Publications

2018

• Reference list optimization for improvement of compression of 2D-multiview content for free-navigation applications
  
  • Nikitin Pavel
  • Jung Joel
  • Cagnazzo Marco
  , 2018.
• Compression adaptative d'hologrammes numériques en utilisant la technique du Matching Pursuit
  
  • El Rhammad Anas
  • Gioia Patrick
  • Gilles Antonin
  • Cagnazzo Marco
  , 2018.
• Fine-Grained Detection of Inverse Tone Mapping in HDR Images
  
  • Fan Wei
  • Valenzise Giuseppe
  • Banterle Francesco
  • Dufaux Frédéric
  Signal Processing, Elsevier, 2018, 152, pp.178-188. High dynamic range (HDR) imaging enables to capture the full range of physical luminance of a real-world scene, and is expected to progressively replace traditional low dynamic range (LDR) pictures and videos. Despite the increasing HDR popularity, very little attention has been devoted to new forensic problems that are characteristic to this content. In this paper, we address for the first time such kind of problem, by identifying the source of an HDR picture. Specifically, we consider the two currently most common techniques to generate an HDR image: by fusing multiple LDR images with different exposure time, or by inverse tone mapping an LDR picture. We show that, in order to apply conventional forensic tools to HDR images, they need to be properly preprocessed, and we propose and evaluate a few simple HDR forensic preprocessing strategies for this purpose. In addition, we propose a new forensic feature based on Fisher scores, calculated under Gaussian mixture models. We show that the proposed feature outperforms the popular SPAM features in classifying the HDR image source on image blocks as small as 3 × 3, which makes our method suitable to detect composite forgeries combining HDR patches originating from different acquisition processes. (10.1016/j.sigpro.2018.05.028)
  DOI : 10.1016/j.sigpro.2018.05.028
• Near-Optimal Detection of TAST Codes Over Multimode Optical Fiber Channels
  
  • Damen Mohamed Oussama
  • Rekaya-Ben Othman Ghaya
  , 2018.
• La programmation orientée modèles au service des télécommunications mobiles
  
  • Enrici Andrea
  • Apvrille Ludovic
  • Pacalet Renaud
  • Roullet Laurent
  Programmez !, Magazine Programmez, 2018, pp.36-44. Les besoins croissants en termes de latence, débit et flexibilité des réseaux futurs poussent les architectures distribuées des réseaux d’accès radio actuels à évoluer vers des architectures plus centralisées qui reposent sur les paradigmes de l’informatique en nuage (=cloud, NDLR). Au sein de ces nouvelles architectures, le traitement du signal numérique s’effectue sur des matériels hétérogènes (processeurs généralistes, circuits dédiés à hautes performances tels des FPGA ou des GPU). De nombreuses questions restent ouvertes à propos de tels systèmes hétérogènes. En particulier, comment les programmer de façon efficace ?
• Explanatory relations in arbitrary logics based on satisfaction systems, cutting and retraction
  
  • Aiguier Marc
  • Atif Jamal
  • Bloch Isabelle
  • Pino Perez Ramon
  International Journal of Approximate Reasoning, Elsevier, 2018, 102, pp.1 - 20. (10.1016/j.ijar.2018.07.014)
  DOI : 10.1016/j.ijar.2018.07.014
• Quasi-automatic 3D reconstruction of the full spine from low-dose biplanar X-rays based on statistical inferences and image analysis
  
  • Gajny Laurent
  • Ebrahimi Shahin
  • Vergari Claudio
  • Angelini Elsa
  • Skalli Wafa
  European Spine Journal, Springer Verlag, 2018, 28 (4), pp.658-664. Purpose: To design a quasi-automated three-dimensional reconstruction method of the spine from biplanar X-rays as the daily used method in clinical routine is based on manual adjustments of a trained operator and the reconstruction time is more than 10 minutes per patient. Methods: The proposed method of 3D reconstruction of the spine (C3-L5) relies first on a new manual input strategy designed to fit clinicians’ skills. Then, a parametric model of the spine is computed using statistical inferences, image analysis techniques and fast manual rigid registration. Results: An agreement study with the clinically used method on a cohort of 57 adolescent scoliotic subjects has shown that both methods have similar performance on vertebral body position and axial rotation (null bias in both cases and standard deviation of signed differences of 1mm and 3.5° around respectively). In average, the solution could be computed in less than 5 minutes of operator time, even for severe scoliosis. Conclusions: The proposed method allows fast and accurate 3D reconstruction of the spine for wide clinical applications and represents a significant step toward full automatization of 3D reconstruction of the spine. Moreover, it is to the best of our knowledge the first method including also the cervical spine.
• Novel integrated sources for short-reach transmission over dispersive channel
  
  • Peucheret Christophe
  • Chaibi Mohamed E
  • Bramerie Laurent
  • Hassan Karim
  • Erasme Didier
  • Gay Mathilde
  , 2018, Optoelectronic Devices and Integration, pp.OT3A.5. We review our recent results on Si or III-V integrated devices in novel transmitter architectures for IM-DD dispersion-uncompensated links. Methods relying on chirp engineering or SSB generation are demonstrated for multi-and single-carrier modulation formats. (10.1364/OEDI.2018.OT3A.5)
  DOI : 10.1364/OEDI.2018.OT3A.5
• Procede et circuit de multiplexage temporel d'acces concurrents a une ressource informatique
  
  • Jan Mathieu
  • Hebbache Farouk
  • Brandner Florian
  • Pautet Laurent
  , 2018.
• Method for transient change detection with adaptive sampling, and detector implementing the method
  
  • Tchamkerten Aslan
  • Chandar Venkat
  , 2018.
• Improving data collection in complex networks with failure-prone agents via local marking
  
  • Gomez Jonathan
  • Rodriguez Arles
  • Botina Nathaly
  • Diaconescu Ada
  , 2018.
• Real-time enforcement of local energy market transactions respecting distribution grid constraints
  
  • Horta José
  • Altman Eitan
  • Caujolle Mathieu
  • Kofman Daniel
  • Menga David
  , 2018. Future electricity distribution grids will host a considerable share of the renewable energy sources needed for enforcing the energy transition. Demand side management mechanisms play a key role in the integration of such renewable energy resources by exploiting the flexibility of elastic loads, generation or electricity storage technologies. In particular, local energy markets enable households to exchange energy with each other while increasing the amount of renewable energy that is consumed locally. Nevertheless, as most ex-ante mechanisms, local market schedules rely on hour-ahead forecasts whose accuracy may be low. In this paper we cope with forecast errors by proposing a game theory approach to model the interactions among prosumers and distribution system operators for the control of electricity flows in real-time. The presented game has an aggregative equilibrium which can be attained in a semi-distributed manner, driving prosumers towards a final exchange of energy with the grid that benefits both households and operators, favoring the enforcement of prosumers' local market commitments while respecting the constraints defined by the operator. The proposed mechanism requires only one-to-all broadcast of price signals, which do not depend either on the amount of players or their local objective function and constraints, making the approach highly scalable. Its impact on distribution grid quality of supply was evaluated through load flow analysis and realistic load profiles, demonstrating the capacity of the mechanism ensure that voltage deviation and thermal limit constraints are respected.
• Throughput Characterization and Beamwidth Selection for Positioning-Assisted mmWave Service
  
  • Koirala R.
  • Ghatak G.
  • Denis B.
  • Uguen Bernard
  • Dardari D.
  • Domenico A.D.
  , 2019, 2018-October, pp.438-443. We propose an optimal beamwidth selection strategy based on the trade-off between localization and communication performance in millimeter wave networks. With larger resources devoted to localization, we achieve a lower beam-selection error due to accurate position information, although the resulting limitation in communication resources reduces the user data rate. Conversely, to obtain a better rate performance the system needs to increase the allocation for communication, consequently increasing the probability of beam selection error. We characterize localization performance bounds and downlink average rate performance of a mmWave network and accordingly introduce a possible multi-service optimization policy. © 2018 IEEE. (10.1109/ACSSC.2018.8645365)
  DOI : 10.1109/ACSSC.2018.8645365
• Joint Optimization of Communication Latency and Resource Allocation in Cloud Radio Access Networks
  
  • Mharsi Niezi
  • Hadji Makhlouf
  , 2018. This paper addresses a constrained resource allocation problem in Cloud Radio Access Networks (C-RAN). This problem consists in determining the best strategies to assign antennas (Remote Radio Head - RRH) demands to available edge data centers (pool of BaseBand Units - BBU) when jointly optimizing communication latency and resource consumption. Telecommunications Service Providers (TSPs) need new algorithms that enable to jointly reduce their OPEX and CAPEX when embracing C-RAN technology. This paper proposes a mathematical model based on an integer linear programming formulation, to optimally solve the constrained resource allocation problem. To scale and handle much larger number of antennas and edge data centers in acceptable times, a faster and more efficient algorithm based on matroid theory is provided. Simulation results show the scalability of our algorithms and quantify the potential benefits of the discussed approaches in the context of C-RAN.
• Stability and Variability Emphasized STT-MRAM Sensing Circuit With Performance Enhancement
  
  • Han Menglin
  • Cai Hao
  • Yang Jun
  • Naviner Lirida
  • Wang You
  • Zhao Weisheng
  , 2018, pp.386-389. Spin transfer torque magnetic random access memory (STT-MRAM) is one of the most promising candidates for the next-generation nonvolatile memory (NVM). However, as the process dimension and supply voltage continue to decrease, the yield of the sensing amplifier is reduced. In this work, the proposed sensing block with high margin, speed and stability (HMSS) with performance enhancement can be applied to variability emphasized MRAM design. The sensing circuit is implemented with a 28-nm CMOS process and a perpendicular magnetic anisotropy (PMA) magnetic tunnel junctions (p-MTJ) based compact model. Working at low voltage with high speed and yield is the main goal of the designed HMSS sensing amplifier (HMSS-SA). For near-threshold operation, at the voltage of 700 mV, the yield of HMSS-SA is 2.06x by transistor sizing, reaching 4.1%. And the speed is increased by 33% by transistor sizing, reaching 0.09 ns with the power of 18.27 μW. The performance of HMSS drops by 0.85% yield and 0.05 ns speed at 0.7 V compared to the 1 V supply voltage which shows that the proposed HMSS-SA has excellent performance at low supply voltages. (10.1109/APCCAS.2018.8605603)
  DOI : 10.1109/APCCAS.2018.8605603
• Experimental characterization of an SOA-based photonic integrated switch
  
  • Freire Hermelo Maria José
  • de Carvalho Rodrigues Eloise
  • Atchutananda Surampudi
  • Gillet Franck
  • Ware Cédric
  • Lavignotte Antoine
  • Lepers Catherine
  , 2018, pp.1 - 3. A semiconductor Optical Amplifier (SOA)-based 2x2 photonic integrated switch has been designed and fabricated in the framework of the ANR N-GREEN project (1),(2). Here, we report on the experimental setup and the results obtained for both static and dynamic characterizations of the switch. The input power dynamic range of the switch, in transparency, is more than 10 dB for both single and multiple channel dynamic configurations. Furthermore, in order to maintain a bit error rate of 10-9, the measured power penalty between the single and the multiple channel cases is less than 3dB for an input power of O dBm injected into the switch (10.1109/ACP.2018.8595878)
  DOI : 10.1109/ACP.2018.8595878
• Learning from ranking data : theory and methods
  
  • Korba Anna
  , 2018. Ranking data, i.e., ordered list of items, naturally appears in a wide variety of situations, especially when the data comes from human activities (ballots in political elections, survey answers, competition results) or in modern applications of data processing (search engines, recommendation systems). The design of machine-learning algorithms, tailored for these data, is thus crucial. However, due to the absence of any vectorial structure of the space of rankings, and its explosive cardinality when the number of items increases, most of the classical methods from statistics and multivariate analysis cannot be applied in a direct manner. Hence, a vast majority of the literature rely on parametric models. In this thesis, we propose a non-parametric theory and methods for ranking data. Our analysis heavily relies on two main tricks. The first one is the extensive use of the Kendall’s tau distance, which decomposes rankings into pairwise comparisons. This enables us to analyze distributions over rankings through their pairwise marginals and through a specific assumption called transitivity, which prevents cycles in the preferences from happening. The second one is the extensive use of embeddings tailored to ranking data, mapping rankings to a vector space. Three different problems, unsupervised and supervised, have been addressed in this context: ranking aggregation, dimensionality reduction and predicting rankings with features.The first part of this thesis focuses on the ranking aggregation problem, where the goal is to summarize a dataset of rankings by a consensus ranking. Among the many ways to state this problem stands out the Kemeny aggregation method, whose solutions have been shown to satisfy many desirable properties, but can be NP-hard to compute. In this work, we have investigated the hardness of this problem in two ways. Firstly, we proposed a method to upper bound the Kendall’s tau distance between any consensus candidate (typically the output of a tractable procedure) and a Kemeny consensus, on any dataset. Then, we have casted the ranking aggregation problem in a rigorous statistical framework, reformulating it in terms of ranking distributions, and assessed the generalization ability of empirical Kemeny consensus.The second part of this thesis is dedicated to machine learning problems which are shown to be closely related to ranking aggregation. The first one is dimensionality reduction for ranking data, for which we propose a mass-transportation approach to approximate any distribution on rankings by a distribution exhibiting a specific type of sparsity. The second one is the problem of predicting rankings with features, for which we investigated several methods. Our first proposal is to adapt piecewise constant methods to this problem, partitioning the feature space into regions and locally assigning as final label (a consensus ranking) to each region. Our second proposal is a structured prediction approach, relying on embedding maps for ranking data enjoying theoretical and computational advantages.
• Combinatorial characterization of asynchronous distributed computability
  
  • Rieutord Thibault
  , 2018. Modern computing systems are distributed, ranging from single-chip multi-processors to large-scale internet systems. In this thesis, we study computability and complexity issues raising in asynchronous crash-prone shared memory systems.The major part of this thesis is devoted to characterizing the power of a shared memory model to solve distributed tasks. Our first contribution is a refined and extended agreement-based simulation technique that allows us to reason about the relative task computability of shared-memory models. Using this simulation technique, we show that the task computability of a shared-memory adversarial model is grasped by its ability to solve specific agreement tasks. We then use the language of combinatorial topology to characterize the task computability of shared-memory models via affine tasks: sub-complexes of a finite iteration of the standard chromatic subdivision. Our characterization applies to the wait-free model enhanced with k-test-and-set objects and a to large class of fair adversarial models. These results generalize and improve all previously derived topological characterizations of the task computability power of shared memory models.In the second part of the thesis, we focus on space complexity of implementing stable storage, i.e., ensuring that written values persists in memory, in the comparison-based model using multi-writer registers. Our results exhibit a non-trivial tradeoff between space complexity of stable-storage implementations and the progress guarantees they provide.
• Procédé de traitement d'un signal audio et dispositif électronique correspondant, produit-programme lisible par ordinateur non transitoire et support d'informations lisible par ordinateur
  
  • Parekh Sanjeel
  • Ozerov Alexey
  • Duong Quang-Khanh-Ngoc
  • Richard Gael
  • Essid Slim
  • Pérez Patrick
  , 2018.
• Analysis of Cryptographic Algorithms on IoT Hardware platforms
  
  • El-Haii Mohammed
  • Chamoun Maroun
  • Fadlallah Ahmad
  • Serhrouchni Ahmed
  , 2018, pp.1-5. Internet of Things (IoT) systems are slowly but steadily becoming part of different aspects of our lives, with their applications ranging from smart homes, to wearable devices, to healthcare, etc. Traditional cryptographic schemes might not be suitable to be implemented on resource limited IoT devices. The decision to utilize a certain cryptographic algorithm, is mainly based on a tradeoff between security and performance, i.e. power consumption. A benchmark of these different cryptographic algorithms on IoT platforms is a must for security architects while designing their protocols and schemes. This paper presents a benchmark of the most known cryptographic algorithms on the Raspberry Pi platform, with a comparison with Arduino benchmark results provided in the literature. (10.1109/CSNET.2018.8602942)
  DOI : 10.1109/CSNET.2018.8602942
• Mémorisation de Commandes: Positions Spatiales versus Gestes Directionnels
  
  • Fruchard Bruno
  • Lecolinet Eric
  • Chapuis Olivier
  , 2018, pp.92–99. Pour exécuter une commande, l’utilisateur peut effectuer une sélection dans un menu à l’aide d’actions de pointage, ou bien, par exemple, utiliser des raccourcis tels que des gestes. Pour aller plus vite, il peut apprendre les positions à pointer ou les gestes à exécuter. Nous présentons dans cet article une étude comparant l’apprentissage de positions et de directions pour sélectionner des commandes. Les résultats obtenus révèlent des taux de rappel sim- ilaires, avec un léger avantage pour les positions. Les résultats qualitatifs suggèrent un avantage des positions sur les gestes en ce qui concerne l’effort physique et cognitif. Finalement, l’étude des stratégies de mémorisation élaborées par les sujets fournit des méthodes mnémoniques pouvant être utiles aux designers et aux utilisateurs. (10.1145/3286689.3286700)
  DOI : 10.1145/3286689.3286700
• Expériences utilisateurs de piétons âgés avec deux dispositifs de navigation portatifs : étude en environnement naturel
  
  • Montuwy Angélique
  • Cahour Béatrice
  • Dommes Aurélie
  , 2018, pp.63-72. Designing navigation aids for older pedestrians could help them stay autonomous in their daily activities. Here we present a rich description of the navigation experience of older pedestrians either with visual (augmented reality glasses) or auditory (bone conduction headphones) wearable devices adapted to age- related declines. In a study with 18 participants we measured the navigation performance and applied the Explicitation Interview Technique to capture detailed descriptions of the users’ experience. We highlight three main phenomena which impact the quality of the user experience with the two devices: (1) the transformation of the peripheral awareness, (2) the contextualization of information, and (3) the emergence of feelings along the route. This study adds a new understanding of the navigation experience by older people and is discussed in terms of design recommendations for navigation devices.
• Ultra-Wideband and Wide-Angle Microwave Metamaterial Absorber
  
  • Begaud Xavier
  • Lepage Anne Claire
  • Varault Stefan
  • Soiron Michel
  • Barka André
  Materials, MDPI, 2018, 11 (2045), pp.1-9. In order to extend the performance of radar absorbing materials, it is necessary to design new structures with wideband properties and large angles of incidence which are also as thin as possible. The objective of this work, realized within the framework of the SAFAS project (self-complementary surface with low signature) is, then, the development of an ultra-wideband microwave absorber of low thickness. The design of such material requires a multilayered structure composed with dielectric layers, metasurfaces, and wide-angle impedance matching layers. This solution has been realized with on-the-shelf materials, and measured to validate the concept. At normal incidence, the bandwidth ratio, defined for a magnitude of the reflection coefficient below -10 dB, is 4.7:1 for an absorber with a total thickness of 11.5 mm, which corresponds to ʎ/7 at the lowest operating frequency. For an incidence of 60°, this bandwidth ratio is reduced to 3.8:1, but the device remains ultra-wideband. (10.3390/ma11102045)
  DOI : 10.3390/ma11102045
• Understanding the experiences of schooling of visually impaired children
  
  • Brulé Emeline
  , 2018. In 2005, France passed a law on equal rights and opportunities, participation and citizenship of people with disabilities. It consecrated the right of all children to attend their neighbourhood school and reorganized the provision of services to this population, including the provision of assistive technologies. This research conducted a decade later between 2014 and 2017, investigates visually impaired children’s experiences of schooling and the roles of technologies in supporting their well-being at school. I developed a mixed-methods interdisciplinary approach, blending qualitative sociological research with Human-Computer Interaction experiments. Specifically, I conducted a two-years-long ethnographic study at a service provider for visually impaired children in the South of France, during which I made several design interventions. This field-work is contextualized by a critical review of the statistics on the schooling of visually impaired children provided by the Ministry of Education. I use an ecological understanding of resilience to examine children’s narratives about school, across different schooling modalities (e.g., mainstream and special education school) and sociodemographic characteristics. I discuss the resources and strategies children and their carers use to open opportunities for well-being at school, including uses of technologies. I contextualize these by investigating desirable schooling outcomes that define who is resilient and what resilience is for. From there I propose to develop a non-visual approach to the (geography) curriculum inspired by the sensory turn. By changing what is considered as a valued way of learning, this thesis aims at providing opportunities to develop the sense of belonging and the perception of self-efficacy in the classroom. It informs us on the uses of hearing, smell, taste, and kinesthesia in geography; it supports pupils in reshaping of the learning activities and spaces; Finally, it opens opportunities for collective geographical knowledge rooted in experiences of social inequalities. More broadly, it opens a discussion on building collective well-being and resilience in schools.
• Wide band digital predistortion using iterative feedback decomposition
  
  • Shokair Ahmad
  • Beydoun Ali
  • Pham Dang-Kièn Germain
  • Jabbour Chadi
  • Desgreys Patricia
  Analog Integrated Circuits and Signal Processing, Springer Verlag, 2018, 100 (1), pp.93-108. (10.1007/s10470-018-1347-6)
  DOI : 10.1007/s10470-018-1347-6