Publications

2018

• Managing 'proto-ecosystems' - two smart mobility case studies
  
  • Marcocchia Giulia
  • Maniak Rémi
  International Journal of Automotive Technology and Management, Inderscience, 2018, 18 (3), pp.209-228. This paper considers how ecosystem-based research projects can be managed for a successful deployment of systemic and disruptive innovation. Such projects are defined as assignments in which heterogeneous organisations must invest upfront, aiming at co-constructing a systemic offer with shared interest, shared uncertainty and high economic, environmental and social impacts. Innovation management, ecosystem, and public-private partnership literatures have been investigated, as well as two European Commission funded research projects aimed at smart mobility infrastructure development. Results show these projects are both critical and disappointing for each player. We explain this contradiction of value perception showing that partners need such ecosystem projects to go forward and update their competences and roadmaps, but that the observed project management approach hampers the collectively built learning and the evolution of the strategic agenda of each partner. In conclusion, we define the concept of proto-ecosystem as an intermediary 'management object' for innovation management, and point out implications to manage such projects in order to unfold their whole potential. (10.1504/IJATM.2018.093413)
  DOI : 10.1504/IJATM.2018.093413
• DyBED: An Efficient Algorithm for Updating Betweenness Centrality in Directed Dynamic Graphs
  
  • Chehreghani Mostafa Haghir
  • Bifet Albert
  • Abdessalem Talel
  , 2018, pp.2114-2123.
• Quarante ans d’imagerie satellitaire radar
  
  • Nicolas Jean-Marie
  • Tupin Florence
  Revue Française de Photogrammétrie et de Télédétection, Société Française de Photogrammétrie et de Télédétection, 2018.
• A Smooth Primal-Dual Optimization Framework for Nonsmooth Composite Minimization
  
  • Tran-Dinh Quoc
  • Fercoq Olivier
  • Cevher Volkan
  SIAM Journal on Optimization, Society for Industrial and Applied Mathematics, 2018, 28 (1), pp.96-134. We propose a new first-order primal-dual optimization framework for a convex optimization template with broad applications. Our optimization algorithms feature optimal convergence guarantees under a variety of common structure assumptions on the problem template. Our analysis relies on a novel combination of three classic ideas applied to the primal-dual gap function: smoothing, acceleration, and homotopy. The algorithms due to the new approach achieve the best known convergence rate results, in particular when the template consists of only non-smooth functions. We also outline a restart strategy for the acceleration to significantly enhance the practical performance. We demonstrate relations with the augmented Lagrangian method and show how to exploit the strongly convex objectives with rigorous convergence rate guarantees. We provide numerical evidence with two examples and illustrate that the new methods can outperform the state-of-the-art, including Chambolle-Pock, and the alternating direction method-of-multipliers algorithms.
• Transcription of Spanish Historical Handwritten Documents with Deep Neural Networks
  
  • Granell Emilio
  • Chammas Edgard
  • Likforman-Sulem Laurence
  • Martínez-Hinarejos Carlos-D
  • Mokbel Chafic
  • Cirstea Bogdan
  Journal of Imaging, MDPI, 2018, 4 (1), pp.22.
• Mathematical models for very high resolution SAR data and their applications
  
  • Deledalle Charles-Alban
  • Denis L.
  • Ferraioli G.
  • Tupin Florence
  , 2018.
• Une approche par patchs, multi-atlas, itérative pour la segmentation du cortex cérébral en IRM néonatale
  
  • Tor-Díez Carlos
  • Passat Nicolas
  • Bloch Isabelle
  • Faisan Sylvain
  • Bednarek Nathalie
  • Rousseau François
  , 2018. L’analyse des structures cérébrales chez le nouveau-né constitue un enjeu de santé majeur, notamment en cas de prématurité, afin de disposer d’informations prédictives sur le développement de l’enfant. Le cortex est, en particulier, une structure d’intérêt, observable en IRM (imagerie par résonance magnétique). Les données IRM néonatales présentent toutefois des spécificités qui les rendent complexes à traiter. Dans ce contexte, les approches multi-atlas constituent une stratégie efficace, tirant parti de données traitées préalablement. La méthode proposée dans cet article repose sur une telle stratégie multi-atlas. Elle s’appuie notamment sur deux paradigmes : l’utilisation d’un modèle non local à base de patchs, et l’utilisation d’un schéma d’optimisation itératif. L’usage couplé de ces deux concepts permet notamment de considérer des patchs liés à l’image ainsi qu’à sa segmentation courante. Cette stratégie, comparée à de précédentes méthodes multi-atlas de la littérature, aboutit à des résultats de segmentation corticale robustes.
• Mass volume curves and anomaly ranking
  
  • Clémençon Stéphan
  • Thomas Albert
  Electronic Journal of Statistics, Shaker Heights, OH : Institute of Mathematical Statistics, 2018, 12 (2), pp.2806-2872. (10.1214/18-EJS1474)
  DOI : 10.1214/18-EJS1474
• Mean value coordinates for quad cages in 3D
  
  • Thiery Jean-Marc
  • Memari Pooran
  • Boubekeur Tamy
  ACM Transactions on Graphics, Association for Computing Machinery, 2018.
• Method, device and computer program for encapsulating media data into a media file
  
  • Denoual Franck
  • Mazé Frédéric
  • Le Feuvre J.
  • Ouedraogo Nael
  , 2018.
• Attack Tree Construction and Its Application to the Connected Vehicle
  
  • Danger Jean-Luc
  • Karray Khaled
  • Guilley Sylvain
  • Abdelaziz Elaabid M.
  , 2018, pp.175-190. (10.1007/978-3-319-98935-8_9)
  DOI : 10.1007/978-3-319-98935-8_9
• Segmentation of pelvic vessels in pediatric MRI using a patch based learning approach
  
  • Virzi Alessio
  • Gori Pietro
  • Muller Cécile
  • Mille Eva
  • Peyrot Quoc
  • Berteloot Laureline
  • Boddaert Nathalie
  • Sarnacki Sabine
  • Bloch Isabelle
  , 2018, pp.617.
• Musical Descriptions Based on Formal Concept Analysis and Mathematical Morphology
  
  • Agon Carlos
  • Andreatta Moreno
  • Atif Jamal
  • Bloch Isabelle
  • Mascarade Pierre
  , 2018, pp.105-119. In the context of mathematical and computational representations of musical structures, we propose algebraic models for formalizing and understanding the harmonic forms underlying musical compositions. These models make use of ideas and notions belonging to two algebraic approaches: Formal Concept Analysis (FCA) and Mathematical Morphology (MM). Concept lattices are built from interval structures whereas mathematical morphology operators are subsequently defined upon them. Special equivalence relations preserving the ordering structure of the lattice are introduced in order to define musically relevant quotient lattices modulo congruences. We show that the derived descrip-tors are well adapted for music analysis by taking as a case study Ligeti's String Quartet No. 2. (10.1007/978-3-319-91379-7_9)
  DOI : 10.1007/978-3-319-91379-7_9
• Practical Random Linear Coding for MultiPath TCP: MPC-TCP
  
  • Paul-Louis Ageneau
  • Boukhatem Nadia
  • Gerla Mario
  , 2018. MPTCP is a TCP extension that enables transparent multipath for multihomed hosts. However, MPTCP is subject to head-of-line blocking, a problem that degrades delay and throughput. This problem is especially critical when used in wireless environments. On wireless, unreliable links, for example, traffic can get stalled on one path, slowing down the entire flow. A related problem is rescheduling the packets in other subflows too early, which could result in increased overhead. Random linear network coding is a potential approach to solve this problem among others, and we choose to focus in its practical capability to attenuate performance drops caused by blocking while guaranteeing full network compatibility. We have developed a version of MPTCP with network coding, MPC-TCP (MultiPath Coded TCP) and implemented it in the Linux kernel. This scheme offers a simple, practical implementation of network coding across subflows, requires minimal changes to MPTCP and preserves the TCP subflows compatibility with middleboxes. We then use our implementation to investigate the network scenarios where efficiency gains are the highest compared to vanilla MPTCP.
• «Informathique»
  
  • Zayana Karim
  • Croix Edwige
  Au fil des maths, APMEP, 2018. Essai sur la didactique de l'informatique, en lien avec les mathématiques
• Segmentation of pelvic vessels in pediatric MRI using a patch-based deep learning approach
  
  • Virzi Alessio
  • Gori Pietro
  • Muller Cécile
  • Mille Eva
  • Peyrot Quoc
  • Berteloot Laureline
  • Boddaert Nathalie
  • Sarnacki Sabine
  • Bloch Isabelle
  , 2018, LNCS 11076, pp.97-106. In this paper, we propose a patch-based deep learning ap- proach to segment pelvic vessels in 3D MRI images of pediatric patients. For a given T2 weighted MRI volume, a set of 2D axial patches are extracted using a limited number of user-selected landmarks. In order to take into account the volumetric information, successive 2D axial patches are combined together, producing a set of pseudo RGB color images. These RGB images are then used as input for a convolutional neural network (CNN), pre-trained on the ImageNet dataset, which re- sults into both segmentation and vessel labeling as veins or arteries. The proposed method is evaluated on 35 MRI volumes of pediatric patients, obtaining an average segmentation accuracy in terms of Average Sym- metric Surface Distance of ASSD = 0.89 ± 0.07 mm and Dice Index of DC = 0.79 ± 0.02.
• Integral estimation based on Markovian design
  
  • Azaïs Romain
  • Delyon Bernard
  • Portier François
  Advances in Applied Probability, Applied Probability Trust, 2018, 50 (3), pp.833-857. Suppose that a mobile sensor describes a Markovian trajectory in the ambient space. At each time the sensor measures an attribute of interest, e.g., the temperature. Using only the location history of the sensor and the associated measurements, the aim is to estimate the average value of the attribute over the space. In contrast to classical probabilistic integration methods, e.g., Monte Carlo, the proposed approach does not require any knowledge on the distribution of the sensor trajectory. Probabilistic bounds on the convergence rates of the estimator are established. These rates are better than the traditional "root n"-rate, where n is the sample size, attached to other probabilistic integration methods. For finite sample sizes, the good behaviour of the procedure is demonstrated through simulations and an application to the evaluation of the average temperature of oceans is considered. (10.1017/apr.2018.38)
  DOI : 10.1017/apr.2018.38
• Weakly Supervised Representation Learning for Unsynchronized Audio-Visual Events
  
  • Parekh Sanjeel
  • Essid Slim
  • Ozerov Alexey
  • Duong Ngoc Q K
  • Pérez Patrick
  • Richard Gael
  , 2018. Audiovisual representation learning is an important task from the perspective of designing machines with the ability to understand complex events. To this end, we propose a novel multimodal framework that instantiates multiple instance learning. We show that the learnt representations are useful for classifying events and localizing their characteristic audiovisual elements. The system is trained using only video-level event labels without any timing information. An important feature of our method is its capacity to learn from unsynchronized audiovisual events. We achieve state-of-the-art results on a large-scale dataset of weakly-labeled audio event videos. Visualizations of localized visual regions and audio segments substantiate our system's efficacy, especially when dealing with noisy situations where modality-specific cues appear asynchronously.
• Behaviour Driven Development for Hardware Design
  
  • Diepenbeck Melanie
  • Kühne Ulrich
  • Soeken Mathias
  • Grosse Daniel
  • Drechsler Rolf
  IPSJ Transactions on System LSI Design Methodology, 2018, 11, pp.29-45. (10.2197/ipsjtsldm.11.29)
  DOI : 10.2197/ipsjtsldm.11.29
• High-speed per-flow software monitoring with limited resources
  
  • Zhang Tianzhu
  • Linguaglossa Leonardo
  • Gallo Massimo
  • Giaccone Paolo
  • Rossi Dario
  , 2018.
• Nonnegative Matrix Factorization
  
  • Badeau Roland
  • Virtanen Tuomas
  , 2018, pp.131-160.
• A Safe Communication Protocol for IoT Devices
  
  • Hammi Mohamed T.
  • Livolant Erwan
  • Bellot Patrick
  • Minet Pascale
  • Serhrouchni Ahmed
  Annals of Telecommunications - annales des télécommunications, Springer, 2018, pp.15. The Internet of Things (IoT) has overturned the information technology world. This new phenomenon is becoming inescapable and already covers almost all fields, from watchmaking to automated factories. IoT simplifies our everyday life and creates value for people and businesses. Things, also called entities, are very heterogeneous, use different communication technologies and, generally, are limited capacity devices. Therefore securing such systems raises many challenges. Communicating entities should authenticate each other and protect the integrity and the confidentiality of the data they exchange while using lightweight, fast and energy-efficient algorithms. In this paper, we propose a robust security protocol, designed especially for constrained IoT devices. We carried out a real implementation and the obtained results prove the efficiency of our protocol.
• Bubbles of Trust: a decentralized Blockchain-based authentication system for IoT
  
  • Hammi Mohamed T.
  • Hammi Badis
  • Bellot Patrick
  • Serhrouchni Ahmed
  Computers & Security, Elsevier, 2018, pp.15. Internet of Things becomes a major part of our lives, billions of autonomous devices are connected and communicate with each other. This revolutionary paradigm creates a new dimension that removes the boundaries between the real and the virtual worlds. The Wireless Sensor Networks are a masterpiece of the success of this technology, using limited capacity sensors and actuators, industrial, medical, agricultural and many other environments can be covered and managed automatically. This autonomous interacting things should authenticate each other, and communicate securely. Otherwise malicious users can cause serious damages on such systems. In this paper we propose a robust, transparent, flexible and energy efficient blockchain-based authentication mechanism called BCTrust, which is designed especially for devices with computational, storage and energy consumption constraints. In order to evaluate our approach, we realized a real implementation with C programming language, and Ethereum Blockchain.
• Remembered events are unexpected (Commentary on Mahr \& Csibra: Why do we remember? The communicative function of episodic memory)
  
  • Dessalles Jean-Louis
  Behavioral and Brain Sciences, Cambridge University Press (CUP), 2018, 41, pp.22. We remember a small proportion of our experiences as events. Are these events selected because they are useful and can be proven true, or rather because they are unexpected? (10.1017/S0140525X17001315)
  DOI : 10.1017/S0140525X17001315
• Lecture on Continuous-Variable Quantum Key Distribution
  
  • Alleaume Romain
  , 2018.