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  • Mémoires en Sciences de l'Information et de la Communication
  • Hal-Diderot

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  • Open Access English
    Authors: 
    Antonio Alguacil; Michaël Bauerheim; Marc C. Jacob; Stéphane Moreau;
    Country: France

    International audience; A deep learning surrogate for the direct numerical prediction of two-dimensional acoustic waves propagation and scattering with obstacles is developed through an auto-regressive spatio- temporal convolutional neural network. A single database of high-fidelity lattice Boltzmann temporal simulations is employed in the training of the network, achieving accurate predictions for long simulation times for a variety of test cases, representative of bounded and unbounded configurations. The capacity of the network to extrapolate outside the manifold of examples seen during the training phase is demonstrated by the obtaining of accurate acoustic predic- tions for relevant applications, such as the scattering of acoustic waves on an airfoil trailing edge, an engine nacelle or in-duct propagation. The method is tested for two types of input normalizations, coupled with an a-posteriori correction which improves the acoustic energy conservation of the predictions. The use of an adaptive local normalization along with the physics-based energy conservation results in an error reduction for all the studied cases.

  • English
    Authors: 
    Dhaou Said; Soumaya Cherkaoui; Lyes Khoukhi;
    Publisher: HAL CCSD
    Country: France

    In this paper, a scheduling protocol for electric vehicle (EV) home charging with time of use pricing is introduced. This work addresses the problem of EVs charging at home by adopting an appropriate charging process protocol over Power Line Communications (PLC). The scheduling protocol is aimed at minimizing peak loads on distribution feeders due to multiple EVs charging while using a time-of-use pricing policy. Energy efficiency and performance are both taken into account. An appropriate analytical formulation of the scheduling problem is given together with the proposed scheduling protocol. Simulations demonstrate the effectiveness of the proposed approach in minimizing peak loads while satisfying the defined constraints.

  • Publication . Part of book or chapter of book . Conference object . Preprint . 2019
    Open Access
    Authors: 
    Quentin Roy; Camelia Zakaria; Simon T. Perrault; Mathieu Nancel; Wonjung Kim; Archan Misra; Andy Cockburn;
    Publisher: Center for Open Science
    Country: France

    Part 8: Pointing, Touch, Gesture and Speech-Based Interaction Techniques; International audience; Eyewear displays allow users to interact with virtual content displayed over real-world vision, in active situations like standing and walking. Pointing techniques for eyewear displays have been proposed, but their social acceptability, efficiency, and situation awareness remain to be assessed. Using a novel street-walking simulator, we conducted an empirical study of target acquisition while standing and walking under different levels of street crowdedness. We evaluated three phone-based eyewear pointing techniques: indirect touch on a touchscreen, and two in-air techniques using relative device rotations around forward and a downward axes. Direct touch on a phone, without eyewear, was used as a control condition. Results showed that indirect touch was the most efficient and socially acceptable technique, and that in-air pointing was inefficient when walking. Interestingly, the eyewear displays did not improve situation awareness compared to the control condition. We discuss implications for eyewear interaction design.

  • Open Access English
    Authors: 
    Xavier Bultel; Sébastien Gambs; David Gérault; pascal lafourcade; Cristina Onete; Jean-Marc Robert;
    Publisher: HAL CCSD
    Country: France
    Project: NSERC

    International audience; Les communications sans contact sont omniprésentes dans notre quotidien, allant des badges de contrôle d'accès au passeport électronique. Ces systèmes sont sensibles aux attaques par relais, dans lesquelles un adversaire transfère simplement les messages entre le prouveur et le vérifieur pour usurper l'identité du prouveur. Les protocoles délimiteurs de distance (distance-bounding) ont été ont ntroduits pour contrer ces attaques en assurant une borne sur la distance entre le prouveur et le vérifieur grâcè a la mesure du temps des communications. Par la suite de nombreux travaux ont amélioré la sécurité de ces protocoles, mais ont aussi cherché à assurer le respect de la vie privée face à des adversaires actifs et également face à des vérifieurs malicieux. En particulier, une menace difficile à prévenir est la fraude terroriste, où un prouveur lointain coopère avec un complice proche pour tromper le vérifieur. La contre-mesure usuelle pour cette menace est de rendre impossible l'action du complice sans l'aide du prouveur lointain, à moins que le prouveur ne lui donne suffisamment d'information pour qu'il retrouve sa clef privée et puisse ainsi toujours se faire passer pour le prouveur. Dans cet article, nous proposons une nouvelle approche où le prouveur ne révèle pas sa clef privée mais utilise une clef de session avec une signature de groupe, la rendant ainsi utilisable plusieurs fois. Ceci permet à un adversaire d'usurper l'identité du prouveur sans même connaître sa clef de signature. Grâce à cette approche nous proposons SPADE le premier protocole de délimiteur de distance qui est anonyme, révocable et formellement prouvé sûr. Mots-clefs : Protocole délimiteur de distance (Distance Bounding), Sécurité, résitance à la fraude terroriste.

  • French
    Authors: 
    Allard, Daniele; Mizoguchi, Riichiro; Bourdeau, Jacqueline;
    Publisher: HAL CCSD
    Country: France

    This research project aims to design a CALL system (Computer-Assisted Language Learning). The goal of the system is to help users overcome cross-linguistic difficulties, that is to say, transfer and interference stemming from a native language (L1) in the process of acquiring a second or foreign language (L2). It is built following an ontological engineering methodology, which is well-known in the artificial intelligence community. In this article, we describe what is cross-linguistic influence, provide a concrete example of what it might entail, and briefly explain how the system might work along with our research methodology.

  • Publication . Conference object . Part of book or chapter of book . 2021
    Open Access English
    Authors: 
    Song Wang; Yuting He; Youyong Kong; Xiaomei Zhu; Shaobo Zhang; Pengfei Shao; Jean-Louis Dillenseger; Jean-Louis Coatrieux; Shuo Li; Guanyu Yang;
    Publisher: HAL CCSD
    Country: France

    Renal compartment segmentation on CT images targets on extracting the 3D structure of renal compartments from abdominal CTA images and is of great significance to the diagnosis and treatment for kidney diseases. However, due to the unclear compartment boundary, thin compartment structure and large anatomy variation of 3D kidney CT images, deep-learning based renal compartment segmentation is a challenging task. We propose a novel weakly supervised learning framework, Cycle Prototype Network, for 3D renal compartment segmentation. It has three innovations: (1) A Cycle Prototype Learning (CPL) is proposed to learn consistency for generalization. It learns from pseudo labels through the forward process and learns consistency regularization through the reverse process. The two processes make the model robust to noise and label-efficient. (2) We propose a Bayes Weakly Supervised Module (BWSM) based on cross-period prior knowledge. It learns prior knowledge from cross-period unlabeled data and perform error correction automatically, thus generates accurate pseudo labels. (3) We present a Fine Decoding Feature Extractor (FDFE) for fine-grained feature extraction. It combines global morphology information and local detail information to obtain feature maps with sharp detail, so the model will achieve fine segmentation on thin structures. Our extensive experiments demonstrated our great performance. Our model achieves Dice of \(79.1\%\) and \(78.7\%\) with only four labeled images, achieving a significant improvement by about \(20\%\) than typical prototype model PANet [16].

  • Publication . Other literature type . Part of book or chapter of book . Conference object . 2019
    Open Access English
    Authors: 
    Ebizimoh Abodei; Alex Norta; Irene Azogu; Chibuzor Udokwu; Dirk Draheim;
    Publisher: HAL CCSD
    Country: France

    Part 7: Digital Governance; International audience; Infrastructural development is a significant determinant of economic growth. It remains an elusive pursuit for many developing economies suffering from public infrastructural project failures. Although the causes of these failures are identifiable, they remain persistent. Government corruption has been identified as the primary cause of project failures amidst a host of other causal factors, spurred by the ambiguity in public service administration. These factors heighten capital expenditures and hence, the need for more transparent systems in public infrastructural project planning and -delivery. This research uses a case-study methodology to examine the importance of public involvement in addressing the causes of failures in public infrastructural project planning and -delivery. Using Nigeria as a case, the findings from conducted interviews and a document review support the proposition of a technologically collaborative approach in addressing the causes of public infrastructural project failures. The institutionalization of transparency-enhancing blockchain systems are vital in government and public involvement in the processes of public infrastructural project planning and -delivery.

  • Open Access English
    Authors: 
    Franck Enguehard; E. Lafond; D. Souche; Marc Dubois; Jean-Charles Gonthier; Lionel Bertrand;
    Publisher: HAL CCSD
    Country: France

    International audience; We present results of photoacoustics and laser-ultrasonics experiments that were performed on a ZnO ceramic sample and that led to optical, thermal and thermo-mechanical characterizations of this material.

  • Publication . Part of book or chapter of book . Conference object . 2008
    Open Access English
    Authors: 
    Linqiao Zhang; Hazel Everett; Sylvain Lazard; Christophe Weibel; Sue Whitesides;
    Publisher: HAL CCSD
    Country: France

    International audience; The 3D visibility skeleton is a data structure used to encode global visibility information about a set of objects. Previous theoretical results have shown that for $k$ convex polytopes with $n$ edges in total, the worst case size complexity of this data structure is $\Theta(n^2 k^2) $ [Brˆnnimann et al. 07]; whereas for $k$ uniformly distributed unit spheres, the expected size is $\Theta(k)$ [Devillers et al. 03]. In this paper, we study the size of the visibility skeleton experimentally. Our results indicate that the size of the 3D visibility skeleton, in our setting, is $ C\,k\sqrt{n\,k}$, where $C$ varies with the scene density but remains small. % This is the first experimentally determined asymptotic estimate of the size of the 3D visibility skeleton for reasonably large $n$ and expressed in terms of both $n$ and $k$. We suggest theoretical explanations for the experimental results we obtained. Our experiments also indicate that the running time of our implementation is $O(n^{3/2} k\log k)$, while its worst-case running time complexity is $O(n^2k^2 \log k)$.

  • Publication . Other literature type . Conference object . 2009
    Open Access
    Authors: 
    Bombrun, Lionel; Beaulieu, Jean-Marie; Vasile, Gabriel; Ovarlez, Jean-Philippe; Pascal, Frédéric; Gay, Michel;
    Publisher: IEEE
    Country: France

    International audience; In this paper, heterogeneous clutter models are introduced to describe Polarimetric Synthetic Aperture Radar (PolSAR) data. Based on the Spherically Invariant Random Vectors (SIRV) estimation scheme, the scalar texture parameter and the normalized covariance matrix are extracted. If the texture parameter is modeled by a Fisher PDF, the observed target scattering vector follows a KummerU PDF. Then, this PDF is implemented in a hierarchical segmentation algorithm. Segmentation results are shown on high resolution PolSAR data at L and X band.

Advanced search in
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
3,411 Research products, page 1 of 342
  • Open Access English
    Authors: 
    Antonio Alguacil; Michaël Bauerheim; Marc C. Jacob; Stéphane Moreau;
    Country: France

    International audience; A deep learning surrogate for the direct numerical prediction of two-dimensional acoustic waves propagation and scattering with obstacles is developed through an auto-regressive spatio- temporal convolutional neural network. A single database of high-fidelity lattice Boltzmann temporal simulations is employed in the training of the network, achieving accurate predictions for long simulation times for a variety of test cases, representative of bounded and unbounded configurations. The capacity of the network to extrapolate outside the manifold of examples seen during the training phase is demonstrated by the obtaining of accurate acoustic predic- tions for relevant applications, such as the scattering of acoustic waves on an airfoil trailing edge, an engine nacelle or in-duct propagation. The method is tested for two types of input normalizations, coupled with an a-posteriori correction which improves the acoustic energy conservation of the predictions. The use of an adaptive local normalization along with the physics-based energy conservation results in an error reduction for all the studied cases.

  • English
    Authors: 
    Dhaou Said; Soumaya Cherkaoui; Lyes Khoukhi;
    Publisher: HAL CCSD
    Country: France

    In this paper, a scheduling protocol for electric vehicle (EV) home charging with time of use pricing is introduced. This work addresses the problem of EVs charging at home by adopting an appropriate charging process protocol over Power Line Communications (PLC). The scheduling protocol is aimed at minimizing peak loads on distribution feeders due to multiple EVs charging while using a time-of-use pricing policy. Energy efficiency and performance are both taken into account. An appropriate analytical formulation of the scheduling problem is given together with the proposed scheduling protocol. Simulations demonstrate the effectiveness of the proposed approach in minimizing peak loads while satisfying the defined constraints.

  • Publication . Part of book or chapter of book . Conference object . Preprint . 2019
    Open Access
    Authors: 
    Quentin Roy; Camelia Zakaria; Simon T. Perrault; Mathieu Nancel; Wonjung Kim; Archan Misra; Andy Cockburn;
    Publisher: Center for Open Science
    Country: France

    Part 8: Pointing, Touch, Gesture and Speech-Based Interaction Techniques; International audience; Eyewear displays allow users to interact with virtual content displayed over real-world vision, in active situations like standing and walking. Pointing techniques for eyewear displays have been proposed, but their social acceptability, efficiency, and situation awareness remain to be assessed. Using a novel street-walking simulator, we conducted an empirical study of target acquisition while standing and walking under different levels of street crowdedness. We evaluated three phone-based eyewear pointing techniques: indirect touch on a touchscreen, and two in-air techniques using relative device rotations around forward and a downward axes. Direct touch on a phone, without eyewear, was used as a control condition. Results showed that indirect touch was the most efficient and socially acceptable technique, and that in-air pointing was inefficient when walking. Interestingly, the eyewear displays did not improve situation awareness compared to the control condition. We discuss implications for eyewear interaction design.

  • Open Access English
    Authors: 
    Xavier Bultel; Sébastien Gambs; David Gérault; pascal lafourcade; Cristina Onete; Jean-Marc Robert;
    Publisher: HAL CCSD
    Country: France
    Project: NSERC

    International audience; Les communications sans contact sont omniprésentes dans notre quotidien, allant des badges de contrôle d'accès au passeport électronique. Ces systèmes sont sensibles aux attaques par relais, dans lesquelles un adversaire transfère simplement les messages entre le prouveur et le vérifieur pour usurper l'identité du prouveur. Les protocoles délimiteurs de distance (distance-bounding) ont été ont ntroduits pour contrer ces attaques en assurant une borne sur la distance entre le prouveur et le vérifieur grâcè a la mesure du temps des communications. Par la suite de nombreux travaux ont amélioré la sécurité de ces protocoles, mais ont aussi cherché à assurer le respect de la vie privée face à des adversaires actifs et également face à des vérifieurs malicieux. En particulier, une menace difficile à prévenir est la fraude terroriste, où un prouveur lointain coopère avec un complice proche pour tromper le vérifieur. La contre-mesure usuelle pour cette menace est de rendre impossible l'action du complice sans l'aide du prouveur lointain, à moins que le prouveur ne lui donne suffisamment d'information pour qu'il retrouve sa clef privée et puisse ainsi toujours se faire passer pour le prouveur. Dans cet article, nous proposons une nouvelle approche où le prouveur ne révèle pas sa clef privée mais utilise une clef de session avec une signature de groupe, la rendant ainsi utilisable plusieurs fois. Ceci permet à un adversaire d'usurper l'identité du prouveur sans même connaître sa clef de signature. Grâce à cette approche nous proposons SPADE le premier protocole de délimiteur de distance qui est anonyme, révocable et formellement prouvé sûr. Mots-clefs : Protocole délimiteur de distance (Distance Bounding), Sécurité, résitance à la fraude terroriste.

  • French
    Authors: 
    Allard, Daniele; Mizoguchi, Riichiro; Bourdeau, Jacqueline;
    Publisher: HAL CCSD
    Country: France

    This research project aims to design a CALL system (Computer-Assisted Language Learning). The goal of the system is to help users overcome cross-linguistic difficulties, that is to say, transfer and interference stemming from a native language (L1) in the process of acquiring a second or foreign language (L2). It is built following an ontological engineering methodology, which is well-known in the artificial intelligence community. In this article, we describe what is cross-linguistic influence, provide a concrete example of what it might entail, and briefly explain how the system might work along with our research methodology.

  • Publication . Conference object . Part of book or chapter of book . 2021
    Open Access English
    Authors: 
    Song Wang; Yuting He; Youyong Kong; Xiaomei Zhu; Shaobo Zhang; Pengfei Shao; Jean-Louis Dillenseger; Jean-Louis Coatrieux; Shuo Li; Guanyu Yang;
    Publisher: HAL CCSD
    Country: France

    Renal compartment segmentation on CT images targets on extracting the 3D structure of renal compartments from abdominal CTA images and is of great significance to the diagnosis and treatment for kidney diseases. However, due to the unclear compartment boundary, thin compartment structure and large anatomy variation of 3D kidney CT images, deep-learning based renal compartment segmentation is a challenging task. We propose a novel weakly supervised learning framework, Cycle Prototype Network, for 3D renal compartment segmentation. It has three innovations: (1) A Cycle Prototype Learning (CPL) is proposed to learn consistency for generalization. It learns from pseudo labels through the forward process and learns consistency regularization through the reverse process. The two processes make the model robust to noise and label-efficient. (2) We propose a Bayes Weakly Supervised Module (BWSM) based on cross-period prior knowledge. It learns prior knowledge from cross-period unlabeled data and perform error correction automatically, thus generates accurate pseudo labels. (3) We present a Fine Decoding Feature Extractor (FDFE) for fine-grained feature extraction. It combines global morphology information and local detail information to obtain feature maps with sharp detail, so the model will achieve fine segmentation on thin structures. Our extensive experiments demonstrated our great performance. Our model achieves Dice of \(79.1\%\) and \(78.7\%\) with only four labeled images, achieving a significant improvement by about \(20\%\) than typical prototype model PANet [16].

  • Publication . Other literature type . Part of book or chapter of book . Conference object . 2019
    Open Access English
    Authors: 
    Ebizimoh Abodei; Alex Norta; Irene Azogu; Chibuzor Udokwu; Dirk Draheim;
    Publisher: HAL CCSD
    Country: France

    Part 7: Digital Governance; International audience; Infrastructural development is a significant determinant of economic growth. It remains an elusive pursuit for many developing economies suffering from public infrastructural project failures. Although the causes of these failures are identifiable, they remain persistent. Government corruption has been identified as the primary cause of project failures amidst a host of other causal factors, spurred by the ambiguity in public service administration. These factors heighten capital expenditures and hence, the need for more transparent systems in public infrastructural project planning and -delivery. This research uses a case-study methodology to examine the importance of public involvement in addressing the causes of failures in public infrastructural project planning and -delivery. Using Nigeria as a case, the findings from conducted interviews and a document review support the proposition of a technologically collaborative approach in addressing the causes of public infrastructural project failures. The institutionalization of transparency-enhancing blockchain systems are vital in government and public involvement in the processes of public infrastructural project planning and -delivery.

  • Open Access English
    Authors: 
    Franck Enguehard; E. Lafond; D. Souche; Marc Dubois; Jean-Charles Gonthier; Lionel Bertrand;
    Publisher: HAL CCSD
    Country: France

    International audience; We present results of photoacoustics and laser-ultrasonics experiments that were performed on a ZnO ceramic sample and that led to optical, thermal and thermo-mechanical characterizations of this material.

  • Publication . Part of book or chapter of book . Conference object . 2008
    Open Access English
    Authors: 
    Linqiao Zhang; Hazel Everett; Sylvain Lazard; Christophe Weibel; Sue Whitesides;
    Publisher: HAL CCSD
    Country: France

    International audience; The 3D visibility skeleton is a data structure used to encode global visibility information about a set of objects. Previous theoretical results have shown that for $k$ convex polytopes with $n$ edges in total, the worst case size complexity of this data structure is $\Theta(n^2 k^2) $ [Brˆnnimann et al. 07]; whereas for $k$ uniformly distributed unit spheres, the expected size is $\Theta(k)$ [Devillers et al. 03]. In this paper, we study the size of the visibility skeleton experimentally. Our results indicate that the size of the 3D visibility skeleton, in our setting, is $ C\,k\sqrt{n\,k}$, where $C$ varies with the scene density but remains small. % This is the first experimentally determined asymptotic estimate of the size of the 3D visibility skeleton for reasonably large $n$ and expressed in terms of both $n$ and $k$. We suggest theoretical explanations for the experimental results we obtained. Our experiments also indicate that the running time of our implementation is $O(n^{3/2} k\log k)$, while its worst-case running time complexity is $O(n^2k^2 \log k)$.

  • Publication . Other literature type . Conference object . 2009
    Open Access
    Authors: 
    Bombrun, Lionel; Beaulieu, Jean-Marie; Vasile, Gabriel; Ovarlez, Jean-Philippe; Pascal, Frédéric; Gay, Michel;
    Publisher: IEEE
    Country: France

    International audience; In this paper, heterogeneous clutter models are introduced to describe Polarimetric Synthetic Aperture Radar (PolSAR) data. Based on the Spherically Invariant Random Vectors (SIRV) estimation scheme, the scalar texture parameter and the normalized covariance matrix are extracted. If the texture parameter is modeled by a Fisher PDF, the observed target scattering vector follows a KummerU PDF. Then, this PDF is implemented in a hierarchical segmentation algorithm. Segmentation results are shown on high resolution PolSAR data at L and X band.

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