Publications

2021

Association between estimated whole-brain radiofrequency electromagnetic fields dose and cognitive function in preadolescents and adolescents
- Cabré-Riera Alba
- van Wel Luuk
- Liorni Ilaria
- Thielens Arno
- Birks Laura Ellen
- Pierotti Livia
- Joseph Wout
- González-Safont Llúcia
- Ibarluzea Jesús
- Ferrero Amparo
- Huss Anke
- Wiart Joe
- Santa-Marina Loreto
- Torrent Maties
- Vrijkotte Tanja
- Capstick Myles
- Vermeulen Roel
- Vrijheid Martine
- Cardis Elisabeth
- Röösli Martin
- Guxens Mònica
International Journal of Hygiene and Environmental Health, Elsevier, 2021, 231, pp.113659. (10.1016/j.ijheh.2020.113659)
DOI : 10.1016/j.ijheh.2020.113659
Self-improving system integration: Mastering continuouschange
- Bellman Kirstie
- Botev Jean F
- Diaconescu Ada
- Esterle Lukas
- Gruhl Christian
- Landauer Christopher
- Lewis Peter R.
- Nelson Phyllis
- Pournaras Evangelos
- Stein Anthony
- Tomforde Sven
Future Generation Computer Systems, Elsevier, 2021.
Risks and security of internet and systems
- Garcia‐alfaro Joaquin
- Leneutre Jean
- Cuppens Nora
- Yaich Reda
, 2021, 12528, pp.xi-378. This book constitutes the proceedings of the 15th International Conference on Risks and Security of Internet and Systems, CRiTIS 2020, which took place during November 4-6, 2020. The conference was originally planned to take place in Paris, France, but had to change to an online format due to the COVID-19 pandemic. The 16 full and 7 short papers included in this volume were carefully reviewed and selected from 44 submissions. In addition, the book contains one invited talk in full paper length. The papers were organized in topical sections named: vulnerabilities, attacks and intrusion detection; TLS, openness and security control; access control, risk assessment and security knowledge; risk analysis, neural networks and Web protection; infrastructure security and malware detection. (10.1007/978-3-030-68887-5)
DOI : 10.1007/978-3-030-68887-5
Depth for Curve Data and Applications
- de Micheaux Pierre Lafaye
- Mozharovskyi Pavlo
- Vimond Myriam
Journal of the American Statistical Association, Taylor & Francis, 2021, 116 (536), pp.1881-1897. In 1975, John W. Tukey defined statistical data depth as a function that determines the centrality of an arbitrary point with respect to a data cloud or to a probability measure. During the last decades, this seminal idea of data depth evolved into a powerful tool proving to be useful in various fields of science. Recently, extending the notion of data depth to the functional setting attracted a lot of attention among theoretical and applied statisticians. We go further and suggest a notion of data depth suitable for data represented as curves, or trajectories, which is independent of the parameterization. We show that our curve depth satisfies theoretical requirements of general depth functions that are meaningful for trajectories. We apply our methodology to diffusion tensor brain images and also to pattern recognition of handwritten digits and letters. Supplementary materials for this article are available online. (10.1080/01621459.2020.1745815)
DOI : 10.1080/01621459.2020.1745815
Optimization of wireless sensor networks deployment with coverage and connectivity constraints
- Elloumi Sourour
- Hudry Olivier
- Marie Estel
- Martin Agathe
- Plateau Agnès
- Rovedakis Stephane
Annals of Operations Research, Springer Verlag, 2021, 298 (1-2), pp.183-206. Wireless sensor networks have been widely deployed in the last decades to provide various services, like environmental monitoring or object tracking. Such a network is composed of a set of sensor nodes which are used to sense and transmit collected information to a base station. To achieve this goal, two properties have to be guaranteed: (i) the sensor nodes must be placed such that the whole environment of interest (represented by a set of targets) is covered, and (ii) every sensor node can transmit its data to the base station (through other sensor nodes). In this paper, we consider the Minimum Connected k-Coverage (MCkC) problem, where a positive integer k ≥ 1 defines the coverage multiplicity of the targets. We propose two mathematical programming formulations for the MCkC problem on square grid graphs and random graphs. We compare them to a recent model proposed by (Rebai et al 2015). We use a standard mixed integer linear programming solver to solve several instances with different formulations. In our results, we point out the quality of the LP-bound of each formulation as well as the total CPU time or the proportion of solved instances to optimality within a given CPU time. (10.1007/s10479-018-2943-7)
DOI : 10.1007/s10479-018-2943-7
A Stochastic Geometry Approach to EMF Exposure Modeling
- Gontier Quentin
- Petrillo Lucas
- Rottenberg Francois
- Horlin Francois
- Wiart Joe
- Oestges Claude
- de Doncker Philippe
IEEE Access, IEEE, 2021, 9, pp.91777-91787. (10.1109/ACCESS.2021.3091804)
DOI : 10.1109/ACCESS.2021.3091804
Optical injection of mid-infrared extreme events in unilaterally coupled quantum cascade lasers
- Spitz Olivier
- Herdt Andreas
- Elsassaer Wolfgang
- Grillot Frédéric
, 2021.
Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases
- Weikum Gerhard
- Dong Xin Luna
- Razniewski Simon
- Suchanek Fabian M.
, 2021, 10 (2-4), pp.108-490. Equipping machines with comprehensive knowledge of the world's entities and their relationships has been a long-standing goal of AI. Over the last decade, large-scale knowledge bases, also known as knowledge graphs, have been automatically constructed from web contents and text sources, and have become a key asset for search engines. This machine knowledge can be harnessed to semantically interpret textual phrases in news, social media and web tables, and contributes to question answering, natural language processing and data analytics. This article surveys fundamental concepts and practical methods for creating and curating large knowledge bases. It covers models and methods for discovering and canonicalizing entities and their semantic types and organizing them into clean taxonomies. On top of this, the article discusses the automatic extraction of entity-centric properties. To support the long-term life-cycle and the quality assurance of machine knowledge, the article presents methods for constructing open schemas and for knowledge curation. Case studies on academic projects and industrial knowledge graphs complement the survey of concepts and methods. (10.1561/1900000064)
DOI : 10.1561/1900000064
Feature Clustering for Support Identification in Extreme Regions
- Jalalzai Hamid
- Leluc Rémi
Proceedings of Machine Learning Research, PMLR, 2021, 139, pp.4733-4743. Understanding the complex structure of multivariate extremes is a major challenge in various fields from portfolio monitoring and environmental risk management to insurance. In the framework of multivariate Extreme Value Theory, a common characterization of extremes' dependence structure is the angular measure. It is a suitable measure to work in extreme regions as it provides meaningful insights concerning the subregions where extremes tend to concentrate their mass. The present paper develops a novel optimization-based approach to assess the dependence structure of extremes. This support identification scheme rewrites as estimating clusters of features which best capture the support of extremes. The dimension reduction technique we provide is applied to statistical learning tasks such as feature clustering and anomaly detection. Numerical experiments provide strong empirical evidence of the relevance of our approach.
Maximizing the Number of Scheduled Lightpath Demands in Optical Networks by Conflict Graphs
- Hudry Olivier
International Journal of Mathematics, Statistics and Operations Research, Academic Research Foundations, 2021.
Automated neurosurgical stereotactic planning for intraoperative use: a comprehensive review of the literature and perspectives
- Zanello Marc
- Carron Romain
- Peeters Sophie
- Gori Pietro
- Roux Alexandre
- Bloch Isabelle
- Oppenheim Catherine
- Pallud Johan
Neurosurgical Review, 2021, 44, pp.867-888.
Sequence-to-Sequence Predictive Model: From Prosody To Communicative Gestures
- Yunus Fajrian
- Clavel Chloé
- Pelachaud Catherine
, 2021. Communicative gestures and speech acoustic are tightly linked. Our objective is to predict the timing of gestures according to the acoustic. That is, we want to predict when a certain gesture occurs. We develop a model based on a recurrent neural network with attention mechanism. The model is trained on a corpus of natural dyadic interaction where the speech acoustic and the gesture phases and types have been annotated. The input of the model is a sequence of speech acoustic and the output is a sequence of gesture classes. The classes we are using for the model output is based on a combination of gesture phases and gesture types. We use a sequence comparison technique to evaluate the model performance. We find that the model can predict better certain gesture classes than others. We also perform ablation studies which reveal that fundamental frequency is a relevant feature for gesture prediction task. In another sub-experiment, we find that including eyebrow movements as acting as beat gesture improves the performance. Besides, we also find that a model trained on the data of one given speaker also works for the other speaker of the same conversation. We also perform a subjective experiment to measure how respondents judge the naturalness, the time consistency, and the semantic consistency of the generated gesture timing of a virtual agent. Our respondents rate the output of our model favorably.
Adaptation Mechanisms in Human-Agent Interaction: Effects on User's Impressions and Engagement
- Biancardi Beatrice
- Dermouche Soumia
- Pelachaud Catherine
Frontiers in Computer Science, Lausanne: Frontiers Media SA, 2021. Adaptation is a key mechanism in human-human interaction. In our work, we aim at endowing embodied conversational agents with the ability to adapt their behaviour when interacting with a human interlocutor. With the goal to better understand what are the main challenges concerning adaptive agents, we investigated the effects on user's experience of three adaptation models for a virtual agent. The adaptation mechanisms performed by the agent take into account user's reaction and learn how to adapt on the fly during the interaction. Agent's adaptation is realised at several levels (i.e., at behavioural, conversational and signal level) and focuses on improving user's experience along different dimensions (i.e., user's impressions and engagement). In our first two studies, we aim to learn agent's multi-modal behaviours and conversational strategies to optimise dynamically user's engagement and impressions of the agent, by taking them as input during the learning process. In our third study, our model takes as input both the user's and the agent's past behaviour and predicts the agent's next behaviour. Our adaptation models have been evaluated through experimental studies sharing the same interacting scenario, with the agent playing the role of a virtual museum guide. These studies showed an impact of the adaptation mechanisms on user's experience of the interaction and their perception of the agent. Interacting with an adaptive agent vs a non-adaptive agent tended to be more positively perceived. Finally, the effects of people's a-priori about virtual agents found in our studies highlight the importance to take into account user's expectancies in human-agent interaction.
Modeling Imprecise and Bipolar Algebraic and Topological Relations using Morphological Dilations
- Bloch Isabelle
Mathematical Morphology - Theory and Applications, De Gruyter, 2021, 5 (1), pp.1-20. (10.1515/mathm-2020-0107)
DOI : 10.1515/mathm-2020-0107
Mathematical Morphology and Spatial Reasoning: Fuzzy and Bipolar Setting
- Bloch Isabelle
TWMS Journal of Pure and Applied Mathematics, TWMS : Turkic World Mathematical Society, 2021, 12 (1), pp.104-125.
EXPERIMENTAL COMPARISON OF REGISTRATION METHODS FOR MULTISENSOR SAR-OPTICAL DATA
- Pinel-Puysségur Béatrice
- Maggiolo Luca
- Roux Michel
- Gasnier Nicolas
- Solarna David
- Moser Gabriele
- Serpico Sebastiano B
- Tupin Florence
, 2021. Synthetic aperture radar (SAR) and optical satellite image registration is a field that developed in the last decades and gave rise to a great number of approaches. The registration process is composed of several steps: feature definition, feature comparison and optimization of a geometric transformation between the images. Feature definition can be done using simple traditional filtering or more complex deep learning (DL) methods. In this paper, two traditional approaches and a DL approach are compared. One can then wonder if the complexity of DL is worth to address the registration task. The aim of this paper is to quantitatively compare approaches rooted in distinct methodological areas on two common datasets with different resolutions. The comparison suggests that, although more complex, the DL approach is more precise than traditional methods.
Slicing-Based Offloading in Vehicular Edge Computing
- Berri Sara
- Hejja Khaled
- Labiod Houda
, 2021.
KM Learning for Millimeter-Wave Beam Alignment and Tracking: Predictability and Interpretability
- Ghauch Hadi
- Duan Qiyou
- Kim Taejoon
IEEE Access, IEEE, 2021.
A Hitchhiker's Guide to Ontology
- Suchanek Fabian
, 2021. A knowledge base (KB) is a computer-processable collection of knowledge about the world. In its simplest variant, a KB takes the form of a labeled graph, where the nodes are entities (such as people, organizations, and geographical locations), and the edges represent the links between these entities in the real world (such as who was born where, which organization is headed by whom, which city is the capital of which country etc.). Knowledge bases provide the background knowledge for different artificial intelligence applications, ranging from personal assistants to Web search, question answering, and text analysis. In particular, KBs are useful in information retrieval (IR), where they serve for structured search and entity disambiguation. Research has made extraordinary progress in the automated construction of KBs, and today's KBs contain billions of entities [1]. Nevertheless, KBs are still far from perfect. In this keynote talk, I outline several challenges in the construction and maintenance of KBs, and show how our research group approached them.
Identification of Rayleigh fading induced phase artifacts in coherent differential ϕ-OTDR
- Dorize Christian
- Guerrier Sterenn
- Awwad Elie
- Renaudier Jérémie
Optics Letters, Optical Society of America - OSA Publishing, 2021, 46 (11), pp.2754. (10.1364/OL.427944)
DOI : 10.1364/OL.427944
Linewidth enhancement factor measurement by using phase modulation method for epitaxial quantum dot laser on silicon
- Ding Shihao
- Dong Bozhang
- Huang Heming
- Bowers John E
- Grillot Frédéric
, 2021.
Stimulating polarization switching dynamics in mid-infrared quantum cascade lasers
- Spitz Olivier
- Herdt Andreas
- Elsässer Wolfgang
- Grillot Frédéric
Journal of the Optical Society of America B, Optical Society of America, 2021, 38 (8), pp.B35. (10.1364/JOSAB.425097)
DOI : 10.1364/JOSAB.425097
Joint Europa Mission (JEM): A Multiscale, Multi-Platform Mission to Characterize Europa's Habitability and Search for Extant Life. A White Paper prepared for the NAS 2023-2032 Decadal Survey for Planetary Science and Astrobiology August 15th, 2020
- Blanc Michel
- Prieto-Ballesteros Olga
- André Nicolas
- Gomez-Elvira Javier
- Jones Geraint
- Sterken Veerle
- Desprats William
- Gurvits Leonid I.
- Khurana Krishan
- Balmino Georges
- Blöcker Aljona
- Broquet Renaud
- Bunce Emma
- Cavel Cyril
- Choblet Gael
- Colins Geoffrey
- Coradini Marcello
- Cooper John
- Dirkx Dominic
- Fontaine D.
- Garnier Philippe
- Gaudin David
- Hartogh Paul
- Hussmann Hauke
- Genova Antonio
- Iess Luciano
- Jäggi Adrian
- Kempf Sascha
- Krupp Norbert
- Lara Luisa
- Lasue Jérémie
- Lainey Valéry
- Leblanc François
- Lebreton Jean-Pierre
- Longobardo Andrea
- Lorenz Ralph
- Martins Philippe
- Martins Zita
- Marty Jean-Charles
- Masters Adam
- Mimoun David
- Palumba Ernesto
- Parro Victor
- Regnier Pascal
- Saur Joachim
- Schutte Adriaan
- Sittler Edward C.
- Spohn Tilman
- Srama Ralf
- Stephan Katrin
- Szegő Károly
- Tosi Federico
- Vance Steve
- Wagner Roland
- Hoolst Tim Van
- Volwerk Martin
- Wahlund Jan-Erik
- Westall Frances
- Wurz Peter
Bulletin of the American Astronomical Society, American Astronomical Society, 2021, 53 (4), pp.e-id. 380. In this White Paper we propose that NASA works with ESA and other potentially interested international partners to design and fly jointly an ambitious and exciting planetary mission to characterize Europa's habitability and search for bio-signatures in the environment of Europa (surface, subsurface and exosphere). A White Paper prepared for the NAS 2023-2032 Decadal Survey for Planetary Science and Astrobiology August 15th, 2020 (10.3847/25c2cfeb.a4c47358)
DOI : 10.3847/25c2cfeb.a4c47358
Uplink Dimensioning Over Log-Normal Shadowing for OMA and NOMA Schemes
- Liu Bin
- Martins Philippe
- Decreusefond Laurent
- Gomez Jean-Sebastien
- Song Rongfang
IEEE Transactions on Vehicular Technology, Institute of Electrical and Electronics Engineers, 2021, 70 (5), pp.5126--5130. This paper investigates the uplink dimensioning problem for OMA (Orthogonal Multiple Access) and NOMA (Non-Orthogonal Multiple Access) schemes. Dimensioning is to make radio resource provision for a service area to fulfill an outage constraint. The radio resource limit and outage in dimensioning make classical inhomogeneous Poisson assumption of uplink served user point process questionable. In this paper, we first prove that this process admits a homogeneous Poisson distribution in the limiting regime. As a consequence, uplink coverage probabilities over log-normal shadowing for both schemes are derived. Then, tractable stochastic geometry models for two schemes are proposed to obtain numbers of total required radio blocks. Their upper bounds under an outage constraint are also given to reduce computing overhead. Finally, the simulations confirm accuracy of derivations and demonstrate the effectiveness of our models. (10.1109/TVT.2021.3073982)
DOI : 10.1109/TVT.2021.3073982
An ontological foundation for multi-paradigm modelling for cyber-physical systems
- Blouin Dominique
- Al-Ali Rima
- Iacono Mauro
- Tekinerdogan Bedir
- Giese Holger
, 2021, pp.9-43. (10.1016/B978-0-12-819105-7.00007-6)
DOI : 10.1016/B978-0-12-819105-7.00007-6

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