Underground Visualization: web-app, virtual reality, ex situ and in situ augmented reality.

International audienceIn this work-in-progress and demo paper, we present an ongoing experiment of underground visualization, in the context of urban 3D geovisualization, for operational purposes in urban planning. After a preliminary project of sewers network digitization (Nguyen et al., 2018), the 3D model of sewers has been made available for web visualization and interaction. In this paper, we show that it is possible to address various use contexts, when adding the ability to visualize and interact with the sewer 3D model in virtual reality (VR) and in ex situ / in situ augmented reality (AR). These experiments will be further experimented to validate our hypotheses to favor collaboration, immersion for simulation and training, and more secured urban development

Real bird dataset with imprecise and uncertain values

The theory of belief functions allows the fusion of imperfect data from different sources. Unfortunately, few real, imprecise and uncertain datasets exist to test approaches using belief functions. We have built real birds datasets thanks to the collection of numerous human contributions that we make available to the scientific community. The interest of our datasets is that they are made of human contributions, thus the information is therefore naturally uncertain and imprecise. These imperfections are given directly by the persons. This article presents the data and their collection through crowdsourcing and how to obtain belief functions from the data

Evidential uncertainties on rich labels for active learning

Recent research in active learning, and more precisely in uncertainty sampling, has focused on the decomposition of model uncertainty into reducible and irreducible uncertainties. In this paper, we propose to simplify the computational phase and remove the dependence on observations, but more importantly to take into account the uncertainty already present in the labels, \emph{i.e.} the uncertainty of the oracles. Two strategies are proposed, sampling by Klir uncertainty, which addresses the exploration-exploitation problem, and sampling by evidential epistemic uncertainty, which extends the reducible uncertainty to the evidential framework, both using the theory of belief functions

Étude de nouvelles méthodologies d'arylation directe en séries azole et pyridine (Application à la synthèse de coeurs de thiopeptides antibiotiques de la série d)

Face à l apparition grandissante de souches bactériennes multi-résistantes à l arsenal d antibiotiques actuels, les thiopeptides antibiotiques, bien que connus depuis plus de 60 ans, suscitent actuellement un fort regain d intérêt. En effet, cette classe de molécules présente une forte activité antibiotique contre des souches bactériennes résistantes et multirésistantes, et met en œuvre deux modes d inhibition originaux de la synthèse protéique encore inexploités en thérapie antibiotique humaine. Leur développement pharmacologique est en particulier freiné par la difficulté de préparation de ces molécules très complexes. L'élaboration d'une stratégie innovante de synthèse de la partie la plus complexe de ces molécules, le cœur hétérocyclique est étudiée dans ce travail. Cette approche repose sur l'étude et la valorisation de nouvelles méthodologies de fonctionnalisation directe des liaisons C-H et C-X de mono- et bis-thiazoles avec une large gamme d hétéroaromatiques. Sa viabilité est démontrée par la préparation du cœur hétérocyclique commun aux amythiamicines.Due to the emergence of multiresistant bacterial strains to standard antibacterial treatments, thiopeptides antibiotics are actually highly considered, though they are known for 60 years. They show an excellent antibiotic activity against multiresistant bacterial strains, and implement two originals inhibition mechanisms of protein synthesis, still unemployed in human therapy. However, the difficulty to prepare these complex macromolecules limits their pharmacological development. The development of a new strategy to synthetize the most complicated part of these macromolecules, their heterocyclic core, is studied here in. This approach is based on the study and the exploitation of novel direct C-H and C-X transition-metal-catalyzed couplings of mono- and bithiazoles units with a broad panel of heteroaromatics. Its viability is here demonstrated trough the multi-step synthesis of the common heterocyclic core of amythiamicins.ROUEN-INSA Madrillet (765752301) / SudocSudocFranceF

Large eddy simulation of turbomachinery flows using a high-order implicit residual smoothing scheme

A recently developed fourth-order accurate implicit residual smoothing scheme (IRS4) is investigated for the large eddy simulation of turbomachinery flows, characterized by moderate to high Reynolds numbers and subject to severe constraints on the maximum allowable time step if an explicit scheme is used. For structured multi-block meshes, the proposed approach leads to the inversion of a scalar pentadiagonal system by mesh direction, which can be done very efficiently. On the other hand, applying IRS4 at each stage of an explicit Runge–Kutta time scheme allows to increase the time step by a factor 5 to 10, leading to substantial savings in terms of overall computational time. With respect to standard second-order fully implicit approaches, the IRS4 does not require approximate linearization and factorization procedures nor inner Newton-Raphson subiterations. As a consequence, it represents a better cost-accuracy compromise for the numerical simulations of turbulent flows where the maximum time step is controlled by the lifetime of the smallest resolved turbulent structures. Numerical results for the well-documented high-pressure VKI LS-89 planar turbine cascade illustrate the potential of IRS4 for significantly reducing the overall cost of turbomachinery large eddy simulations, while preserving an accuracy similar to the explicit solver even for sensitive quantities like the heat transfer coefficient and the turbulent kinetic energy field

3D URBAN GEOVISUALIZATION: IN SITU AUGMENTED AND MIXED REALITY EXPERIMENTS

In this paper, we assume that augmented reality (AR) and mixed reality (MR) are relevant contexts for 3D urban geovisualization, especially in order to support the design of the urban spaces. We propose to design an in situ MR application, that could be helpful for urban designers, providing tools to interactively remove or replace buildings in situ. This use case requires advances regarding existing geovisualization methods. We highlight the need to adapt and extend existing 3D geovisualization pipelines, in order to adjust the specific requirements for AR/MR applications, in particular for data rendering and interaction. In order to reach this goal, we focus on and implement four elementary in situ and ex situ AR/MR experiments: each type of these AR/MR experiments helps to consider and specify a specific subproblem, i.e. scale modification, pose estimation, matching between scene and urban project realism, and the mix of real and virtual elements through portals, while proposing occlusion handling, rendering and interaction techniques to solve them

Silicene on Ag(111): domains and local defects of the observed superstructures

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Real bird dataset with imprecise and uncertain values

International audienceThe theory of belief functions allows the fusion of imperfect data from different sources. Unfortunately, few real, imprecise and uncertain datasets exist to test approaches using belief functions. We have built real birds datasets thanks to the collection of numerous human contributions that we make available to the scientific community. The interest of our datasets is that they are made of human contributions, thus the information is therefore naturally uncertain and imprecise. These imperfections are given directly by the persons. This article presents the data and their collection through crowdsourcing and how to obtain belief functions from the data