Deep Learning for Metagenomic Data: using 2D Embeddings and Convolutional Neural Networks

Deep learning (DL) techniques have had unprecedented success when applied to images, waveforms, and texts to cite a few. In general, when the sample size (N) is much greater than the number of features (d), DL outperforms previous machine learning (ML) techniques, often through the use of convolution neural networks (CNNs). However, in many bioinformatics ML tasks, we encounter the opposite situation where d is greater than N. In these situations, applying DL techniques (such as feed-forward networks) would lead to severe overfitting. Thus, sparse ML techniques (such as LASSO e.g.) usually yield the best results on these tasks. In this paper, we show how to apply CNNs on data which do not have originally an image structure (in particular on metagenomic data). Our first contribution is to show how to map metagenomic data in a meaningful way to 1D or 2D images. Based on this representation, we then apply a CNN, with the aim of predicting various diseases. The proposed approach is applied on six different datasets including in total over 1000 samples from various diseases. This approach could be a promising one for prediction tasks in the bioinformatics field.Comment: Accepted at NIPS 2017 Workshop on Machine Learning for Health (https://ml4health.github.io/2017/); In Proceedings of the NIPS ML4H 2017 Workshop in Long Beach, CA, USA

Defining scanning trajectory for on-machine inspection using a laser-plane scanner

International audienceScan path planning for on-machine inspection in a 5-axis machine tool is still a challenge to measure part geometry in a minimum amount of time with a given scanning quality. Indeed, as the laser-plane scanner takes the place of the cutting tool, the time allocated to measurement must be reduced, but not at detrimental of the quality. In this direction, this paper proposes a method for scan path planning in a 5-axis machine tool with the control of scanning overlap. This method is an adaptation of a method dedicated to a robot that has proved its efficiency for part inspection

Quantum calculations of the carrier mobility in thin films: Methodology, Matthiessen's rule and comparison with semi-classical approaches

We discuss the calculation of the carrier mobility in silicon films within the quantum Non-Equilibrium Green's Functions (NEGF) framework. We introduce a new method for the extraction of the carrier mobility that is free from contact resistance contamination, and provides accurate mobilities at a reasonable cost, with minimal needs for ensemble averages. We then introduce a new paradigm for the definition of the partial mobility $\mu_{M}$ associated with a given elastic scattering mechanism "M", taking phonons (PH) as a reference ($\mu_{M}^{-1}=\mu_{PH+M}^{-1}-\mu_{PH}^{-1}$). We argue that this definition makes better sense in a quantum transport framework as it is free from long range interference effects that can appear in purely ballistic calculations. As a matter of fact, these mobilities satisfy Matthiessen's rule for three mechanisms [surface roughness (SR), remote Coulomb scattering (RCS) and phonons] much better than the usual, single mechanism calculations. We also discuss the problems raised by the long range spatial correlations in the RCS disorder. Finally, we compare semi-classical Kubo-Greenwood (KG) and quantum NEGF calculations. We show that KG and NEGF are in reasonable agreement for phonon and RCS, yet not for SR. We point to possible deficiencies in the treatment of SR scattering in KG, opening the way for further improvements.Comment: Submitted to Journal of Applied Physic

Probabilistic simulation for the certification of railway vehicles

The present dynamic certification process that is based on experiments has been essentially built on the basis of experience. The introduction of simulation techniques into this process would be of great interest. However, an accurate simulation of complex, nonlinear systems is a difficult task, in particular when rare events (for example, unstable behaviour) are considered. After analysing the system and the currently utilized procedure, this paper proposes a method to achieve, in some particular cases, a simulation-based certification. It focuses on the need for precise and representative excitations (running conditions) and on their variable nature. A probabilistic approach is therefore proposed and illustrated using an example. First, this paper presents a short description of the vehicle / track system and of the experimental procedure. The proposed simulation process is then described. The requirement to analyse a set of running conditions that is at least as large as the one tested experimentally is explained. In the third section, a sensitivity analysis to determine the most influential parameters of the system is reported. Finally, the proposed method is summarized and an application is presented

Modélisation par éléments finis d'essais de caractérisation de la sensibilité des tôles métalliques à l'hydrogène

La modélisation des interactions hydrogène-matériau et des risques de fragilisation par l’hydrogène constitue un enjeu important pour la fiabilité des simulations numériques de structures, notamment dans les secteurs du stockage et de transport de l’hydrogène. Dans le domaine de la mise en forme des tôles métalliques, les interactions entre la plasticité et l’hydrogène doivent également être prises en compte, nécessitant la maitrise dans des simulations par éléments finis de couplages diffusion-plasticité-rupture. Dans la présente étude, des procédures numériques spécifiques (UMAT, UMATHT, DISP, UEL) ont été développées dans le code de calcul par éléments finis Abaqus© pour résoudre des problèmes non-linéaires couplés impliquant diffusion, comportement mécanique et rupture en chargement complexe. Des lois phénoménologiques ont été utilisées pour décrire le comportement élastoplastique, la diffusion et le piégeage de l’hydrogène. La rupture assistée par diffusion d’hydrogène a été modélisée par éléments cohésifs dont la loi de comportement dépend de la concentration locale en hydrogène. Ces outils numériques ont été appliqués à la simulation de deux types d’essais mécaniques spécifiques de caractérisation de la sensibilité des tôles métalliques à l’hydrogène : - un « essai de disque » à rupture sous pression d’hydrogène gazeux, prenant en compte l’interaction entre diffusion et rupture via des éléments cohésifs. Les calculs ont permis de reproduire des résultats expérimentaux pour différentes conditions d’essai. - un essai de pliage en U (U-Bend), consistant en un chargement en hydrogène cathodique après déformation plastique par pliage. Le couplage entre diffusion et champs mécaniques, et la rupture assistée par la diffusion sont considérés. Des simulations ont également été effectuées sur des polycristaux afin d’analyser les hétérogénéités de contrainte et de déformation liées à l’anisotropie locale du matériau, et leur influence sur la diffusion et le piégeage d’hydrogène

Trajectoire de numérisation pour mesure On-Machine sur MOCN 5 axes

International audienceL'objectif des travaux présentés est de proposer une méthode de planification de trajectoire de numérisation pour la mesure on-machine (On-machine Measurement-OMM) dans une machine-outil 5 axes. Compte tenu des 5 degrés de liberté et de la rotation de la broche, il est possible d'améliorer l'accessibilité du capteur. Le capteur laser-plan positionné dans la broche permet de réduire le temps de mesure ; permettant ainsi une prise de décision rapide concernant la conformité géométrique de la pièce fabriquée et les corrections d'usinage potentielles. La planification de trajectoire de numérisation est basée sur le contrôle du recouvrement entre deux passes consécutives en gérant les orientations et le taux de couverture du faisceau laser. Par conséquent, la qualité et le temps de numérisation peuvent être contrôlés en optimisant les zones de recouvrement. Cette méthode est une adaptation pour une machine-outil à 5 axes résultant d'une méthode précédente développée pour un robot à 6 axes. Mots-clés-Mesure on-machine, Capteur laser plan, Recouvrement, Machine-outil 5 axes, Numérisatio

Rubber Impact on 3D Textile Composites

A low velocity impact study of aircraft tire rubber on 3D textile-reinforced composite plates was performed experimentally and numerically. In contrast to regular unidirectional composite laminates, no delaminations occur in such a 3D textile composite. Yarn decohesions, matrix cracks and yarn ruptures have been identified as the major damage mechanisms under impact load. An increase in the number of 3D warp yarns is proposed to improve the impact damage resistance. The characteristic of a rubber impact is the high amount of elastic energy stored in the impactor during impact, which was more than 90% of the initial kinetic energy. This large geometrical deformation of the rubber during impact leads to a less localised loading of the target structure and poses great challenges for the numerical modelling. A hyperelastic Mooney-Rivlin constitutive law was used in Abaqus/Explicit based on a step-by-step validation with static rubber compression tests and low velocity impact tests on aluminium plates. Simulation models of the textile weave were developed on the meso- and macro-scale. The final correlation between impact simulation results on 3D textile-reinforced composite plates and impact test data was promising, highlighting the potential of such numerical simulation tools