Publications

2017

• Tile-based high resolution VR contents delivery
  
  • Grégory Lucas
  • Raulet Mickael
  • Toullec Eric
  • Le Feuvre J.
  , 2017.
• Sphere Decoder with Dichotomic Search
  
  • Khsiba Mohamed-Achraf
  • Rekaya-Ben Othman Ghaya
  , 2017.
• Massive Online Analytics for the Internet of Things (IoT)
  
  • Bifet Albert
  , 2017. Big Data and the Internet of Things (IoT) have the potential to fundamentally shift the way we interact with our surroundings. The challenge of deriving insights from the Internet of Things (IoT) has been recognized as one of the most exciting and key opportunities for both academia and industry. Advanced analysis of big data streams from sensors and devices is bound to become a key area of data mining research as the number of applications requiring such processing increases. Dealing with the evolution over time of such data streams, i.e., with concepts that drift or change completely, is one of the core issues in stream mining. In this talk, I will present an overview of data stream mining, and I will introduce some popular open source tools for data stream mining.
• Secure and Resilient Scheme for Data Protection in Unattanded Wireless Sensor Networks
  
  • Kapusta Katarzyna
  • Memmi Gérard
  • Noura Hassan
  , 2017.
• Cognitive Computation and Communication: A Complement Solution to Cloud for IoT
  
  • Nguyen V. T.
  • Nguyen-Thanh N.
  • Yang Lita
  • Duy H. N. Nguyen
  • Jabbour Chadi
  • Murmann Boris
  , 2017.
• Dual Logic Concepts based on Mathematical Morphology in Stratified Institutions: Applications to Spatial Reasoning
  
  • Aiguier Marc
  • Bloch Isabelle
  , 2017.
• A survey on fiber nonlinearity compensation for 400 Gbps and beyond optical communication systems
  
  • Amari Abdelkerim
  • Dobre Octavia
  • Venkatesan R.
  • Kumar O.
  • Ciblat Philippe
  • Jaouën Yves
  Communications Surveys and Tutorials, IEEE Communications Society, Institute of Electrical and Electronics Engineers, 2017.
• Guiding Audio Source Separation by Video Object Information
  
  • Parekh Sanjeel
  • Essid Slim
  • Ozerov Alexey
  • Duong Quang-Khanh-Ngoc
  • Perez Patrick
  • Richard Gael
  , 2017.
• Formal methode for safe and Verification of RailWay Signaling Sustems
  
  • Belabed Lilia
  • Tanzi Tullio
  • Coudert Sophie
  , 2017.
• Auto-Adaptive Multi-Hop Clustering for Hybrid Cellular-Vehicular Networks
  
  • Garbiso Julian
  • Diaconescu Ada
  • Coupechoux Marceau
  • Leroy Bertrand
  , 2017, pp.1-6. In this paper, we consider a hybrid vehicular network, in which vehicles transmit data via the cellular network and dispose of a V2V interface. In this context, we propose an auto-adaptive multi-hop clustering algorithm, which optimizes the cellular radio resource under the constraint of a maximum packet loss rate (PLR) in the V2V network. The larger V2V based clusters are, the higher the data compression ratio at the cluster head is and the smaller the amount of required resource on the cellular link is. However, PLR becomes higher due to the collision on the V2V channel when increasing the number of hops. The proposed algorithm thus adapts dynamically the maximum number of hops in clusters according to the vehicular traffic density. By simulations, we show that it performs better in terms of aggregated cellular data and packet loss rate than any fixed-hop clustering algorithm in a dynamic scenario.
• The potential of Image Schemas for computing automatically metaphoric gestures for embodied conversational agents
  
  • Ravenet Brian
  • Clavel Chloé
  • Pelachaud Catherine
  , 2017.
• Leveraging deep neural networks with nonnegative representations for improved environmental sound classification
  
  • Bisot Victor
  • Serizel Romain
  • Essid Slim
  • Richard Gael
  , 2017. This paper introduces the use of representations based on non-negative matrix factorization (NMF) to train deep neural networks with applications to environmental sound classification. Deep learning systems for sound classification usually rely on the network to learn meaningful representations from spectrograms or hand-crafted features. Instead, we introduce a NMF-based feature learning stage before training deep networks , whose usefulness is highlighted in this paper, especially for multi-source acoustic environments such as sound scenes. We rely on two established unsupervised and supervised NMF techniques to learn better input representations for deep neural networks. This will allow us, with simple architectures, to reach competitive performance with more complex systems such as convolutional networks for acoustic scene classification. The proposed systems outperform neu-ral networks trained on time-frequency representations on two acoustic scene classification datasets as well as the best systems from the 2016 DCASE challenge.
• Information-Theoretic Analysis of Human Performance for Command Selection
  
  • Liu Wanyu
  • Rioul Olivier
  • Beaudouin-Lafon Michel
  • Guiard Yves
  , 2017, LNCS-10515 (Part III), pp.515-524. Selecting commands is ubiquitous in current GUIs. While a number of studies have focused on improving rapid command selection through novel interaction techniques, new interface design and innovative devices, user performance in this context has received little attention. Inspired by a recent study which formulated information-theoretic hypotheses to support experimental results on command selection, we aim at explaining user performance from an information-theoretic perspective. We design an ad-hoc command selection experiment for information-theoretic analysis, and explain theoretically why the transmitted information from the user to the computer levels off as difficulty increases. Our reasoning is based on basic information-theoretic concepts such as entropy, mutual information and Fano’s inequality. This implies a bell-shaped behavior of the throughput and therefore an optimal level of difficulty for a given input technique. (10.1007/978-3-319-67687-6_35)
  DOI : 10.1007/978-3-319-67687-6_35
• Grab 'n' Drop: User Configurable Toolglasses
  
  • Eagan James R
  , 2017, 10515 (Part III), pp.315-334. We introduce the grab 'n' drop toolglass, an extension of the toolglass bi-manual interaction technique. It enables users to create and configure their own toolglasses from existing user interfaces that were not designed for toolglasses. Users compose their own toolglass interactions at runtime from an application's user interface elements, bringing interaction closer to the objects of interest in a workspace. Through a proof-of-concept implementation for Mac OS X, we show how grab 'n' drop capabilities could be added to existing applications at the toolkit level, without modifying application source code or UI design. Finally, we evaluate the power and flexibility of this approach by applying it to a variety of applications. We further identify limitations and risks associated with this approach and propose changes to existing toolkits to foster such user-reconfigurable interaction. (10.1007/978-3-319-67687-6_21)
  DOI : 10.1007/978-3-319-67687-6_21
• One Fitts’ Law, Two Metrics
  
  • Gori Julien
  • Rioul Olivier
  • Guiard Yves
  • Beaudouin-Lafon Michel
  , 2017, LNCS-10515 (Part III), pp.525-533. Movement time in Fitts’ law is usually considered through the ambiguous notion of the average of minimum movement times. In this paper, we argue that using two distinct metrics, one relating to minimum time and the other relating to average time can be advantageous. Both metrics have a lot of support from theoretical and empirical perspectives. We also give two examples, one in a controlled experiment and the other in a field study of pointing, where making the minimum versus average distinction is fruitful. (10.1007/978-3-319-67687-6_36)
  DOI : 10.1007/978-3-319-67687-6_36
• Contrôle orbital pour le tracé de trajectoires 3D à l'aide des mouvements de la tête
  
  • Jacob Thibaut
  , 2017. Le domaine du son 3D est aujourd'hui en pleine effervescence du fait d'une combinaison de facteurs (normalisation de nouveaux formats audio, équipement des salles de cinéma, etc.). Les travaux effectués dans ce domaine se sont principalement concentrés sur le codage et le traitement du son 3D. Cependant, la création interactive de contenus sonores 3D n'est pas un problème trivial, car cette tâche nécessite de tracer ou d'éditer des trajectoires en trois dimensions pour animer des sources sonores dans l'espace. Dans cette thèse en Interaction Homme-Machine (IHM), nous considérons l'édition de trajectoires de sources sonores en 3D comme un cas particulier de tâche de modélisation 3D et proposons plusieurs contributions. Sur le plan conceptuel, nous proposons un espace de conception pour le tracé de trajectoires en trois dimensions. Nous présentons également une classification des contrôles de caméra existants en fonction du type de contrôle et des modalités utilisées. Sur le plan empirique, nous conduisons 5 études utilisateurs dans le but de créer une technique d'interaction pour le contrôle du point de vue orbital permettant d'effectuer une rotation de 3600 en utilisant le roulis de la tête. Enfin , nous présentons une implémentation de notre technique ainsi que son intégration dans le logiciel de modélisation 3D Blender et dans le logiciel Performer utilisé par Radio France pour contrôler la position de sources sonores dans le cadre de performances en son 3D.
• Procédé et dispositif de détermination indirecte d'un flux solaire incident
  
  • Nabil Tahar
  • Jicquel Jean-Marc
  • Girard Alexandre
  • Roueff François
  , 2017, pp.https://permalink.orbit.com/RenderStaticFirstPage?XPN=QOanRZ3izCL4%252BC%252F5M6pym3fDUqlXTJ5uwQdFuycu4uk%3D%26n%3D1&id=0&base=FAMPAT. The invention relates to a device for indirectly determining a solar flux incident on a structure, comprising means for calculating solar flux according to a theoretical solar flux model taking into account a current value of cloudiness, The device being characterized in that it comprises a first external temperature sensor situated at a location exposed to solar radiation, and a second external temperature sensor situated in the shadow, the calculation means receiving as input a temperature bias value, Defined as the difference between the temperatures measured by the first sensor and the second sensor, and the calculation means being configured to perform an estimation of the nebulosity value as a function of said temperature bias value.
• MEG-BIDS: an extension to the Brain Imaging Data Structure for magnetoencephalography
  
  • Julia Guiomar Niso Galan
  • Gorgolewski Krzysztof J.
  • Bock Elizabeth
  • Brooks Teon
  • Flandin Guillaume
  • Gramfort Alexandre
  • Henson Richard N.
  • Jas Mainak
  • Litvak Vladimir
  • Moreau Jeremy
  • Oostenveld Robert
  • Schoffelen Jan-Mathijs
  • Tadel François
  • Wexler Joseph
  • Baillet Sylvain
  , 2017. We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG provides direct measurement of brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS has provided a solution to structure the organization of magnetic resonance imaging (MRI) data, which nature and acquisition parameters are different. Despite the lack of standard data format for MEG, MEG-BIDS is a principled solution to store, organize and share the typically-large data volumes produced. It builds on BIDS for MRI, and therefore readily yields a multimodal data organization by construction. This is particularly valuable for the anatomical and functional registration of MEG source imaging with MRI. With MEG-BIDS and a growing range of software adopting the standard, the MEG community has a solution to minimize curation overheads, reduce data handling errors and optimize usage of computational resources for analytics. The standard also includes well-defined metadata, to facilitate future data harmonization and sharing efforts.
• METHODS FOR RECOVERING SECRET DATA OF A CRYPTOGRAPHIC DEVICE AND FOR EVALUATING THE SECURITY OF SUCH A DEVICE
  
  • Guilley Sylvain
  • Heuser Annelie
  • Rioul Olivier
  , 2017.
• Experimental Energy Profiling of Energy-Critical Embedded Applications
  
  • Rao Vaddina Kameswar
  • Brandner Florian
  • Memmi Gérard
  • Jouvelot Pierre
  , 2017, pp.1-6. Despite recent advances that have greatly improved the performance of embedded systems, we still face many challenges with regard to energy consumption in energy-constrained embedded and communication platforms. Optimizing applications for energy consumption remains a challenge and thus is a compelling research direction, both on the practical and theoretical sides. This paper presents a new experimental bench for energy profiling of non-performance-critical embedded and mobile applications and reports preliminary results obtained on two embedded boards. The experiments are driven by an online energy monitoring mechanism using National Instruments' cDAQ and LabVIEW running on a host machine. The host monitors a target device, which runs a set of benchmarks. We describe the experience gained from using and modding two different target boards, namely an Nvidia Jetson TX1 and a TI AM572x evaluation module. In particular, we confirm, and thus further validate, the existence of the Energy/Frequency Convexity Rule for CPU-bound benchmarks. This rule states that there exists an optimal clock frequency that minimizes the CPU energy consumption for non-performance-critical applications. We also show that the gain of frequency scaling is highly dependent on workload characteristics. Any future energy-management approach should take these behavioral traits into consideration. I. INTRODUCTION Continuous CMOS technology scaling (Moore's law) increases the on-chip power density due to the higher transistor integration. As power density increases, many factors like power dissipation, leakage, data activity, and electro-migration contribute to higher on-chip temperatures. The increase in temperature leads to an increase in leakage power, thereby increasing the total energy dissipation and thus forming a part of a vicious circle significantly limitting system performance. The bulk of today's computing does not happen on desktops, laptops, servers, or data centers, but rather on embedded media devices like mobile phones [1]. The embedded computing applications running on those devices demand better energy efficiency and flexibility in operation, while delivering better performance per Watt. At the same time, they cannot compete with application-specific integrated circuits (ASIC) in terms of energy efficiency. Indeed, a well-designed ASIC can achieve an efficiency of 5 pJ/op in a 90-nm CMOS process, whereas a very efficient embedded processor would require about 250 pJ/op. That means the embedded processor may consume about 50 times more energy than a custom designed ASIC [1]. Today's system-on-a-chip (SoC) platforms have a lot of software acting in unison, trying to deliver a seamless user
• Impact of ferromagnetic obstacles on LF-RFID based indoor positioning systems
  
  • Gharat Vighnesh
  • Colin Elizabeth
  • Baudoin Geneviève
  • Richard Damien Richard
  , 2017. (10.1109/RFID-TA.2017.8098876)
  DOI : 10.1109/RFID-TA.2017.8098876
• Indoor performance analysis of LF-RFID based positioning system: Comparison with UHF-RFID and UWB
  
  • Gharat Vighnesh
  • Colin Elizabeth
  • Baudoin Geneviève
  • Richard Damien Richard
  , 2017. (10.1109/IPIN.2017.8115901)
  DOI : 10.1109/IPIN.2017.8115901
• Correlations with on-chip detection and modulation for CVQKD
  
  • Persechino Mauro
  • Trigo Vidarte Luis
  • Ziebell Melissa
  • Crozat Paul
  • Villing André
  • Marris-Morini Delphine
  • Vivien Laurent
  • Diamanti Eleni
  • Grangier Philippe
  , 2017.
• Experimental demonstration of practical unforgeable quantum money
  
  • Bozzio Mathieu
  • Orieux Adeline
  • Trigo Vidarte Luis
  • Zaquine Isabelle
  • Kerenidis Iordanis
  • Diamanti Eleni
  , 2017.
• Experimental detection of steerability for Bell-local states with two measurement settings
  
  • Diamanti Eleni
  • Orieux Adeline
  • Zaquine Isabelle
  • Kaplan Marc
  • Pramanik Tanumoy
  • Venuti Vivien
  , 2017.