation frameworks. We highlight the similarities and differences between weak admissibility-based approaches and undecidedness-blocking approaches using examples and principles as well as a study of their computational complexity. We introduce a kind of strengthened undecidedness-blocking semantics combining some of the distinctive behaviours of weak admissibility-based semantics with the lower complexity of undecidedness-blocking approaches. We call it loop semantics, because in our new semantics, an argument can only be undecided if it is part of a loop of undecided arguments. Our paper shows how a principle-based approach and a complexity-based approach can be used in tandem to further develop the foundations of formal argumentation. [less ▲]

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See detailTransforming IoT Data Preprocessing: A Holistic, Normalized and Distributed Approach
Tawakuli, Amal UL; Kaiser, Daniel UL; Engel, Thomas UL

in The Fifth International Workshop on Data: Acquisition To Analysis (2022)

Data preprocessing is an integral part of Artificial Intelligence (AI) pipelines. It transforms raw data into input data that fulfill algorithmic criteria and improve prediction accuracy. As the adoption ... [more ▼]

Data preprocessing is an integral part of Artificial Intelligence (AI) pipelines. It transforms raw data into input data that fulfill algorithmic criteria and improve prediction accuracy. As the adoption of Internet of Things (IoT) gains more momentum, the data volume generated from the edge is exponentially increasing that far exceeds any expansion of infrastructure. Social responsibilities and regulations (e.g., GDPR) must also be adhered when handling IoT data. In addition, we are currently witnessing a shift towards distributing AI to the edge. The aforementioned reasons render the distribution of data preprocessing to the edge an urgent requirement. In this paper, we introduce a modern data preprocessing framework that consists of two main parts. Part1 is a design tool that reduces the complexity and costs of the data preprocessing phase for AI via generalization and normalization. The design tool is a standard template that maps specific techniques into abstract categories and highlights dependencies between them. In addition, it presents a holistic notion of data preprocessing that is not limited to data cleaning. The second part is an IoT tool that adopts the edge-cloud collaboration model to progressively improve the quality of the data. It includes a synchronization mechanism that ensures adaptation to changes in data characteristics and a coordination mechanism that ensures correct and complete execution of preprocessing plans between the cloud and the edge. The paper includes an empirical analysis of the framework using a developed prototype and an automotive use-case. Our results demonstrate reductions in resource consumption (e.g., energy, bandwidth) while maintaining the value and integrity of the data. [less ▲]

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See detailTarget Control of Boolean Networks with Permanent Edgetic Perturbations
Zeyen, Olivier Georges Rémy UL; Pang, Jun UL

in Proceedings of the 61st International Conference on Decision and Control (CDC 2022) (2022)

Boolean network is a popular and well-established modelling framework for gene regulatory networks. The steady-state behaviour of Boolean networks can be described as attractors, which are hypothesised to ... [more ▼]

Boolean network is a popular and well-established modelling framework for gene regulatory networks. The steady-state behaviour of Boolean networks can be described as attractors, which are hypothesised to characterise cellular phenotypes. In this work, we study the target control problem of Boolean networks, which has important applications for cellular reprogramming. More specifically, we want to reduce the total number of attractors of a Boolean network to a single target attractor. Different from existing approaches to solving control problems of Boolean networks with node perturbations, we aim to develop an approach utilising edgetic perturbations. Namely, our objective is to modify the update functions of a Boolean network such that there remains only one attractor. The design of our approach is inspired by Thomas’ first rule, and we primarily focus on the removal of cycles in the interaction graph of a Boolean network. We further use results in the literature to only remove positive cycles which are responsible for the appearance of multiple attractors. We apply our solution to a number of real-life biological networks modelled as Boolean networks, and the experimental results demonstrate its efficacy and efficiency. [less ▲]

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See detailAkuter Stress und kardiale interozeptive Genauigkeit in einer Herzschlagzählaufgabe
Hansen, Greta UL; Vögele, Claus UL; Bellingrath, Silja et al

in Heinrichs, Markus; Schönauer, Monika (Eds.) 47. Jahrestagung Psychologie und Gehirn (2022)

Interozeption, d.h. die Wahrnehmung und Verarbeitung körperinnerer Signale, hängt mit der Aktivität eines Körperorgans (z.B. kardiale Aktivierung) zusammen. Die Organaktivität wird maßgeblich durch Stress ... [more ▼]

Interozeption, d.h. die Wahrnehmung und Verarbeitung körperinnerer Signale, hängt mit der Aktivität eines Körperorgans (z.B. kardiale Aktivierung) zusammen. Die Organaktivität wird maßgeblich durch Stress beeinflusst, der beispielsweise durch soziale Situationen oder Schmerz ausgelöst wird. Auch wenn erste Erkenntnisse implizieren, dass Stress die bewusste Ebene der Interozeption („interozeptive Genauigkeit“/IG) beeinflussen könnte, sind der Zeitverlauf dieses Effekts und die Rolle von Organaktivierung bislang unklar. Anhand eines Gruppenexperiments mit gesunden Versuchspersonen (je n=33 Stress- und Kontrollgruppe, w=48) wurde die Auswirkung von akutem Stress (sozial-evozierter Kaltwassertest) auf IG in einer Herzschlagzählaufgabe zu vier unterschiedlichen Zeitpunkten (pre-Stress/post-Stress-1/2/3) untersucht. Der Stressor führte zu einem Anstieg von selbstberichtetem Stress (sowie Speichelcortisol). Die Herzrate (Organaktivität) sowie die IG blieben jedoch, entgegen der Erwartungen, sowohl zwischen den Gruppen als auch über die Zeit, unverändert. Unabhängig von der Bedingung und den Zeitpunkten zeigte sich außerdem eine Tendenz, die tatsächlichen Herzschläge zu 56% zu unterschätzen. Bei konstanter Herzrate (M=81.5 bpm) über alle Versuchsbedingungen hinweg konnten die gezählten Herzschläge alleine (M=28.55) somit die IG (M=.43) vorhersagen (r=.962, p<.001). Diese Ergebnisse legen nahe, dass sowohl die zentrale Rolle der gezählten Herzschläge auf die IG, als auch jene Organaktivierung, die durch akuten Stress verändert wird und sich in einer Veränderung der gezählten Herzschläge widerspiegelt, bei Anwendung der Herzschlagzählaufgabe, berücksichtigt werden muss. [less ▲]

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See detail5G Space Communications Lab: Reaching New Heights
Kodheli, Oltjon UL; Querol, Jorge UL; Astro, Abdelrahman et al

in Proceedings of the 18th International Conference on Distributed Computing in Sensor Systems (DCOSS) (2022)

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See detailDeep Mining Covid-19 Literature
Sirajzade, Joshgun UL; Bouvry, Pascal UL; Schommer, Christoph UL

in Applied Informatics, 5th International Conference, ICAI 2022, Arequipa, Peru, October 27–29, 2022, Proceedings (2022)

In this paper we investigate how scientific and medical papers about Covid-19 can be effectively mined. For this purpose we use the CORD19 dataset which is a huge collection of all papers published about ... [more ▼]

In this paper we investigate how scientific and medical papers about Covid-19 can be effectively mined. For this purpose we use the CORD19 dataset which is a huge collection of all papers published about and around the SARS-CoV2 virus and the pandemic it caused. We discuss how classical text mining algorithms like Latent Semantic Analysis (LSA) or its modern version Latent Drichlet Allocation (LDA) can be used for this purpose and also touch more modern variant of these algorithms like word2vec which came with deep learning wave and show their advantages and disadvantages each. We finish the paper with showing some topic examples from the corpus and answer questions such as which topics are the most prominent for the corpus or how many percentage of the corpus is dedicated to them. We also give a discussion of how topics around RNA research in connection with Covid-19 can be examined. [less ▲]

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See detailWikiDoMiner: Wikipedia Domain-Specific Miner
Ezzini, Saad UL; Abualhaija, Sallam UL; Sabetzadeh, Mehrdad

in ACM SIGSOFT CONFERENCE ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (2022)

We introduce WikiDoMiner -- a tool for automatically generating domain-specific corpora by crawling Wikipedia. WikiDoMiner helps requirements engineers create an external knowledge resource that is ... [more ▼]

We introduce WikiDoMiner -- a tool for automatically generating domain-specific corpora by crawling Wikipedia. WikiDoMiner helps requirements engineers create an external knowledge resource that is specific to the underlying domain of a given requirements specification (RS). Being able to build such a resource is important since domain-specific datasets are scarce. WikiDoMiner generates a corpus by first extracting a set of domain-specific keywords from a given RS, and then querying Wikipedia for these keywords. The output of WikiDoMiner is a set of Wikipedia articles relevant to the domain of the input RS. Mining Wikipedia for domain-specific knowledge can be beneficial for multiple requirements engineering tasks, e.g., ambiguity handling, requirements classification, and question answering. WikiDoMiner is publicly available on Zenodo under an open-source license (https://doi.org/10.5281/zenodo.6672682) [less ▲]

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See detailSpatial Spectrum Nulling for Wideband OFDM-DFRC System With Hybrid Beamforming Architecture
Wang, Bowen; Cheng, Ziyang; Wu, Linlong UL et al

in 2022 IEEE Wireless Communications and Networking Conference (WCNC) (2022)

This paper deals with the problem of the hybrid beamforming design of wideband orthogonal frequency division multiplexing (OFDM) dual-function radar-communication (DFRC) system, which is expected to ... [more ▼]

This paper deals with the problem of the hybrid beamforming design of wideband orthogonal frequency division multiplexing (OFDM) dual-function radar-communication (DFRC) system, which is expected to achieve a satisfactory user's spectral efficiency and form excellent space-frequency spectrum behavior as well as spatial nulls on the directions of strong signal-dependent interference (such as clutters) simultaneously. For such purpose, we formulate our problem by maximizing the communication spectral efficiency subject to the constraints of radar integrated sidelobe to mainlobe ratio (ISMR) and spatial spectrum nulling (SSN). Due to the fact that the analog beamformer for all subcarriers and digital beamformer for each subcarrier are simultaneously optimized in the wideband OFDM system, the resultant problem is difficult to solve. Towards that end, an efficient algorithm is devised based on the consensus alternating direction method of multipliers (CADMM) framework. Numerical simulation results demonstrate the superiority of the proposed hybrid beamforming algorithm. [less ▲]

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See detailA RNN-Based Hyper-Heuristic for Combinatorial Problems
Kieffer, Emmanuel UL; Duflo, Gabriel UL; Danoy, Grégoire UL et al

in A RNN-Based Hyper-Heuristic for Combinatorial Problems (2022)

Designing efficient heuristics is a laborious and tedious task that generally requires a full understanding and knowledge of a given optimization problem. Hyper-heuristics have been mainly introduced to ... [more ▼]

Designing efficient heuristics is a laborious and tedious task that generally requires a full understanding and knowledge of a given optimization problem. Hyper-heuristics have been mainly introduced to tackle this issue and are mostly relying on Genetic Programming and its variants. Many attempts in the literature have shown that an automatic training mechanism for heuristic learning is possible and can challenge human-based heuristics in terms of gap to optimality. In this work, we introduce a novel approach based on a recent work on Deep Symbolic Regression. We demonstrate that scoring functions can be trained using Recurrent Neural Networks to tackle a well-know combinatorial problem, i.e., the Multi-dimensional Knapsack. Experiments have been conducted on instances from the OR-Library and results show that the proposed modus operandi is an alternative and promising approach to human- based heuristics and classical heuristic generation approaches. [less ▲]

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See detailA Unified Framework for Adversarial Attack and Defense in Constrained Feature Space
Simonetto, Thibault Jean Angel UL; Dyrmishi, Salijona UL; Ghamizi, Salah UL et al

in Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22 (2022)

The generation of feasible adversarial examples is necessary for properly assessing models that work in constrained feature space. However, it remains a challenging task to enforce constraints into ... [more ▼]

The generation of feasible adversarial examples is necessary for properly assessing models that work in constrained feature space. However, it remains a challenging task to enforce constraints into attacks that were designed for computer vision. We propose a unified framework to generate feasible adversarial examples that satisfy given domain constraints. Our framework can handle both linear and non-linear constraints. We instantiate our framework into two algorithms: a gradient-based attack that introduces constraints in the loss function to maximize, and a multi-objective search algorithm that aims for misclassification, perturbation minimization, and constraint satisfaction. We show that our approach is effective in four different domains, with a success rate of up to 100%, where state-of-the-art attacks fail to generate a single feasible example. In addition to adversarial retraining, we propose to introduce engineered non-convex constraints to improve model adversarial robustness. We demonstrate that this new defense is as effective as adversarial retraining. Our framework forms the starting point for research on constrained adversarial attacks and provides relevant baselines and datasets that future research can exploit. [less ▲]

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See detailQoE-Oriented Resource Allocation Design Coping with Time-Varying Demands in Wireless Communication Networks
Kebedew, Teweldebrhan Mezgebo UL; Ha, Vu Nguyen UL; Lagunas, Eva UL et al

in IEEE 96st Vehicular Technology Conference, London-Beijing, Sept. 2022 (2022)

Detailed reference viewed: 32 (11 UL)
See detailThe legacy of coal mining – a view on examples in Belgium and France
Helfer, Malte UL

in Bluma, Lars; Farrenkopf, Michael; Meyer, Torsten (Eds.) Boom – Crisis – Heritage. King Coal and Energy Revolutions after 1945; proceedings of the international conference March 14th-16th 2018, Technische Hochschule Georg Agricola, Bochum (2022)

Following the end of coalmining in Belgium (1992) and France (2004), the year 2018 marks the end of hard coal mining in Germany as well. This contribution looks at the legacy of coalmining of Germany’s ... [more ▼]

Following the end of coalmining in Belgium (1992) and France (2004), the year 2018 marks the end of hard coal mining in Germany as well. This contribution looks at the legacy of coalmining of Germany’s French-speaking neighbours and presents the most important remaining coal mining heritage sites as well as some extraordinary converted sites in France and the Belgian province Wallonia. [less ▲]

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See detailWhich companies go public via SPACs? The role of venture capital
Hansen, Christopher UL

Scientific Conference (2022)

This study investigates the characteristics and stock market performance of companies going public via special-purpose acquisition companies (SPACs). Using a sample of 798 companies that went public in ... [more ▼]

This study investigates the characteristics and stock market performance of companies going public via special-purpose acquisition companies (SPACs). Using a sample of 798 companies that went public in 2020 and 2021, we compare those companies that went public via SPAC to companies that conducted a traditional IPO. Moreover, we examine the potential impact of venture capital funding on the mode of going public and the post-listing performance of the respective companies. Our results show that companies going public via SPAC in 2020 and 2021 did not systematically differ in their firm characteristics from traditional IPO companies. However, they perform nevertheless constantly and significantly worse in terms of stock return over a period of six months after becoming publicly listed. Venture capital funding has not per se an impact on the mode of going public, but companies with more prestigious VCs invested prefer to chose a traditional IPO over a SPAC to go public. [less ▲]

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See detailControlling Smart Propagation Environments: Long-Term Versus Short-Term Phase Shift Optimization
Van Chien, Trinh; Tu, Lam Thanh; Tran Dinh, Hieu UL et al

in ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2022)

Reconfigurable intelligent surfaces (RISs) have recently gained significant interest as an emerging technology for future wireless networks. This paper studies an RIS-assisted propagation environment ... [more ▼]

Reconfigurable intelligent surfaces (RISs) have recently gained significant interest as an emerging technology for future wireless networks. This paper studies an RIS-assisted propagation environment, where a single-antenna source transmits data to a single-antenna destination in the presence of a weak direct link. We analyze and compare RIS designs based on long-term and short-term channel statistics in terms of coverage probability and ergodic rate. For the considered optimization designs, closed-form expressions for the coverage probability and ergodic rate are derived. We use numerical simulations to validate the obtained analytical framework. Also, we show that the considered optimal phase shift designs outperform several heuristic benchmarks. [less ▲]

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See detailWith or Without Blockchain? Towards a Decentralized, SSI-based eRoaming Architecture
Höß, Alexandra UL; Roth, Tamara UL; Sedlmeir, Johannes UL et al

in Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS) (2022)

Fragmentation and limited accessibility of charging infrastructure impede the adoption of electric vehicles. To improve the availability of charging infrastructure independent of providers, eRoaming ... [more ▼]

Fragmentation and limited accessibility of charging infrastructure impede the adoption of electric vehicles. To improve the availability of charging infrastructure independent of providers, eRoaming offers a promising solution. Yet, current eRoaming systems are typically centralized, which raises concerns of market power concentration. While the use of blockchain technology can obviate such concerns, it comes with significant privacy challenges. To address these challenges, we explore a combination of blockchain with self-sovereign identity. Specifically, we apply a design science research approach, which helps us to identify requirements, derive a conceptual architecture, and deduce design principles for decentralized eRoaming and beyond. We find that blockchain may best leverage its benefits when it takes a backseat as a public registry for legal entities. Moreover, we find that the use of self-sovereign identities could improve compliance with privacy regulations, but they should not be overused. [less ▲]

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See detailThe influence of tens and units inversion in a two-digit number matching task in German and French monolinguals and bilinguals
Lachelin, Remy UL; Poncin, Alexandre; Van Rinsveld, Amandine et al

Poster (2022)

Detailed reference viewed: 28 (0 UL)
See detailImage Enhancement for Space Surveillance and Tracking
Jamrozik, Michele Lynn UL; Gaudilliere, Vincent UL; Mohamed Ali, Mohamed Adel UL et al

in Jamrozik, Michele Lynn; Gaudilliere, Vincent; Musallam, Mohamed Adel (Eds.) et al Proceedings of the 73rd International Astronautical Congress (2022)

Images generated in space with monocular camera payloads suffer degradations that hinder their utility in precision tracking applications including debris identification, removal, and in-orbit servicing ... [more ▼]

Images generated in space with monocular camera payloads suffer degradations that hinder their utility in precision tracking applications including debris identification, removal, and in-orbit servicing. To address the substandard quality of images captured in space and make them more reliable in space object tracking applications, several Image Enhancement (IE) techniques are investigated in this work. In addition, two novel space IE methods were developed. The first method called REVEAL, relies upon the application of more traditional image processing enhancement techniques and assumes a Retinex image formation model. A subsequent method, based on a UNet Deep Learning (DL) model was also developed. Image degradations addressed include blurring, exposure issues, poor contrast, and noise. The shortage of space-generated data suitable for supervised DL is also addressed. A visual comparison of both techniques developed was conducted and compared against the current state-of-the-art in DL-based IE methods relevant to images captured in space. It is determined in this work that both the REVEAL and the UNet-based DL solutions developed are well suited to correct for the degradations most often found in space images. In addition, it has been found that enhancing images in a pre-processing stage facilitates the subsequent extraction of object contours and metrics. By extracting information through image metrics, object properties such as size and orientation that enable more precise space object tracking may be more easily determined. Keywords: Deep Learning, Space, Image Enhancement, Space Debris [less ▲]

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See detailDerogations Analysis of European Legislation Through Hybrid AI Approach
Palmirani, Monica; Liga, Davide UL

in Electronic Government and the Information Systems Perspective: 11th International Conference, EGOVIS 2022 (2022)

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See detailChallenges of protecting confidentiality in social media data and their ethical import
Rossi, Arianna; Arenas Correa, Monica Patricia UL; Kocyigit, Emre UL et al

in 2022 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) (2022)

This article discussed the challenges of pseudonymizing unstructured, noisy social media data for cybersecurity research purposes and presents an open- source package developed to pseudonymize personal ... [more ▼]

This article discussed the challenges of pseudonymizing unstructured, noisy social media data for cybersecurity research purposes and presents an open- source package developed to pseudonymize personal and confidential information (i.e., personal names, companies, and locations) contained in such data. Its goal is to facilitate compliance with EU data protection obligations and the upholding of research ethics principles like the respect for the autonomy, privacy and dignity of research participants, the social responsibility of researchers, and scientific integrity. We discuss the limitations of the pseudonymizer package, their ethical import, and the additional security measures that should be adopted to protect the confidentiality of the data. [less ▲]

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See detailMULTI LABEL IMAGE CLASSIFICATION USING ADAPTIVE GRAPH CONVOLUTIONAL NETWORKS (ML-AGCN)
Singh, Inder Pal UL; Ghorbel, Enjie UL; Oyedotun, Oyebade UL et al

in IEEE International Conference on Image Processing (2022)

In this paper, a novel graph-based approach for multi-label image classification called Multi-Label Adaptive Graph Convolutional Network (ML-AGCN) is introduced. Graph-based methods have shown great ... [more ▼]

In this paper, a novel graph-based approach for multi-label image classification called Multi-Label Adaptive Graph Convolutional Network (ML-AGCN) is introduced. Graph-based methods have shown great potential in the field of multi-label classification. However, these approaches heuristically fix the graph topology for modeling label dependencies, which might be not optimal. To handle that, we propose to learn the topology in an end-to-end manner. Specifically, we incorporate an attention-based mechanism for estimating the pairwise importance between graph nodes and a similarity-based mechanism for conserving the feature similarity between different nodes. This offers a more flexible way for adaptively modeling the graph. Experimental results are reported on two well-known datasets, namely, MS-COCO and VG-500. Results show that ML-AGCN outperforms state-of-the-art methods while reducing the number of model parameters. [less ▲]

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See detailIterative structural inference of directed graphs
Wang, Aoran UL; Pang, Jun UL

in Proceedings of the 36th Annual Conference on Neural Information Processing Systems (NeurIPS'22) (2022)

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See detailNon-Orthogonal Multicast and Unicast Robust Beamforming in Integrated Terrestrial-Satellite Networks
Peng, Deyi; Domouchtsidis, Stavros UL; Chatzinotas, Symeon UL et al

in IEEE Global Communications Conference (2022)

This paper studies the non-orthogonal multicast and unicast coordinated beamforming design for integrated terrestrial and satellite networks (ITSN), when the channel state information at the transmitter ... [more ▼]

This paper studies the non-orthogonal multicast and unicast coordinated beamforming design for integrated terrestrial and satellite networks (ITSN), when the channel state information at the transmitter (CSIT) is imperfect. In order to mitigate the interference induced by simultaneous multicast and unicast links along with the spectrum coexisting mechanism for integrated terrestrial and satellite transmissions, we consider a two-layer layered division multiplexing (LDM) structure where the mul ticast and unicast services are provided in different layers. We formulate a coordinated beamforming problem with the objective to minimize the transmit power under individual quality of service (QoS) constraints. With regard to the unknown convexity of the transmit power minimization problem, we transform the original infeasible optimization into a deterministic optimization form with linear matrix inequality (LMI) by utilizing S-procedure and semi-definite relaxation (SDR) methods. Then, we introduce a penalty function and propose an iterative algorithm with guaranteed convergence to obtain optimal solutions. Simulation results demonstrate the superiority of the proposed coordinated beamforming scheme, especially for the case of imperfect CSIT, while our LDM based coordinated beamforming scheme signifi cantly outperforms the conventional ones in terms of sum rate. Index Terms—Integrated terrestrial and satellite networks (IT SN), beamforming, robust, layered division multiplexing (LDM) [less ▲]

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See detailCubeSat-CDT: A Cross-Domain Dataset for 6-DoF Trajectory Estimation of a Symmetric Spacecraft
Mohamed Ali, Mohamed Adel UL; Rathinam, Arunkumar UL; Gaudilliere, Vincent UL et al

in Proceedings of the 17th European Conference on Computer Vision Workshops (ECCVW 2022) (2022)

This paper introduces a new cross-domain dataset, CubeSat- CDT, that includes 21 trajectories of a real CubeSat acquired in a labora- tory setup, combined with 65 trajectories generated using two ... [more ▼]

This paper introduces a new cross-domain dataset, CubeSat- CDT, that includes 21 trajectories of a real CubeSat acquired in a labora- tory setup, combined with 65 trajectories generated using two rendering engines – i.e. Unity and Blender. The three data sources incorporate the same 1U CubeSat and share the same camera intrinsic parameters. In ad- dition, we conduct experiments to show the characteristics of the dataset using a novel and efficient spacecraft trajectory estimation method, that leverages the information provided from the three data domains. Given a video input of a target spacecraft, the proposed end-to-end approach re- lies on a Temporal Convolutional Network that enforces the inter-frame coherence of the estimated 6-Degree-of-Freedom spacecraft poses. The pipeline is decomposed into two stages; first, spatial features are ex- tracted from each frame in parallel; second, these features are lifted to the space of camera poses while preserving temporal information. Our re- sults highlight the importance of addressing the domain gap problem to propose reliable solutions for close-range autonomous relative navigation between spacecrafts. Since the nature of the data used during training impacts directly the performance of the final solution, the CubeSat-CDT dataset is provided to advance research into this direction. [less ▲]

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See detailArtificial Intelligence as an undue influence in criminal trials: Issuing the use of algorithms under the principle of independence of judges in Europe.
Antunes, Théo UL

in Artificial Intelligence from the Perspective of Law and Ethics: Contemporary Issues, Challenges and Perspectives (2022)

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See detailHomomorphic encryption for privacy-friendly augmented democracy
Brabant, Matthieu; Pereira, Olivier; Meaux, Pierrick UL

in 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON) (2022)

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See detailInterference Mitigation via NMF for Radio Astronomy Applications: A Feasibility Study
Silva, Felipe Barboza; Cetin, Ediz; Alves Martins, Wallace UL et al

in 15th International Conference on Sensing Technology (ICST), Sydney 5-7 December 2022 (2022)

This work assesses the feasibility of using nonnegative matrix factorization (NMF) for radio frequency interference (RFI) mitigation in radio astronomy applications. Two NMF-based mitigation approaches ... [more ▼]

This work assesses the feasibility of using nonnegative matrix factorization (NMF) for radio frequency interference (RFI) mitigation in radio astronomy applications. Two NMF-based mitigation approaches are proposed, one using RFI frequency information extracted from the received signals and the other using an RFI template. The suitability and efficacy of these approaches are evaluated by targeting automatic dependent surveillance-broadcast (ADS-B) RFI using data collected from the Parkes radio telescope in Australia. Results show that the proposed approaches can mitigate the RFI with minimal degradation to the underlying observation of a double pulsar, and without discarding any received data, indicating the applicability of NMF-based approaches as potential RFI mitigation tools in radio astronomy applications. [less ▲]

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See detailNovel chalcogenides, pnictides and defecttolerant semiconductors: general discussion
Dale, Phillip UL; siebentritt; Sood, Mohit UL et al

in Faraday Discussions (2022)

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See detailIntelligent Human-input-based Blockchain Oracle (IHiBO)
Yu, Liuwen; Zichichi, Mirko; Markovich, Réka UL et al

in Proceedings of the 14th International Conference on Agents and Artificial Intelligence, ICAART 2022, Volume 1 (2022)

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See detailTAPHSIR: Towards AnaPHoric Ambiguity Detection and ReSolution In Requirements
Ezzini, Saad UL; Abualhaija, Sallam UL; Arora, Chetan et al

in ACM SIGSOFT CONFERENCE ON THE FOUNDATIONS OF SOFTWARE ENGINEERING (2022)

We introduce TAPHSIR -- a tool for anaphoric ambiguity detection and anaphora resolution in requirements. TAPHSIR facilities reviewing the use of pronouns in a requirements specification and revising ... [more ▼]

We introduce TAPHSIR -- a tool for anaphoric ambiguity detection and anaphora resolution in requirements. TAPHSIR facilities reviewing the use of pronouns in a requirements specification and revising those pronouns that can lead to misunderstandings during the development process. To this end, TAPHSIR detects the requirements which have potential anaphoric ambiguity and further attempts interpreting anaphora occurrences automatically. TAPHSIR employs a hybrid solution composed of an ambiguity detection solution based on machine learning and an anaphora resolution solution based on a variant of the BERT language model. Given a requirements specification, TAPHSIR decides for each pronoun occurrence in the specification whether the pronoun is ambiguous or unambiguous, and further provides an automatic interpretation for the pronoun. The output generated by TAPHSIR can be easily reviewed and validated by requirements engineers. TAPHSIR is publicly available on Zenodo (https://doi.org/10.5281/zenodo.5902117). [less ▲]

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See detailJOINT CARRIER ALLOCATION AND PRECODING OPTIMIZATION FOR INTERFERENCE-LIMITED GEO SATELLITE
Abdu, Tedros Salih UL; Kisseleff, Steven UL; Lagunas, Eva UL et al

Scientific Conference (2022)

The rise of flexible payloads on satellites opens a door for controlling satellite resources according to the user demand, user location, and satellite position. In addition to resource management ... [more ▼]

The rise of flexible payloads on satellites opens a door for controlling satellite resources according to the user demand, user location, and satellite position. In addition to resource management, applying precoding on flexible payloads is essential to obtain high spectral efficiency. However, these cannot be achieved using a conventional resource allocation algorithm that does not consider the user demand. In this paper, we propose a demand-aware algorithm based on multiobjective optimization to jointly design the carrier allocation and precoding for better spectral efficiency and demand matching with proper management of the satellite resources. The optimization problem is non-convex, and we solve it using convex relaxation and successive convex approximation. Then, we evaluate the performance of the proposed algorithm through numerical results. It is shown that the proposed method outperforms the benchmark schemes in terms of resource utilization and demand satisfaction. [less ▲]

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See detailIs this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness
Tian, Haoye UL; Tang, Xunzhu UL; Habib, Andrew UL et al

in Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness (2022)

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See detailBeware of Greeks bearing entanglement? Quantum covert channels, information flow and non-local games
Mestel, David UL

in 35th IEEE Computer Security Foundations Symposium (2022)

Can quantum entanglement increase the capacity of (classical) covert channels? To one familiar with Holevo's Theorem it is tempting to think that the answer is obviously no. However, in this work we show ... [more ▼]

Can quantum entanglement increase the capacity of (classical) covert channels? To one familiar with Holevo's Theorem it is tempting to think that the answer is obviously no. However, in this work we show: quantum entanglement can in fact increase the capacity of a classical covert channel, in the presence of an active adversary; on the other hand, a zero-capacity channel is not improved by entanglement, so entanglement cannot create `purely quantum' covert channels; the problem of determining the capacity of a given channel in the presence of entanglement is undecidable; but there is an algorithm to bound the entangled capacity of a channel from above, adapted from the semi-definite hierarchy from the theory of non-local games, whose close connection to channel capacity is at the core of all of our results. [less ▲]

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See detailWhen a Kippah Represents All Jews: Navigating Shifting Signs from Talmud Torah to School in Luxembourg
Badder, Anastasia UL

Scientific Conference (2021, December 20)

Across the contexts of the lives of Luxembourg's Liberal Talmud Torah students, secularism and mobility are highly valued and understood to be key characteristics of modern living. Talmud Torah students ... [more ▼]

Across the contexts of the lives of Luxembourg's Liberal Talmud Torah students, secularism and mobility are highly valued and understood to be key characteristics of modern living. Talmud Torah students feel they easily meet these criteria – they are multilingual, they currently lead and anticipate highly mobile lives, they see themselves as cosmopolitan and their approach to Jewish life as flexible, and, equally importantly, they look, dress, and comport themselves "like everyone else", all of which are understood to facilitate movement (in the sense of movement across geographic, economic, social, and religious/secular spheres) and belonging in the modern world. The students directly contrast their ways of being with those of more observant Jews. Identifiable by their rootedness, linguistic stringency, and, especially, their ways of dressing (e.g. wearing a kippah in public), the embodied practices and visibility of observant Jews are perceived to be impediments to participation and success in the secular realm. For Talmud Torah students, the public kippah in particular indexes a religious individual and a "backwards" and undesirable life. However, when Jewishness appears in their school classrooms, it is usually visually represented by orthodox-presenting men – often a man in a white shirt and black kippah. In the school classroom, these men and their kippot are framed as representing all Jews, understood as a homogenous group of adherents to the religion Judaism. For many Talmud Torah students, their first encounter with this new meaning of the kippah, visualization and associated conceptualization of Jewishness is jarring – they suddenly find themselves on the 'wrong' side of the religious/secular divide and grouped together with those from whom they could not feel more distant. Based on 31 months of ethnographic fieldwork with Luxembourg's Liberal Jewish community, this paper will explore how the kippah is remediated from the Talmud Torah to the school classroom, how students grapple with this uncomfortable process, and some of its implications. [less ▲]

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See detailModel-Based Systems Engineering to Design An Onboard Surround Vision System for Cooperative Automated Vehicles
Kemsaram, Narsimlu UL; Das, Anweshan; Dubbelman, Gijs

Scientific Conference (2021, December 17)

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See detailA SysML-based Design and Development of Stereo Vision System with Pose and Velocity Estimation for Cooperative Automated Vehicles
Kemsaram, Narsimlu UL; Das, Anweshan; Dubbelman, Gijs

Scientific Conference (2021, December 09)

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See detailDual-DNN Assisted Optimization for Efficient Resource Scheduling in NOMA-Enabled Satellite Systems
Wang, Anyue UL; Lei, Lei UL; Lagunas, Eva UL et al

Scientific Conference (2021, December 08)

In this paper, we apply non-orthogonal multiple access (NOMA) in satellite systems to assist data transmission for services with latency constraints. We investigate a problem to minimize the transmission ... [more ▼]

In this paper, we apply non-orthogonal multiple access (NOMA) in satellite systems to assist data transmission for services with latency constraints. We investigate a problem to minimize the transmission time by jointly optimizing power allocation and terminal-timeslot assignment for accomplishing a transmission task in NOMA-enabled satellite systems. The problem appears non-linear/non-convex with integer variables and can be equivalently reformulated in the format of mixed-integer convex programming (MICP). Conventional iterative methods may apply but at the expenses of high computational complexity in approaching the optimum or near-optimum. We propose a combined learning and optimization scheme to tackle the problem, where the primal MICP is decomposed into two learning-suited classification tasks and a power allocation problem. In the proposed scheme, the first learning task is to predict the integer variables while the second task is to guarantee the feasibility of the solutions. Numerical results show that the proposed algorithm outperforms benchmarks in terms of average computational time, transmission time performance, and feasibility guarantee. [less ▲]

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See detailShort-Packet Communications in Multi-Hop WPINs: Performance Analysis and Deep Learning Design
Nguyen, Toan-Van; Nguyen, van Dinh UL; Costa, Daniel Benevides da et al

Scientific Conference (2021, December 07)

In this paper, we study short-packet communications (SPCs) in multi-hop wireless-powered Internet-of-Things networks (WPINs), where IoT devices transmit short packets to multiple destination nodes by ... [more ▼]

In this paper, we study short-packet communications (SPCs) in multi-hop wireless-powered Internet-of-Things networks (WPINs), where IoT devices transmit short packets to multiple destination nodes by harvesting energy from multiple power beacons. To improve system block error rate (BLER) and throughput, we propose a best relay-best user (bR-bU) selection scheme with an accumulated energy harvesting mechanism. Closed-form expressions for the BLER and throughput of the proposed scheme over Rayleigh fading channels are derived and the respective asymptotic analysis is also carried out. To support real-time settings, we design a deep neural network (DNN) framework to predict the system throughput under different channel settings. Numerical results demonstrate that the proposed bR-bU selection scheme outperforms several baseline ones in terms of the BLER and throughput, showing to be an efficient strategy for multi-hop SPCs. The resulting DNN can estimate accurately the throughput with low execution time. The effects of message size on reliability and latency are also evaluated and discussed. [less ▲]

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See detailSelf-Sovereign Identity for the Financial Sector: A Case Study of PayString Service
Scheidt de Cristo, Flaviene UL; Shbair, Wazen UL; Trestioreanu, Lucian Andrei UL et al

Scientific Conference (2021, December 06)

PayString is an initiative to make payment identifiers global and human-readable, facilitating the exchange of payment information. However, the reference implementation lacks privacy and security ... [more ▼]

PayString is an initiative to make payment identifiers global and human-readable, facilitating the exchange of payment information. However, the reference implementation lacks privacy and security features, making it possible for anyone to access the payment information as long as the PayString identifier is known. Also this paper presents the first performance evaluation of PayString. Via a large-scale testbed our experimental results show an overhead which, given the privacy and security advantages offered, is acceptable in practice, thus making the proposed solution feasible. [less ▲]

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See detailTo verify or tolerate, that’s the question
Pinto Gouveia, Ines UL; Sakr, Mouhammad UL; Graczyk, Rafal UL et al

Scientific Conference (2021, December 06)

Formal verification carries the promise of absolute correctness, guaranteed at the highest level of assurance known today. However, inherent to many verification attempts is the assumption that the ... [more ▼]

Formal verification carries the promise of absolute correctness, guaranteed at the highest level of assurance known today. However, inherent to many verification attempts is the assumption that the underlying hardware, the code-generation toolchain and the verification tools are correct, all of the time. While this assumption creates interesting recursive verification challenges, which already have been executed successfully for all three of these elements, the coverage of this assumption remains incomplete, in particular for hardware. Accidental faults, such as single-event upsets, transistor aging and latchups keep causing hardware to behave arbitrarily in situations where such events occur and require other means (e.g., tolerance) to safely operate through them. Targeted attacks, especially physical ones, have a similar potential to cause havoc. Moreover, faults of the above kind may well manifest in such a way that their effects extend to all software layers, causing incorrect behavior, even in proven correct ones. In this position paper, we take a holistic system-architectural point of view on the role of trusted-execution environments (TEEs), their implementation complexity and the guarantees they can convey and that we want to be preserved in the presence of faults. We find that if absolute correctness should remain our visionary goal, TEEs can and should be constructed differently with tolerance embedded at the lowest levels and with verification playing an essential role. Verification should both assure the correctness of the TEE construction protocols and mechanisms as well as help protecting the applications executing inside the TEEs. [less ▲]

Detailed reference viewed: 71 (2 UL)