Publications

2018

• Algorithms for concurrent systems
  
  • Kuznetsov Petr
  • Guerraoui Rachid
  , 2018.
• Large-signal capabilities of an optically injection-locked semiconductor laser using gain lever
  
  • Sarraute Jean-Maxime
  • Schires Kevin
  • Larochelle Sophie
  • Grillot Frédéric
  , 2018.
• The relation between MOS and pairwise comparisons and the importance of cross-content comparisons
  
  • Zerman Emin
  • Hulusic Vedad
  • Valenzise Giuseppe
  • Mantiuk Rafał
  • Dufaux Frédéric
  , 2018, 30 (14), pp.1-6. Subjective quality assessment is considered a reliable method for quality assessment of distorted stimuli for several mul-timedia applications. The experimental methods can be broadly categorized into those that rate and rank stimuli. Although ranking directly provides an order of stimuli rather than a continuous measure of quality, the experimental data can be converted using scaling methods into an interval scale, similar to that provided by rating methods. In this paper, we compare the results collected in a rating (mean opinion scores) experiment to the scaled results of a pairwise comparison experiment, the most common ranking method. We find a strong linear relationship between results of both methods, which, however, differs between content. To improve the relationship and unify the scale, we extend the experiment to include cross-content comparisons. We find that the cross-content comparisons reduce the confidence intervals for pairwise comparison results, but also improve the relationship with mean opinion scores. (10.2352/ISSN.2470-1173.2018.14.HVEI-517)
  DOI : 10.2352/ISSN.2470-1173.2018.14.HVEI-517
• Ultrafast and nonlinear dynamics of InAs/GaAs semiconductor quantum dot lasers
  
  • Grillot Frédéric
  • Arsenijevic Dejan
  • Huang Heming
  • Bimberg Dieter
  , 2018.
• 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.
• High-speed per-flow software monitoring with limited resources
  
  • Zhang Tianzhu
  • Linguaglossa Leonardo
  • Gallo Massimo
  • Giaccone Paolo
  • Rossi Dario
  , 2018.
• Lecture on Continuous-Variable Quantum Key Distribution
  
  • Alleaume Romain
  , 2018.
• Semiconductor quantum dot lasers epitaxially grown on silicon with low linewidth enhancement factor
  
  • Duan J.
  • Huang H.
  • Jung D.
  • Zhang Z.
  • Norman J.
  • Bowers J. E.
  • Grillot F.
  Applied Physics Letters, American Institute of Physics, 2018, 112 (25), pp.251111. This work reports on the ultra-low linewidth enhancement factor (αH-factor) of semiconductor quantum dot lasers epitaxially grown on silicon. Owing to the low density of threading dislocations and resultant high gain, an αH value of 0.13 that is rather independent of the temperature range (288 K–308 K) is measured. Above the laser threshold, the linewidth enhancement factor does not increase extensively with the bias current which is very promising for the realization of future integrated circuits including high performance laser sources. (10.1063/1.5025879)
  DOI : 10.1063/1.5025879
• Nonnegative Matrix Factorization
  
  • Badeau Roland
  • Virtanen Tuomas
  , 2018, pp.131-160.
• 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
• 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.
• 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.
• 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.
• 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
• «Informathique»
  
  • Zayana Karim
  • Croix Edwige
  Au fil des maths, APMEP, 2018. Essai sur la didactique de l'informatique, en lien avec les mathématiques
• 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.
• IoT technologies for smart cities
  
  • Hammi Badis
  • Khatoun Rida
  • Zeadally Sherali
  • Fayad Achraf
  • Khoukhi Lyes
  IET Networks, John Wiley & Sons Inc., 2018, 7 (1), pp.1-13. The large deployment of Internet of things (IoT) is actually enabling smart city projects and initiatives all over the world. Objects used in daily life are being equipped with electronic devices and protocol suites in order to make them interconnected and connected to the Internet. According to a recent Gartner study, 50 billion connected objects will be deployed in smart cities by 2020. These connected objects will make the authors’ cities smart. However, they will also open up risks and privacy issues. As various smart city initiatives and projects have been launched in recent years, theyhave witnessed not only the expected benefits, but the risks introduced. They describe the current and future trends of smart city and IoT. They also discuss the interaction between smart cities and IoT and explain some of the drivers behind the evolution and development of IoT and smart city. Finally, they discuss some of the IoT weaknesses and how they can be addressed when used for smart cities. (10.1049/iet-net.2017.0163)
  DOI : 10.1049/iet-net.2017.0163
• Physical Security Versus Masking Schemes
  
  • Danger Jean-Luc
  • Guilley Sylvain
  • Heuser Annelie
  • Legay Axel
  • Ming Tang
  , 2018, pp.269-284. (10.1007/978-3-319-98935-8_13)
  DOI : 10.1007/978-3-319-98935-8_13
• Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach
  
  • Le Laetitia Minh Maï
  • Kégl Balázs
  • Gramfort Alexandre
  • Marini Camille
  • Nguyen David
  • Cherti Mehdi
  • Tfaili Sana
  • Tfayli Ali
  • Baillet-Guffroy Arlette
  • Prognon Patrice
  • Chaminade Pierre
  • Caudron Eric
  Talanta, Elsevier, 2018, 184, pp.260-265. The use of monoclonal antibodies (mAbs) constitutes one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. These antibodies are prescribed by the physician and prepared by hospital pharmacists. An analytical control enables the quality of the preparations to be ensured. The aim of this study was to explore the development of a rapid analytical method for quality control. The method used four mAbs (Infliximab, Bevacizumab, Rituximab and Ramucirumab) at various concentrations and was based on recording Raman data and coupling them to a traditional chemometric and machine learning approach for data analysis. Compared to conventional linear approach, prediction errors are reduced with a data-driven approach using statistical machine learning methods. In the latter, preprocessing and predictive models are jointly optimized. An additional original aspect of the work involved on submitting the problem to a collaborative data challenge platform called Rapid Analytics and Model Prototyping (RAMP). This allowed using solutions from about 300 data scientists in collaborative work. Using machine learning, the prediction of the four mAbs samples was considerably improved. The best predictive model showed a combined error of 2.4% versus 14.6% using linear approach. The concentration and classification errors were 5.8% and 0.7%, only three spectra were misclassified over the 429 spectra of the test set. This large improvement obtained with machine learning techniques was uniform for all molecules but maximal for Bevacizumab with an 88.3% reduction on combined errors (2.1% versus 17.9%). (10.1016/j.talanta.2018.02.109)
  DOI : 10.1016/j.talanta.2018.02.109
• Parallel Combining: Benefits of Explicit Synchronization
  
  • Aksenov Vitaly
  • Kuznetsov Petr
  • Shalyto Anatoly
  , 2018, pp.11:1-11:16. (10.4230/LIPIcs.OPODIS.2018.11)
  DOI : 10.4230/LIPIcs.OPODIS.2018.11
• Task Computability in Unreliable Anonymous Networks
  
  • Kuznetsov Petr
  • Yanagisawa Nayuta
  , 2018, pp.23:1-23:13. (10.4230/LIPIcs.OPODIS.2018.23)
  DOI : 10.4230/LIPIcs.OPODIS.2018.23
• Finding events in temporal networks: Segmentation meets densest-subgraph discovery
  
  • Rozenshtein Polina
  • Bonchi Francesco
  • Gionis Aristides
  • Sozio Mauro
  • Tatti Nikolaj
  , 2018. In this paper we study the problem of discovering a timeline of events in a temporal network. We model events as dense subgraphs that occur within intervals of network activity. We formulate the event-discovery task as an optimization problem, where we search for a partition of the network timeline into k non-overlapping intervals, such that the intervals span subgraphs with maximum total density. The output is a sequence of dense subgraphs along with corresponding time intervals, capturing the most interesting events during the network lifetime. A naïve solution to our optimization problem has polynomial but prohibitively high running time complexity. We adapt existing recent work on dynamic densest-subgraph discovery and approximate dynamic programming to design a fast approximation algorithm. Next, to ensure richer structure, we adjust the problem formulation to encourage coverage of a larger set of nodes. This problem is NP-hard even for static graphs. However, on static graphs a simple greedy algorithm leads to approximate solution due to submodularity. We extended this greedy approach for the case of temporal networks. However, the approximation guarantee does not hold. Nevertheless, according to the experiments, the algorithm finds good quality solutions. (10.1109/ICDM.2018.00055)
  DOI : 10.1109/ICDM.2018.00055
• EviDense: a Graph-based Method for Finding Unique High-impact Events with Succinct Keyword-based Descriptions
  
  • Balalau Oana
  • Castillo Carlos
  • Sozio Mauro
  , 2018. Despite the significant efforts made by the research community in recent years, automatically acquiring valuable information about high impact-events from social media remains challenging. We present EVIDENSE, a graph-based approach for finding high-impact events (such as disaster events) in social media. Our evaluation shows that our method outper-forms state-of-the-art approaches for the same problem, in terms of having higher precision, lower number of duplicates, while providing a keyword-based description that is succinct and informative.
• Belief revision, minimal change and relaxation: A general framework based on satisfaction systems, and applications to description logics
  
  • Aiguier Marc
  • Atif Jamal
  • Bloch Isabelle
  • Hudelot Céline
  Artificial Intelligence (AIJ), Elsevier, 2018, 256, pp.160 - 180. Belief revision of knowledge bases represented by a set of sentences in a given logic has been extensively studied but for specific logics, mainly propositional, and also recently Horn and description logics. Here, we propose to generalize this operation from a model-theoretic point of view, by defining revision in the abstract model theory of satisfaction systems. In this framework, we generalize to any satisfaction system the characterization of the AGM postulates given by Katsuno and Mendelzon for propositional logic in terms of minimal change among interpretations. In this generalization, the constraint on syntax independence is partially relaxed. Moreover, we study how to define revision, satisfying these weakened AGM postulates, from relaxation notions that have been first introduced in description logics to define dissimilarity measures between concepts, and the consequence of which is to relax the set of models of the old belief until it becomes consistent with the new pieces of knowledge. We show how the proposed general framework can be instantiated in different logics such as propositional, first-order, description and Horn logics. In particular for description logics, we introduce several concrete relaxation operators tailored for the description logic ALC and its fragments EL and ELU, discuss their properties and provide some illustrative examples. (10.1016/j.artint.2017.12.002)
  DOI : 10.1016/j.artint.2017.12.002