• Publicationsclose
• 2017-2021close
• Conference object close
• CA close
• AT close
• Mémoires en Sciences de l'Information et de la Communication close
• HAL AMU close

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.

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.

International audience; The purposes of this study were to: (a) identify emotion profiles of athletes involved in an intensive training setting across three measurement points (beginning, middle and end of the season); (b) explore the stability and change of those emotion profiles over the season; and (c) examine if self-determined motivation predicts membership to the emotion profiles. Method: Three hundred and forty-three adolescent athletes in intensive training settings filled out measures of emotions (sadness, anxiety, anger, happiness, confidence, love, harmony, and vitality) and self-determined motivation (autonomous and controlled). Data were analyzed using a latent profile transition analysis (LPTA) approach. Design: longitudinal three-wave design. Results: LPTA results revealed four emotion profiles: High positive emotions (PE) and low negative emotions (NE), moderately high PE and low NE, moderately high PE and NE, and moderate PE and NE. Individuals exhibited both changes and stability in their emotion profile over time. Membership of emotion profiles were predicted by autonomous and controlled motivation assessed at baseline. Conclusions: The emotion profile approach was proven useful in understanding emotions experienced over time by adolescent athletes involved in intensive training settings and has implications for psychological intervention.

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.

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].

The beta decay of the free neutron provides several probes to test the Standard Model of particle physics as well as to search for extensions thereof. Hence, multiple experiments investigating the decay have already been performed, are under way or are being prepared. These measure the mean lifetime, angular correlation coefficients or various spectra of the charged decay products (proton and electron). NoMoS, the Neutron decay prOducts MOmentum Spectrometer, presents a novel method of momentum spectroscopy: it utilizes the $R \times B$ drift effect to disperse charged particles dependent on their momentum in an uniformly curved magnetic field. This spectrometer is designed to precisely measure momentum spectra and angular correlation coefficients in free neutron beta decay to test the Standard Model and to search for new physics beyond. With NoMoS, we aim to measure inter alia the electron-antineutrino correlation coefficient $a$ and the Fierz interference term $b$ with an ultimate precision of $\Delta a/a < 0.3\%$ and $\Delta b < 10^{-3}$ respectively. In this paper, we present the measurement principles, discuss measurement uncertainties and systematics, and give a status update. Comment: 7 pages, 4 figures, accepted to the Proceedings of the International Workshop on Particle Physics at Neutron Sources PPNS 2018, Grenoble, France, May 24-26, 2018

International audience; In many disaster scenarios, communication infrastructure fails to provide network services for both civilians and first responders. One solution is to have rapidly deployable mobile networks formed by interconnected base stations, that are easy to move, deploy, and configure. Such public safety-oriented networks are different from classical mobile networks in terms of scale, deployment, and architecture. In this context, we revisit the user association problem, for two main reasons. First, the backhaul, formed by the links interconnecting the base stations, must be accounted for when deciding on the association, since it may present a bottleneck with its limited bandwidth. Second, the mission-critical nature of the traffic imposes strict guaranteed bit rate constraints, that must be respected when associating users. Therefore, we propose a network-aware optimal association that minimizes the bandwidth consumption on the backhaul, while still respecting the stringent performance requirements.

International audience; Sliced Inverse Regression (SIR) has been extensively used to reduce the dimension of the predictor space before performing regression. SIR is originally a model free method but it has been shown to actually correspond to the maximum likelihood of an inverse regression model with Gaussian errors. This intrinsic Gaussianity of standard SIR may explain its high sensitivity to outliers as observed in a number of studies. To improve robustness, the inverse regression formulation of SIR is therefore extended to non-Gaussian errors with heavy-tailed distributions. Considering Student distributed errors it is shown that the inverse regression remains tractable via an Expectation- Maximization (EM) algorithm. The algorithm is outlined and tested in the presence of outliers, both in simulated and real data, showing improved results in comparison to a number of other existing approaches.

The emergence of electronic health records has highlighted the need for semantic standards for representation of observations in laboratory medicine. Two such standards are LOINC, with a focus on detailed encoding of lab tests, and SNOMED CT, which is more general, including the representation of qualitative and ordinal test results. In this paper we will discuss how lab observation entries can be represented using SNOMED CT. We use resources provided by the Regenstrief Institute and SNOMED International collaboration, which formalize LOINC terms as SNOMED CT post-coordinated expressions. We demonstrate the benefits brought by SNOMED CT to classify lab tests. We then propose a SNOMED CT based model for lab observation entries aligned with the BioTopLite2 (BTL2) upper level ontology. We provide examples showing how a model designed with no ontological foundation can produce misleading interpretations of inferred observation results. Our solution based on a BTL2 conformant formal interpretation of SNOMED CT concepts allows representing lab test without creating unintended models. We argue in favour of an ontologically explicit bridge between compositional clinical terminologies, in order to safely use their formal representations in intelligent systems.

International audience