Écologie culturelle d’une petite littérature européenne

in Écocritique : nouvelles territorialités 2 (in press)

L’exposition d’objets ou de collections de « marque » : cobranding, réécriture, réénonciation

in Laval, Sylvie (Ed.) Marques muséales : un espace public revisité ? (in press)

Le cobranding est une pratique habituelle du secteur marchand. Mais lorsque deux musées réalisent ensemble une exposition, peut-on parler de cobranding muséal ? Quelles en seraient les spécificités  ... [more ▼]

Le cobranding est une pratique habituelle du secteur marchand. Mais lorsque deux musées réalisent ensemble une exposition, peut-on parler de cobranding muséal ? Quelles en seraient les spécificités ? Quels effets peut avoir cette démarche sur la communication ou sur l’exposition ? Notamment, le musée d’accueil s’approprie-t-il simplement l’imaginaire et les valeurs de la marque invitée par un phénomène de « transfert » ? Pour répondre à ces questions, nous étudions trois expositions qui reprennent des objets ou collections de musées dont la marque est internationalement reconnue. L’analyse sémiotique des images de marque du musée d’accueil et du musée invité ainsi que l’analyse sémiopragmatique des expositions montrent l’impact de la présence d’une grande marque internationale sur l’exposition et réciproquement, l’impact de l’exposition sur l’image de marque du musée d’accueil. Plus qu’un simple cobranding, c’est une réécriture impliquant une réénonciation du discours et des valeurs portés par les marques qui est proposée à travers ces expositions. Le processus aboutit à la création de nouveaux espaces symboliques et d’expositions réflexives, avec plusieurs niveaux de lecture. [less ▲]

Fuzzing for CPS Mutation Testing

in Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering (in press)

Les archevêques de Milan face aux premières expériences seigneuriales: stratégies et positionnements (milieu XIIIe-début XIVe s.)

in Barralis, Christine (Ed.) L’évêque face à son métier. Actes du colloque international, Metz. 15-17 novembre 2017 (in press)

DaMAT: A Data-driven Mutation Analysis Tool

in Proceedings of the 45th International Conference on Software Engineering (ICSE ’23) (in press)

We present DaMAT, a tool that implements data- driven mutation analysis. In contrast to traditional code-driven mutation analysis tools it mutates (i.e., modifies) the data ex- changed by components ... [more ▼]

We present DaMAT, a tool that implements data- driven mutation analysis. In contrast to traditional code-driven mutation analysis tools it mutates (i.e., modifies) the data ex- changed by components instead of the source of the software under test. Such an approach helps ensure that test suites appropriately exercise components interoperability — essential for safety-critical cyber-physical systems. A user-provided fault model drives the mutation process. We have successfully evalu- ated DaMAT on software controlling a microsatellite and a set of libraries used in deployed CubeSats. A demo video of DaMAT is available at https://youtu.be/s5M52xWCj84 [less ▲]

Eaux polymorphes dans l’œuvre de Jean Portante. Lecture-entretien avec l’auteur

in Breaking the Waves: Water (Issues) in Contemporary Verbal and Visual Arts (in press)

Triangular Intertwined Frequency Selective Surface

in Vasquez-Peralvo, Juan Andres; Merlano Duncan, Juan Carlos; Chatzinotas, Symeon (Eds.) et al International symposium on antennas and propagation (in press)

This paper presents a frequency selective surface design and simulation using intertwined triangular structures. It has been discovered that by using the proposed tessellated intertwined lattice, the ... [more ▼]

This paper presents a frequency selective surface design and simulation using intertwined triangular structures. It has been discovered that by using the proposed tessellated intertwined lattice, the reduction of the resonance frequency of a frequency selective surface can be improved by 22.58% compared with other triangular structures. Additionally, this structure is used as a MEFSS to improve the miniaturization of the structure and obtain a compact, angular stable band-pass filter. The simulations presented in this paper have been obtained using CST Microwave Studio. [less ▲]

La littérature luxembourgeoise à l’école : une didactique interculturelle de la littérature en contexte multilingue

in Transnationale und interkulturelle Literaturwissenschaft und Litertaturdidaktik : Konzeptionelle und digitale Transformationen (in press)

In Luxembourg, multilingual requirements are a corollary of the country’s historical trilingualism and characterize its school system: Luxembourgish is the national language, French and German the ... [more ▼]

In Luxembourg, multilingual requirements are a corollary of the country’s historical trilingualism and characterize its school system: Luxembourgish is the national language, French and German the official languages. Like other European countries, English tends to occupy an increasingly important place, as a language taught in secondary school, while Luxembourgish plays only a minor role as a school subject. Rooted in the traditional association of language and literature, Luxembourg’s school environment is still largely organized according to a juxtaposed multilingualism, with clear linguistic separations and specific disciplinary cultures. These characteristics considerably hinder, among others, the entry of works from the Luxembourg literary field into the curricular path of secondary education. In fact, Luxembourgish literature, an essentially multilingual (Luxembourgish, French, German and more recently English, Italian, Portuguese) and small literature, is hardly taught in schools: the national literature struggles to impose itself compared to the cultural references of the large neighboring countries. At the same time, the weak literary production intended for adolescent readers, which translates socio-literarily into the absence of specific editorial collections, finds only a slight echo with its recipients. Starting from this double literary and didactic context, we wish to present our project to publish a novel by a French-language Luxembourg author in a digital format, thus remediatizing the texts, and broadening them with educational content and activities. The development of these new media considers the multilingual and intercultural particularities of Luxembourg’s literary and school environments and targets a readership fond of new reading practices. By adopting a research-action approach, we’d like to cover multiple research areas (multilingual children's literature in a small literary field, digital reading practices, teaching of literary reading in a multilingual school context) and we could integrate the project in our teaching in the Master in Secondary Education to train future teachers. [less ▲]

Le dialogue entre les juges en matière de protection des droits de l'homme

in Menetrey, Séverine; Hess, Burkhard (Eds.) Les dialogues des juges en Europe (in press)

Dans cet article, nous allons mettre en exergue quelques aspects des arrêts récents provenant de la Cour de justice de l’UE (Akerberg Frasson, Melloni, Kamberaj)qui démontrent l’émergence d’un standard ... [more ▼]

Dans cet article, nous allons mettre en exergue quelques aspects des arrêts récents provenant de la Cour de justice de l’UE (Akerberg Frasson, Melloni, Kamberaj)qui démontrent l’émergence d’un standard propre de l’UE en matière des droits de l’homme. Cette tendance de la C.J.U.E. contredira le prescrit normatif découlant du « dialogue des juges » d’interprétation conforme à la jurisprudence de la C.E.D.H. avant que l’adhésion de l’UE à la Convention E.D.H. ne soit formellement acquise. [less ▲]

Wide-Beamwidth Circular Polarized Antenna for Diversity Combining Applications

in Vasquez-Peralvo, Juan Andres; Merlano Duncan, Juan Carlos; Eappen, Geoffrey (Eds.) et al Global Communications Conference, Rio de Janeiro, 4 - 9 December 2022 (in press)

This paper presents the design, simulation, and manufacturing of a right-hand circularly polarized antenna working in the frequency band 17.7-20.2 GHz with a beamwidth of 42.4$^\circ$ and 5.4$^\circ$ for ... [more ▼]

This paper presents the design, simulation, and manufacturing of a right-hand circularly polarized antenna working in the frequency band 17.7-20.2 GHz with a beamwidth of 42.4$^\circ$ and 5.4$^\circ$ for the H-plane and E-plane, respectively. The presented antenna is part of a set of three antennas, two high-gain antennas, and, presented in this paper, a low directive antenna used for reception. The application we describe in this paper combines the radio-frequency signals obtained from the O3b satellite constellation, using three antennas to apply path diversity later to reconstruct the original signal. Moreover, using an antenna with a beamwidth in one plane allows receiving two satellite signals at the same time, increasing by 3 dB the overall gain. The wide-band capabilities of the antenna are obtained using aperture coupling. In particular, the circular polarization of the antenna is generated using a truncated corner square patch. Further, a metasurface is placed at the top to enhance the axial ratio. Importantly, the simulation results obtained using CST Microwave Studio show that the antenna has a reflection coefficient below -10 dB and an axial ratio below -3 dB in the intended frequency range. [less ▲]

AML/CFT/CPF endeavors in the crypto space: from blockchain analytics to machine learning

in Proceedings of Artificial Intelligence Governance Ethics and Law (AIGEL) (in press)

Financial applications of distributed ledger technologies (DLTs) generate regulatory concerns. In the crypto sphere, pseudonymity may safeguard privacy and data protection, but lack of identifiability ... [more ▼]

Financial applications of distributed ledger technologies (DLTs) generate regulatory concerns. In the crypto sphere, pseudonymity may safeguard privacy and data protection, but lack of identifiability cripples investigation and enforcement. This challenges the fight against money laundering and the financing of terrorism and proliferation (AML/CFT/CPF). Nonetheless, forensic techniques trace transfers across blockchain ecosystems and provide intelligence to regulated entities. This working paper addresses anomaly detection in the crypto space, the role of machine learning, and the impact of disintermediation. [less ▲]

Glwssiki ikanotita, glwssiki chrisi kai glwssikes staseis Alvanwn metanastwn prwtis kai defteris genias stin Ellada.

(in press)

Discrete-Phase Sequence Design with Stopband and PSL Constraints for Cognitive Radar

in Proceedings of EuRAD 2020 (in press)

We present the design of discrete-phase sequences considering simultaneously the peak sidelobe level (PSL) and avoiding reserved frequency bands which are occupied by narrowband interferers or ... [more ▼]

We present the design of discrete-phase sequences considering simultaneously the peak sidelobe level (PSL) and avoiding reserved frequency bands which are occupied by narrowband interferers or communications. We use the coordinate descent framework and propose an algorithm to design discrete-phase sequences with spectral power suppressed in arbitrary bands and with low auto-correlation sidelobes in terms of PSL. Our proposed algorithm exploits fast Fourier transform and is, therefore, computationally efficient. The over-the-air experiments using implementation on software-defined radio show reasonable agreement with numerical simulations and feasibility for field-deployment [less ▲]

Towards Modeling and Predicting the Resilience of Ecosystems

in Sousa, Tiago (Ed.) Towards Modeling and Predicting the Resilience of Ecosystems (in press)

Since the Stockholm Declaration on the human environment in 1972, there has been a growing recognition of the impact of human activities on Earth's ecosystems. This has created an increasing need for ... [more ▼]

Since the Stockholm Declaration on the human environment in 1972, there has been a growing recognition of the impact of human activities on Earth's ecosystems. This has created an increasing need for modeling and predicting the resilience of ecosystems, which is crucial not only for understanding ecosystem patterns and processes but also for addressing climate change and implementing effective conservation and management strategies. Despite the importance of this issue, the intrinsic complexity of ecosystems and the lack of sufficient data present considerable challenges. To address these challenges, we propose an approach that combines model-driven engineering and artificial intelligence. Specifically, we propose a formalization for modeling and verifying ecosystem requirements, a method for synthesizing heterogeneous ecosystem resilience data, and a product line of neural network architectures adaptable to diverse properties and types of ecosystem scenarios to study. Additionally, we propose a model-driven process specification detailing the different artifacts, stakeholder roles, tasks, and model transformations of the proposed approach. This paper outlines the problem and preliminary work, presents the proposed approach, which is the current focus of an ongoing Ph.D. thesis, and discusses the future research contributions. [less ▲]

Introduction : Indicible et littérature jeunesse, une antinomie ?

in Peut-on tout leur dire ? Formes de l’indicible en littérature jeunesse (in press)

Conservazione e ricezione dei documenti pontifici in Italia settentrionale: il caso del monastero cistercense di Chiaravalle Milanese (secoli XII-XVI)

in Salemme, Timothy; Renault, Jean-Baptiste (Eds.) Conservation et réception des documents pontificaux par les Ordres religieux (XIe-XVe siècles). Actes du colloque international. Nancy, 12-13 décembre 2013 (in press)

Luxembourg écopostcolonial ? La nature dans les romans de la migration Mrs Haroy ou La Mémoire de la baleine de Jean Portante et Neubrasilien de Guy Helminger

in Écocritique : nouvelles territorialités (in press)

Ink and Paper in the Camp. Ego-Documents of Luxembourger Conscripts in the Soviet Captivity

in Janz, Nina; Scuto, Denis (Eds.) The Impact of War Experiences in Europe (2024)

In the paper by Inna Ganschow, the camp experience in the Soviet Union as a result of forced conscription will be treated, specifically in its artistic processing: secretly written diaries and letters by ... [more ▼]

In the paper by Inna Ganschow, the camp experience in the Soviet Union as a result of forced conscription will be treated, specifically in its artistic processing: secretly written diaries and letters by Luxembourg Wehrmacht soldiers. Contemporary historical research today calls them ego documents – private, handwritten texts of a personal nature. The range of texts to be examined in the lecture ranges from the smuggled out notes and letters that their released comrades took with them to Luxembourg, through diaries, speeches and self-made dictionaries to poems, short stories and drawings, some of which were in the camp and some immediately after the return from Tambov and other camps in the Soviet Union. The focus is on the question of dealing with the thesis of the Auschwitz concentration camp survivor Viktor Frankl, psychiatrist and neurologist from Vienna, that the meaning of camp life - logotherapy - can have a self-healing effect and increase the self-healing powers, which increases the chances of survival. [less ▲]

Self-Determination Theory Applied To Museum Website Experiences: Fulfill Visitor Needs, Increase Motivation, and Promote Engagement

in European Conference in Cognitive Ergonomics (ECCE ’23) (2023, September)

The rise of online experiences in the domain of cultural heritage offers new forms of interaction that are no longer limited by the physical presence of museums. However, sustaining online visitors’ ... [more ▼]

The rise of online experiences in the domain of cultural heritage offers new forms of interaction that are no longer limited by the physical presence of museums. However, sustaining online visitors’ engagement is challenging, and museum professionals seek to understand how to increase motivation. We conducted a user study (N = 32) of three museum websites to investigate users’ intrinsic motivations to engage with the sites through observation, questionnaires, and semi-structured interviews. Building on self- determination theory, we identified design characteristics that meet users’ psychological needs, such as autonomy, competence, and relatedness, and increase their intrinsic motivation to interact with the interface. Our results show that this could consequently lead to higher user engagement. We contribute new empirical insights into the intrinsic motivation mechanisms of museum website visitors, which have relevant implications for the design of museum websites to improve user engagement. [less ▲]

Pour une approche hydrocritique du genre épique : Les Lusiades de Camões comme méta-épopée de l’eau

in Roelens, Nathalie; Erchadi, Armand; MacLeod (Eds.) et al Water and Sea in Word and Image / L'Eau et la mer dans les textes et les images (2023, August 31)

EXPLORING THE USE OF PHONOLOGICAL FEATURES FOR PARKINSON’S DISEASE DETECTION

in Hosseini Kivanani, Nina; Vásquez-Correa, Juan Camilo; Schommer, Christoph (Eds.) et al EXPLORING THE USE OF PHONOLOGICAL FEATURES FOR PARKINSON’S DISEASE DETECTION (2023, August)

Parkinson’s disease (PD) is a neurodegenerative disorder that causes motor and non-motor symptoms. Speech impairments are one of the early symptoms of PD, but they are not always fully exploited by ... [more ▼]

Parkinson’s disease (PD) is a neurodegenerative disorder that causes motor and non-motor symptoms. Speech impairments are one of the early symptoms of PD, but they are not always fully exploited by clinicians. In this study, the use of phonological features extracted from speech data collected from Spanish-speaking patients was explored to predict PD patients from healthy subjects using phonet, which was trained on Spanish data, and PhonVoc, which was trained on English data. These features were then used to train and test several machine learning models. The XGBoost model achieved the best performance in classifying patients from HCs, with an accuracy of over 0.76. However, the model performed better when using a phonological model trained on Spanish data rather than English data. [less ▲]

Evaluation of PTP Security Controls on gPTP

in 28th IEEE International Symposium on Computers and Communications (ISCC 2023), Tunis, July 2023 (2023, July 09)

In recent years, the scientific community has been focusing on deterministic Ethernet, which has helped drive the adoption of Time-Sensitive Networking (TSN) standards. Precision Time Protocol (PTP ... [more ▼]

In recent years, the scientific community has been focusing on deterministic Ethernet, which has helped drive the adoption of Time-Sensitive Networking (TSN) standards. Precision Time Protocol (PTP), specified in IEEE1588, is a TSN standard that enables network devices to be synchronized with a degree of precision that is noticeably higher than other Ethernet synchronization protocols. Generic Precision Time Protocol (gPTP), a profile of PTP, is designed to have low latency and jitter, which makes it suitable for industrial applications. However, like PTP, gPTP does not have any built-in security measures. In this work, we assess the efficacy of additional security mechanisms that were suggested for inclusion in IEEE 1588 (PTP) 2019. The analysis consists of implementing these security mechanisms on a physical gPTP-capable testbed and evaluating them on several high-risk attacks against gPTP. [less ▲]

From Awareness to Action: Energy Literacy and Household Energy Use

in Proceedings of the 18th IAEE European Conference. Milan, 24-27 July 2023 (2023, July)

An Intrusion Detection System Against Rogue Master Attacks on gPTP

in Buscemi, Alessio; Ponaka, Manasvi; Fotouhi, Mahdi (Eds.) et al IEEE Vehicular Technology Conference (VTC2023-Spring), Florence 20-23 June 2023 (2023, July)

Due to the promise of deterministic Ethernet networking, Time Sensitive Network (TSN) standards are gaining popularity in the vehicle on-board networks sector. Among these, Generalized Precision Time ... [more ▼]

Due to the promise of deterministic Ethernet networking, Time Sensitive Network (TSN) standards are gaining popularity in the vehicle on-board networks sector. Among these, Generalized Precision Time Protocol (gPTP) allows network devices to be synchronized with a greater degree of precision than other synchronization protocols, such as Network Time Protocol (NTP). However, gPTP was developed without security measures, making it susceptible to a variety of attacks. Adding security controls is the initial step in securing the protocol. However, due to current gPTP design limitations, this countermeasure is insufficient to protect against all types of threats. In this paper, we present a novel supervised Machine Learning (ML)-based pipeline for the detection of high-risk rogue master attacks. [less ▲]

Together Yet Apart: Multimodal Representation Learning for Personalised Visual Art Recommendation

in Yilma, Bereket Abera; Leiva, Luis A. (Eds.) Proceedings of the ACM Conference on User Modeling, Adaptation and Personalization (UMAP 2023) (2023, June 26)

With the advent of digital media, the availability of art content has greatly expanded, making it increasingly challenging for individuals to discover and curate works that align with their personal ... [more ▼]

With the advent of digital media, the availability of art content has greatly expanded, making it increasingly challenging for individuals to discover and curate works that align with their personal preferences and taste. The task of providing accurate and personalised Visual Art (VA) recommendations is thus a complex one, requiring a deep understanding of the intricate interplay of multiple modalities such as images, textual descriptions, or other metadata. In this paper, we study the nuances of modalities involved in the VA domain (image and text) and how they can be effectively harnessed to provide a truly personalised art experience to users. Particularly, we develop four fusion-based multimodal VA recommendation pipelines and conduct a large-scale user-centric evaluation. Our results indicate that early fusion (i.e, joint multimodal learning of visual and textual features) is preferred over a late fusion of ranked paintings from unimodal models (state-of-the-art baselines) but only if the latent representation space of the multimodal painting embeddings is entangled. Our findings open a new perspective for a better representation learning in the VA RecSys domain. [less ▲]

The impact of executive functioning and age-related cognitive decline on distraction from pain

in Merz, Simon; Frings, Christian; Leuchtenberg, Bettina (Eds.) et al Abstracts of the 65th TeaP (2023, June 21)

Older people, suffering from pain and its consequences more often than younger people, would benefit significantly from non-pharmacological pain treatment. So far, little is known about how age affects ... [more ▼]

Older people, suffering from pain and its consequences more often than younger people, would benefit significantly from non-pharmacological pain treatment. So far, little is known about how age affects psychological pain modulation strategies. Preliminary findings hint towards a less efficient pain inhibition through cognition-based pain modulation strategies, as cognitive distraction from pain. Here, executive functions (EFs) have been considered a key factor in the age – pain relationship, with age-related cognitive decline in EFs being associated with reduced pain relief through distraction in older adults. We investigated influence of four core EFs on distraction from pain in aging. In a two-session design, healthy young (18-30 years) and older participants (60+ years) performed a Go-Nogo task, the Stroop-Color-Word-Task, the Sternberg-Task, and the Attentional Network Task. Afterwards, participants performed a pain distraction task, namely a n-Back working memory task with low and high cognitive load, during which participants received individually adjusted transdermal electrical pulse trains in non-painful and moderately painful intensities to the inner forearm. Ratings of intensity and unpleasantness were collected and stimulus-related (EF tasks) and pain-related evoked potentials were recorded with a 64-channel EEG. Unexpectedly, first analyses on the currently small sample suggest a more efficient pain relief through distraction under low relative to high cognitive load in older adults. The distraction effect was related to EFs, some of which showed age-related cognitive impairment. Our findings could lead to a better understanding how to adapt pain treatments in this population by including selective cognitive trainings and optimizing distraction task difficulty. [less ▲]

Using Emotions and Topics to Understand Online Misinformation

in Web Engineering. ICWE 2023. Lecture Notes in Computer Science, vol 13893. Springer, Cham. (2023, June 16)

Misinformation has become one of the most pressing social issues in the twenty-first century. How the combinations of emotions and topics trigger the spread of misinformation, however, still remains to be ... [more ▼]

Misinformation has become one of the most pressing social issues in the twenty-first century. How the combinations of emotions and topics trigger the spread of misinformation, however, still remains to be revealed. This study comprehensively examines misinformation and its diffusion by correlating emotions and topics. First, we examine how specific emotions and topics are combined in misinformation. Second, we identify the effects of emotions and topics on the virality of misinformation. Finally, we further explore how to employ users’ topic preferences and emotion reactions to detect and analyze echo chambers in misinformation cascades. The findings can help construct a detailed and consistent understanding on misinformation diffusion in terms of emotions and topics. Potential practical implications are also provided to prevent the spread of misinformation online. [less ▲]

Personal Informatics at the Office: User-Driven, Situated Sensor Kits in the Workplace

in CHIWORK '23: Proceedings of the 2nd Annual Meeting of the Symposium on Human-Computer Interaction for Work (2023, June)

Workplaces are increasingly leveraging data-driven technological interventions to optimize employee productivity, health, and wellbeing. Yet employees are rarely involved in designing these initiatives ... [more ▼]

Workplaces are increasingly leveraging data-driven technological interventions to optimize employee productivity, health, and wellbeing. Yet employees are rarely involved in designing these initiatives, nor have access to the data collected to act upon it. Building on approaches from personal informatics, we investigate the use of user-driven, open-ended sensor kits in an office context. We conducted a 3-week field study, deploying a research probe at a workplace (N=5). Findings show that users explored aspects meaningful to them yet highlight discrepancies between the envisioned self-tracking goals and participants’ practices. Regarding sensors’ open-endedness, a balance between the burden of data collection and the value derived from it appeared critical. We contribute new insights into how an open-ended sensor kit can be designed to support self-tracking practices in the underexplored context of office work. We discuss implications for the use of personal informatics at the office and highlight opportunities for future research. [less ▲]

Managing Fahsionable Organizing Visions: Evidence From the European Blockchain Services Infrastructure

in Proceedings of the Thirty-first European Conference on Information Systems (2023, June)

Grand visions for organizational transformation increasingly build on fashionable information technologies. Organizational leaders may be tempted to adopt these visions due the high degree of legitimacy ... [more ▼]

Grand visions for organizational transformation increasingly build on fashionable information technologies. Organizational leaders may be tempted to adopt these visions due the high degree of legitimacy and mobilization they afford. However, their fashionable nature makes adoption risky. In this paper, we explore how organizations can manage this risk and successfully navigate the adoption of fashionable organizing visions. Specifically, we track how over the last five years the European Blockchain Partnership adopted a self-sovereign identity organizing vision based on blockchain. We find that successful adoption requires dynamic coupling and decoupling between vision and IT – both on a discursive and the material levels. Moreover, it requires effective management of ‘sensegiving’ and ‘sensebreaking’ by the innovation community. [less ▲]

Modelling Attention Levels with Ocular Responses in a Speech-in-Noise Recall Task

in ETRA '23: Proceedings of the 2023 Symposium on Eye Tracking Research and Applications (2023, May 30)

We applied state-space modelling technique to estimate the cognitive workload of a speech-in-noise (SIN) recall task, based on participants’ oculo-motor responses to speech signals. We estimated common ... [more ▼]

We applied state-space modelling technique to estimate the cognitive workload of a speech-in-noise (SIN) recall task, based on participants’ oculo-motor responses to speech signals. We estimated common latent attention levels in 15 time bins and observed temporal changes between pupillary dilations and saccade frequencies, given that the both conditions were independent. We also compared two speech type factors (natural vs. synthetic) and three levels of signal-to-noise (-1dB, -3dB, and -5dB) using the estimated parameter distribution. The comparison of experimental factors provided us with insights into differences in participants’ processing of spoken information during a SIN recall task. [less ▲]

Many-Objective Reinforcement Learning for Online Testing of DNN-Enabled Systems

in 45th International Conference on Software Engineering (ICSE ’23) (2023, May)

Deep Neural Networks (DNNs) have been widely used to perform real-world tasks in cyber-physical systems such as Autonomous Driving Systems (ADS). Ensuring the correct behavior of such DNN-Enabled Systems ... [more ▼]

Deep Neural Networks (DNNs) have been widely used to perform real-world tasks in cyber-physical systems such as Autonomous Driving Systems (ADS). Ensuring the correct behavior of such DNN-Enabled Systems (DES) is a crucial topic. Online testing is one of the promising modes for testing such systems with their application environments (simulated or real) in a closed loop, taking into account the continuous interaction between the systems and their environments. However, the environmental variables (e.g., lighting conditions) that might change during the systems' operation in the real world, causing the DES to violate requirements (safety, functional), are often kept constant during the execution of an online test scenario due to the two major challenges: (1) the space of all possible scenarios to explore would become even larger if they changed and (2) there are typically many requirements to test simultaneously. In this paper, we present MORLOT (Many-Objective Reinforcement Learning for Online Testing), a novel online testing approach to address these challenges by combining Reinforcement Learning (RL) and many-objective search. MORLOT leverages RL to incrementally generate sequences of environmental changes while relying on many-objective search to determine the changes so that they are more likely to achieve any of the uncovered objectives. We empirically evaluate MORLOT using CARLA, a high-fidelity simulator widely used for autonomous driving research, integrated with Transfuser, a DNN-enabled ADS for end-to-end driving. The evaluation results show that MORLOT is significantly more effective and efficient than alternatives with a large effect size. In other words, MORLOT is a good option to test DES with dynamically changing environments while accounting for multiple safety requirements. [less ▲]

AI-based Question Answering Assistance for Analyzing Natural-language Requirements

in In Proceedings of the 45th International Conference on Software Engineering (ICSE'23), Melbourne 14-20 May 2023 (2023, May)

Abstract—By virtue of being prevalently written in natural language (NL), requirements are prone to various defects, e.g., inconsistency and incompleteness. As such, requirements are frequently subject to ... [more ▼]

Abstract—By virtue of being prevalently written in natural language (NL), requirements are prone to various defects, e.g., inconsistency and incompleteness. As such, requirements are frequently subject to quality assurance processes. These processes, when carried out entirely manually, are tedious and may further overlook important quality issues due to time and budget pressures. In this paper, we propose QAssist – a question-answering (QA) approach that provides automated assistance to stakeholders, including requirements engineers, during the analysis of NL requirements. Posing a question and getting an instant answer is beneficial in various quality-assurance scenarios, e.g., incompleteness detection. Answering requirements-related questions automatically is challenging since the scope of the search for answers can go beyond the given requirements specification. To that end, QAssist provides support for mining external domain-knowledge resources. Our work is one of the first initiatives to bring together QA and external domain knowledge for addressing requirements engineering challenges. We evaluate QAssist on a dataset covering three application domains and containing a total of 387 question-answer pairs. We experiment with state-of-the-art QA methods, based primarily on recent large-scale language models. In our empirical study, QAssist localizes the answer to a question to three passages within the requirements specification and within the external domain-knowledge resource with an average recall of 90.1% and 96.5%, respectively. QAssist extracts the actual answer to the posed question with an average accuracy of 84.2%. Index Terms—Natural-language Requirements, Question Answering (QA), Language Models, Natural Language Processing (NLP), Natural Language Generation (NLG), BERT, T5. [less ▲]

FlakyCat: Predicting Flaky Tests Categories using Few-Shot Learning

in FlakyCat: Predicting Flaky Tests Categories using Few-Shot Learning (2023, May)

Flaky tests are tests that yield different outcomes when run on the same version of a program. This non-deterministic behaviour plagues continuous integration with false signals, wasting developers’ time ... [more ▼]

Flaky tests are tests that yield different outcomes when run on the same version of a program. This non-deterministic behaviour plagues continuous integration with false signals, wasting developers’ time and reducing their trust in test suites. Studies highlighted the importance of keeping tests flakiness-free. Recently, the research community has been pushing towards the detection of flaky tests by suggesting many static and dynamic approaches. While promising, those approaches mainly focus on classifying tests as flaky or not and, even when high performances are reported, it remains challenging to understand the cause of flakiness. This part is crucial for researchers and developers that aim to fix it. To help with the comprehension of a given flaky test, we propose FlakyCat, the first approach to classify flaky tests based on their root cause category. FlakyCat relies on CodeBERT for code representation and leverages Siamese networks to train a multi-class classifier. We train and evaluate FlakyCat on a set of 451 flaky tests collected from open-source Java projects. Our evaluation shows that FlakyCat categorises flaky tests accurately, with an F1 score of 73%. Furthermore, we investigate the performance of our approach for each category, revealing that Async waits, Unordered collections and Time-related flaky tests are accurately classified, while Concurrency-related flaky tests are more challenging to predict. Finally, to facilitate the comprehension of FlakyCat’s predictions, we present a new technique for CodeBERT-based model interpretability that highlights code statements influencing the categorization. [less ▲]

Anwendung einer Kombination von KI-Methoden für die automatische Fehlererkennung und -diagnose an raumlufttechnischen Anlagen

in TGA-Kongress 2023 - Kongressband (2023, May)

Die Grenzen aufgezeigt:Technische Innovation und räumliche Abstraktion am Beispiel früher Landkarten der Grenzregion zwischen dem Herzogtum Luxemburg und dem Kurfürstentum Trier

in Schröder, Lina; Wegewitz, Markus (Eds.) Raum- und Grenzkonzeptionen in der Erforschung europäischer Regionen (2023, April 13)

Die Ausbildung und Verfestigung der kurtrierischen und luxemburgischen Landesherrschaften war im 14. Jahrhundert weitgehend zum Abschluss gekommen. Die Transformation vom Personenverbands- zum ... [more ▼]

Die Ausbildung und Verfestigung der kurtrierischen und luxemburgischen Landesherrschaften war im 14. Jahrhundert weitgehend zum Abschluss gekommen. Die Transformation vom Personenverbands- zum Flächenstaat frühneuzeitlicher Prägung hatte die Ausbildung einer zunehmend deutlicheren Grenze zwischen beiden Territorien zur Folge. Ebenso formierte sich auch eine Grenze im Grenzraum mit Frankreich und Lothringen. Die vereinfachende Darstellung komplexer teils überlagerter Grenzzonen in Form von abstrahierenden Linien musste von den zeitgenössischen Kartographen jedoch erst noch entwickelt werden. Die älteste regionale Karte mit einer angedeuteten partiellen Grenzmarkierung stammt aus dem Jahr 1555. Eine zunehmende Professionalisierung der Kartographie gelang ab der zweiten Hälfte des 16. Jahrhunderts durch Landesaufnahmen, initiiert von den jeweiligen Landesherren. Die Intention der Auftraggeber war dabei ähnlich: einerseits sollte das jeweilige Territorium durch die Karte möglichst als geschlossen beherrschter Raum dargestellt werden, andererseits galt es, die bisher nur verbal beschriebenen teils strittigen Grenzen als abstrakte Linien deutlich sichtbar zu machen. Die Karten der Landesaufnahmen waren zunächst geheim, dennoch fanden sie bereits nach wenigen Jahren Eingang in die Atlanten von Ortelius, de Jode und Mercator. Diese beeinflussten wiederum die Karten der Region in den späteren Atlanten der niederländischen, französischen und süddeutschen Kartenverleger. Der Beitrag beschreibt, ab wann und in welcher Form Grenzen in frühen Karten (16.-18. Jahrhundert) dargestellt wurden. Besonders in den Blick genommen wird der Prozess der Ausbildung von Linien zur abstrakten Darstellung unklarer, teils strittiger Grenzräume sowie die zunehmende Professionalisierung und Genauigkeit in der kartographischen Darstellung durch Vermessungen im Feld. [less ▲]

Assessing the Impact of Attacks on an Automotive Ethernet Time Synchronization Testbed

in Fotouhi, Mahdi; Buscemi, Alessio; Boualouache, Abdelwahab (Eds.) et al 2023 IEEE Vehicular Networking Conference (VNC), Istanbul 26-28 April 2023 (2023, April)

Time Sensitive Network (TSN) standards are gaining traction in the scientific community and automotive Original Equipment Manufacturers (OEMs) due their promise of deterministic Ethernet networking. Among ... [more ▼]

Time Sensitive Network (TSN) standards are gaining traction in the scientific community and automotive Original Equipment Manufacturers (OEMs) due their promise of deterministic Ethernet networking. Among these standards, Generalized Precision Time Protocol (gPTP) - IEEE 802.1AS - allows network devices to be synchronized with a precision far higher than other synchronization standards, such as Network Time Protocol (NTP). gPTP is a profile of Precision Time Protocol (PTP) which, due to its robustness to delay variations, has been designated for automotive applications. Nonetheless, gPTP was designed without security controls, which makes it vulnerable to a number of attacks. This work reveals a critical vulnerability caused by a common implementation practice that opens the door to spoofing attacks on gPTP. To assess the impact of this vulnerability, we built two real gPTP-capable testbeds. Our results show high risks of this vulnerability destabilizing the system functionality. [less ▲]

The Elements of Visual Art Recommendation: Learning Latent Semantic Representations of Paintings

in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23) (2023, April)

Artwork recommendation is challenging because it requires understanding how users interact with highly subjective content, the complexity of the concepts embedded within the artwork, and the emotional and ... [more ▼]

Artwork recommendation is challenging because it requires understanding how users interact with highly subjective content, the complexity of the concepts embedded within the artwork, and the emotional and cognitive reflections they may trigger in users. In this paper, we focus on efficiently capturing the elements (i.e., latent semantic relationships) of visual art for personalized recommendation. We propose and study recommender systems based on textual and visual feature learning techniques, as well as their combinations. We then perform a small-scale and a large-scale user-centric evaluation of the quality of the recommendations. Our results indicate that textual features compare favourably with visual ones, whereas a fusion of both captures the most suitable hidden semantic relationships for artwork recommendation. Ultimately, this paper contributes to our understanding of how to deliver content that suitably matches the user's interests and how they are perceived. [less ▲]

Visual Narratives of the Great War in Luxembourg: One Hundred Years of History Manuals

in Morin, Denis; Prévot, Cédric (Eds.) Guerres en images, images de guerres : L’illustration des conflits en Europe dans les manuels d’histoire (2023, April)

Internships in Times of Crisis: Collaborative Production of Instructional Videos at a Distance

in Willemse, Martijn (Ed.) EAPRIL 2022 CONFERENCE PROCEEDINGS (2023, March)

The Bachelor in Educational Sciences (BScE) at the University of Luxembourg offers a thorough and demanding teacher training program that combines academic and practical knowledge. As in many other ... [more ▼]

The Bachelor in Educational Sciences (BScE) at the University of Luxembourg offers a thorough and demanding teacher training program that combines academic and practical knowledge. As in many other initial teacher training programs, internships are a key part of each semester in the BScE. In the face of the COVID-19 health crisis, this essential part of our teacher training program could not be maintained. Indeed, the schools were closed, and the pupils were taught at a distance by their teachers. We therefore had to quickly innovate and set up alternative learning activities that best met the objectives of the internships. We thus asked our students to design and produce educational videos, in dyads, for the country's schools. The aim was to enable our students to develop the necessary skills to produce such learning resources and to make them available to schools via the Internet. We will describe, analyse, and evaluate the solution we had to urgently put in place and the videos that were produced as a result. We will also discuss possible lessons learned that might lead to adaptations in our training program. [less ▲]

User Requirement Analysis for a Real-Time NLP-Based Open Information Retrieval Meeting Assistant

in Alcaraz, Benoît; Hosseini Kivanani, Nina; Najjar, Amro (Eds.) et al Advances in Information Retrieval (2023, March)

Meetings are recurrent organizational tasks intended to drive progress in an interdisciplinary and collaborative manner. They are, however, prone to inefficiency due to factors such as differing knowledge ... [more ▼]

Meetings are recurrent organizational tasks intended to drive progress in an interdisciplinary and collaborative manner. They are, however, prone to inefficiency due to factors such as differing knowledge among participants. The research goal of this paper is to design a recommendation-based meeting assistant that can improve the efficiency of meetings by helping to contextualize the information being discussed and reduce distractions for listeners. Following a Wizard-of-Oz setup, we gathered user feedback by thematically analyzing focus group discussions and identifying this kind of system’s key challenges and requirements. The findings point to shortcomings in contextualization and raise concerns about distracting listeners from the main content. Based on the findings, we have developed a set of design recommendations that address context, interactivity and personalization issues. These recommendations could be useful for developing a meeting assistant that is tailored to the needs of meeting participants, thereby helping to optimize the meeting experience. [less ▲]

Performance Analysis and Benchmarking of a Temperature Downscaling Deep Learning Model

in 31st Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, Naples, Italy 1-3 March 2023 (2023, March)

We are presenting here a detailed analysis and performance characterization of a statistical temperature downscaling application used in the MAELSTROM EuroHPC project. This application uses a deep ... [more ▼]

We are presenting here a detailed analysis and performance characterization of a statistical temperature downscaling application used in the MAELSTROM EuroHPC project. This application uses a deep learning methodology to convert low-resolution atmospheric temperature states into high-resolution. We have performed in-depth profiling and roofline analysis at different levels (Operators, Training, Distributed Training, Inference) of the downscaling model on different hardware architectures (Nvidia V100 & A100 GPUs). Finally, we compare the training and inference cost of the downscaling model with various cloud providers. Our results identify the model bottlenecks which can be used to enhance the model architecture and determine hardware configuration for efficiently utilizing the HPC. Furthermore, we provide a comprehensive methodology for in-depth profiling and benchmarking of the deep learning models. [less ▲]

Negative Results of Fusing Code and Documentation for Learning to Accurately Identify Sensitive Source and Sink Methods An Application to the Android Framework for Data Leak Detection

in 30th IEEE International Conference on Software Analysis, Evolution and Reengineering (2023, March)

Apps on mobile phones manipulate all sorts of data, including sensitive data, leading to privacy related concerns. Recent regulations like the European GDPR provide rules for the processing of personal ... [more ▼]

Apps on mobile phones manipulate all sorts of data, including sensitive data, leading to privacy related concerns. Recent regulations like the European GDPR provide rules for the processing of personal and sensitive data, like that no such data may be leaked without the consent of the user. Researchers have proposed sophisticated approaches to track sensitive data within mobile apps, all of which rely on specific lists of sensitive source and sink methods. The data flow analysis results greatly depend on these lists' quality. Previous approaches either used incomplete hand-written lists and quickly became outdated or relied on machine learning. The latter, however, leads to numerous false positives, as we show. This paper introduces CoDoC that aims to revive the machine-learning approach to precisely identify the privacy-related source and sink API methods. In contrast to previous approaches, CoDoC uses deep learning techniques and combines the source code with the documentation of API methods. Firstly, we propose novel definitions that clarify the concepts of taint analysis, source, and sink methods. Secondly, based on these definitions, we build a new ground truth of Android methods representing sensitive source, sink, and neither methods that will be used to train our classifier. We evaluate CoDoC and show that, on our validation dataset, it achieves a precision, recall, and F1 score of 91%, outperforming the state-of-the-art SuSi. However, similarly to existing tools, we show that in the wild, i.e., with unseen data, CoDoC performs poorly and generates many false-positive results. Our findings suggest that machine-learning models for abstract concepts such as privacy fail in practice despite good lab results. To encourage future research, we release all our artifacts to the community. [less ▲]

Bringing Movement to Digital Tasks at the Office: Designing an Acceptably Active Interface Interaction for Sending Emails

in Proceedings of the Seventeenth International Conference on Tangible, Embedded, and Embodied Interaction TEI'23 (2023, February)

While working on a computer typically involves sitting for prolonged periods of time, sedentary work routines are associated with numerous health issues. To address this societal concern, existing ... [more ▼]

While working on a computer typically involves sitting for prolonged periods of time, sedentary work routines are associated with numerous health issues. To address this societal concern, existing solutions trigger physical activity as a break from work, rather than a part of it. In this research, we explore a vision for physically active ways of working, by transforming mundane digital tasks into physically active ones. As a research artifact and design exemplar, we present A2-I2, an innovative tangible system for sending emails. After loading their email onto a physical “letter” token, office workers must walk to a physical mailbox located in the office space. Understanding what design qualities influence the experience and acceptability of such systems is a necessary step toward the design of acceptably active interface interactions. We report on a preliminary user test with 8 participants. With this project, we aim to inspire future tangible and embodied systems addressing the timely issue of sedentary behavior at work. [less ▲]

Federated Learning for Credit Risk Assessment

in Proceedings of the 56th Hawaii International Conference on System Sciences (2023, January 03)

Credit risk assessment is a standard procedure for financial institutions (FIs) when estimating their credit risk exposure. It involves the gathering and processing quantitative and qualitative datasets ... [more ▼]

Credit risk assessment is a standard procedure for financial institutions (FIs) when estimating their credit risk exposure. It involves the gathering and processing quantitative and qualitative datasets to estimate whether an individual or entity will be able to make future required payments. To ensure effective processing of this data, FIs increasingly use machine learning methods. Large FIs often have more powerful models as they can access larger datasets. In this paper, we present a Federated Learning prototype that allows smaller FIs to compete by training in a cooperative fashion a machine learning model which combines key data derived from several smaller datasets. We test our prototype on an historical mortgage dataset and empirically demonstrate the benefits of Federated Learning for smaller FIs. We conclude that smaller FIs can expect a significant performance increase in their credit risk assessment models by using collaborative machine learning. [less ▲]

Astute Approach to Handling Memory Layouts of Regular Data Structures

in Algorithms and Architectures for Parallel Processing (2023, January)

Programmers of high-performance applications face many challenging aspects of contemporary hardware architectures. One of the critical aspects is the efficiency of memory operations which is affected not ... [more ▼]

Programmers of high-performance applications face many challenging aspects of contemporary hardware architectures. One of the critical aspects is the efficiency of memory operations which is affected not only by the hardware parameters such as memory throughput or cache latency but also by the data-access patterns, which may influence the utilization of the hardware, such as re-usability of the cached data or coalesced data transactions. Therefore, a performance of an algorithm can be highly impacted by the layout of its data structures or the order of data processing which may translate into a more or less optimal sequence of memory operations. These effects are even more pronounced on highly-parallel platforms, such as GPUs, which often employ specific execution models (lock-step) or memory models (shared memory). In this work, we propose a modern, astute approach for managing and implementing memory layouts with first-class structures that is very efficient and straightforward. This approach was implemented in Noarr, a GPU-ready portable C++ library that utilizes generic programming, functional design, and compile-time computations to allow the programmer to specify and compose data structure layouts declaratively while minimizing the indexing and coding overhead. We describe the main principles on code examples and present a performance evaluation that verifies our claims regarding its efficiency. [less ▲]

Integrated Access and Backhaul via Satellites

in IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Toronto, Canada, Sept. 2023 (2023)

Efficient Hessian-based DNN Optimization via Chain-Rule Approximation

in Proceedings of the 6th Joint International Conference on Data Science Management of Data (10th ACM IKDD CODS and 28th COMAD) (2023)

Learning non use-case specific models has been shown to be a challenging task in Deep Learning (DL). Hyperparameter tuning requires long training sessions that have to be restarted any time the network or ... [more ▼]

Learning non use-case specific models has been shown to be a challenging task in Deep Learning (DL). Hyperparameter tuning requires long training sessions that have to be restarted any time the network or the dataset changes and are not affordable by most stakeholders in industry and research. Many attempts have been made to justify and understand the source of the use-case specificity that distinguishes DL problems. To this date, second-order optimization methods have been partially shown to be effective in some cases but have not been sufficiently investigated in the context of learning and optimization. In this work, we present a chain rule for the efficient approximation of the Hessian matrix (i.e., the second-order derivatives) of the weights across the layers of a Deep Neural Network (DNN). We show the application of our approach for weight optimization during DNN training, as we believe that this is a step that particularly suffers from the enormous variety of the optimizers provided by state-of-the-art libraries such as Keras and PyTorch. We demonstrate—both theoretically and empirically—the improved accuracy of our approximation technique and that the Hessian is a useful diagnostic tool which helps to more rigorously optimize training. Our preliminary experiments prove the efficiency as well as the improved convergence of our approach which both are crucial aspects for DNN training. [less ▲]

A Comparative Study of Sentence Embeddings for Unsupervised Extractive Multi-document Summarization

in Artificial Intelligence and Machine Learning (2023)

Obtaining large-scale and high-quality training data for multi-document summarization (MDS) tasks is time-consuming and resource-intensive, hence, supervised models can only be applied to limited domains ... [more ▼]

Obtaining large-scale and high-quality training data for multi-document summarization (MDS) tasks is time-consuming and resource-intensive, hence, supervised models can only be applied to limited domains and languages. In this paper, we introduce unsupervised extractive methods for both generic and query-focused MDS tasks, intending to produce a relevant summary from a collection of documents without using labeled training data or domain knowledge. More specifically, we leverage the potential of transfer learning from recent sentence embedding models to encode the input documents into rich semantic representations. Moreover, we use a coreference resolution system to resolve the broken pronominal coreference expressions in the generated summaries, aiming to improve their cohesion and textual quality. Furthermore, we provide a comparative analysis of several existing sentence embedding models in the context of unsupervised extractive multi-document summarization. Experiments on the standard DUC'2004-2007 datasets demonstrate that the proposed methods are competitive with previous unsupervised methods and are even comparable to recent supervised deep learning-based methods. The empirical results also show that the SimCSE embedding model, based on contrastive learning, achieves substantial improvements over strong sentence embedding models. Finally, the newly involved coreference resolution method is proven to bring a noticeable improvement to the unsupervised extractive MDS task. [less ▲]

Federated Learning for Zero-Day Attack Detection in 5G and Beyond V2X Networks

in IEEE ICC 2023 - IEEE International Conference on Communications (2023)

Deploying Connected and Automated Vehicles (CAVs) on top of 5G and Beyond networks (5GB) makes them vulnerable to increasing vectors of security and privacy attacks. In this context, a wide range of ... [more ▼]

Deploying Connected and Automated Vehicles (CAVs) on top of 5G and Beyond networks (5GB) makes them vulnerable to increasing vectors of security and privacy attacks. In this context, a wide range of advanced machine/deep learning-based solutions have been designed to accurately detect security attacks. Specifically, supervised learning techniques have been widely applied to train attack detection models. However, the main limitation of such solutions is their inability to detect attacks different from those seen during the training phase, or new attacks, also called zero-day attacks. Moreover, training the detection model requires significant data collection and labeling, which increases the communication overhead, and raises privacy concerns. To address the aforementioned limits, we propose in this paper a novel detection mechanism that leverages the ability of the deep auto-encoder method to detect attacks relying only on the benign network traffic pattern. Using federated learning, the proposed intrusion detection system can be trained with large and diverse benign network traffic, while preserving the CAVs’ privacy, and minimizing the communication overhead. The in-depth experiment on a recent network traffic dataset shows that the proposed system achieved a high detection rate while minimizing the false positive rate, and the detection delay. [less ▲]

NGSO-To-GSO Satellite Interference Detection Based on Autoencoder

in IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Toronto, Canada, Sept. 2023 (2023)